Special Issue "Distributed Energy Resources Management"

A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: closed (15 September 2017).

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editor

Dr. Pedro Faria
E-Mail Website
Guest Editor
GECAD–Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Polytechnic of Porto, Portugal
Interests: demand response; electricity markets; renewable energy integration; real-time simulation; smart grids; virtual power players
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Special Issue Information

Dear Colleagues,

The impact of distributed energy resources in the operation of power and energy systems is nowadays unquestionable at the distribution level, but also at the whole power system management level. Increased flexibility is required to accommodate intermittent distributed generation and electric vehicles charging. Demand response already proved to have a great potential to contribute to an increased system efficiency while bringing additional benefits, especially to the consumers. Distributed storage is also promising, i.e., when jointly used with the currently increasing use of photovoltaic panels.

This Special Issue will address the management of distributed energy resources. The focus will include methods and techniques to achieve an optimized operation, to aggregate the resources namely by virtual power players, and to remunerate them. The integration of distributed resources in electricity markets will also be addressed as a main drive for their efficient use.

Dr. Pedro Faria
Guest Editor

Manuscript Submission Information

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Keywords

  • demand response

  • distributed energy resources

  • distributed generation

  • electric vehicles

  • energy resource optimization

  • energy storage

  • intelligent resource management

  • renewable energy sources

  • smart grids

Published Papers (14 papers)

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Editorial

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Open AccessEditorial
Distributed Energy Resources Management
Energies 2019, 12(3), 550; https://doi.org/10.3390/en12030550 - 11 Feb 2019
Abstract
The impact of distributed energy resources in the operation of power and energy systems is nowadays unquestionable at the distribution level but also at the whole power system management level [...] Full article
(This article belongs to the Special Issue Distributed Energy Resources Management) Printed Edition available

Research

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Open AccessArticle
Reschedule of Distributed Energy Resources by an Aggregator for Market Participation
Energies 2018, 11(4), 713; https://doi.org/10.3390/en11040713 - 22 Mar 2018
Cited by 7
Abstract
Demand response aggregators have been developed and implemented all through the world with more seen in Europe and the United States. The participation of aggregators in energy markets improves the access of small-size resources to these, which enables successful business cases for demand-side [...] Read more.
Demand response aggregators have been developed and implemented all through the world with more seen in Europe and the United States. The participation of aggregators in energy markets improves the access of small-size resources to these, which enables successful business cases for demand-side flexibility. The present paper proposes aggregator’s assessment of the integration of distributed energy resources in energy markets, which provides an optimized reschedule. An aggregation and remuneration model is proposed by using the k-means and group tariff, respectively. The main objective is to identify the available options for the aggregator to define tariff groups for the implementation of demand response. After the first schedule, the distributed energy resources are aggregated into a given number of groups. For each of the new groups, a new tariff is computed and the resources are again scheduled according to the new group tariff. In this way, the impact of implementing the new tariffs is analyzed in order to support a more sustained decision to be taken by the aggregator. A 180-bus network in the case study accommodates 90 consumers, 116 distributed generators, and one supplier. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management) Printed Edition available
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Open AccessArticle
Aggregation Potentials for Buildings—Business Models of Demand Response and Virtual Power Plants
Energies 2017, 10(10), 1646; https://doi.org/10.3390/en10101646 - 20 Oct 2017
Cited by 10
Abstract
Buildings as prosumers have an important role in the energy aggregation market due to their potential flexible energy consumption and distributed energy resources. However, energy flexibility provided by buildings can be very complex and depend on many factors. The immaturity of the current [...] Read more.
Buildings as prosumers have an important role in the energy aggregation market due to their potential flexible energy consumption and distributed energy resources. However, energy flexibility provided by buildings can be very complex and depend on many factors. The immaturity of the current aggregation market with unclear incentives is still a challenge for buildings to participate in the aggregation market. However, few studies have investigated business models for building participation in the aggregation market. Therefore, this paper develops four business models for buildings to participate in the energy aggregation market: (1) buildings participate in the implicit Demand Response (DR) program via retailers; (2) buildings with small energy consumption participate in the explicit DR via aggregators; (3) buildings directly access the explicit DR program; (4) buildings access energy market via Virtual Power Plant (VPP) aggregators by providing Distributed Energy Resources (DER)s. This paper also determines that it is essential to understand building owners’ needs, comforts, and behaviours to develop feasible market access strategies for different types of buildings. Meanwhile, the incentive programs, national regulations and energy market structures strongly influence buildings’ participation in the aggregation market. Under the current Nordic market regulation, business model one is the most feasible one, and business model two faces more challenges due to regulation barriers and limited monetary incentives. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management) Printed Edition available
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Open AccessArticle
Location of Faults in Power Transmission Lines Using the ARIMA Method
Energies 2017, 10(10), 1596; https://doi.org/10.3390/en10101596 - 13 Oct 2017
Cited by 7
Abstract
One of the major problems in transmission lines is the occurrence of failures that affect the quality of the electric power supplied, as the exact localization of the fault must be known for correction. In order to streamline the work of maintenance teams [...] Read more.
One of the major problems in transmission lines is the occurrence of failures that affect the quality of the electric power supplied, as the exact localization of the fault must be known for correction. In order to streamline the work of maintenance teams and standardize services, this paper proposes a method of locating faults in power transmission lines by analyzing the voltage oscillographic signals extracted at the line monitoring terminals. The developed method relates time series models obtained specifically for each failure pattern. The parameters of the autoregressive integrated moving average (ARIMA) model are estimated in order to adjust the voltage curves and calculate the distance from the initial fault localization to the terminals. Simulations of the failures are performed through the ATPDraw ® (5.5) software and the analyses were completed using the RStudio ® (1.0.143) software. The results obtained with respect to the failures, which did not involve earth return, were satisfactory when compared with widely used techniques in the literature, particularly when the fault distance became larger in relation to the beginning of the transmission line. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management) Printed Edition available
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Open AccessArticle
Demand-Side Energy Management Based on Nonconvex Optimization in Smart Grid
Energies 2017, 10(10), 1538; https://doi.org/10.3390/en10101538 - 04 Oct 2017
Cited by 2
Abstract
Demand-side energy management is used for regulating the consumers’ energy usage in smart grid. With the guidance of the grid’s price policy, the consumers can change their energy consumption in response. The objective of this study is jointly optimizing the load status and [...] Read more.
Demand-side energy management is used for regulating the consumers’ energy usage in smart grid. With the guidance of the grid’s price policy, the consumers can change their energy consumption in response. The objective of this study is jointly optimizing the load status and electric supply, in order to make a tradeoff between the electric cost and the thermal comfort. The problem is formulated into a nonconvex optimization model. The multiplier method is used to solve the constrained optimization, and the objective function is transformed to the augmented Lagrangian function without constraints. Hence, the Powell direction acceleration method with advance and retreat is applied to solve the unconstrained optimization. Numerical results show that the proposed algorithm can achieve the balance between the electric supply and demand, and the optimization variables converge to the optimum. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management) Printed Edition available
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Open AccessFeature PaperArticle
A Decentralized Multi-Agent-Based Approach for Low Voltage Microgrid Restoration
Energies 2017, 10(10), 1491; https://doi.org/10.3390/en10101491 - 27 Sep 2017
Cited by 8
Abstract
Although a well-organized power system is less subject to blackouts, the existence of a proper restoration plan is nevertheless still essential. The goal of a restoration plan is to bring the power system back to its normal operating conditions in the shortest time [...] Read more.
Although a well-organized power system is less subject to blackouts, the existence of a proper restoration plan is nevertheless still essential. The goal of a restoration plan is to bring the power system back to its normal operating conditions in the shortest time after a blackout occurs and to minimize the impact of the blackout on society. This paper presents a decentralized multi-agent system (MAS)-based restoration method for a low voltage (LV) microgrid (MG). In the proposed method, the MG local controllers are assigned to the specific agents who interact with each other to achieve a common decision in the restoration procedure. The evaluation of the proposed decentralized technique using a benchmark low-voltage MG network demonstrates the effectiveness of the proposed restoration plan. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management) Printed Edition available
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Open AccessArticle
Demand Response Unit Commitment Problem Solution for Maximizing Generating Companies’ Profit
Energies 2017, 10(10), 1465; https://doi.org/10.3390/en10101465 - 22 Sep 2017
Cited by 6
Abstract
Over the recent years there has been an immense growth in load consumption due to which, Load Management (LM) has become more significant. Energy providers around the world apply different load management concepts and techniques to improve the load profile. In order to [...] Read more.
Over the recent years there has been an immense growth in load consumption due to which, Load Management (LM) has become more significant. Energy providers around the world apply different load management concepts and techniques to improve the load profile. In order to reduce the stress over the load management, Demand Response Unit Commitment (DRUC), a new concept, has been implemented in this paper. The main feature of this concept is that both the energy providers and consumers must participate in order to get mutual benefits hence maximizing each of their profits. In this paper we discuss the time-based Demand Response Program since there is no penalty observed in this program. When the Demand Response was combined with Unit Commitment and compiled it was observed that a satisfactory solution resulted, which is proved to be mutually beneficial for both Generating Companies (GENCOs) and their customers. Here, we have used a Cat Swarm Optimization (CSO) technique to find the solution for the DRUC problem. The results are obtained using CSO technique for UC problem with and without DR program. This is compared with the results obtained using other conventional methods. The test system considered for the study is IEEE39 bus system. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management) Printed Edition available
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Open AccessArticle
Energy Flexibility Management Based on Predictive Dispatch Model of Domestic Energy Management System
Energies 2017, 10(9), 1397; https://doi.org/10.3390/en10091397 - 13 Sep 2017
Cited by 13
Abstract
This paper proposes a predictive dispatch model to manage energy flexibility in the domestic energy system. Electric Vehicles (EV), batteries and shiftable loads are devices that provide energy flexibility in the proposed system. The proposed energy management problem consists of two stages: day-ahead [...] Read more.
This paper proposes a predictive dispatch model to manage energy flexibility in the domestic energy system. Electric Vehicles (EV), batteries and shiftable loads are devices that provide energy flexibility in the proposed system. The proposed energy management problem consists of two stages: day-ahead and real time. A hybrid method is defined for the first time in this paper to model the uncertainty of the PV power generation based on its power prediction. In the day-ahead stage, the uncertainty is modeled by interval bands. On the other hand, the uncertainty of PV power generation is modeled through a stochastic scenario-based method in the real-time stage. The performance of the proposed hybrid Interval-Stochastic (InterStoch) method is compared with the Modified Stochastic Predicted Band (MSPB) method. Moreover, the impacts of energy flexibility and the demand response program on the expected profit and transacted electrical energy of the system are assessed in the case study presented in this paper. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management) Printed Edition available
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Open AccessArticle
Optimal Energy Management for Microgrids with Combined Heat and Power (CHP) Generation, Energy Storages, and Renewable Energy Sources
Energies 2017, 10(9), 1288; https://doi.org/10.3390/en10091288 - 29 Aug 2017
Cited by 13
Abstract
This paper studies an energy management problem for a typical grid-connected microgrid system that consists of renewable energy sources, Combined Heat and Power (CHP) co-generation, and energy storages to satisfy electricity and heat demand simultaneously. We formulate this problem into a stochastic non-convex [...] Read more.
This paper studies an energy management problem for a typical grid-connected microgrid system that consists of renewable energy sources, Combined Heat and Power (CHP) co-generation, and energy storages to satisfy electricity and heat demand simultaneously. We formulate this problem into a stochastic non-convex optimization programming to achieve the minimum microgrid’s operating cost, which is difficult to solve due to its non-convexity and coupling feature of constraints. Existing approaches such as dynamic programming (DP) assume that all the system dynamics are known, which results in a high computational complexity and thus are not feasible in practice. The focus of this paper is on the design of a real-time energy management strategy for the optimal operation of microgrids with low computational complexity. Specifically, derived from a modified Lyapunov optimization technique, an online algorithm with random inputs (e.g., the charging/discharging of energy storage devices, power from the CHP system, the electricity from external power grid, and the renewables generation, etc.), which requires no statistic system information, is proposed. We provide an implementation of the proposed energy management algorithm and prove its optimality theoretically. Based on real-world data traces, extensive empirical evaluations are presented to verify the performance of our algorithm. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management) Printed Edition available
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Open AccessArticle
Diffusion Strategy-Based Distributed Operation of Microgrids Using Multiagent System
Energies 2017, 10(7), 903; https://doi.org/10.3390/en10070903 - 02 Jul 2017
Cited by 6
Abstract
In distributed operation, each unit is operated by its local controller instead of using a centralized controller, which allows the action to be based on local information rather than global information. Most of the distributed solutions have implemented the consensus method, however, convergence [...] Read more.
In distributed operation, each unit is operated by its local controller instead of using a centralized controller, which allows the action to be based on local information rather than global information. Most of the distributed solutions have implemented the consensus method, however, convergence time of the consensus method is quite long, while diffusion strategy includes a stochastic gradient term and can reach convergence much faster compared with consensus method. Therefore, in this paper, a diffusion strategy-based distributed operation of microgrids (MGs) is proposed using multiagent system for both normal and emergency operation modes. In normal operation, the MG system is operated by a central controller instead of the distributed controller to minimize the operation cost. If any event (fault) occurs in the system, MG system can be divided into two parts to isolate the faulty region. In this case, the MG system is changed to emergency operation mode. The normal part is rescheduled by the central controller while the isolated part schedules its resources in a distributed manner. The isolated part carries out distributed communication using diffusion between neighboring agents for optimal operation of this part. The proposed method enables peer-to-peer communication among the agents without the necessity of a centralized controller, and simultaneously performs resource optimization. Simulation results show that the system can be operated in an economic way in both normal operation and emergency operation modes. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management) Printed Edition available
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Open AccessArticle
Implementation of a Real-Time Microgrid Simulation Platform Based on Centralized and Distributed Management
Energies 2017, 10(6), 806; https://doi.org/10.3390/en10060806 - 14 Jun 2017
Cited by 19
Abstract
Demand response and distributed generation are key components of power systems. Several challenges are raised at both technical and business model levels for integration of those resources in smart grids and microgrids. The implementation of a distribution network as a test bed can [...] Read more.
Demand response and distributed generation are key components of power systems. Several challenges are raised at both technical and business model levels for integration of those resources in smart grids and microgrids. The implementation of a distribution network as a test bed can be difficult and not cost-effective; using computational modeling is not sufficient for producing realistic results. Real-time simulation allows us to validate the business model’s impact at the technical level. This paper comprises a platform supporting the real-time simulation of a microgrid connected to a larger distribution network. The implemented platform allows us to use both centralized and distributed energy resource management. Using an optimization model for the energy resource operation, a virtual power player manages all the available resources. Then, the simulation platform allows us to technically validate the actual implementation of the requested demand reduction in the scope of demand response programs. The case study has 33 buses, 220 consumers, and 68 distributed generators. It demonstrates the impact of demand response events, also performing resource management in the presence of an energy shortage. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management) Printed Edition available
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Open AccessFeature PaperArticle
Energy Trading and Pricing in Microgrids with Uncertain Energy Supply: A Three-Stage Hierarchical Game Approach
Energies 2017, 10(5), 670; https://doi.org/10.3390/en10050670 - 11 May 2017
Cited by 8
Abstract
This paper studies an energy trading and pricing problem for microgrids with uncertain energy supply. The energy provider with the renewable energy (RE) generation (wind power) determines the energy purchase from the electricity markets and the pricing strategy for consumers to maximize its [...] Read more.
This paper studies an energy trading and pricing problem for microgrids with uncertain energy supply. The energy provider with the renewable energy (RE) generation (wind power) determines the energy purchase from the electricity markets and the pricing strategy for consumers to maximize its profit, and then the consumers determine their energy demands to maximize their payoffs. The hierarchical game is established between the energy provider and the consumers. The energy provider is the leader and the consumers are the followers in the hierarchical game. We consider two types of consumers according to their response to the price, i.e., the price-taking consumers and the price-anticipating consumers. We derive the equilibrium point of the hierarchical game through the backward induction method. Comparing the two types of consumers, we study the influence of the types of consumers on the equilibrium point. In particular, the uncertainty of the energy supply from the energy provider is considered. Simulation results show that the energy provider can obtain more profit using the proposed decision-making scheme. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management) Printed Edition available
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Open AccessArticle
Aggregators’ Optimal Bidding Strategy in Sequential Day-Ahead and Intraday Electricity Spot Markets
Energies 2017, 10(4), 450; https://doi.org/10.3390/en10040450 - 01 Apr 2017
Cited by 9
Abstract
This paper proposes a probabilistic optimization method that produces optimal bidding curves to be submitted by an aggregator to the day-ahead electricity market and the intraday market, considering the flexible demand of his customers (based in time dependent resources such as batteries and [...] Read more.
This paper proposes a probabilistic optimization method that produces optimal bidding curves to be submitted by an aggregator to the day-ahead electricity market and the intraday market, considering the flexible demand of his customers (based in time dependent resources such as batteries and shiftable demand) and taking into account the possible imbalance costs as well as the uncertainty of forecasts (market prices, demand, and renewable energy sources (RES) generation). The optimization strategy aims to minimize the total cost of the traded energy over a whole day, taking into account the intertemporal constraints. The proposed formulation leads to the solution of different linear optimization problems, following the natural temporal sequence of electricity spot markets. Intertemporal constraints regarding time dependent resources are fulfilled through a scheduling process performed after the day-ahead market clearing. Each of the different problems is of moderate dimension and requires short computation times. The benefits of the proposed strategy are assessed comparing the payments done by an aggregator over a sample period of one year following different deterministic and probabilistic strategies. Results show that probabilistic strategy reports better benefits for aggregators participating in power markets. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management) Printed Edition available
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Open AccessArticle
Distributed Control Strategy for Autonomous Operation of Hybrid AC/DC Microgrid
Energies 2017, 10(3), 373; https://doi.org/10.3390/en10030373 - 16 Mar 2017
Cited by 13
Abstract
This paper proposes a distributed control strategy that considers several source characteristics to achieve reliable and efficient operation of a hybrid ac/dc microgrid. The proposed control strategy has a two-level structure. The primary control layer is based on an adaptive droop method, which [...] Read more.
This paper proposes a distributed control strategy that considers several source characteristics to achieve reliable and efficient operation of a hybrid ac/dc microgrid. The proposed control strategy has a two-level structure. The primary control layer is based on an adaptive droop method, which allows local controllers to operate autonomously and flexibly during disturbances such as fault, load variation, and environmental changes. For efficient distribution of power, a higher control layer adjusts voltage reference points based on optimized energy scheduling decisions. The proposed hybrid ac/dc microgrid is composed of converters and distributed generation units that include renewable energy sources (RESs) and energy storage systems (ESSs). The proposed control strategy is verified in various scenarios experimentally and by simulation. Full article
(This article belongs to the Special Issue Distributed Energy Resources Management) Printed Edition available
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