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Open AccessArticle
Optimal Economic Analysis of Battery Energy Storage System Integrated with Electric Vehicles for Voltage Regulation in Photovoltaics Connected Distribution System
by
Qingyuan Yan
Qingyuan Yan 1,*,
Zhaoyi Wang
Zhaoyi Wang 1,
Ling Xing
Ling Xing 1 and
Chenchen Zhu
Chenchen Zhu 2
1
College of Information Engineering, Henan University of Science and Technology, Luoyang 471000, China
2
State Grid Taizhou Electric Power Co., Ltd., Taizhou 225300, China
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(19), 8497; https://doi.org/10.3390/su16198497 (registering DOI)
Submission received: 27 July 2024
/
Revised: 1 September 2024
/
Accepted: 27 September 2024
/
Published: 29 September 2024
Abstract
Abstract: The integration of photovoltaic and electric vehicles in distribution networks is rapidly increasing due to the shortage of fossil fuels and the need for environmental protection. However, the randomness of photovoltaic and the disordered charging loads of electric vehicles cause imbalances in power flow within the distribution system. These imbalances complicate voltage management and cause economic inefficiencies in power dispatching. This study proposes an innovative economic strategy utilizing battery energy storage system and electric vehicles cooperation to achieve voltage regulation in photovoltaic-connected distribution system. Firstly, a novel pelican optimization algorithm-XGBoost is introduced to enhance the accuracy of photovoltaic power prediction. To address the challenge of disordered electric vehicles charging loads, a wide-local area scheduling method is implemented using Monte Carlo simulations. Additionally, a scheme for the allocation of battery energy storage system and a novel slack management method are proposed to optimize both the available capacity and the economic efficiency of battery energy storage system. Finally, we recommend a day-ahead real-time control strategy for battery energy storage system and electric vehicles to regulate voltage. This strategy utilizes a multi-particle swarm algorithm to optimize economic power dispatching between battery energy storage system on the distribution side and electric vehicles on the user side during the day-ahead stage. At the real-time stage, the superior control capabilities of the battery energy storage system address photovoltaic power prediction errors and electric vehicle reservation defaults. This study models an IEEE 33 system that incorporates high-penetration photovoltaics, electric vehicles, and battery storage energy systems. A comparative analysis of four scenarios revealed significant financial benefits. This approach ensures economic cooperation between devices on both the user and distribution system sides for effective voltage management. Additionally, it encourages trading activities of these devices in the power market and establishes a foundation for economic cooperation between devices on both the user and distribution system sides.
Share and Cite
MDPI and ACS Style
Yan, Q.; Wang, Z.; Xing, L.; Zhu, C.
Optimal Economic Analysis of Battery Energy Storage System Integrated with Electric Vehicles for Voltage Regulation in Photovoltaics Connected Distribution System. Sustainability 2024, 16, 8497.
https://doi.org/10.3390/su16198497
AMA Style
Yan Q, Wang Z, Xing L, Zhu C.
Optimal Economic Analysis of Battery Energy Storage System Integrated with Electric Vehicles for Voltage Regulation in Photovoltaics Connected Distribution System. Sustainability. 2024; 16(19):8497.
https://doi.org/10.3390/su16198497
Chicago/Turabian Style
Yan, Qingyuan, Zhaoyi Wang, Ling Xing, and Chenchen Zhu.
2024. "Optimal Economic Analysis of Battery Energy Storage System Integrated with Electric Vehicles for Voltage Regulation in Photovoltaics Connected Distribution System" Sustainability 16, no. 19: 8497.
https://doi.org/10.3390/su16198497
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