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Optimal Storage Planning in Active Distribution Network Considering Uncertainty of Wind Power Distributed Generation

机译:考虑风电分布式发电不确定性的主动配电网最优存储规划

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摘要

The penetration of renewable distributed generation (DG) sources has been increased in active distribution networks due to their unique advantages. However, non-dispatchable DGs such as wind turbines raise the risk of distribution networks. Such a problem could be eliminated using the proper application of energy storage units. In this paper, optimal planning of batteries in the distribution grid is presented. The optimal planning determines the location, capacity and power rating of batteries while minimizing the cost objective function subject to technical constraints. The optimal long-term planning is based on the short-term optimal power flow considering the uncertainties. The point estimate method (PEM) is employed for probabilistic optimal power flow. The batteries are scheduled optimally for several purposes to maximize the benefits. A hybrid Tabu search/particle swarm optimization (TS/PSO) algorithm is used to solve the problem. The numerical studies on a 21-node distribution system show the advantages of the proposed methodology. The proposed approach can also be applied to the realistic sized networks when some sensitive nodes are considered as candidate locations for installing the storage units.
机译:由于有源分布式网络的独特优势,可再生分布式发电(DG)源的渗透已得到提高。但是,不可分派的DG(例如风力涡轮机)会增加配电网络的风险。使用能量存储单元的适当应用可以消除这种问题。本文提出了配电网中电池的最佳计划。最佳规划确定电池的位置,容量和额定功率,同时将受技术限制的成本目标函数降至最低。最佳长期计划是基于考虑了不确定性的短期最佳潮流。点估计法(PEM)用于概率最优潮流。出于多种目的,对电池进行了最佳调度,以最大程度地发挥效益。混合禁忌搜索/粒子群优化(TS / PSO)算法用于解决该问题。对21个节点的配电系统进行的数值研究表明了所提出方法的优势。当某些敏感节点被视为安装存储单元的候选位置时,建议的方法也可以应用于实际大小的网络。

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