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Advances and Trends in Smart Energy Communities

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "G1: Smart Cities and Urban Management".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 16636

Special Issue Editors


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Guest Editor
Department of Management and Innovation Systems, University of Salerno, 84084 Salerno, Italy
Interests: smart grids; energy management; power systems; demand response
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We would like to invite submissions to a Special Issue of Energies on the subject of smart cities and smart grids, entitled “Advances and Trends in Smart Energy Communities”.

Due to environment concerns, energy security risks, and fossil fuel problems, many countries around the world have decided to implement smart energy communities. These new communities are built based on smart cities and smart grids concepts. One of the main aims in this new environment is to increase the penetration level of renewable energy resources in energy networks. Likewise, there are activities to help achieve the reliable and secure operation of their power systems with a high penetration level of renewable energy resources by the implementation of smart grid concepts, including microgrid, active distribution systems and deregulation concepts in reality. In future smart energy systems, keeping the operation in stable modes requires new techniques and technologies for better controlling and security assessment in such systems. Likewise, reliability, stability and security, which are the main issues in smart grids, should be studied and analyzed. Moreover, new protection schemes are in demand in order to face any unexpected operation problems, contingencies, and cyber-attack issues in the smart grid environment.

In order to cope with ever-increasing operation and control complexity and security in modern and future smart energy communities, new architectures, concepts, algorithms, and procedures are essential. This Special Issue aims to encourage researchers to address the technical issues and research gaps in smart energy communities.

Prof. Dr. Pierluigi Siano
Dr. Hassan Haes Alhelou

Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Smart energy communities;
  • Smart grids and microgrids;
  • Smart electric transportation systems;
  • The design, modeling, and management of smart energy communities, smart grids, and microgrids;
  • Smart energy systems reliability, sustainability, flexibility, and resiliency;
  • Smart energy systems dynamics, stability, protection and security;
  • Methodologies and applications of modern methods for the operation and control of smart grids;
  • Intelligent systems, solving methods, optimization, and advanced heuristics;
  • The modeling, planning, and operating of renewable energy resources;
  • Business models for different electricity market players;
  • Demand side management and demand response;
  • The sizing, placement, and operation of energy storage systems and electric vehicles;
  • Smart homes and building energy management;
  • Electricity market, electrical power, and energy systems;
  • The modeling, forecasting, and management of uncertainty in smart grids;
  • Microgrids and islanded networks;
  • Smart cities, smart energy, and IoT;
  • Modern power systems and renewable energy resources.

Published Papers (7 papers)

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Research

18 pages, 2792 KiB  
Article
Evaluation Metrics to Assess the Most Suitable Energy Community End-Users to Participate in Demand Response
by Ruben Barreto, Calvin Gonçalves, Luis Gomes, Pedro Faria and Zita Vale
Energies 2022, 15(7), 2380; https://doi.org/10.3390/en15072380 - 24 Mar 2022
Cited by 10 | Viewed by 2097
Abstract
In the energy sector, prosumers are becoming relevant entities for energy management systems since they can share energy with their citizen energy community (CEC). Thus, this paper proposes a novel methodology based on demand response (DR) participation in a CEC context, where unsupervised [...] Read more.
In the energy sector, prosumers are becoming relevant entities for energy management systems since they can share energy with their citizen energy community (CEC). Thus, this paper proposes a novel methodology based on demand response (DR) participation in a CEC context, where unsupervised learning algorithms such as convolutional neural networks and k-means are used. This novel methodology can analyze future events on the grid and balance the consumption and generation using end-user flexibility. The end-users’ invitations to the DR event were according to their ranking obtained through three metrics. These metrics were energy flexibility, participation ratio, and flexibility history of the end-users. During the DR event, a continuous balancing assessment is performed to allow the invitation of additional end-users. Real data from a CEC with 50 buildings were used, where the results demonstrated that the end-users’ participation in two DR events allows reduction of energy costs by EUR 1.31, balancing the CEC energy resources. Full article
(This article belongs to the Special Issue Advances and Trends in Smart Energy Communities)
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17 pages, 3124 KiB  
Article
Enhanced Energy Savings with Adaptive Watchful Sleep Mode for Next Generation Passive Optical Network
by Rizwan Aslam Butt, Adnan Akhunzada, Muhammad Faheem and Basit Raza
Energies 2022, 15(5), 1639; https://doi.org/10.3390/en15051639 - 23 Feb 2022
Cited by 2 | Viewed by 1951
Abstract
A single watchful sleep mode (WSM) combines the features of both cyclic sleep mode (CSM) and cyclic doze mode (CDM) in a single process by periodically turning ON and OFF the optical receiver (RX) of the optical network terminal (ONT) in a symmetric [...] Read more.
A single watchful sleep mode (WSM) combines the features of both cyclic sleep mode (CSM) and cyclic doze mode (CDM) in a single process by periodically turning ON and OFF the optical receiver (RX) of the optical network terminal (ONT) in a symmetric manner. This results in almost the same energy savings for the ONTs as achieved by the CSM process while significantly reducing the upstream delays. However, in this study we argue that the periodic ON and OFF periods of the ONT RX is not an energy efficient approach, as it reduces the ONT Asleep (AS) state time. Instead, this study proposes an adaptive watchful sleep mode (AWSM) in which the RX ON time of ONT is minimized during ONT Watch state by choosing it according to the length of the traffic queue of the type 1 (T1) traffic class. The performance of AWSM is compared with standard WSM and CSM schemes. The investigation reveals that by minimizing the RX ON time, the AWSM scheme achieves up to 71% average energy saving per ONT at low traffic loads. The comparative study results show that the ONT energy savings achieved by AWSM are 9% higher than the symmetric WSM with almost the same delay and delay variance performance. Full article
(This article belongs to the Special Issue Advances and Trends in Smart Energy Communities)
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20 pages, 2778 KiB  
Article
Testing Smart Grid Scenarios with Small Volume Testbed and Flexible Power Inverter
by Milosz Krysik, Krzysztof Piotrowski and Krzysztof Turchan
Energies 2022, 15(2), 428; https://doi.org/10.3390/en15020428 - 07 Jan 2022
Cited by 4 | Viewed by 1861
Abstract
The growing penetration of Renewable Energy Sources (RES) due to the transition to future smart grid requires a huge number of power converters that participate in the power flow. Each of these devices needs the use of a complex control and communication system, [...] Read more.
The growing penetration of Renewable Energy Sources (RES) due to the transition to future smart grid requires a huge number of power converters that participate in the power flow. Each of these devices needs the use of a complex control and communication system, thus a platform for testing real-life scenarios is necessary. Several test techniques have been so far proposed that are subject to a trade-off between cost, test coverage, and test fidelity. This paper presents an approach for testing microgrids, by developing an emulator, with emphasis on the micro-inverter unit and the possibility of flexible configuration for different grid topologies. In contrast to other approaches, our testbed is characterized by small volume and significantly scaled-down voltages for safety purposes. The examination is concentrated specifically on the inverter behavior. The test scenarios include behaviors in case of load changes, transition between grid-tied and islanded mode, connection and removal of subsequent inverters, and prioritization of inverters. Full article
(This article belongs to the Special Issue Advances and Trends in Smart Energy Communities)
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23 pages, 5661 KiB  
Article
Elastic Energy Management Algorithm Using IoT Technology for Devices with Smart Appliance Functionality for Applications in Smart-Grid
by Piotr Powroźnik, Paweł Szcześniak and Krzysztof Piotrowski
Energies 2022, 15(1), 109; https://doi.org/10.3390/en15010109 - 23 Dec 2021
Cited by 10 | Viewed by 2595
Abstract
Currently, ensuring the correct functioning of the electrical grid is an important issue in terms of maintaining the normative voltage parameters and local line overloads. The unpredictability of Renewable Energy Sources (RES), the occurrence of the phenomenon of peak demand, as well as [...] Read more.
Currently, ensuring the correct functioning of the electrical grid is an important issue in terms of maintaining the normative voltage parameters and local line overloads. The unpredictability of Renewable Energy Sources (RES), the occurrence of the phenomenon of peak demand, as well as exceeding the voltage level above the nominal values in a smart grid makes it justifiable to conduct further research in this field. The article presents the results of simulation tests and experimental laboratory tests of an electricity management system in order to reduce excessively high grid load or reduce excessively high grid voltage values resulting from increased production of prosumer RES. The research is based on the Elastic Energy Management (EEM) algorithm for smart appliances (SA) using IoT (Internet of Things) technology. The data for the algorithm was obtained from a message broker that implements the Message Queue Telemetry Transport (MQTT) protocol. The complexity of selecting power settings for SA in the EEM algorithm required the use of a solution that is applied to the NP difficult problem class. For this purpose, the Greedy Randomized Adaptive Search Procedure (GRASP) was used in the EEM algorithm. The presented results of the simulation and experiment confirmed the possibility of regulating the network voltage by the Elastic Energy Management algorithm in the event of voltage fluctuations related to excessive load or local generation. Full article
(This article belongs to the Special Issue Advances and Trends in Smart Energy Communities)
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29 pages, 10035 KiB  
Article
A Novel Real-Time Electricity Scheduling for Home Energy Management System Using the Internet of Energy
by Bilal Naji Alhasnawi, Basil H. Jasim, Pierluigi Siano and Josep M. Guerrero
Energies 2021, 14(11), 3191; https://doi.org/10.3390/en14113191 - 29 May 2021
Cited by 35 | Viewed by 2917
Abstract
This paper presents a novel scheduling scheme for the real-time home energy management systems based on Internet of Energy (IoE). The scheme is a multi-agent method that considers two chief purposes including user satisfaction and energy consumption cost. The scheme is designed under [...] Read more.
This paper presents a novel scheduling scheme for the real-time home energy management systems based on Internet of Energy (IoE). The scheme is a multi-agent method that considers two chief purposes including user satisfaction and energy consumption cost. The scheme is designed under environment of microgrid. The user impact in terms of energy cost savings is generally significant in terms of system efficiency. That is why domestic users are involved in the management of domestic appliances. The optimization algorithms are based on an improved version of the rainfall algorithm and the salp swarm algorithm. In this paper, the Time of Use (ToU) model is proposed to define the rates for shoulder-peak and on-peak hours. A two-level communication system connects the microgrid system, implemented in MATLAB, to the cloud server. The local communication level utilizes IP/TCP and MQTT and is used as a protocol for the global communication level. The scheduling controller proposed in this study succeeded the energy saving of 25.3% by using the salp swarm algorithm and saving of 31.335% by using the rainfall algorithm. Full article
(This article belongs to the Special Issue Advances and Trends in Smart Energy Communities)
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15 pages, 1958 KiB  
Article
Assessing Insider Attacks and Privacy Leakage in Managed IoT Systems for Residential Prosumers
by Giuseppe De Marco, Vincenzo Loia, Hadis Karimipour and Pierluigi Siano
Energies 2021, 14(9), 2385; https://doi.org/10.3390/en14092385 - 22 Apr 2021
Cited by 2 | Viewed by 1571
Abstract
The transition towards the massive penetration of Renewable Energy Resources (RESs) into the electricity system requires the implementation of the Smart Grid (SG) paradigm with innovative control systems and equipment. In this new context, Distributed Energy Resources (DERs), including renewable sources and responsive [...] Read more.
The transition towards the massive penetration of Renewable Energy Resources (RESs) into the electricity system requires the implementation of the Smart Grid (SG) paradigm with innovative control systems and equipment. In this new context, Distributed Energy Resources (DERs), including renewable sources and responsive loads, should be redesigned to enable aggregators to provide ancillary services. In fact, by using the Internet of Things (IoT) systems, aggregators can explore energy usage patterns from residential users, also known as prosumers and predict their services. This is undoubtedly important especially for SGs facing the presence of several RESs, where understanding the optimal match between demand and production is desirable from several points of view. However, revealing energy patterns and information can be of concern for privacy if the entire system is not properly designed. In this article, by assuming that the security of low-level communication protocols is guaranteed, we focus our attention at higher levels, in particular at the application level of managed IoT systems used by aggregators. In this regard, we provide an overview of the best practices and outline possible privacy leakages risks along with a list of correlated attacks. Full article
(This article belongs to the Special Issue Advances and Trends in Smart Energy Communities)
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17 pages, 15544 KiB  
Article
A Novel Algorithm to Optimize the Energy Consumption Using IoT and Based on Ant Colony Algorithm
by Baohui Shi and Yuexia Zhang
Energies 2021, 14(6), 1709; https://doi.org/10.3390/en14061709 - 19 Mar 2021
Cited by 10 | Viewed by 2249
Abstract
Internet of Things (IoT) is a new concept in the information and communication technology studies which indicates that any creature (human, animal, or object) can send and receive data through communication networks, such as the internet or intranet platform. Wireless sensors have limited [...] Read more.
Internet of Things (IoT) is a new concept in the information and communication technology studies which indicates that any creature (human, animal, or object) can send and receive data through communication networks, such as the internet or intranet platform. Wireless sensors have limited energy resources due to the use of batteries to supply energy, and since it is usually not possible to replace the batteries of these sensors. In addition, the lifespan of the wireless sensor network is limited and short. Therefore, reducing the energy consumption of sensors in IoT networks for increasing network lifespan is one of the fundamental challenges and issues in these networks. In this paper, a routing protocol is proposed and simulated based on an ant colony optimization algorithm’s performance. The clustering is performed with a routing method based on energy level criteria, collision reduction, distance from the cluster-head to the destination, and neighborhood energy in the proposed method. The cluster head is selected based on the maximum residual energy, minimum distance with other clusters, and consumed energy. This energy is minimized to reach the base station. The node with more energy than the threshold is selected as the new cluster head. Then, four conditions are applied for routing: the shortest path, the leading path, the shortest distance to the source node and the destination node, and routing. Results show that after about 50 cycles of transferring information, only the average of 19.4% of the initial energy is consumed in the network nodes. Therefore, obtained results illustrate that the proposed method helps to retain the energy more than 40% comparing the available methods. Full article
(This article belongs to the Special Issue Advances and Trends in Smart Energy Communities)
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