Optimal capacity determination of photovoltaic and energy storage systems for electric vehicle charging stations

IF 8.9 2区 工程技术 Q1 ENERGY & FUELS
Seung-Ryong Jang, Ah-Yun Yoon, Sung-Soo Kim
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Abstract

With the growing interest in integrating photovoltaic (PV) systems and energy storage systems (ESSs) into electric vehicle (EV) charging stations (ECSs), extensive research has focused on methods to increase the profits of ECS operators (ECSOs). Conventional studies have primarily relied on empirical methods, such as assuming a constant value for the power conversion system (PCS) capacity or modeling it as being dependent on the battery capacity, to design ESSs. However, such empirical methods can lead to suboptimal or excessive determinations of the capacity of a facility. This study proposes a battery-independent PCS model that independently models the battery and PCS capacities in ESS design to overcome the limitations of the conventional model and maximize the profit for ECSOs. The proposed model determines the optimal capacity of ESS and PV to maximize ECSO's profit. The nonlinearities that arise from using a battery-independent PCS model are linearized by the BIG-M method to effectively solve the optimization problem. The proposed model achieved an additional profit of up to 1.5 % compared to the conventional model. Additionally, the proposed model was simulated under various conditions (e.g., decreasing capital investment costs of ESS, changing EV charging demand, changing time-of-use rates, and applying real-time price rates). Accordingly, it is confirmed that the proposed model greatly contributes to improving ECSO profit even under various conditions. Moreover, the proposed model offers a means to determine the optimal capacities of PV and ESS in an ECS, ultimately maximizing ECSO profits.
电动汽车充电站光伏与储能系统的最优容量确定
随着人们对将光伏(PV)系统和储能系统(ess)集成到电动汽车(EV)充电站(ECSs)中的兴趣日益浓厚,如何提高充电站运营商(ecso)的利润已成为广泛研究的重点。传统研究主要依靠经验方法来设计ess,例如假设电源转换系统(PCS)容量为恒定值或将其建模为依赖于电池容量。然而,这种经验方法可能导致对设施容量的次优或过度确定。本文提出了一个独立于电池的PCS模型,该模型在ESS设计中对电池和PCS容量进行独立建模,以克服传统模型的局限性,使ecso的利润最大化。该模型确定了ESS和PV的最优容量,以使ECSO的利润最大化。采用BIG-M方法对与电池无关的PCS模型产生的非线性进行线性化处理,有效地解决了优化问题。与传统模型相比,所提出的模型实现了高达1.5%的额外利润。此外,还在不同条件下(如降低ESS的资本投资成本、改变电动汽车充电需求、改变使用时间和采用实时电价)对所提出的模型进行了仿真。由此证实,即使在各种条件下,所提出的模型也对提高ECSO利润有很大的贡献。此外,所提出的模型提供了一种方法来确定光伏和ESS在ECS中的最佳容量,最终使ECSO利润最大化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of energy storage
Journal of energy storage Energy-Renewable Energy, Sustainability and the Environment
CiteScore
11.80
自引率
24.50%
发文量
2262
审稿时长
69 days
期刊介绍: Journal of energy storage focusses on all aspects of energy storage, in particular systems integration, electric grid integration, modelling and analysis, novel energy storage technologies, sizing and management strategies, business models for operation of storage systems and energy storage developments worldwide.
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