ORIGINAL RESEARCH article
Front. Energy Res.
Sec. Sustainable Energy Systems
Volume 13 - 2025 | doi: 10.3389/fenrg.2025.1627113
Energy Management Optimization of a Distribution Network with Sizing and Allocation of Distributed Generations and Interconnected Electric Vehicles Charging Stations
Provisionally accepted
- 1Karabuk University, Karabuk, Türkiye
- 2Istanbul Technical University, Istanbul, Türkiye
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Distributed generations (DGs) is one of the most beneficial and effective methods for reducing power loss in distribution networks (DNs). Optimal sizing and allocation of DGs is a crucial matter that needs to be focused on, as the improper location and sizing leads to a reverse effect from the intended purpose of using DGs. In this paper, an optimal energy management and load sharing scheme is implemented in three stages to optimize the DN integrated with renewable energy sources (RESs) based DGs and interconnected electric vehicles charging stations (EVCSs). In first stage, optimal sizing and placement of DGs using particle swarm optimization (PSO) technique to solve the minimization problem of active power loss and voltage deviation. In second stage, the optimization problem of the day ahead power scheduling and load sharing is solved using genetic algorithm (GA) to minimize the operation cost. Optimization problem of the profit of interconnected EVCSs is solved in third stage of the management scheme using a proposed fuzzy logic system (FLS). The scheme is tested on an IEEE 33-bus standard distribution system to verify the effectiveness of the implemented energy management scheme. The simulation results show that the distribution system power loss and voltage deviation are reduced by 32.65% and 36.88 % respectively. The total annual energy loss and operation cost are reduced by 86.72% and 16% respectively. The total annual power demand of EVCSs is reduced by 19.5%, and the annual increase of profit is increased by 375.5%.
Keywords: distributed generations, Energy Management, Photovoltaic solar, Electric Vehicles, Cost optimization
Received: 12 May 2025; Accepted: 26 Aug 2025.
Copyright: © 2025 Aljwary, Yusupov, Tahir and Habbal. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Adel Aljwary, Karabuk University, Karabuk, Türkiye
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