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A comprehensive approach for energy storage systems optimal planning and operation in presence of wind power generation

机译：在存在风力发电的情况下，能量存储系统的最佳计划和运行的综合方法

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Energy storage systems (ESSs) are among the most effective techniques that offer several benefits to achieve greater system reliability and efficiency. ESS could be used for deferring network upgrades, demand side management, maximizing the arbitrage benefits, minimizing of energy losses, and allowing the integration of more renewable power. However, optimal planning of ESS is a must in order to achieve the utmost benefits. This paper presents a novel approach for optimal planning of ESS in order to maximize the arbitrage benefits and minimize the total cost of energy losses. The proposed approach relies on the modeling results obtained from a Monte Carlo based probabilistic modeling strategy for wind power and system demand. In the presented planning approach, the optimal operation schedule of ESS is firstly determined in order to maximize the distribution system arbitrage benefit. Secondly, the grey wolf optimization method is employed to determine the optimal location of wind based distributed generators and ESS in order to minimize the total net present value of energy losses cost. The modeling strategy and the optimization algorithms are implemented in MATLAB environment and tested on 33 bus distribution feeder and the results obtained show the efficiency of the proposed approach.
机译：储能系统（ESS）是最有效的技术之一，可带来多种好处，以提高系统的可靠性和效率。 ESS可以用于推迟网络升级，需求侧管理，最大化套利，最大程度地减少能源损失并允许集成更多可再生能源。但是，为了获得最大收益，必须对ESS进行最佳规划。本文提出了一种用于ESS最佳计划的新颖方法，以使套利收益最大化，并使能源损失的总成本最小化。所提出的方法依赖于从基于蒙特卡洛的风能和系统需求的概率建模策略中获得的建模结果。在提出的规划方法中，首先确定ESS的最佳运行计划，以使分配系统的套利收益最大化。其次，使用灰狼优化方法来确定基于风力的分布式发电机和ESS的最佳位置，以使能量损失成本的总净现值最小化。在MATLAB环境下实现了建模策略和优化算法，并在33路配电馈线上进行了测试，结果表明了该方法的有效性。

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