论文标题
多功能公用规模共享储能系统的最佳尺寸和选址
Optimal Sizing and Siting of Multi-purpose Utility-scale Shared Energy Storage Systems
论文作者
论文摘要
本文提出了一种非主导分类遗传算法II（NSGA-II）的方法，以确定多用途多用途（例如，电压调节和损失最小化）的最佳或接近最佳尺寸以及基于社区的，基于社区的，基于社区的，实用程序，实用程序，实用程序，实用型，共享的共享能量存储在具有较高型号的太阳能photovoltaic photovaltaic photovoltaic photovaltaic photovaltaic systems的分配系统中。小型幕后电池（BTM）电池很昂贵，尚未充分利用，其净值很难概括并控制网格服务。另一方面，公用事业规模的共享能量存储（USSES）系统有可能提供主要（例如需求侧管理，系统升级和减少需求费用）以及次要（例如频率调节，资源充足性和能源套利）网格服务。在现有的成本结构下，仅用于主要目的的存储不能证明所有者的经济利益是合理的。但是，主要服务存储的交付仅利用总电池寿命容量的1-50％。在提议的方法中，对于每个候选位置和大小的候选人集，USSES系统对网格电压偏差和功率损失的贡献进行了评估，并创建了不同的帕累托前沿。 USSES系统通过一种新的染色体表示方法分散。从帕累托（Pareto）最佳阵线的列表中，分配系统规划人员将有机会根据所需的目标选择适当的位置。在IEEE 123节点分配测试馈线上，使用实用程序尺度的PV和USSES系统展示了所提出的方法。
This paper proposes a nondominated sorting genetic algorithm II (NSGA-II) based approach to determine optimal or near-optimal sizing and siting of multi-purpose (e.g., voltage regulation and loss minimization), community-based, utility-scale shared energy storage in distribution systems with high penetration of solar photovoltaic energy systems. Small-scale behind-the-meter (BTM) batteries are expensive, not fully utilized, and their net value is difficult to generalize and to control for grid services. On the other hand, utility-scale shared energy storage (USSES) systems have the potential to provide primary (e.g., demand-side management, deferral of system upgrade, and demand charge reduction) as well as secondary (e.g., frequency regulation, resource adequacy, and energy arbitrage) grid services. Under the existing cost structure, storage deployed only for primary purpose cannot justify the economic benefit to owners. However, the delivery of storage for primary service utilizes only 1-50\% of total battery lifetime capacity. In the proposed approach, for each candidate set of locations and sizes, the contribution of USSES systems to grid voltage deviation and power loss are evaluated and diverse Pareto-optimal front is created. USSES systems are dispersed through a new chromosome representation approach. From the list of Pareto-optimal front, distribution system planners will have the opportunity to select appropriate locations based on desired objectives. The proposed approach is demonstrated on the IEEE 123-node distribution test feeder with utility-scale PV and USSES systems.
