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Recent Advances in Power Distribution Networks: Applications and Technologies for Local Energy Communities Integration

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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: closed (3 September 2023) | Viewed by 12149

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Special Issue Editors

Dr. Bruno Canizes

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1. GECAD -Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Porto, Portugal
2. ISEP - Institute of Engineering at Polytechnic of Porto, Porto, Portugal
Interests: distribution network planning; operation and reconfiguration; smart grids; smart cities; electric mobility; local energy communities; distributed energy resources management; power systems reliability; future power systems; optimization; electricity markets and intelligent house management systems.
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Prof. Dr. João Soares

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GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, LASI—Intelligent Systems Associate Laboratory, Polytechnic of Porto, 4200-072 Porto, Portugal
Interests: energy resource management; energy systems simulation; electric vehicles; metaheuristic optimization; smart grid; swarm intelligence
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Prof. Dr. Sérgio Ramos

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Guest Editor

Engineering Institute, Polytechnic of Porto, 4200-072 Porto, Portugal
Interests: data mining; artificial intelligence; power systems; electricity markets; renewable energy resources management; shared PV generation; electricity communities
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Dr. Zahra Foroozandeh

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Guest Editor

GECAD-Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Porto, Portugal
Interests: optimal control; calculus of variations and optimization of energy systems

Special Issue Information

Dear Colleagues,

Several innovative developments in power distribution systems have taken place around the world. One of them is related to minimizing the carbon footprint using a large-scale integration of renewable energy sources, such as wind and solar.

Distribution networks are suffering a transition into active networks, creating bidirectional power flows and providing an open way for the integration of distributed energy resources based on renewable energy sources and on the practical implementation of the so-called smart grid. Thus, the evolution of novel concepts such as local energy communities is emerging. According to the European Union strategy, there is interest in placing the citizens as core players in the future energy markets as part of the effort to reduce greenhouse gas emissions. In local energy communities, energy consumers with renewable energy sources on the distribution network will have the right to generate, consume, store, and sell their energy based on renewable energy sources, obtaining equal market opportunities and incentives.

This Special Issue invites original research papers for publication focusing on topics of interest, including but not limited to the following:

Local energy communities’ modeling;
Local energy markets and P2P market modeling;
Innovative models for distribution network planning, operation, reconfiguration, and energy resources management in the smart grid paradigm;
Coordination and interactions between markets at different levels;
Coordination between distribution system operators and energy resource aggregators;
Innovative flexibility strategies for smart distribution grids;
Modern and classical optimization methods applied to distribution systems in a smart grid context;
Electric mobility integration;
Smart grid-enabling technologies (e.g., real-time information systems, communication and control systems, advanced metering systems, reactive power sources, advanced switching, energy storage systems, etc.).

Dr. Bruno Canizes
Prof. Dr. João Soares
Prof. Dr. Sérgio Ramos
Dr. Zahra Foroozandeh
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 grid
distribution power systems
microgrids
local energy communities
optimization techniques
computation intelligence
electricity markets
renewable energy sources
power flexibility
electric mobility
energy storage systems

Published Papers (6 papers)

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Research

17 pages, 5781 KiB

Open AccessArticle

A Novel Renewable Smart Grid Model to Sustain Solar Power Generation

by Mohammad Abdul Baseer and Ibrahim Alsaduni

Energies 2023, 16(12), 4784; https://0-doi-org.brum.beds.ac.uk/10.3390/en16124784 - 18 Jun 2023

Cited by 1 | Viewed by 1831

Abstract

The stability performance of smart grid power systems is critical and requires special attention. Additionally, the combination of Battery Energy Storage (BES) systems, Solar Photovoltaic (SPV), and wind systems in the intelligent grid model provides utilities with excellent efficiency and dependability. However, a coordination grid with PV and other resources frequently results in severe issues, such as outages or power disruptions. A power outage in the grid might result in a power loss in the delivery system. As a result, the distributed grid model’s dependable performance is intended for integrated wind energy, SPV arrays, and BE systems. This paper proposes a renewable intelligent grid model to sustain solar power generation. The model incorporates a boost converter to optimize the performance of solar panels by converting the DC power generated by the panels into AC power for use in the grid. The boost converter is optimized using a novel Horse Herd Optimization Algorithm (HOA) method. In this case, the HOA method is used to optimize the control parameters of the boost converter, such as the duty cycle and the inductor and capacitor values. According to the final results, the proposed method has reduced the Total Harmonic Deformation (THD) and power loss. Additionally, the proposed method outperformed existing strategies related to the Expected Energy Not Supplied (EENS), Loss of Load Probability (LOLP), and Loss of Load Expected (LOLE), indicating the sustainability of power generation. Full article

(This article belongs to the Special Issue Recent Advances in Power Distribution Networks: Applications and Technologies for Local Energy Communities Integration)

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26 pages, 10788 KiB

Open AccessArticle

Local Renewable Energy Communities: Classification and Sizing

by Bruno Canizes, João Costa, Diego Bairrão and Zita Vale

Energies 2023, 16(5), 2389; https://0-doi-org.brum.beds.ac.uk/10.3390/en16052389 - 02 Mar 2023

Cited by 1 | Viewed by 1820

Abstract

The transition from the current energy architecture to a new model is evident and inevitable. The coming future promises innovative and increasingly rigorous projects and challenges for everyone involved in this value chain. Technological developments have allowed the emergence of new concepts, such as renewable energy communities, decentralized renewable energy production, and even energy storage. These factors have incited consumers to play a more active role in the electricity sector and contribute considerably to the achievement of environmental objectives. With the introduction of renewable energy communities, the need to develop new management and optimization tools, mainly in generation and load management, arises. Thus, this paper proposes a platform capable of clustering consumers and prosumers according to their energy and geographical characteristics to create renewable energy communities. Thus, this paper proposes a platform capable of clustering consumers and prosumers according to their energy and geographical characteristics to create renewable energy communities. Moreover, through this platform, the identification (homogeneous energy communities, mixed energy communities, and self-sufficient energy communities) and the size of each community are also obtained. Three algorithms are considered to achieve this purpose: K-means, density-based spatial clustering of applications with noise, and linkage algorithms (single-link, complete-link, average-link, and Wards’ method). With this work, it is possible to verify each algorithm’s behavior and effectiveness in clustering the players into communities. A total of 233 members from 9 cities in the northern region of Portugal (Porto District) were considered to demonstrate the application of the proposed platform. The results demonstrate that the linkage algorithms presented the best classification performance, achieving 0.631 by complete-ink in the Silhouette score, 2124.174 by Ward’s method in the Calinski-Harabasz index, and 0.329 by single-link on the Davies-Bouldin index. Additionally, the developed platform demonstrated adequacy, versatility, and robustness concerning the classification and sizing of renewable energy communities. Full article

(This article belongs to the Special Issue Recent Advances in Power Distribution Networks: Applications and Technologies for Local Energy Communities Integration)

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16 pages, 1637 KiB

Open AccessArticle

Distributed Network-Constrained P2P Community-Based Market for Distribution Networks

by Carlos Oliveira, Micael Simões, Leonardo Bitencourt, Tiago Soares and Manuel A. Matos

Energies 2023, 16(3), 1520; https://0-doi-org.brum.beds.ac.uk/10.3390/en16031520 - 03 Feb 2023

Cited by 4 | Viewed by 1586

Abstract

Energy communities have been designed to empower consumers while maximizing the self-consumption of local renewable energy sources (RESs). Their presence in distribution systems can result in strong modifications in the operation and management of such systems, moving from a centralized operation to a distributed one. In this scope, this work proposes a distributed community-based local energy market that aims at minimizing the costs of each community member, accounting for the technical network constraints. The alternating direction method of multipliers (ADMM) is adopted to distribute the market, and preserve, as much as possible, the privacy of the prosumers’ assets, production, and demand. The proposed method is tested on a 10-bus medium voltage radial distribution network, in which each node contains a large prosumer, and the relaxed branch flow model is adopted to model the optimization problem. The market framework is proposed and modeled in a centralized and distributed fashion. Market clearing on a day-ahead basis is carried out taking into account actual energy exchanges, as generation from renewable sources is uncertain. The comparison between the centralized and distributed ADMM approach shows an 0.098% error for the nodes’ voltages. The integrated OPF in the community-based market is a computational burden that increases the resolution of the market dispatch problem by about eight times the computation time, from 200.7 s (without OPF) to 1670.2 s. An important conclusion is that the proposed market structure guarantees that P2P exchanges avoid the violation of the network constraints, and ensures that community agents’ can still benefit from the community-based architecture advantages. Full article

(This article belongs to the Special Issue Recent Advances in Power Distribution Networks: Applications and Technologies for Local Energy Communities Integration)

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22 pages, 608 KiB

Open AccessArticle

Community Energy Markets with Battery Energy Storage Systems: A General Modeling with Applications

by Wanessa Guedes, Lucas Deotti, Bruno Dias, Tiago Soares and Leonardo Willer de Oliveira

Energies 2022, 15(20), 7714; https://0-doi-org.brum.beds.ac.uk/10.3390/en15207714 - 19 Oct 2022

Cited by 6 | Viewed by 1615

Abstract

Traditional models of power systems are undergoing a restructuring process, stimulated by the growing deployment of renewable energy sources, making them more decentralized and progressively increasing the focus on the consumer. New arrangements are being explored, allowing consumers to play a more active role in energy systems, highlighting the concept of consumer-centric markets. This work presents an optimization model that considers the insertion of the battery energy storage system (BESS) in the concept of community energy markets. This model aims to increase the community income and includes the degradation of BESS, also evaluating different arrangements of BESS in the community markets. In the investigated scenarios, discussions about the feasibility of inserting BESS through the analysis of social welfare (SW) and fairness indicators were carried out. With the results, it was possible to observe that there are structures that are more advantageous from the perspective of the communities and others from the perspective of the members of the communities, bringing some insights into the different impacts of a BESS in an energy community. Full article

(This article belongs to the Special Issue Recent Advances in Power Distribution Networks: Applications and Technologies for Local Energy Communities Integration)

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12 pages, 2160 KiB

Open AccessArticle

Implementation of a Novel Tabu Search Optimization Algorithm to Extract Parasitic Parameters of Solar Panel

by Naveena Bhargavi Repalle, Pullacheri Sarala, Lucian Mihet-Popa, Shashidhar Reddy Kotha and Nagalingam Rajeswaran

Energies 2022, 15(13), 4515; https://0-doi-org.brum.beds.ac.uk/10.3390/en15134515 - 21 Jun 2022

Cited by 5 | Viewed by 1442

Abstract

The aging of PV cells reduces their electrical performance i.e., the parasitic parameters are introduced in the solar panel. The shunt resistance (R_Sh), series resistance (R_S), photo current (I_Ph), diode current (I_d), and diffusion constant (a₁) are known as parasitic or extraction parameters. Cracks and hotspots reduce the performance of PV cells and result in poor V–I characteristics. Certain tests are carried out over a long period of time to determine the quality of solar cells; for example, 1000 h of testing is comparable to 20 years of operation. The extraction of solar parameters is important for PV modules. The Tabu Search Optimization (TSO) algorithm is a robust meta-heuristic algorithm that was employed in this study for the extraction of parasitic parameters. Particle Swarm Optimization (PSO) and a Genetic lgorithm (GA), as well as other well-known optimization methods, were used to test the proposed method’s correctness. The other approaches included the lightning search algorithm (LSA), gravitational search algorithm (GSA), and pattern search (PS). It can be concluded that the TSO approach extracts all six parameters in a reasonably short period of time. The work presented in this paper was developed and analyzed using a MATLAB-Simulink software environment. Full article

(This article belongs to the Special Issue Recent Advances in Power Distribution Networks: Applications and Technologies for Local Energy Communities Integration)

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16 pages, 20596 KiB

Open AccessArticle

A Comparative Analysis of Peak Load Shaving Strategies for Isolated Microgrid Using Actual Data

by Md Masud Rana, Akhlaqur Rahman, Moslem Uddin, Md Rasel Sarkar, Sk. A. Shezan, Md. Fatin Ishraque, S M Sajjad Hossain Rafin and Mohamed Atef

Energies 2022, 15(1), 330; https://0-doi-org.brum.beds.ac.uk/10.3390/en15010330 - 04 Jan 2022

Cited by 19 | Viewed by 2190

Abstract

Peak load reduction is one of the most essential obligations and cost-effective tasks for electrical energy consumers. An isolated microgrid (IMG) system is an independent limited capacity power system where the peak shaving application can perform a vital role in the economic operation. This paper presents a comparative analysis of a categorical variable decision tree algorithm (CVDTA) with the most common peak shaving technique, namely, the general capacity addition technique, to evaluate the peak shaving performance for an IMG system. The CVDTA algorithm deals with the hybrid photovoltaic (PV)—battery energy storage system (BESS) to provide the peak shaving service where the capacity addition technique uses a peaking generator to minimize the peak demand. An actual IMG system model is developed in MATLAB/Simulink software to analyze the peak shaving performance. The model consists of four major components such as, PV, BESS, variable load, and gas turbine generator (GTG) dispatch models for the proposed algorithm, where the BESS and PV models are not applicable for the capacity addition technique. Actual variable load data and PV generation data are considered to conduct the simulation case studies which are collected from a real IMG system. The simulation result exhibits the effectiveness of the CVDTA algorithm which can minimize the peak demand better than the capacity addition technique. By ensuring the peak shaving operation and handling the economic generation dispatch, the CVDTA algorithm can ensure more energy savings, fewer system losses, less operation and maintenance (O&M) cost, etc., where the general capacity addition technique is limited. Full article

(This article belongs to the Special Issue Recent Advances in Power Distribution Networks: Applications and Technologies for Local Energy Communities Integration)

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