Abstract This paper proposes a procedure for the optimal siting and sizing of energy storage systems (ESSs) within active distribution networks (ADNs) hosting a large amount of stochastic distributed renewable energy resources. The optimization objective is to minimize the ADN’s day-ahead computed dispatch error. The allocation of ESS is determined while taking advantages from their operational features regarding the ADN’s dispatchability. The proposed ESS planning is defined by formulating, and solving, a scenario-based non-linear non-convex optimal power flow (OPF). The OPF problem is converted to a piecewise linearized OPF (PWL-OPF). The ESS control strategy is designed to fully exploit the energy capacity of the ESS. It is integrated within the PWL-OPF to achieve the ADN’s dispatchability regarding all operating scenarios. The Benders decomposition technique is employed to tackle the computational complexity of the proposed planning problem. The problem is decomposed into two sub-ones: a master problem where the allocation of the ESSs is decided, and several subproblems where the dispatchability of ADN with the support of the allocated ESS is evaluated through the scenario-based OPF. To validate the proposed method, extensive simulations are conducted on a real Swiss grid embedding significant PV generation capacity.

中文翻译：

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主动配电网储能系统调度感知规划

摘要 本文提出了一种在拥有大量随机分布式可再生能源的主动配电网络 (ADN) 内优化储能系统 (ESS) 选址和规模的程序。优化目标是最小化 ADN 的日前计算调度误差。ESS 的分配是在利用其关于 ADN 可调度性的操作特性的同时确定的。拟议的 ESS 规划是通过制定和解决基于场景的非线性非凸最优潮流 (OPF) 来定义的。OPF 问题被转换为分段线性化 OPF (PWL-OPF)。ESS 控制策略旨在充分利用 ESS 的能量容量。它集成在 PWL-OPF 中，以实现 ADN 对所有操作场景的可调度性。Benders 分解技术被用来解决所提出的规划问题的计算复杂性。该问题被分解为两个子问题：一个是决定 ESS 分配的主问题，另一个是通过基于场景的 OPF 评估在分配的 ESS 支持下 ADN 的可调度性的几个子问题。为了验证所提出的方法，对嵌入显着光伏发电容量的真实瑞士电网进行了广泛的模拟。