Smart Distribution Networks : A Review of Modern Distribution Concepts from a Planning Perspective

Smart grids (SGs), as an emerging grid modernization concept, is spreading across diverse research areas for revolutionizing power systems. SGs realize new key concepts with intelligent technologies, maximizing achieved objectives and addressing critical issues that are limited in conventional grids. The SG modernization is more noticeable at the distribution grid level. Thus, the transformation of the traditional distribution network (DN) into an intelligent one, is a vital dimension of SG research. Since future DNs are expected to be interconnected in nature and operation, hence traditional planning methods and tools may no longer be applicable. In this paper, the smart distribution network (SDN) concept under the SG paradigm, has presented and reviewed from the planning perspective. Also, developments in the SDN planning process have been surveyed on the basis of SG package (SGP). The package presents a SDN planning foundation via major SG-enabling technologies (SGTF), anticipated functionalities (SGAF), new consumption models (MDC) as potential SDN candidates, associated policies and pilot projects and multi-objective planning (MOP) as a real-world optimization problem. In addition, the need for an aggregated SDN planning model has also been highlighted. The paper discusses recent notable related works, implementation activities, various issues/challenges and potential future research directions; all aiming at SDN planning.


Introduction
The ever increasing load demands, aging infrastructure, limited expansion options, and environmental concerns make it difficult for hierarchical-based traditional grids (TGs) to keep pace with modern era requirements [1].Nevertheless, power grids have not been upgraded considerably for decades.Moreover, the competitive electricity market and service requirements close to the technical limits of current technology, have resulted in overstressed grid operations (at the transmission/distribution level), particularly in the distribution network (DN).Conventionally, the DN has purposely been planned to retain unidirectional power flow with radial topology, aimed at efficient power delivery to the end consumer.However, escalating load requirements over large geographical distances have resulted in serious technical issues in DNs, predominately higher system losses, lower voltage regulation, compromised power quality, reliability concerns, and expensive planning alternatives [2,3].The possible solution strategy calls for planned (long/medium/short-term) modernizations that include countermeasures to deal with technical and commercial issues.The anticipated modernization needs to investigate the potential key enablers and associated developments; in planning and modifications supported by various studies, mainly under the paradigm shift of active DN (ADN), as mentioned in [5,10,12].
The SDN concept on the basis of voltage stability, interconnected topology, reliability to consumers and high DG penetration favors loop and mesh topologies, aiming primarily at advanced power distribution configuration in SG [13,14].Gamarra et al. [15] presented a technical review of the literature on optimization techniques for planning, applied to one of the most popular SDN concepts, known as a microgrid (MG).The reviewed work serves as a guideline for innovative planning methodologies, primarily based on economic feasibility.Also, new MG planning approaches and a few trending techniques are pointed out.Siddaiah et al. [16] presented a review of the research work carried out in planning, configuration, modeling, and optimization techniques of hybrid RES for isolated/off-grid applications.The reviewed work offers several mathematical models proposed by various researchers.The models are developed based on objective functions, reliability and economics studies involving design parameters.Besides MG, virtual power plant (VPP) is a concept that deals with providing a reliable electricity supply to the end consumer.Comprehensively reviewed work on MG and VPP concepts has been carried out by Nosratabadi in [17], aiming at solving the DER scheduling problem.The problem has surveyed from perspectives of formulation type, objective function, solution techniques, uncertainty, reliability, reactive power, control, automation, emission, stability, demand response and multi-objective optimization.
On a small scale, smart homes (SHs) and smart building (SBs) are concepts which reside on the consumer side of the grid.Lobaccaro et al. [18] presented a review of works carried out on SHs, from the perspectives of concept, smart home technologies, selection criteria, challenges, benefits and associated benefits.In addition, Zhou et al. [19] offered a review of the development status and research progress on smart home energy management systems (HEMSs) with renewable and stored energy sources.The work provides initially an overview of HEMS architectures and fundamental functions, followed by configurations and home appliances, finally covering utilization techniques for various RES in a SH.Similarly, on the large and complex scale, Calvillo et al. [20] have reviewed the smart city concept, aiming at energy-related work on planning and operation models.Moreover, the scopes of the reviewed works can be classified into five interventions, namely; generation, storage, infrastructure, facilities, and transport.In addition, complex urban energy models integrating more than one intervention area are also reviewed with their respective benefits, limitations, trends, challenges and applications.Also, a methodology is proposed for developing an improved energy model for a smart-city.The literature review indicates that considerable amounts of literature regarding SDN concepts are available.Still, there is a need to consider planned grid modernizations and new planning strategies from the viewpoint of SDN.The anticipated grid transformation and modifications aiming at DN are shown in development (modernization) stages of the past, today (present), and future [21], as shown in Figure 1.Energies 2017, 10, 501 4 of 47

Futuristic SDN Planning: Aim and Scope of Work
In the SG paradigm, diverse stakeholder participation is inevitable from various SDN viewpoints, primarily planning.Foremost stakeholders in the electricity industry include primarily utilities, manufacturers, vendors, regulators, governments, research organizations, and consumers.The need to motivate the stakeholders enables them to recognize, participate and address the challenges in SDN planning, development and deployment respectively [8].The expected compromise or trade-off solutions addressing conflicting objectives for satisfying multiple stakeholders, make multi-objective planning (MOP) a suitable choice for SDNs [22].The real-world planning problem can be considered a multi-objective (MO), constrained and practically stochastic basic optimization problem [15].The optimal DER sizing and placement will be the focus of SDN planning [23].Various test (demonstration) and pilot projects are in progress across the globe that identify and realize the associated SG features.In addition, such developments point out the potential areas to addressed concerns and new challenges that can arise, from a future perspective.
Hence, in the light of the above literature, a real world, deeper, wider and aggregated planning approach is inevitable.The usual planning problems focus on finding a feasible economic (cost effective) solution.In addition, objectives like reliability, power quality and low (negative) environmental impact, system stability, energy efficiency and customer satisfaction can also be considered in SDN problem formulation.The SDN planning problems have been classified as follows [15,17,24,25].
1a.Long-term SDN planning: Long (several years) and medium term (one year) planning problems have been carried out over large (single and/or multi-stage) planning horizons.The classification mainly deals with a number of energy sources (DG, DER, RES, REG, storage, ESS, EV, DR, associated devices, reinforcements, etc.) selection, their sizing, and location within SDN. 1b.Off-line planning problem: Off-line (scenario/model-based) planning studies have been carried out for a specific operational scenario, since practically a planning problem is an off-line problem.Hence, scenario-concerned problems in coordination with ANM-based schemes are considered a variant of the classification above.2.
Scheduling: Medium (seasonal-year) and short-term (one-several days) planning problem studies have been carried out over a scheduled horizon (one day-a season-a year).The classification primarily deals with scheduling problem of renewable/conventional sources (energy sources assets) selection and demand forecasting within a SDN framework.

3.
Real-time operational planning (RT-OP): The real-time (15 min-day) operational planning problems have been studied over a short term operational horizon.The classification primarily deals with operational planning problem of asset selection and topology alteration based on state-estimation algorithms and communication-based signals.In addition, real-time operational planning (RT-OP) has expected to be critical in complex real-time SDN operations.
This study aims to present a systematic review of distribution grid modernization from the planning viewpoint.It offers an overview of the status of SDN planning by featured intelligent technologies, anticipated functionalities, modern distribution concepts (MDC), policies, work maps, related pilot projects and MOP as a real world planning option.This study should serve as a guideline for researchers and planning engineers to formulate approaches, addressing future SDN planning scenarios.In the literature, several methods are available concerning the planning of current power DN and [10,12,14,23,26] and the abovementioned planning problems have been separately addressed.
The traditional planning methods may not be applicable to plan new DN models or transform current DNs into SDNs [24,26].In addition, few accounts are available in the literature that considers grid modernization from the planning perspective of future distribution mechanisms.Hence, new interconnected SDN concepts, exploitation of SG functionalities, key enabling smart technologies, ANM schemes, multiple stakeholders, MOP as real-world planning problems and integrated planning strategies; constitute the key features of modern SDN planning.Thus, SDN as a grid modernization Energies 2017, 10, 501 5 of 47 concept, supported by a detailed account of research works in several aspects, is comprehensively surveyed in the paper.This works compliments existing works by offering: (1) Examination of the SG package (SGP) concept, including key enablers that aim at future SDN planning.(2) Current planning status of real world (multi-objective) optimization from a SDN's viewpoint.(3) The challenges in SDN planning and future research directions.
The paper is organized as follows: Section 3 provides an overarching diagram of smart grid packages (SGPs), offered for SDNs.Section 4 describes an overview of enabling technologies and functionalities for SDN concept realization.A brief overview of potential modern distribution (SDN) concepts in the SG paradigm is presented in Section 5. Section 6 summarizes an overview of policies, workmaps, leading countries, pilot projects and focused objectives from the standpoint of SDN.Section 7 presents a composite review of the current MOP status from an SDN's perspective.Current challenges in SDN studies and future research directions have been presented in Section 8.The paper concludes in Section 9.

Smart Grid Packages (SGPs) for Smart Distribution Networks (SDNs)
The literature review indicates that a considerable amount of research work has been carried out on various aspects of SG in particular and the benefits offered are amalgamated in general with overall SG concepts.In his study, key enablers involved in development and deployment of SG concepts, in particular SDN is arranged in accordance with the proposed smart grid package (SGP) concept.SGP and its prominent features are presented in this paper as the overarching diagram in Figure 2 and aree discussed in the following Sections 4-7.The key components in SGP are indicated as follows: (1) The enabling technologies and anticipated functionalities in SGP → SGTF (2) Modern distribution (consumption) concepts (models) in SGP → MDC (3) Policies by leading countries, work maps and pilot projects for SG concepts realization → PWP (4) Real world optimization planning problems (in multi-objective planning framework) → RWO Energies 2017, 10, 501 5 of 45 modernization concept, supported by a detailed account of research works in several aspects, is comprehensively surveyed in the paper.This works compliments existing works by offering: (1) Examination of the SG package (SGP) concept, including key enablers that aim at future SDN planning.(2) Current planning status of real world (multi-objective) optimization from a SDN's viewpoint.(3) The challenges in SDN planning and future research directions.
The paper is organized as follows: Section 3 provides an overarching diagram of smart grid packages (SGPs), offered for SDNs.Section 4 describes an overview of enabling technologies and functionalities for SDN concept realization.A brief overview of potential modern distribution (SDN) concepts in the SG paradigm is presented in Section 5. Section 6 summarizes an overview of policies, workmaps, leading countries, pilot projects and focused objectives from the standpoint of SDN.Section 7 presents a composite review of the current MOP status from an SDN's perspective.Current challenges in SDN studies and future research directions have been presented in Section 8.The paper concludes in Section 9.

Smart Grid Packages (SGPs) for Smart Distribution Networks (SDNs)
The literature review indicates that a considerable amount of research work has been carried out on various aspects of SG in particular and the benefits offered are amalgamated in general with overall SG concepts.In his study, key enablers involved in development and deployment of SG concepts, in particular SDN is arranged in accordance with the proposed smart grid package (SGP) concept.SGP and its prominent features are presented in this paper as the overarching diagram in Figure 2 and aree discussed in the following Sections 4-7.The key components in SGP are indicated as follows: (1) The enabling technologies and anticipated functionalities in SGP → SGTF (2) Modern distribution (consumption) concepts (models) in SGP → MDC

SG Components Integration (SGCI)
The future SDNs are expected to house large DG/DER/REG penetration and to be capable of accommodating bidirectional power flow [27][28][29].The developments in power electronics (PE), mainly power converters, enables smooth integration of DER/REGs in coordination with storage and ICT, respectively.The major SG components primarily include various DER/DG technologies, smart metering systems, flexible loads, storage systems, smart substations equipped with automated transformers and online tap changers (OLTC), all interconnected with advanced automation and control infrastructures [30].

Information and Communication Technologies (ICT)
The widespread information and communication (ICT) infrastructure forms the backbone of sensing, measurement, monitoring, and metering operations.Besides, the implementation of modern distribution concepts (MDC) like SHs, SBs, VPP and SC; depends on the advancements in ICT.The ICT enable data flows from sensing devices to smart meters, further to utility data centers, and back [31].The advanced metering infrastructure (AMI) empowers SG with nearly real-time condition monitoring, ensuring accurate bills and allowing consumer a position of decision-making towards their energy use [5].Communication technologies (wired and wireless) serve as a medium to implement SG solutions aiming at control, protection, automation and monitoring [32,33].The research issues include; homogenization of standards to attain interoperability and scalability.

Advanced Distributed Automation (ADA)
The ADA together with AMI facilitates DN modification, particularly the implementation of SG functionalities at the distribution grid level, employing transformer/feeder monitoring, effective fault detection/isolation, outage management (quicker fault restoration), electrical vehicle (EV) integration and protection of assets.The ADA can assist implementation of new distribution topologies like loops to improve DN reliability and stability.Moreover, the use of intelligent electronic devices (IED) enables ADA by performing control, communication, protection, metering and logic processing functions autonomously, resulting in coordinated operation of the key enablers [34,35].The important research issues include [30]; integration of ICT and ADA into one SG based control solution considering generation, distribution, EST, and loads.Also, new methods for design, development, and validation represent research-worthy areas.

Energy Storage Technologies (EST)
The energy storage applications include consumer energy management, seamless REG integration on various scales (utility and consumer), EV infrastructure support, and short-term active and reactive power support to the system [36,37].The prime EST-based objectives include better voltage and frequency support during transients, long term REG integration, power quality and reliability of the service [38,39].The MDC-based EST applications mainly include optimized storage utilization with DG, EV, and DR for asset planning and scheduling [40].The research-worthy issues in EST include cost effective economic solution and advance control functions provided by EST, DER, and controllable loads.

Power Electronics (PE)
The PE devices, interfaces and mechanisms are vital components of future power distribution mechanisms.Colak et al. in [41] have broadly reviewed the PE contributions to SG on the basis of their applications in SG, particularly REG integration and MG.The notably associated objectives include improving reliability, sustainability, stability and power quality.The research worthy issues include; parallel inverter operation in MG, stability in large-scale centralized solar energy generation, bidirectional power flow control, agent-based control and optimization of fault tolerance, respectively.4.1.6.Electric Vehicles (EVs) EVs are one of the important paradigms of the SG package.It broadly encompasses the concepts of EV, plug-in hybrid EV (PHEV), vehicle to grid and grid to vehicle (V2G & G2V).The major attributes of EVs include system stability, reliability, and efficiency of the grid [42][43][44].The objectives are achieved in terms of REG storage/backup, spinning reserve (SR) and contribution to the decreasing peak power demand curve in coordination with demand response (DR) The REG and EV infrastructure, interaction and integration to the current DN and SDN, are new research dimensions [45,46].

Sensing, Measurement, and Monitoring Technologies (SMMT)
The sensing devices mainly includes smart meters, wireless sensor networks (WSNs), remote terminal units (RTU) and phasor measurement units (PMUs).The SMMT detect anomalies such as deviation from normal conditions and assist in remote monitoring of energy sources and related equipment [47].

Control Technologies (CT)
Control technologies have generally been classified in terms of centralized (high computation cost), decentralized/distributed (high synchronization time) and hybrid methodologies.Tuballa et al. [7] have arranged SG-based control methods/technologies on the basis of a multi-agent system (MAS), power electronics (PE), advanced fault management (AFM) and virtual power plant (VPP)-based control technologies, respectively.Decentralized control schemes, known as MAS, unlike their centralized counterparts, can manage a large amount of interconnected SG components and micro grids (MGs).PE-based control schemes can manage large scale DG using inverters into the grid.AFM through coordination of local automation, relay protection and switchgear control for optimum MG islanding can serve critical consumers during main grid outages.The real-time control approach for VPP aiming at REG fluctuation and nonlinear loads can be addressed in an effective manner.Intelligence-based architectures such as service-oriented architecture (SoA), MAS-based control and artificial intelligence (AI)-based control solutions in MDC concepts (Section 5) need further research consideration [30].

Advanced Protection Schemes (APS)
The modernization challenge of distribution grids aiming at protection in coordination with ADA is emphasized to coordinate advanced control on the basis of information provided by sensor networks and smart meters in the field to integrate REG/DER with DMS to enhance overall performance.Moreover, the incorporation of intelligent electronic devices (IEDs) will facilitate self-adaptive protection (mainly fault location, isolation, and service restoration or FLISR and high impedance fault detection or HIFD), metering, and control and communication functions.The anticipated major objectives expected to be achieved include system stability, reliability and personal safety [35,48].Mirsaeidi et al. [49] reviewed current protection schemes and proposed advanced protection schemes considering a digital central protection unit and PMUs.The proposed method aims at interconnected MG with complicated power flows during both normal and islanded operations.

Demand Side Management (DSM) and Demand Response (DR)
Demand Side Management (DSM) is an important planning tool, aimed at ensuring the reliability and stability of power systems on a long-term basis.The utilities implement DSM programs to manage demands on the consumer side of the meter.The primary DSM objectives include energy efficiency, peak load management; load shifting, rebound peak shifting, valley filling, strategically addressing load growth and reshaping demands [50,51].DSM allows consumers "freedom of choice" regarding decision making in their energy consumption and enables utilities to reduce peak load demands [52].Demand response (DR), as a subset of DSM, are programs design to encourage consumers to involve in grid operations on short-term basis, by shifting their loads/consumption patterns (during peak to low demand periods) on the basis of financial incentives.A state-of-the-art survey is presented by Siano et al. [53], encompassing various aspects of DR, prominently concepts, potential benefits, enabling smart technologies, applications and case studies.The DR technologies are classified based on control, monitoring (information) and communication systems, respectively.The prominent research dimensions include DR provider implementation and associated infrastructure for plugged-in EVs.

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) and Effective Management (EM) The asset optimization in SDN demands promising functionalities and services for efficient operation and effective management of resources [5].In particular, peak loadings, unexpected rebound peaks and valley filling (low load demand) must be optimized, to avoid overprovision of resources.The key SG enabling technologies for "efficient grids" primarily consist of advanced forecasting support for optimized operations (generation-load balance) [30], DR for energy management support at small levels [53] and greenhouse gas (GHG) emission control [5].Also, DSM on a large scale proactively addresses complex consumption dynamics (utilities' and consumers' behaviors); with the support of (ICT) and dynamic pricing schemes, respectively [50].In addition, advanced active network management (ANM) techniques mentioned in [54] and enhanced outage management systems (OMS) described in [6]; have expected to play a vital role in optimized asset utilization.The SDN-based management models need to consider factors like load forecasting, uncertainty, and economic viability.In addition, the management problem must also be evaluated from the viewpoint of solutions considering the environment and social benefits.

Power Quality and Stability (PQS)
The ability to maintain power quality is vital, particularly to allow higher hosting intermittent renewable sources capacity, free from power interruptions, voltage sag, and spikes, respectively [8,55,56].In relation to that, renewable DG technologies may lead to various challenges in system stability, mainly low voltage stability resulting from low support for power sharing, decrease in angular stability due to overall lower system inertia (in photovoltaics), low frequency power oscillations and inability to serve as reserve for the power system.SDN under the SG paradigm has expected to ensure reasonable power quality and power system stability, during transients and high DG penetration [8,57,58].

Advanced Real Time Monitoring (ARTM)
Traditionally, distribution system operators (DSO) have limited capability in terms of remote monitoring and control abilities, which restrict quick fault tracing and isolation.The smart meter with ICT support enables two-way communications among the distribution operating center (utility) and consumers.The amount of data (information) exchange provides real-time monitoring/display of energy consumption data (of the consumer), dynamic tariff negotiations and load control [59].In addition, real-time condition monitoring and system state estimation capabilities have expected to be provided in medium/low voltage SDNs.Other potential enabling technologies include sensor networks and PMUs.

Reliability (Rel.)
Reliable SG operation and particularly SDN are vital in terms of accommodating high DG, complex power flows and the interconnected structure of distribution mechanisms.The associated SG requires improvement in fault detection, self-healing, adaptive protection, and proactive fault detection and prevention mechanisms, respectively [5,7,30,49].The primarily SGETs include APA, ADA, ICT, CT and storage technologies aiming at SGCI.

Security and Privacy (S & P)
The expected high penetration of information technology and consequential huge data generation, transmission and storage may result in privacy and (cyber) security violations, on both the utility and consumer levels [60].The security (passive and active attacks) must be addressed to realize secure MDC (for example, SH) from the consumer and utility's viewpoint (further details are given in Section 5.8).An intrusion detection system (IDS) was proposed in [61] to counter cyber-attacks on information networks under the SG paradigm.Prominent proposed SG-based cyber-security solutions include cryptographic algorithms (and protocols), privacy (billing) protocols, encryption, decryption and authentication keys [62].Yu et al. in [63] discussed new technologies, mainly big data, cloud computing and internet of things (IoT) in SG.

New Market Models, Opportunities, and Management (NMOM)
The SG enables a new era of "plug-and-play" opportunities from the electricity market (operators' and participants') perspective.Divshali et al. in [64] presented an overview of electrical market management and opportunities from the perspective of supply side management (SSM), DSM and EV.Major enabling technologies include ICT, ADA, DR, DSM, SG components and SMMT.Moreover, competitive environment and decision making are new research dimensions in new market models, particularly for DSM and DR providers in long-term market feasibility studies [65].

Implementation of New Concepts and Paradigms (INC & P)
The high DG penetration backed by SG technologies has led to several new distribution mechanisms.Notable future distribution paradigms include MG and VPP [17].The structure of the future DN has expected to be more interconnected (topology/structure), aiming at ensuring reliability and voltage stability to end consumers.A detailed account on INC & P or MDC is presented in Section 5 to follow.

Distributed Intelligence Decision Support (DIDS) and Interoperability
The SG realization at the distribution level needs several mandatory features, mainly distributed intelligence, decision support, and interoperability.Strasser et al. [30] have categorized distributed intelligence on the basis of subcomponent level (PE/inverters/power converters), component level (DER and associated services), subsystem level (MG) and system level (DSM), respectively.Decision support in particular, for consumer participation in market operations, is the main feature of SG.Interoperability among various stakeholders, for infrastructure modernization and standard harmonization, is a vital requirement in planning and implementing new grid structures.

"Freedom of Choices" (FoC) for Consumers
This attribute is particularly important from the viewpoint of empowering consumers with their participation in the decision-making process of SG operations through incentive-based DSM and DR programs, respectively [53,64].

Modern Distribution Concepts (MDC) and Models
Recent trends and discussion regarding new consumption models from a future perspective have given way to the implementation of non-conventional generation and new distribution concepts in the SG environment.The new power delivery paradigms or MDCs are expected to constitute the building blocks of SGs, capable of accommodating a wide range of high DG (particularly REG) penetration.The current distribution infrastructure (being radial in structure) has limitations for integrating REG, since it may result in challenges like protection issues, dynamic stability issues, complicated power flows and complex control mechanisms.The modifications in the current infrastructure should be made in accordance with the developments in technologies.However, such planning needs to be coordinated in accordance with future needs and SDN concepts.In this section, a few future distribution concepts are briefly discussed, that constitute the backbone of future SDN as a whole in, as shown throughout in Figures 3-7, respectively

Active Radial Distribution Network (ARDN)
The radial topology constraint was considered by the researchers in various studies while studying the implementation of SG concepts [26,66].The ARDN concept is basically RDN reconfiguration, facilitating DG placement and loss minimization.The reconfiguration is realized by changing the open/close status of switches (tie-switches or TS/normally-open and sectionalized-switches or SS/normally-closed) in order to transfer loads among a group of interconnected radial feeders and to retain unified power flow [67] (as shown in Figure 3a).However, reconfiguration problems aimed at DG placement become a complex mixed-integer non-linear optimization problem (MINLP), since they have to deal with a bidirectional flow rather than a unidirectional one [10,12].

Loop Distribution Network (LDN)
The loop distribution network (LDN) is an upgraded version of the conventional DN under the application of an advanced power distribution system (APDS) [13,68,69].Such a DN structure/topology is advocated over its radial counterpart, primarily due to better reliability than the radial counterpart, voltage stability, fault traceability and high DG/REG penetration, respectively [13].However, higher upgrading cost constraints, upgraded protection requirements, advance automation, expected increase of short-circuit currents (SCCs), complex control needs and comparatively high losses usually ocurr in LDNs compared to traditional planning methodologies.Costs and losses are among the major constraints that force DN operations to adopt a radial configuration.Some power utilities still serve their consumers using LDNs from a high-reliability perspective like Singapore Power, Taiwan Power, Hong Kong Electrical Supply Company, etc.
LDNs are also considered as a configuration of the future SDN, since the previous limitations are expected to be met with future SG technologies like advanced distribution automation (ADA), robust control, advanced PE, advanced protection design (including protection device coordination to meet bidirectional power flow) and cost of reliability, respectively [13,[70][71][72][73].The normal distribution topologies in LDN include need-based loops and normally closed loops.Both modes are achieved by closing a select number of tie switches (TS) to convert a part (two feeders/laterals) or a selection of TS to convert the whole system into a loop [13,70,71], as shown in Figure 3b.The need-based loops are addressed on an "if and when needed" basis for load balancing between high and low loaded feeders (partial LDN) [72].The latter mode works under normal operation (complete LDN) and can include other loop options to retain the quality of service [72,73].and low loaded feeders (partial LDN) [72].The latter mode works under normal operation (complete LDN) and can include other loop options to retain the quality of service [72,73].

Mesh Distribution Network (MDN)
The meshed distribution network (MDN) is also considered as a multi-loop network, as shown in Figure 4a.It is usually subjected to same issues and more or less same requirements as LDN.It has advantages of comparatively higher reliability, DG penetration, better voltage response (for DG critical voltage mode) and comparatively fewer power losses compared to LDN from objective viewpoint [74,75].However, complex fault traceability makes is more susceptible to faults and early recovery from reliability viewpoint in traditional planning methods [76].The limitations in MDN, serve as a vital research area, from planning and operation perspective.The normal topologies in MDN include weakly mesh or all mesh [77,78].The former mode is realized with topologies attain by closing a selective number of TS, whereas the later mode works under normal operation by closing all TS [12,14,26,75].

Micro Grid (MG)
The MG, according to CERTS, is defined as a cluster of generators, including heat recovery, storage, and loads, and operated as single control entity as shown in Figure 4b.It is considered to be a building block of future distribution mechanisms and a vital component of future SG, including fixed number of resources within restricted geographical area [5,79].MG is a confined consortium of DG/REG, storage technology (ST, in particular, electrical/energy storage system or simply ESS), PE, concerned loads, information and ICT support with defined electrical boundaries.A detailed account of control levels with concerned MG architecture and applications can be found in [80,81].
The MG as a distribution mechanism is capable of operating in synchronization with utility grid (grid tied) at the point of common coupling (PCC) as well as an independent islanded mode to serve consumers during main grid blackout [82,83].The modes of operation for DER based MG in SG paradigm includes grid/utility connected mode (centralized power control), the transition to island mode, islanded/isolated mode (decentralized power control) and reconnection to the main grid mode [84].
The intentional islanding is not allowed in TDP, mainly due to voltage stability and synchronization issues; among DG units, substation and interference with protection mechanisms, respectively.Moreover, the normal working topology of MG is usually considered radial or reconfigured radial in order to synchronize concerned operation with current utilities [14].However, Che et al. [85] have proposed integrated (graph partitioning and integer programming) methodology, aiming at loop topology in MG planning (with controllable DERs); from the reliability and operational efficiency's perspective.

Mesh Distribution Network (MDN)
The meshed distribution network (MDN) is also considered as a multi-loop network, as shown in Figure 4a.It is usually subjected to same issues and more or less same requirements as LDN.It has advantages of comparatively higher reliability, DG penetration, better voltage response (for DG critical voltage mode) and comparatively fewer power losses compared to LDN from objective viewpoint [74,75].However, complex fault traceability makes is more susceptible to faults and early recovery from reliability viewpoint in traditional planning methods [76].The limitations in MDN, serve as a vital research area, from planning and operation perspective.The normal topologies in MDN include weakly mesh or all mesh [77,78].The former mode is realized with topologies attain by closing a selective number of TS, whereas the later mode works under normal operation by closing all TS [12,14,26,75].

Micro Grid (MG)
The MG, according to CERTS, is defined as a cluster of generators, including heat recovery, storage, and loads, and operated as single control entity as shown in Figure 4b.It is considered to be a building block of future distribution mechanisms and a vital component of future SG, including fixed number of resources within restricted geographical area [5,79].MG is a confined consortium of DG/REG, storage technology (ST, in particular, electrical/energy storage system or simply ESS), PE, concerned loads, information and ICT support with defined electrical boundaries.A detailed account of control levels with concerned MG architecture and applications can be found in [80,81].
The MG as a distribution mechanism is capable of operating in synchronization with utility grid (grid tied) at the point of common coupling (PCC) as well as an independent islanded mode to serve consumers during main grid blackout [82,83].The modes of operation for DER based MG in SG paradigm includes grid/utility connected mode (centralized power control), the transition to island mode, islanded/isolated mode (decentralized power control) and reconnection to the main grid mode [84].
The intentional islanding is not allowed in TDP, mainly due to voltage stability and synchronization issues; among DG units, substation and interference with protection mechanisms, respectively.Moreover, the normal working topology of MG is usually considered radial or reconfigured radial in order to synchronize concerned operation with current utilities [14].However, Che et al. [85] have proposed integrated (graph partitioning and integer programming) methodology, aiming at loop topology in MG planning (with controllable DERs); from the reliability and operational efficiency's perspective.The multi-objective-based independent mode transitions of MG in favor of stakeholders is another research dimension in SG environment and is required to be examined [86].Several pilot projects, notably CERT MG, has attributed to addressing various potential issues [87].The possible key enablers offered by SGP include ADA, high performance coordinated protection (especially during islanding and reconnection to the main grid), advance PE for efficient power control in various modes, essential storage technologies and high-speed communication infrastructure for enabled support.The MG primarily depends on hardware innovations (in PE, storage, etc.).Normal trading in MG involves retail distributions.The anticipated objectives include reliability, cost optimization, voltage/frequency stability, improved efficiency and stakeholders' satisfaction [17].

Isolated (Off-Grid) Distribution System (IDS)
The IDS concept as shown in Figure 5a refers to the applications like stand-alone (SA) off-grid rural electrification.The normal operating mode of IMG is same as that of islanded mode MG.IMGs can be generally classified in terms of stand-alone/(home and community-based) systems and isolated distribution network based MG.Off-grid small-scale technologies are mainly divided into conventional (diesel-based generation), non-conventional (small-scale hydro, solar, the wind, storage) and hybrid (both conventional and non-conventional) [16,88].
The normal distribution topologies in IMG (with distribution network) includes passive radial, active radial and active (loop/mesh), whereas AC/DC distribution systems for SA homes and communities are separate [2].However, voltage and frequency (V & F) regulation along with reactive power compensation and storage system optimized operation; are important research areas [3].The concerned key enablers in SGP for IMG are the same as that of a MG under islanded mode.

Clustered/Multi-Micro Grids (CMG/MMG)
The CMG/MMG concept as shown in Figure 5b refers to a group of MGs that offers new ways to cope with control complexity in new distribution scenarios and achieve certain objectives notably power quality, reliability and multiple DG placements.The normal distribution topologies in MMG includes loop (for urban) and radial (for rural) distribution mechanisms.A detail discussion regarding MMG operation can be found in [89].Still, MMG concept has not addressed in detail.The concept and offers valuable research directions such as MG penetration (multi-DG in each MG) and islanding within test MMG incorporating features such as; ADA, upgraded protection, DSM, market support, communication, AMI, ICT, PE, advanced control, storage technologies (STs), etc.The multi-objective-based independent mode transitions of MG in favor of stakeholders is another research dimension in SG environment and is required to be examined [86].Several pilot projects, notably CERT MG, has attributed to addressing various potential issues [87].The possible key enablers offered by SGP include ADA, high performance coordinated protection (especially during islanding and reconnection to the main grid), advance PE for efficient power control in various modes, essential storage technologies and high-speed communication infrastructure for enabled support.The MG primarily depends on hardware innovations (in PE, storage, etc.).Normal trading in MG involves retail distributions.The anticipated objectives include reliability, cost optimization, voltage/frequency stability, improved efficiency and stakeholders' satisfaction [17].

Isolated (Off-Grid) Distribution System (IDS)
The IDS concept as shown in Figure 5a refers to the applications like stand-alone (SA) off-grid rural electrification.The normal operating mode of IMG is same as that of islanded mode MG.IMGs can be generally classified in terms of stand-alone/(home and community-based) systems and isolated distribution network based MG.Off-grid small-scale technologies are mainly divided into conventional (diesel-based generation), non-conventional (small-scale hydro, solar, the wind, storage) and hybrid (both conventional and non-conventional) [16,88].
The normal distribution topologies in IMG (with distribution network) includes passive radial, active radial and active (loop/mesh), whereas AC/DC distribution systems for SA homes and communities are separate [2].However, voltage and frequency (V & F) regulation along with reactive power compensation and storage system optimized operation; are important research areas [3].The concerned key enablers in SGP for IMG are the same as that of a MG under islanded mode.

Clustered/Multi-Micro Grids (CMG/MMG)
The CMG/MMG concept as shown in Figure 5b refers to a group of MGs that offers new ways to cope with control complexity in new distribution scenarios and achieve certain objectives notably power quality, reliability and multiple DG placements.The normal distribution topologies in MMG includes loop (for urban) and radial (for rural) distribution mechanisms.A detail discussion regarding MMG operation can be found in [89].Still, MMG concept has not addressed in detail.The concept and offers valuable research directions such as MG penetration (multi-DG in each MG) and islanding within test MMG incorporating features such as; ADA, upgraded protection, DSM, market support, communication, AMI, ICT, PE, advanced control, storage technologies (STs), etc.

Virtual Power Plants (VPP)
The VPP concept, as shown in Figure 6a, is similar to the cluster MMG concept that is controlled and managed by a central entity and comprises a variety of DG units with responsive loads spreading either over large geographical areas or across a number of clustered MGs [90].The VPP (connected in grid-tied mode only) can be classified in terms of operational type (technical and commercial VPPs), ownership, capacity and asset optimization planning (with location and the optimal size of the VPP components) [91].Some notable key enablers for VPP operations in SG package includes ICT, new market concept, energy management system (EMS), Demand side management (DSM), AMI, STs, monitoring, PE, advanced control devices, sensor networks, etc. [92].Information and smart metering technologies make the backbone of VPP, enabling both retail and wholesale market trading.

Smart Homes (SH)
SH is a distribution mechanism that unlike previous concepts, resides on the consumer side of the grid.SH normally comprises of sensor networks, home area network (HAN), smart information box (SIB), home display unit (HDU) as consumer interface, in-house AC/DC distribution with smart plugs, advanced PE (converters and inverters for DG, EV and ESS) and diverse (AC/DC) loads.The general architecture of SH based on HAN has presented in Figure 6b.Saponara et al. [93] have reviewed SG to SH connection from the realization perspectives of architecture, security concerns and hardware employment for HAN in SG environment.Authors have also employed the ZigBee protocol in proposed solutions.
HAN architecture in Figure 6b consists of a smart meter (via a transceiver), SIB, appliances, smart plugs and distribution components, respectively.The smart meters collect energy utilization information from HAN through SIB.The gateway (simple WiFi) router is an interface between HAN, distribution utility's local area network (LAN), server provider based wide area network (WAN) and respective interactions among them.Hence, the overall SH-based HAN model enables the consumer to access SIB and remain in contact with server providers.The HDU is the consumer's graphical user interface (GUI), connected with HAN and WAN based service platforms, and enables preference based energy information, aims to generate optimize power consumption plans.
The anticipated benefits offered by SH model under SG environment includes effective feedback on energy aware consumption, DR programs encouraging the customer reduced tariffs in the end-of-month electricity bill, dynamic pricing schemes enabling peak shaving and energy interchanges among consumers owning DG units [18,19,32].Despite various benefits offered by SH under SG environment, the secure communication among various entities may prone to malicious cyber-attacks and security issues.Komninos et al. [32] have reviewed security issues of SH to SG models from the viewpoints of mandatory objectives, countermeasures to several types of security threats (SH to SG and vice versa) and concern standardization followed across the globe.The

Virtual Power Plants (VPP)
The VPP concept, as shown in Figure 6a, is similar to the cluster MMG concept that is controlled and managed by a central entity and comprises a variety of DG units with responsive loads spreading either over large geographical areas or across a number of clustered MGs [90].The VPP (connected in grid-tied mode only) can be classified in terms of operational type (technical and commercial VPPs), ownership, capacity and asset optimization planning (with location and the optimal size of the VPP components) [91].Some notable key enablers for VPP operations in SG package includes ICT, new market concept, energy management system (EMS), Demand side management (DSM), AMI, STs, monitoring, PE, advanced control devices, sensor networks, etc. [92].Information and smart metering technologies make the backbone of VPP, enabling both retail and wholesale market trading.

Smart Homes (SH)
SH is a distribution mechanism that unlike previous concepts, resides on the consumer side of the grid.SH normally comprises of sensor networks, home area network (HAN), smart information box (SIB), home display unit (HDU) as consumer interface, in-house AC/DC distribution with smart plugs, advanced PE (converters and inverters for DG, EV and ESS) and diverse (AC/DC) loads.The general architecture of SH based on HAN has presented in Figure 6b.Saponara et al. [93] have reviewed SG to SH connection from the realization perspectives of architecture, security concerns and hardware employment for HAN in SG environment.Authors have also employed the ZigBee protocol in proposed solutions.
HAN architecture in Figure 6b consists of a smart meter (via a transceiver), SIB, appliances, smart plugs and distribution components, respectively.The smart meters collect energy utilization information from HAN through SIB.The gateway (simple WiFi) router is an interface between HAN, distribution utility's local area network (LAN), server provider based wide area network (WAN) and respective interactions among them.Hence, the overall SH-based HAN model enables the consumer to access SIB and remain in contact with server providers.The HDU is the consumer's graphical user interface (GUI), connected with HAN and WAN based service platforms, and enables preference based energy information, aims to generate optimize power consumption plans.
The anticipated benefits offered by SH model under SG environment includes effective feedback on energy aware consumption, DR programs encouraging the customer reduced tariffs in the end-of-month electricity bill, dynamic pricing schemes enabling peak shaving and energy interchanges among consumers owning DG units [18,19,32].Despite various benefits offered by SH under SG environment, the secure communication among various entities may prone to malicious cyber-attacks and security issues.Komninos et al. [32] have reviewed security issues of SH to SG models from the viewpoints of mandatory objectives, countermeasures to several types of security threats (SH to SG and vice versa) and concern standardization followed across the globe.The security objectives include; ensure confidentiality of data to authorized parties only, maintain integrity (consistency) of data, validating (authenticity) of the actual interactive entities, guarantee (authorization) access privileges to defined parties and confirm irrefutable proofs (non-repudiation) against any entity's claim.
Energies 2017, 10, 501 14 of 45 security objectives include; ensure confidentiality of data to authorized parties only, maintain integrity (consistency) of data, validating (authenticity) of the actual interactive entities, guarantee (authorization) access privileges to defined parties and confirm irrefutable proofs (non-repudiation) against any entity's claim.The security threats have generally classified into passive (illegal system monitoring) and active (deliberate data modification) attacks.The intensity of attack depends on the violation of any aforementioned objective and respective extent of impact from low/L-medium/M-high/H in SH to SG model (operation, entities/stakeholders, components, resources, etc.).The security attacks associated with SH normally aim at; energy consumption report (L-M), energy interchange signal at HAN/WAN (M), interfering with a physical smart meter (L), alterations to remote home monitoring and control (L-H) and impersonation attack for energy consumption data (L-M).Similarly, security attacks linked with SH-SG interaction aims at; DR signals at HAN/WAN (L-M), impersonating outage report (L), false DG isolation-shutdown report (M-H) and forward consumer data to a third party (L-M).
Details on security solutions and relevant approaches to effective countermeasures can be found in [32,93], whereas modern encryption techniques stand out amongst the most prominent.The aim of these solutions is to attain maximum security objectives and ensure the intensity of malicious attacks intensity is the lowest possible level.The future research directions associated with SHs include enabling automation to accommodate smart devices, harmonization of associated standards, security solutions to realize multi-functionalities, adaptable enough to predict and meet users' requirements in an interactive manner, resulting in efficient operation in favor of consumers' bills and time [18,19].

Smart Buildings (SB)
This concept, like SH as shown in Figure 7a, concerns the efficient operation of SB and the neighborhood.This concept is broadly spread across residential, commercial and industrial loads.The SGP regarding SB includes smart building EMS (SBEMS), AMI, ICT, IoT, EV parking lots, DR, load forecasting techniques, etc. [94].A few SB objectives include reducing GHG emissions, minimize cost with energy optimization, real-time pricing, EV accommodation and REG/DG The security threats have generally classified into passive (illegal system monitoring) and active (deliberate data modification) attacks.The intensity of attack depends on the violation of any aforementioned objective and respective extent of impact from low/L-medium/M-high/H in SH to SG model (operation, entities/stakeholders, components, resources, etc.).The security attacks associated with SH normally aim at; energy consumption report (L-M), energy interchange signal at HAN/WAN (M), interfering with a physical smart meter (L), alterations to remote home monitoring and control (L-H) and impersonation attack for energy consumption data (L-M).Similarly, security attacks linked with SH-SG interaction aims at; DR signals at HAN/WAN (L-M), impersonating outage report (L), false DG isolation-shutdown report (M-H) and forward consumer data to a third party (L-M).
Details on security solutions and relevant approaches to effective countermeasures can be found in [32,93], whereas modern encryption techniques stand out amongst the most prominent.The aim of these solutions is to attain maximum security objectives and ensure the intensity of malicious attacks intensity is the lowest possible level.The future research directions associated with SHs include enabling automation to accommodate smart devices, harmonization of associated standards, security solutions to realize multi-functionalities, adaptable enough to predict and meet users' requirements in an interactive manner, resulting in efficient operation in favor of consumers' bills and time [18,19].

Smart Buildings (SB)
This concept, like SH as shown in Figure 7a, concerns the efficient operation of SB and the neighborhood.This concept is broadly spread across residential, commercial and industrial loads.The SGP regarding SB includes smart building EMS (SBEMS), AMI, ICT, IoT, EV parking lots, DR, load forecasting techniques, etc. [94].A few SB objectives include reducing GHG emissions, minimize cost with energy optimization, real-time pricing, EV accommodation and REG/DG integration [95].Also, SH and SB concepts under SG environment; allows consumers to participate in control, monitoring and shaping their energy demands.

Smart Cities (SC)
The SC is a futuristic concept as shown in Figure 7b, which besides being a new research area; envisions a distributed, hierarchical and autonomous structure with the incorporation of smart technologies for solutions to address challenges in large scale SDNs.The notable technologies for SC include; DER, ICT, AMI, ADA, DSM, etc. [96].The main objective of the SC includes improvement in performance and quality of urban electricity delivery.Moreover, other objectives include optimized utilization of electrical infrastructure for demand management, minimization of overall costs, reducing GHG emissions, maximize power quality, benefit in terms of pricing, availability, and reliability [20].
Energies 2017, 10, 501 15 of 45 integration [95].Also, SH and SB concepts under SG environment; allows consumers to participate in control, monitoring and shaping their energy demands.

Smart Cities (SC)
The SC is a futuristic concept as shown in Figure 7b, which besides being a new research area; envisions a distributed, hierarchical and autonomous structure with the incorporation of smart technologies for solutions to address challenges in large scale SDNs.The notable technologies for SC include; DER, ICT, AMI, ADA, DSM, etc. [96].The main objective of the SC includes improvement in performance and quality of urban electricity delivery.Moreover, other objectives include optimized utilization of electrical infrastructure for demand management, minimization of overall costs, reducing GHG emissions, maximize power quality, benefit in terms of pricing, availability, and reliability [20].

Policies by Leading Countries, Work Maps & Pilot Projects (PWP) for SDN Concepts Realization
An overview of prominent leading countries, with policies and work maps pertaining to SDN realization, are briefly shown in Table 1.The review of policies and work maps around the globe; is vital for paving way for implementation of new concepts in various SG domains.In addition, pilot projects, test beds, and their findings are helpful in addressing SDN issues of various natures.It is important to mention that any planning process aims towards achieving maximization (↑↑) and minimization (↓↓) of certain objectives, respectively.The prominent countries regarding PWP have indicated with main guidelines, major objectives, and core focus respectively.Please refer to Sections 4 (SGTF) and 5 (MDC), regarding core focus, respectively.
An overview of notable pilot projects on ground with relevant attributes and future objectives to be addressed are shown in Table 2.

Policies by Leading Countries, Work Maps & Pilot Projects (PWP) for SDN Concepts Realization
An overview of prominent leading countries, with policies and work maps pertaining to SDN realization, are briefly shown in Table 1.The review of policies and work maps around the globe; is vital for paving way for implementation of new concepts in various SG domains.In addition, pilot projects, test beds, and their findings are helpful in addressing SDN issues of various natures.It is important to mention that any planning process aims towards achieving maximization (↑↑) and minimization (↓↓) of certain objectives, respectively.The prominent countries regarding PWP have indicated with main guidelines, major objectives, and core focus respectively.Please refer to Section 4 (SGTF) and Section 5 (MDC), regarding core focus, respectively.
An overview of notable pilot projects on ground with relevant attributes and future objectives to be addressed are shown in Table 2.

Real World Optimization (RWO) Planning Problems (Multi-Objective Planning)
SG technologies and associated enabling functionalities result in the realization of new MDC concepts.The lack of current and need for new standards, have motivated researchers to propose various MDC models, mainly from the perspectives of economic viability, scale of implementation (size) and consumer contentment (reliability of service, power quality, and environment impact).Every planning process, regardless of classification (in Section 2.3), is proposed around particular objectives and system constraints (technical, social, geographical, environmental and regulatory).Moreover, diverse stakeholder participation, an uncertainty factor (outside and within the control of decision maker) and decision-making (DM) for solutions among conflicting objectives (e.g., cost effectiveness vs. reliability); describe real world MDC planning problems as a MOP problem.It is also a well-established fact that real world planning problems are mostly multi-objective in nature.Hence, in this section, the various MDC concepts have reviewed on the basis of MOP problems.

Need for an Aggregated Planning Model for SDN
Previously in Section 2.3, three broader classifications of SDN planning were proposed, namely: long-term (with off-line variant), scheduling and operational planning, respectively.Conventionally, these problems have been individually addressed in the literature.The multi-objective-based RWO problems aiming at SDN planning has to be addressed in a deeper, broader and integrated/aggregated manner, as advocated in [15].The aggregated planning model (APM)-based primitive approach has proposed in this subsection, aiming at the implementation of RWO based SDN aggregated planning, as shown in Figure 8. SG technologies and associated enabling functionalities result in the realization of new MDC concepts.The lack of current and need for new standards, have motivated researchers to propose various MDC models, mainly from the perspectives of economic viability, scale of implementation (size) and consumer contentment (reliability of service, power quality, and environment impact).Every planning process, regardless of classification (in Section 2.3), is proposed around particular objectives and system constraints (technical, social, geographical, environmental and regulatory).Moreover, diverse stakeholder participation, an uncertainty factor (outside and within the control of decision maker) and decision-making (DM) for solutions among conflicting objectives (e.g., cost effectiveness vs. reliability); describe real world MDC planning problems as a MOP problem.It is also a well-established fact that real world planning problems are mostly multi-objective in nature.Hence, in this section, the various MDC concepts have reviewed on the basis of MOP problems.

Need for an Aggregated Planning Model for SDN
Previously in Section 2.3, three broader classifications of SDN planning were proposed, namely: long-term (with off-line variant), scheduling and operational planning, respectively.Conventionally, these problems have been individually addressed in the literature.The multi-objective-based RWO problems aiming at SDN planning has to be addressed in a deeper, broader and integrated/aggregated manner, as advocated in [15].The aggregated planning model (APM)-based primitive approach has proposed in this subsection, aiming at the implementation of RWO based SDN aggregated planning, as shown in Figure 8.The approach starts from top-to-bottom manner and deals with new long-term SDN planning and implementation of new infrastructure across the horizon (several years-1 year).Later, scheduling of available resources on preferential basis is followed over a scheduled time horizon The approach starts from top-to-bottom manner and deals with new long-term SDN planning and implementation of new infrastructure across the horizon (several years-1 year).Later, scheduling of available resources on preferential basis is followed over a scheduled time horizon (year/seasons-1 day).Finally, the operational planning (real-time and off-line) is followed on the short-term operational horizon (15 min-1 day).
The first step in a bottom-to-top approach is realizing real-time operational planning (RT-OP).The distribution system operator (DSO) backed by state estimation algorithms, ICT (AMI and SMMT) infrastructure (as discussed in Section 5.8), is capable of monitoring SDN systems in real time (RT), during a short-term operational horizon.The DSO takes necessary actions by employing ANM techniques, DR (on the very short term) and DSM (on the long term and large scale) to obtain certain objectives and satisfy the system constraints, aiming at the optimal operation of SDN.
In RT-OP, MDC on the utility (discussed later in Section 8.2) or consumer side (SH and SB), can also plan for supplying ancillary services, prominently; voltage control, active/reactive power support, DER control, power factor (adaptive) control, network reconfiguration management, optimal spinning reserve provision (with DR and ESS) and peak load reduction (with DSM).
Later, scheduling of available resources (DER, ESS, DR and EV) within each MDC on utility or consumer side, is supported by multi-agent system (MAS) that integrates; forecasting techniques (load, price, weather dependent DER), global information system (GIS), historical data aggregator (market, utility, consumer consumption, DER, etc.) and MOP based optimization methods.This stage of bottom-to-top approach needs to ensure; reliability, reactive power support, control, automation, stability and emission reduction, across scheduled horizon.
Finally, long-term multistage expansion planning is followed, based on the futuristic smart components reinforcement, demand side (load) and supply side (DER) requirements, respectively.The main aim of aggregated planning approach is to ensure, overall short-to-long-term technical and economic success of MDC, across all three planning horizons in SDN planning.

Current Status of SDN from the Perspective of Multiple-Objective Planning MOP
The MOP formulations are classified into two major types: The a priori class (MO + W) and a posterori class (MO-P).In the a priori class, the multiple objectives transform into a single objective function.Later, individual weights are assigned to each objective by the decision maker (user-defined) preferences before execution of the optimization algorithm.In other words, in the MO + W formulation, decision making precedes optimization to sort out trade-off (qualitative) solution among a set of conflicting objectives.In the a posterori class (MO-P), optimization is preferred over decision making to achieve realistic (quantitative) solutions among a set of potential solutions (Pareto frontier).The decision maker then chooses a solution from the resulting Pareto frontier, on the basis of respective preferences, also known as a posteriori articulation of preferences.
On the basis of a literature review of MOP, a detailed study is presented in Table 3, from the viewpoint of the aforementioned MDC models and real world planning.The works in literature have arranged according to reference, MDC model under SDN paradigm, decision variables, objectives considered, major system constraints, test SDN, planning type (horizon-based), MOP formulations, optimization methods and load characteristics (load level and profile), respectively.Furthermore, from the readers' comfort viewpoint, the information about MOP under MDC models have been presented in a self-explanatory manner.For MDC (SDN concepts), please refer to Section 5 of this paper.The decision variables have been indicated by type, number, size, and location in MDC concept.The objective function indicates aimed multiple objectives in each reviewed work.The test SDN indicates the work bench, which is used to validate respective idea under each MDC concept.Later, planning types as shown in Section 2.3 have indicated.The major constraints that a problem must abide, are also shown in detail for each reviewed work.Also, the reviewed works are shown in the context of respective SGTF (in Section 4.1) and SGAF (in Section 4.2) respectively.The MO optimization (MOO) techniques are shown with the respective classifications (in Section 7.2) and associated decision making (DM) techniques, respectively.Finally, year of publication is highlighted with associated load model and load profile (as load level or LL) in the respective MOO problem, as shown in Table 3. CLLI (Reliability index) 3.
Overall power loss 4.
Standard component size Feeder current flow 3.
Network power losses 4.
External cost of electricity 5.
Standard component size 7.
REG penetration constraint    Voltage deviation along MG buses 3.
Line current security margin 1.
P/Q compensation limit   Power-flow limit 3.
Radial constraint Flexibility of loads 3.
Devices satisfaction index 4.
Power similarity for load delay 5.
High power consumption with tariff consideration 1.
Types of loads 7. Load

Investigation of MOP Formulations
The MOP formulations usually comprise interaction among inner optimization, outer or main optimization and decision making (DM) methods, respectively.The inner optimization aims at (usually load flow) solution techniques to address system constraints.The main (outer) optimization algorithm aims at finding various solutions of the concerned planning problem.Finally, the DM method sorts out the final trade-off solution, according to the needs of decision makers (or stakeholders).

Inner Optimization (Analytical/Numerical)
The inner optimization techniques in MOP formulations primarily comprises analytical, numerical and meta-heuristic based methods.The main aim of inner optimization is to deal with system constraints.Load/power flows (analytical) and numerical techniques mostly dominate this part, based on the nature of planning problem.Inner optimization solution technique have classified on the basis of formulation type, solver, initialization and interaction among them [167].The non-linear formulation needs a potential solver that can deal efficiently with varying load scenarios and associated uncertainties.The improved (optimized) starting point (hot start), unlike random or flat starts, can significantly reduce the computation cost of the concerned problem.

a. Analytical Methods
The prominent analytical techniques mainly include conventional load flows and sensitivity-based methods.Newton-Raphson (NR) load flows are prominently employed in interconnected nature (structure) SDNs, as shown in [125,129,150].Sensitivity analysis methods have also been employed in [127,128,158]; for potential initial solutions.

Outer/Main Optimization (Meta-Heuristics/Artificial Intelligence)
The main optimization techniques in MOP formulations mostly comprise meta-heuristic (MH) and/or artificial intelligence (AI)-based methods.The main aim of the main optimization is to find a potential set of solutions for concerned planning problems.The prominent meta-heuristic techniques addressed in the literature (Table 3) include: genetic algorithm (GA) and associated evolutionary algorithms with various variants as in [122,128,131,137,139,143,147,152,155,157,162,165,166].Also, PSO with various variants have addressed SDN planning problems as in [125,127,130,132,138,158,163].Furthermore, an improved variant of the teaching learning algorithm (ITLBO) [133] and bacterial foraging algorithm (MBFO) [134] have been employed for short term MO planning (scheduling) problems, respectively.An improved variant of an evolutionary algorithm, the seeker optimization algorithm (SOA) in [123,126]; and AI-based artificial neural network-based methods (NNE) [86] have been employed to solve offline planning and scheduling (real time) problems, respectively.Also, the tabu search algorithm (TSA) was employed to optimize equipment placement, aiming at long-term SDN planning.In the literature, MOP problems aiming at conventional DN planning have successfully employed MH/AI techniques [26].The prominent techniques include harmony search (HS), big bang big crunch (BB-BC), artificial bee colony (ABC), immune algorithm (IA), simulated annealing (SA), honey bee mating (HBMO), ant colony optimization (ACO), bat algorithm (BA), differential evolution (DE), gravitational search algorithm (GSA), shuffled frog leaping (SFL) and hybrid algorithms respectively.Hybrid MH/AI methods results in efficient performance towards global solution aiming at complex planning problems [26].The use of the aforesaid methods, from a future SDN planning viewpoint, offers potential research perspectives.

Decision-Making Methods
The decision making (DM) methods are vital, both as main optimization algorithms and as a means of sorting out a trade-off solutions among a set of multiple conflicting objectives.The prominent DM techniques addressed in the literature (Table 3) include weight methods that include both weighted sum (WSM) and product (WPM) methods, respectively, as in [132,139,140,148,149,157]. The analytical hierarchy process (AHP) has been employed for both long and short term SDN planning, as in [124,154].Fuzzy decision making (FDM) is among the most popular DM methods and employed in many studies, mainly due to its ability to address varying, uncertain nature and various scenarios of the concerned problem.The FDM aiming at MOP problems has been employed in literature with various variants and associated methods as in [86,125,128,133,135,137,141].Other multi-criteria decision analysis methods addressed in this study include the min-max approach [123,126,134,138,160]; rank order centroid (ROC) in [136] and TOPSIS in [141], respectively.A detailed account of MCDA methods can be found in [168,169].

Analysis of Potential Methods in MOP Formulations
The analysis of potential methods in MOP formulation, aiming at optimized SDN planning, are summarized, from the perspective of various performance indicators, in employed MH/AI techniques [26].The prominent techniques include harmony search (HS), big bang big crunch (BB-BC), artificial bee colony (ABC), immune algorithm (IA), simulated annealing (SA), honey bee mating (HBMO), ant colony optimization (ACO), bat algorithm (BA), differential evolution (DE), gravitational search algorithm (GSA), shuffled frog leaping (SFL) and hybrid algorithms respectively.Hybrid MH/AI methods results in efficient performance towards global solution aiming at complex planning problems [26].The use of the aforesaid methods, from a future SDN planning viewpoint, offers potential research perspectives.

Decision-Making Methods
The decision making (DM) methods are vital, both as main optimization algorithms and as a means of sorting out a trade-off solutions among a set of multiple conflicting objectives.The prominent DM techniques addressed in the literature (Table 3) include weight methods that include both weighted sum (WSM) and product (WPM) methods, respectively, as in [132,139,140,148,149,157]. The analytical hierarchy process (AHP) has been employed for both long and short term SDN planning, as in [124,154].Fuzzy decision making (FDM) is among the most popular DM methods and employed in many studies, mainly due to its ability to address varying, uncertain nature and various scenarios of the concerned problem.The FDM aiming at MOP problems has been employed in literature with various variants and associated methods as in [86,125,128,133,135,137,141].Other multi-criteria decision analysis methods addressed in this study include the min-max approach [123,126,134,138,160]; rank order centroid (ROC) in [136] and TOPSIS in [141], respectively.A detailed account of MCDA methods can be found in [168,169].

Analysis of Potential Methods in MOP Formulations
The analysis of potential methods in MOP formulation, aiming at optimized SDN planning, are summarized, from the perspective of various performance indicators, in Table 4.The performance indicators include sub-optimizations in MOP formulations, respective execution (implementation and coding), and computation cost, solution quality, initial parameter dependence (tuning complexity) and application.The performance indicators have shown with desired requirements, as best (√), better/average (❉) and poor (×) as indication metrics, respectively.) and poor (×) as indication metrics, respectively.employed MH/AI techniques [26].The prominent techniques include harmony search (HS), big bang big crunch (BB-BC), artificial bee colony (ABC), immune algorithm (IA), simulated annealing (SA), honey bee mating (HBMO), ant colony optimization (ACO), bat algorithm (BA), differential evolution (DE), gravitational search algorithm (GSA), shuffled frog leaping (SFL) and hybrid algorithms respectively.Hybrid MH/AI methods results in efficient performance towards global solution aiming at complex planning problems [26].The use of the aforesaid methods, from a future SDN planning viewpoint, offers potential research perspectives.

Decision-Making Methods
The decision making (DM) methods are vital, both as main optimization algorithms and as a means of sorting out a trade-off solutions among a set of multiple conflicting objectives.The prominent DM techniques addressed in the literature (Table 3) include weight methods that include both weighted sum (WSM) and product (WPM) methods, respectively, as in [132,139,140,148,149,157]. The analytical hierarchy process (AHP) has been employed for both long and short term SDN planning, as in [124,154].Fuzzy decision making (FDM) is among the most popular DM methods and employed in many studies, mainly due to its ability to address varying, uncertain nature and various scenarios of the concerned problem.The FDM aiming at MOP problems has been employed in literature with various variants and associated methods as in [86,125,128,133,135,137,141].Other multi-criteria decision analysis methods addressed in this study include the min-max approach [123,126,134,138,160]; rank order centroid (ROC) in [136] and TOPSIS in [141], respectively.A detailed account of MCDA methods can be found in [168,169].

Analysis of Potential Methods in MOP Formulations
The analysis of potential methods in MOP formulation, aiming at optimized SDN planning, are summarized, from the perspective of various performance indicators, in Table 4.The performance indicators include sub-optimizations in MOP formulations, respective execution (implementation and coding), and computation cost, solution quality, initial parameter dependence (tuning complexity) and application.The performance indicators have shown with desired requirements, as best (√), better/average (❉) and poor (×) as indication metrics, respectively.employed MH/AI techniques [26].The prominent techniques include harmony search (HS), big bang big crunch (BB-BC), artificial bee colony (ABC), immune algorithm (IA), simulated annealing (SA), honey bee mating (HBMO), ant colony optimization (ACO), bat algorithm (BA), differential evolution (DE), gravitational search algorithm (GSA), shuffled frog leaping (SFL) and hybrid algorithms respectively.Hybrid MH/AI methods results in efficient performance towards global solution aiming at complex planning problems [26].The use of the aforesaid methods, from a future SDN planning viewpoint, offers potential research perspectives.

Decision-Making Methods
The decision making (DM) methods are vital, both as main optimization algorithms and as a means of sorting out a trade-off solutions among a set of multiple conflicting objectives.The prominent DM techniques addressed in the literature (Table 3) include weight methods that include both weighted sum (WSM) and product (WPM) methods, respectively, as in [132,139,140,148,149,157]. The analytical hierarchy process (AHP) has been employed for both long and short term SDN planning, as in [124,154].Fuzzy decision making (FDM) is among the most popular DM methods and employed in many studies, mainly due to its ability to address varying, uncertain nature and various scenarios of the concerned problem.The FDM aiming at MOP problems has been employed in literature with various variants and associated methods as in [86,125,128,133,135,137,141].Other multi-criteria decision analysis methods addressed in this study include the min-max approach [123,126,134,138,160]; rank order centroid (ROC) in [136] and TOPSIS in [141], respectively.A detailed account of MCDA methods can be found in [168,169].

Analysis of Potential Methods in MOP Formulations
The analysis of potential methods in MOP formulation, aiming at optimized SDN planning, are summarized, from the perspective of various performance indicators, in Table 4.The performance indicators include sub-optimizations in MOP formulations, respective execution (implementation and coding), and computation cost, solution quality, initial parameter dependence (tuning complexity) and application.The performance indicators have shown with desired requirements, as best (√), better/average (❉) and poor (×) as indication metrics, respectively.Table 4. Brief comparison review of the merits and demerits of potential approaches applied for SDN planning.employed MH/AI techniques [26].The prominent techniques include harmony search (HS), big bang big crunch (BB-BC), artificial bee colony (ABC), immune algorithm (IA), simulated annealing (SA), honey bee mating (HBMO), ant colony optimization (ACO), bat algorithm (BA), differential evolution (DE), gravitational search algorithm (GSA), shuffled frog leaping (SFL) and hybrid algorithms respectively.Hybrid MH/AI methods results in efficient performance towards global solution aiming at complex planning problems [26].The use of the aforesaid methods, from a future SDN planning viewpoint, offers potential research perspectives.

Decision-Making Methods
The decision making (DM) methods are vital, both as main optimization algorithms and as a means of sorting out a trade-off solutions among a set of multiple conflicting objectives.The prominent DM techniques addressed in the literature (Table 3) include weight methods that include both weighted sum (WSM) and product (WPM) methods, respectively, as in [132,139,140,148,149,157]. The analytical hierarchy process (AHP) has been employed for both long and short term SDN planning, as in [124,154].Fuzzy decision making (FDM) is among the most popular DM methods and employed in many studies, mainly due to its ability to address varying, uncertain nature and various scenarios of the concerned problem.The FDM aiming at MOP problems has been employed in literature with various variants and associated methods as in [86,125,128,133,135,137,141].Other multi-criteria decision analysis methods addressed in this study include the min-max approach [123,126,134,138,160]; rank order centroid (ROC) in [136] and TOPSIS in [141], respectively.A detailed account of MCDA methods can be found in [168,169].

Analysis of Potential Methods in MOP Formulations
The analysis of potential methods in MOP formulation, aiming at optimized SDN planning, are summarized, from the perspective of various performance indicators, in Table 4.The performance indicators include sub-optimizations in MOP formulations, respective execution (implementation and coding), and computation cost, solution quality, initial parameter dependence (tuning complexity) and application.The performance indicators have shown with desired requirements, as best (√), better/average (❉) and poor (×) as indication metrics, respectively.Table 4. Brief comparison review of the merits and demerits of potential approaches applied for SDN planning.employed MH/AI techniques [26].The prominent technique bang big crunch (BB-BC), artificial bee colony (ABC), immune (SA), honey bee mating (HBMO), ant colony optimization (A evolution (DE), gravitational search algorithm (GSA), shuf algorithms respectively.Hybrid MH/AI methods results in solution aiming at complex planning problems [26].The use o SDN planning viewpoint, offers potential research perspective

Decision-Making Methods
The decision making (DM) methods are vital, both as m means of sorting out a trade-off solutions among a set of prominent DM techniques addressed in the literature (Table 3 both weighted sum (WSM) and product (WPM) [132,139,140,148,149,157]. The analytical hierarchy process (AH and short term SDN planning, as in [124,154].Fuzzy decisio popular DM methods and employed in many studies, mainly uncertain nature and various scenarios of the concerned p problems has been employed in literature with various va [86,125,128,133,135,137,141].Other multi-criteria decision anal include the min-max approach [123,126,134,138,160]; rank orde in [141], respectively.A detailed account of MCDA methods ca

Analysis of Potential Methods in MOP Formulations
The analysis of potential methods in MOP formulation, ai summarized, from the perspective of various performance in indicators include sub-optimizations in MOP formulations, r and coding), and computation cost, solution quality, ini complexity) and application.The performance indicators have best (√), better/average (❉) and poor (×) as indication metrics, Table 4. Brief comparison review of the merits and demerits of p planning.

Decision-Making Methods
The decision making (DM) methods are vital, both as main optimization algorithms and as a means of sorting out a trade-off solutions among a set of multiple conflicting objectives.The prominent DM techniques addressed in the literature (Table 3) include weight methods that include both weighted sum (WSM) and product (WPM) methods, respectively, as in [132,139,140,148,149,157]. The analytical hierarchy process (AHP) has been employed for both long and short term SDN planning, as in [124,154].Fuzzy decision making (FDM) is among the most popular DM methods and employed in many studies, mainly due to its ability to address varying, uncertain nature and various scenarios of the concerned problem.The FDM aiming at MOP problems has been employed in literature with various variants and associated methods as in [86,125,128,133,135,137,141].Other multi-criteria decision analysis methods addressed in this study include the min-max approach [123,126,134,138,160]; rank order centroid (ROC) in [136] and TOPSIS in [141], respectively.A detailed account of MCDA methods can be found in [168,169].

Analysis of Potential Methods in MOP Formulations
The analysis of potential methods in MOP formulation, aiming at optimized SDN planning, are summarized, from the perspective of various performance indicators, in Table 4.The performance indicators include sub-optimizations in MOP formulations, respective execution (implementation and coding), and computation cost, solution quality, initial parameter dependence (tuning complexity) and application.The performance indicators have shown with desired requirements, as best (√), better/average (❉) and poor (×) as indication metrics, respectively.Table 4. Brief comparison review of the merits and demerits of potential approaches applied for SDN planning.employed MH/AI techniques [26].The prominent techniques include harmony search (HS), big bang big crunch (BB-BC), artificial bee colony (ABC), immune algorithm (IA), simulated annealing (SA), honey bee mating (HBMO), ant colony optimization (ACO), bat algorithm (BA), differential evolution (DE), gravitational search algorithm (GSA), shuffled frog leaping (SFL) and hybrid algorithms respectively.Hybrid MH/AI methods results in efficient performance towards global solution aiming at complex planning problems [26].The use of the aforesaid methods, from a future SDN planning viewpoint, offers potential research perspectives.

Decision-Making Methods
The decision making (DM) methods are vital, both as main optimization algorithms and as a means of sorting out a trade-off solutions among a set of multiple conflicting objectives.The prominent DM techniques addressed in the literature (Table 3) include weight methods that include both weighted sum (WSM) and product (WPM) methods, respectively, as in [132,139,140,148,149,157]. The analytical hierarchy process (AHP) has been employed for both long and short term SDN planning, as in [124,154].Fuzzy decision making (FDM) is among the most popular DM methods and employed in many studies, mainly due to its ability to address varying, uncertain nature and various scenarios of the concerned problem.The FDM aiming at MOP problems has been employed in literature with various variants and associated methods as in [86,125,128,133,135,137,141].Other multi-criteria decision analysis methods addressed in this study include the min-max approach [123,126,134,138,160]; rank order centroid (ROC) in [136] and TOPSIS in [141], respectively.A detailed account of MCDA methods can be found in [168,169].

Analysis of Potential Methods in MOP Formulations
The analysis of potential methods in MOP formulation, aiming at optimized SDN planning, are summarized, from the perspective of various performance indicators, in Table 4.The performance indicators include sub-optimizations in MOP formulations, respective execution (implementation and coding), and computation cost, solution quality, initial parameter dependence (tuning complexity) and application.The performance indicators have shown with desired requirements, as best (√), better/average (❉) and poor (×) as indication metrics, respectively.Table 4. Brief comparison review of the merits and demerits of potential approaches applied for SDN planning.employed MH/AI techniques [26].The prominent techniques include harmony search (HS), big bang big crunch (BB-BC), artificial bee colony (ABC), immune algorithm (IA), simulated annealing (SA), honey bee mating (HBMO), ant colony optimization (ACO), bat algorithm (BA), differential evolution (DE), gravitational search algorithm (GSA), shuffled frog leaping (SFL) and hybrid algorithms respectively.Hybrid MH/AI methods results in efficient performance towards global solution aiming at complex planning problems [26].The use of the aforesaid methods, from a future SDN planning viewpoint, offers potential research perspectives.

Decision-Making Methods
The decision making (DM) methods are vital, both as main optimization algorithms and as a means of sorting out a trade-off solutions among a set of multiple conflicting objectives.The prominent DM techniques addressed in the literature (Table 3) include weight methods that include both weighted sum (WSM) and product (WPM) methods, respectively, as in [132,139,140,148,149,157]. The analytical hierarchy process (AHP) has been employed for both long and short term SDN planning, as in [124,154].Fuzzy decision making (FDM) is among the most popular DM methods and employed in many studies, mainly due to its ability to address varying, uncertain nature and various scenarios of the concerned problem.The FDM aiming at MOP problems has been employed in literature with various variants and associated methods as in [86,125,128,133,135,137,141].Other multi-criteria decision analysis methods addressed in this study include the min-max approach [123,126,134,138,160]; rank order centroid (ROC) in [136] and TOPSIS in [141], respectively.A detailed account of MCDA methods can be found in [168,169].

Analysis of Potential Methods in MOP Formulations
The analysis of potential methods in MOP formulation, aiming at optimized SDN planning, are summarized, from the perspective of various performance indicators, in Table 4.The performance indicators include sub-optimizations in MOP formulations, respective execution (implementation and coding), and computation cost, solution quality, initial parameter dependence (tuning complexity) and application.The performance indicators have shown with desired requirements, as best (√), better/average (❉) and poor (×) as indication metrics, respectively.Table 4. Brief comparison review of the merits and demerits of potential approaches applied for SDN planning.employed MH/AI techniques [26].The prominent techniques include harmony search (HS), big bang big crunch (BB-BC), artificial bee colony (ABC), immune algorithm (IA), simulated annealing (SA), honey bee mating (HBMO), ant colony optimization (ACO), bat algorithm (BA), differential evolution (DE), gravitational search algorithm (GSA), shuffled frog leaping (SFL) and hybrid algorithms respectively.Hybrid MH/AI methods results in efficient performance towards global solution aiming at complex planning problems [26].The use of the aforesaid methods, from a future SDN planning viewpoint, offers potential research perspectives.

Decision-Making Methods
The decision making (DM) methods are vital, both as main optimization algorithms and as a means of sorting out a trade-off solutions among a set of multiple conflicting objectives.The prominent DM techniques addressed in the literature (Table 3) include weight methods that include both weighted sum (WSM) and product (WPM) methods, respectively, as in [132,139,140,148,149,157]. The analytical hierarchy process (AHP) has been employed for both long and short term SDN planning, as in [124,154].Fuzzy decision making (FDM) is among the most popular DM methods and employed in many studies, mainly due to its ability to address varying, uncertain nature and various scenarios of the concerned problem.The FDM aiming at MOP problems has been employed in literature with various variants and associated methods as in [86,125,128,133,135,137,141].Other multi-criteria decision analysis methods addressed in this study include the min-max approach [123,126,134,138,160]; rank order centroid (ROC) in [136] and TOPSIS in [141], respectively.A detailed account of MCDA methods can be found in [168,169].

Analysis of Potential Methods in MOP Formulations
The analysis of potential methods in MOP formulation, aiming at optimized SDN planning, are summarized, from the perspective of various performance indicators, in Table 4.The performance indicators include sub-optimizations in MOP formulations, respective execution (implementation and coding), and computation cost, solution quality, initial parameter dependence (tuning complexity) and application.The performance indicators have shown with desired requirements, as best (√), better/average (❉) and poor (×) as indication metrics, respectively.Table 4. Brief comparison review of the merits and demerits of potential approaches applied for SDN planning.employed MH/AI techniques [26].The prominent techniques include harmony search (HS), big bang big crunch (BB-BC), artificial bee colony (ABC), immune algorithm (IA), simulated annealing (SA), honey bee mating (HBMO), ant colony optimization (ACO), bat algorithm (BA), differential evolution (DE), gravitational search algorithm (GSA), shuffled frog leaping (SFL) and hybrid algorithms respectively.Hybrid MH/AI methods results in efficient performance towards global solution aiming at complex planning problems [26].The use of the aforesaid methods, from a future SDN planning viewpoint, offers potential research perspectives.

Decision-Making Methods
The decision making (DM) methods are vital, both as main optimization algorithms and as a means of sorting out a trade-off solutions among a set of multiple conflicting objectives.The prominent DM techniques addressed in the literature (Table 3) include weight methods that include both weighted sum (WSM) and product (WPM) methods, respectively, as in [132,139,140,148,149,157]. The analytical hierarchy process (AHP) has been employed for both long and short term SDN planning, as in [124,154].Fuzzy decision making (FDM) is among the most popular DM methods and employed in many studies, mainly due to its ability to address varying, uncertain nature and various scenarios of the concerned problem.The FDM aiming at MOP problems has been employed in literature with various variants and associated methods as in [86,125,128,133,135,137,141].Other multi-criteria decision analysis methods addressed in this study include the min-max approach [123,126,134,138,160]; rank order centroid (ROC) in [136] and TOPSIS in [141], respectively.A detailed account of MCDA methods can be found in [168,169].

Analysis of Potential Methods in MOP Formulations
The analysis of potential methods in MOP formulation, aiming at optimized SDN planning, are summarized, from the perspective of various performance indicators, in Table 4.The performance indicators include sub-optimizations in MOP formulations, respective execution (implementation and coding), and computation cost, solution quality, initial parameter dependence (tuning complexity) and application.The performance indicators have shown with desired requirements, as best (√), better/average (❉) and poor (×) as indication metrics, respectively.Table 4. Brief comparison review of the merits and demerits of potential approaches applied for SDN planning.employed MH/AI techniques [26].The prominent techniques include harmony search (HS), big bang big crunch (BB-BC), artificial bee colony (ABC), immune algorithm (IA), simulated annealing (SA), honey bee mating (HBMO), ant colony optimization (ACO), bat algorithm (BA), differential evolution (DE), gravitational search algorithm (GSA), shuffled frog leaping (SFL) and hybrid algorithms respectively.Hybrid MH/AI methods results in efficient performance towards global solution aiming at complex planning problems [26].The use of the aforesaid methods, from a future SDN planning viewpoint, offers potential research perspectives.

Decision-Making Methods
The decision making (DM) methods are vital, both as main optimization algorithms and as a means of sorting out a trade-off solutions among a set of multiple conflicting objectives.The prominent DM techniques addressed in the literature (Table 3) include weight methods that include both weighted sum (WSM) and product (WPM) methods, respectively, as in [132,139,140,148,149,157]. The analytical hierarchy process (AHP) has been employed for both long and short term SDN planning, as in [124,154].Fuzzy decision making (FDM) is among the most popular DM methods and employed in many studies, mainly due to its ability to address varying, uncertain nature and various scenarios of the concerned problem.The FDM aiming at MOP problems has been employed in literature with various variants and associated methods as in [86,125,128,133,135,137,141].Other multi-criteria decision analysis methods addressed in this study include the min-max approach [123,126,134,138,160]; rank order centroid (ROC) in [136] and TOPSIS in [141], respectively.A detailed account of MCDA methods can be found in [168,169].

Analysis of Potential Methods in MOP Formulations
The analysis of potential methods in MOP formulation, aiming at optimized SDN planning, are summarized, from the perspective of various performance indicators, in Table 4.The performance indicators include sub-optimizations in MOP formulations, respective execution (implementation and coding), and computation cost, solution quality, initial parameter dependence (tuning complexity) and application.The performance indicators have shown with desired requirements, as best (√), better/average (❉) and poor (×) as indication metrics, respectively.Table 4. Brief comparison review of the merits and demerits of potential approaches applied for SDN planning.employed MH/AI techniques [26].The prominent techniques incl bang big crunch (BB-BC), artificial bee colony (ABC), immune algor (SA), honey bee mating (HBMO), ant colony optimization (ACO), evolution (DE), gravitational search algorithm (GSA), shuffled f algorithms respectively.Hybrid MH/AI methods results in efficie solution aiming at complex planning problems [26].The use of the a SDN planning viewpoint, offers potential research perspectives.

Decision-Making Methods
The decision making (DM) methods are vital, both as main op means of sorting out a trade-off solutions among a set of mult prominent DM techniques addressed in the literature (Table 3) inclu both weighted sum (WSM) and product (WPM) me [132,139,140,148,149,157]. The analytical hierarchy process (AHP) ha and short term SDN planning, as in [124,154].Fuzzy decision mak popular DM methods and employed in many studies, mainly due t uncertain nature and various scenarios of the concerned proble problems has been employed in literature with various variants [86,125,128,133,135,137,141].Other multi-criteria decision analysis m include the min-max approach [123,126,134,138,160]; rank order cent in [141], respectively.A detailed account of MCDA methods can be f

Analysis of Potential Methods in MOP Formulations
The analysis of potential methods in MOP formulation, aiming summarized, from the perspective of various performance indicato indicators include sub-optimizations in MOP formulations, respec and coding), and computation cost, solution quality, initial p complexity) and application.The performance indicators have show best (√), better/average (❉) and poor (×) as indication metrics, respec Table 4. Brief comparison review of the merits and demerits of potentia planning.

Decision-Making Methods
The decision making (DM) methods are vital, both as main optimization algorithms and as a means of sorting out a trade-off solutions among a set of multiple conflicting objectives.The prominent DM techniques addressed in the literature (Table 3) include weight methods that include both weighted sum (WSM) and product (WPM) methods, respectively, as in [132,139,140,148,149,157]. The analytical hierarchy process (AHP) has been employed for both long and short term SDN planning, as in [124,154].Fuzzy decision making (FDM) is among the most popular DM methods and employed in many studies, mainly due to its ability to address varying, uncertain nature and various scenarios of the concerned problem.The FDM aiming at MOP problems has been employed in literature with various variants and associated methods as in [86,125,128,133,135,137,141].Other multi-criteria decision analysis methods addressed in this study include the min-max approach [123,126,134,138,160]; rank order centroid (ROC) in [136] and TOPSIS in [141], respectively.A detailed account of MCDA methods can be found in [168,169].

Analysis of Potential Methods in MOP Formulations
The analysis of potential methods in MOP formulation, aiming at optimized SDN planning, are summarized, from the perspective of various performance indicators, in Table 4.The performance indicators include sub-optimizations in MOP formulations, respective execution (implementation and coding), and computation cost, solution quality, initial parameter dependence (tuning complexity) and application.The performance indicators have shown with desired requirements, as best (√), better/average (❉) and poor (×) as indication metrics, respectively.Table 4. Brief comparison review of the merits and demerits of potential approaches applied for SDN planning.employed MH/AI techniques [26].The prominent techniques include harmony search (HS), big bang big crunch (BB-BC), artificial bee colony (ABC), immune algorithm (IA), simulated annealing (SA), honey bee mating (HBMO), ant colony optimization (ACO), bat algorithm (BA), differential evolution (DE), gravitational search algorithm (GSA), shuffled frog leaping (SFL) and hybrid algorithms respectively.Hybrid MH/AI methods results in efficient performance towards global solution aiming at complex planning problems [26].The use of the aforesaid methods, from a future SDN planning viewpoint, offers potential research perspectives.

Decision-Making Methods
The decision making (DM) methods are vital, both as main optimization algorithms and as a means of sorting out a trade-off solutions among a set of multiple conflicting objectives.The prominent DM techniques addressed in the literature (Table 3) include weight methods that include both weighted sum (WSM) and product (WPM) methods, respectively, as in [132,139,140,148,149,157]. The analytical hierarchy process (AHP) has been employed for both long and short term SDN planning, as in [124,154].Fuzzy decision making (FDM) is among the most popular DM methods and employed in many studies, mainly due to its ability to address varying, uncertain nature and various scenarios of the concerned problem.The FDM aiming at MOP problems has been employed in literature with various variants and associated methods as in [86,125,128,133,135,137,141].Other multi-criteria decision analysis methods addressed in this study include the min-max approach [123,126,134,138,160]; rank order centroid (ROC) in [136] and TOPSIS in [141], respectively.A detailed account of MCDA methods can be found in [168,169].

Analysis of Potential Methods in MOP Formulations
The analysis of potential methods in MOP formulation, aiming at optimized SDN planning, are summarized, from the perspective of various performance indicators, in Table 4.The performance indicators include sub-optimizations in MOP formulations, respective execution (implementation and coding), and computation cost, solution quality, initial parameter dependence (tuning complexity) and application.The performance indicators have shown with desired requirements, as best (√), better/average (❉) and poor (×) as indication metrics, respectively.Table 4. Brief comparison review of the merits and demerits of potential approaches applied for SDN planning.employed MH/AI techniques [26].The prominent techniques include harmony search (HS), big bang big crunch (BB-BC), artificial bee colony (ABC), immune algorithm (IA), simulated annealing (SA), honey bee mating (HBMO), ant colony optimization (ACO), bat algorithm (BA), differential evolution (DE), gravitational search algorithm (GSA), shuffled frog leaping (SFL) and hybrid algorithms respectively.Hybrid MH/AI methods results in efficient performance towards global solution aiming at complex planning problems [26].The use of the aforesaid methods, from a future SDN planning viewpoint, offers potential research perspectives.

Decision-Making Methods
The decision making (DM) methods are vital, both as main optimization algorithms and as a means of sorting out a trade-off solutions among a set of multiple conflicting objectives.The prominent DM techniques addressed in the literature (Table 3) include weight methods that include both weighted sum (WSM) and product (WPM) methods, respectively, as in [132,139,140,148,149,157]. The analytical hierarchy process (AHP) has been employed for both long and short term SDN planning, as in [124,154].Fuzzy decision making (FDM) is among the most popular DM methods and employed in many studies, mainly due to its ability to address varying, uncertain nature and various scenarios of the concerned problem.The FDM aiming at MOP problems has been employed in literature with various variants and associated methods as in [86,125,128,133,135,137,141].Other multi-criteria decision analysis methods addressed in this study include the min-max approach [123,126,134,138,160]; rank order centroid (ROC) in [136] and TOPSIS in [141], respectively.A detailed account of MCDA methods can be found in [168,169].

Analysis of Potential Methods in MOP Formulations
The analysis of potential methods in MOP formulation, aiming at optimized SDN planning, are summarized, from the perspective of various performance indicators, in Table 4.The performance indicators include sub-optimizations in MOP formulations, respective execution (implementation and coding), and computation cost, solution quality, initial parameter dependence (tuning complexity) and application.The performance indicators have shown with desired requirements, as best (√), better/average (❉) and poor (×) as indication metrics, respectively.Table 4. Brief comparison review of the merits and demerits of potential approaches applied for SDN planning.employed MH/AI techniques [26].The prominent techniques includ bang big crunch (BB-BC), artificial bee colony (ABC), immune algorit (SA), honey bee mating (HBMO), ant colony optimization (ACO), ba evolution (DE), gravitational search algorithm (GSA), shuffled fro algorithms respectively.Hybrid MH/AI methods results in efficient solution aiming at complex planning problems [26].The use of the afo SDN planning viewpoint, offers potential research perspectives.

Decision-Making Methods
The decision making (DM) methods are vital, both as main opti means of sorting out a trade-off solutions among a set of multip prominent DM techniques addressed in the literature (Table 3) include both weighted sum (WSM) and product (WPM) meth [132,139,140,148,149,157]. The analytical hierarchy process (AHP) has and short term SDN planning, as in [124,154].Fuzzy decision makin popular DM methods and employed in many studies, mainly due to uncertain nature and various scenarios of the concerned problem problems has been employed in literature with various variants a [86,125,128,133,135,137,141].Other multi-criteria decision analysis me include the min-max approach [123,126,134,138,160]; rank order centro in [141], respectively.A detailed account of MCDA methods can be fou

Analysis of Potential Methods in MOP Formulations
The analysis of potential methods in MOP formulation, aiming at summarized, from the perspective of various performance indicators indicators include sub-optimizations in MOP formulations, respectiv and coding), and computation cost, solution quality, initial par complexity) and application.The performance indicators have shown best (√), better/average (❉) and poor (×) as indication metrics, respecti  ) and poor (×).

Challenges and Future Research Directions
The current challenges in SDN planning and possible research directions have arranged from viewpoint of each SGP classification and presented throughout Sections 8.1-8.4,as follows.New simulators and solvers (for various scenarios), pilot projects and support tools.FoC: Proposing consumer-centered schemes for active participation (DM) in grid operations.

MDC Perspective
The futuristic SDN planning, like traditional counterpart, can be addressed as an expansion and new planning development.The MDCs is envisioned as being intelligent in nature, interconnected in structure and capable of accommodating bidirectional power (& communication)  The limitations in current standards and guidelines result in a variety of MDCs, complex variations and definitions across the globe.Unlike hierarchal TGs, SG and associated concepts must be differentiated on a distinct scale of implementation, which includes geographical and electrical boundaries, respectively.The proposed primitive architecture of SDN planning based on distinct scaling approach is illustrated in Figure 9.The approach indicates the scale of implementation of each MDC concept on the basis of geographical area, starting from small scale (such as SH, SB, and MG) to medium scale (MG, LDN/MDN, MMG, and VPP) and finally large scale (LDN, MMG, VPP and SC).Among six scale levels (SL), SL1 indicates the small SL and covers MDCs like SH and SB on the consumer side of the smart meter.The SL1 has briefly discussed in following Section 8.2.3.1 and shown with the dotted box in Figure 9.The medium scale level (SL2) covers MG.Medium/large scale level covers SL3 (MG, LDN), SL4 (LDN, MDN, and MMG) and SL5 indicated a variant of medium/large scale level covers VPP.Finally, SL6 indicates SC that covers all the MDC on the utility's end and is briefly discussed in the following Section 8.2.3.2 and shown with composite boxes in Figure 9, respectively.o Large-SL6: SC houses all MDC on large (city) scale, as shown in Figures 7b and 9, respectively.

PWP Perspective
The SDN concept (MDC) realization have motivated stakeholders such as many countries (regions), leading policy makers, research institutes, and researchers, towards efforts from various perspectives, as shown in Table 5, since the cost is a vital factor (constraint) in traditional planning.However, the SDN development under the SG paradigm need to compromise cost constraints to a certain level.The pilot projects and policies around the world offer valuable experience that can help stakeholders to utilize maximum key enabler (SGTF) potential in mature SDN planning strategies.Technical and other objectives need to be prioritized in DM and the cost impact needs to be considered over a certain planning horizon.The prominent SDN motivations around the globe, with possible key enablers (SGTF), prominent stakeholders and focused objectives are presented in Table 5.

•
Likely features: Technical, economic and environmental/social objectives-based approaches must be introduced in HEMS to enable and serve consumers towards efficient scheduling of available resources.Also, flexible home automation systems (for consumer interaction in real-time) need further consideration.

•
The scale of implementation: Small Scale Level-SL1: The possible scale-based planning approach starts from consumer level MDC (SH and SB) at smart meter side (of consumers).
However, SDNs have expected to be interconnected in nature and complex in operation, hence, traditional power/load flow methods may not be applicable.

Optimized Initial Parameters Setting
The optimized initial parameterization can help both inner and outer optimization, in finding a global optimal solution at less computation cost and time, respectively.Simply, optimize initial parameters, speed-up the whole optimization process.The optimal weight allocation in DM can provide a feasible trade-off and can avoid surpassing technically (reliable/feasible) solutions in comparison with a cost effective oriented solution.SDN simulators and pilot projects can provide an opportunity for finding optimal objective weights to speed-up the DM process.

Conclusions
In this paper, the smart distribution network (SDN) as a SG modernization concept has presented from a planning perspective.SDN planning has motivated by various key enabling technologies and features under the SG paradigm that was limited in traditional planning (TDP).Since SDN will be capable of accommodating bi-directional power flow and is interconnected in nature and operation, as a consequence, traditional planning techniques and tools may not remain relevant.
The requirement of smooth SDN evolution needs roadmaps (plans and policies) for building new consumption models (MDC) either from the start or intelligently expands the traditional RDN.Thus, the SDN concept has presented via SGP, which includes SGTF, MDC, PWP, and RWO, respectively.The SGTF have been reviewed on the basis of their literature, limitations, applications, associated technologies, and benefits towards the realization of SDN concepts.Similarly, the expected SGAF have been reviewed by means of objective attainment, concept realization features, limitations, and SGET, which can be helpful in optimal SDN planning and operation.The new consumption models or MDC have been reviewed as potential SDN candidates, primarily by concepts, architecture, literature, prominent features, requirements, associated SGTF and research directions, respectively.
The SG policies of seven leading countries (and regions) with key guidelines, major policy objectives and core motivation (focus) with respective SGTF have been summarized in Table 1.Also, the fifteen notable SDN projects with associated details, related SGET, aimed SGAF and required objectives in the form of indicators (OI) have been presented in Table 2.
The real world optimization (RWO) planning problems, due to the involvement of a large number of stakeholders, are multi-objective (MO) in nature.MOP tools can provide trade-off solutions of the concerned problem among contradictory objectives and satisfy multiple stakeholders.The MOP problems aiming at SDN (MDC) have emphasized the need to address as aggregated planning model (APM).The main aim of the APM is to ensure the long-term success of MDC under SDN, on both technical and economic basis.
The current status of MOP-based literature works associated with SDN has been thoroughly reviewed and arranged in Table 3.Moreover, MOP formulations have been investigated on the basis of their structure, such as interaction between initialization, inner and outer optimization, decisionmaking procedures and respective solution techniques, respectively.It has been found that analytical and numerical techniques constitute the maximum portion of the inner optimization.MH/AI makes a large portion of outer optimization (for a set of feasible solutions) and MCDA methods represent a prominent portion of DM solutions.A brief comparison of MOO-based solution techniques applied for SDN planning, on the basis of merits and demerits, has illustrated in Table 4.
The challenges in SDN planning, possible research directions for their solutions and research motivations have arranged according to each classification in SGP.The research options in SGET have been presented as infrastructure limitations, need for improved methods and issues in the existing phase of respective technology.Similarly, SGAF was reviewed on the basis of operational issues, performance indication and limitation in addressing techniques.
The futuristic SDN planning has been addressed, as proposed primitive architecture on a distinct scale of implementation, including both electrical and geographical boundaries.The scaling approaches have two categories: the first corresponds to small scale MDC (such as SH, SB, and MG) on the consumer side and the rest of MDC on the utility side of the smart meter, respectively.In addition, the prominent SDN motivations around the globe were presented in Table 5, with possible key enablers (SGTF), prominent stakeholders and focused objectives.
Finally, integrated planning approaches and new power flow models should be further explored, aiming at efficient SDN planning.Also, artificial intelligence (AI) and hybrid techniques need to be employed for MOP problems in finding global optimal solutions.Still, limitations in new planning tools, hot (optimally predefined parameters) initialization methods, improved solution techniques and prioritization of decision objectives weights serves as a prospective research area to exploit various SDN planning options.

Figure 1 .
Figure 1.Development process of distribution grids from the past to a smart future (adapted from IEA [21]).

Figure 1 .
Figure 1.Development process of distribution grids from the past to a smart future (adapted from IEA [21]).

( 3 )Figure 2 .
Figure 2. Overarching Diagram of the Smart Grid Package (SGP) in the paper.Figure 2. Overarching Diagram of the Smart Grid Package (SGP) in the paper.

Figure 2 .
Figure 2. Overarching Diagram of the Smart Grid Package (SGP) in the paper.Figure 2. Overarching Diagram of the Smart Grid Package (SGP) in the paper.

Energies 2017, 10 , 501 33 of 45 o
Medium-SL2: MG equipped with PCC, is capable of islanding and grid connection.o Medium/Large-SL3, SL4: The MG connects with modified (upgraded) LDN/MDN, which can house several MGs, hence realizing MMG concept.o Medium/Large-SL5: Several MG, LDN/MDN, and MMG; can cluster together in a grid connected VPP configuration, on the basis of deregulated market environment.

Figure 9 .
Figure 9. Scale-based planning architecture of SDNs, varying from small (SH) to large level (SC).

Figure 9 .
Figure 9. Scale-based planning architecture of SDNs, varying from small (SH) to large level (SC).

8. 4 . 4 .
New Methods and Tools Still various AI and hybrid techniques have not yet employed in finding a global optimal solution for SDN planning perspective.Despite comparatively highly efficient, they are difficult to code and few examples are available in the literature.Hence, the limitation serves as a likely research area to exploit various SGTF options in SDN planning.8.4.5.Prioritization of Objectives in DM

Table 1 .
Leading countries/unions with SG Policies/SG guidelines.

Table 2 .
Notable SDN-based pilot projects, anticipated objectives, and motives.

Table 3 .
MOP from the perspectives of various MDC Models.

Table 4 .
The performance indicators include sub-optimizations in MOP formulations, respective execution (implementation and coding), and computation cost, solution quality, initial parameter dependence (tuning complexity) and application.The performance indicators have shown with desired requirements, as best (

Table 4 .
Brief comparison review of the merits and demerits of potential approaches applied for SDN planning.

Table 4 .
Brief comparison review of the merits and demerits of potential approaches applied for SDN planning.

Table 4 .
Brief comparison review of the merits and demerits of potential approaches applied for SDN planning.

Table 4 .
Brief comparison review of the merits and demerits of potential a planning.
flows.8.2.1.Expansion/Modification-Based SDN Planning • Candidate SDNs: Modification of RDN (ARDN) to LDN and/or MDN with SGTF support.• Motivation: Maximum objective attainment (multi-objective optimization).• Likely features: ADA, ICT, MAS (advance control) and advanced protection schemes.8.2.2.Emerging Concepts-Based New SDN Planning • Candidate SDNs: MG and MMG concepts mainly center on the innovations in enabling SG hardware (EST, EV, PE, etc.).The SH, SB, VPP and SC, on the other hand, depends on main innovations in automation, ICT, and control technologies, respectively.• Motivation: Develop new specified standards, formulation of new tools and techniques.• Likely features: Still gray research areas in MOP under SGTF from a MDC perspective.The possible research-worthy areas include power quality, stability, reliability and DER housing.8.2.3.Futuristic SDN Planning Based on Scaling Approach

Table 5 .
The PWP perspective of SDN planning.