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December 4, 2025Modelling—International Open Access Journal of Modelling in Engineering Science5 citationsOpen Access

Optimal Planning of Electric Vehicle Charging Stations with DSTATCOM and PV Supports Using Metaheuristic Optimization

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AEAhmad EidAEAhmad Eid

Key Points

  • Electric Vehicle Charging Stations energy increases with the addition of photovoltaic units, optimizing system performance.
  • Results demonstrate a 29.22 MWh increase in PV hosting energy in cases with 3 EVCSs, showcasing significant enhancements.
  • The study employs a multi-objective optimization approach, focusing on reducing system losses while enhancing energy capacities of key components.
  • Effective integration of Photovoltaic units and DSTATCOM ensures reliable power flow, adhering to system constraints throughout the analysis.

Abstract

This study investigates the optimal operation of distribution systems incorporating Photovoltaic (PV) units, Electric Vehicle Charging Stations (EVCSs), and DSTATCOM devices using the Starfish Optimization Algorithm (SFOA). The main goal of the SFOA is to minimize a combined function that encompasses three key objectives: reducing system losses, increasing PV capacity, and enhancing EVCS power. By applying the SFOA within a multi-objective optimization framework, the optimal locations and sizes of PV units, EVCSs, and DSTATCOMs are identified to meet these objectives. This study analyzes and compares several case studies with different numbers of EVCSs, focusing on the operation of a modified 51-bus distribution system over 24 h. Results show that PV hosting energy increases to 21.73, 23.83, and 29.22 MWh for cases with 1, 2, and 3 EVCSs, respectively. EVCS energy also rises to 12.41, 19.50, and 37.23 MWh for the same cases. The corresponding optimized DSTATCOM reactive powers are 11.02, 12.02, and 13.74 MVarh. Throughout all cases, system constraints—such as voltage limits, utility current, and power flow equations—remain within acceptable ranges. The findings demonstrate the SFOA’s effectiveness in optimizing distribution systems with various devices, ensuring efficient operation and meeting all key objectives while adhering to system constraints.

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Cite This Study

Eid et al. (2025) studied this question.

synapsesocial.com/papers/6930dc9eea1aef094cca2d94https://doi.org/10.3390/modelling6040156
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