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Optimal Charging of Electric Vehicles in Smart Stations and Its Effects on the Distribution Network Using the Particle Swarm Optimization Algorithm
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Alireza Kashki1   , Azita Azarfar1 , Mahmoud Samiei Moghaddam *2 , Reza Davarzani3 , Nasrin Salehi4 |
1- Department of Electrical Engineering, Shahrood Branch, Islamic Azad University, Shahrood, Iran
2- Department of Electrical Engineering, Damghan Branch, Islamic Azad University, Damghan, Iran
3- Department of Electrical Engineering, Shahrood Branch, Islamic Azad University, Shahrood, Iran
4- Department of Basic Sciences , Shahrood Branch, Islamic Azad University, Shahrood, Iran |
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Abstract: (505 Views) |
The proliferation of electric vehicles (EVs) presents both a significant challenge and opportunity for the energy sector. This study proposes a novel approach to optimizing EV charging in smart stations, considering its impact on the distribution network. Using the Particle Swarm Optimization (PSO) algorithm, we address the complex optimization problem of balancing EV charging demands with network constraints. Navigating the complexities of energy management in the distribution network, including renewable resources and dynamic demand, is challenging. We introduce a sophisticated optimization model designed for network operations, featuring precise formulations for energy management. This model optimizes battery usage, EV energy management, compensator utilization, and distributed generation distribution. Through extensive simulations, we demonstrate the effectiveness of this approach in minimizing charging costs, reducing network congestion, and enhancing overall system performance. The multi-objective performance minimizes energy losses, electricity purchases, load reduction, distributed generation, and battery/EV costs over 24 hours. Simulations confirm a significant reduction in the operational costs of the distribution network. This research highlights the potential of advanced optimization techniques in smart charging infrastructure to facilitate widespread EV adoption while ensuring network reliability and efficiency. Incorporating EVs into the system results in significant improvements in performance indices compared to scenarios without electric vehicles. The results indicate a 14% reduction in the objective function value, with a notable 60% reduction in energy purchases and a 40% decrease in energy losses. Additionally, load reduction decreases by approximately 60%, while voltage deviation reduces by around 20%. Importantly, no reduction in PV or WD is observed with EV integration, indicating its compatibility with renewable energy generation profiles and emphasizing its potential to enhance system efficiency, reliability, and sustainability.
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| Keywords: Distribution network, PSO optimization algorithm, demand response, storage, electric vehicle |
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Type of Study: Research |
Received: 2024/05/24 | Accepted: 2024/10/5 | Published: 2025/04/6
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Kashki A, Azarfar A, Samiei Moghaddam M, Davarzani R, Salehi N. Optimal Charging of Electric Vehicles in Smart Stations and Its Effects on the Distribution Network Using the Particle Swarm Optimization Algorithm. ieijqp 2024; 13 (2) URL: http://ieijqp.ir/article-1-999-en.html
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