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Robust planning of distributed battery energy storage systems in flexible smart distribution networks: A comprehensive study

机译:柔性智能配送网络中分布式电池储能系统的鲁棒规划:综合研究

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摘要

This paper presents a robust planning of distributed battery energy storage systems (DBESSs) from the viewpoint of distribution system operator (DSO) to increase the network flexibility. Initially, the deterministic model of the proposed problem is expressed by minimizing the difference between the DBESS planning, degradation and operation (charging) costs and the revenue of DBESS from selling its stored energy subject to the constraints of AC power flow equations in the presence of RESs and DBESSs, and technical limits of the network indexes, variable renewable energy sources (vRESs) and DBESSs. This problem is modeled as a non-linear programming (NLP), then, an equivalent linear programming (LP) model is proposed using the first-order expansion of Taylor's series for linearization of power flow equations and a polygon for linearization of circular inequalities. Also, to model the uncertain parameters in the proposed problem including forecasted active and reactive loads, energy and charging/discharging prices and the output power of vRES, the bounded uncertainty-based robust optimization (BURO) framework is proposed in the next step. Finally, the proposed scheme is applied to 19-bus MV CIGRE benchmark grid by GAMS software to investigate the capability and efficiency of the model.
机译:本文从分布系统操作员(DSO)的观点来看,分布式电池储能系统(DBESS)的强大规划,以提高网络灵活性。最初,所提出的问题的确定性模型是通过最小化DBESS计划,降级和运营(充电)成本的差异以及DBESS销售所存储的能量的差异在存在的情况下销售其存储的能量的差异RESS和DBESSS,以及网络索引的技术限制,可变可再生能源(返绩)和DBESS。该问题被建模为非线性编程(NLP),然后,使用Taylor系列的一阶扩展来提出等效的线性编程(LP)模型,用于电流方程的线性化和用于线性化不等式的多边形。此外,为了在所提出的问题中模拟不确定的参数,包括预测的主动和无功负载,能量和充电/放电价格以及VRE的输出功率,在下一步骤中提出了界限的不确定性的鲁棒优化(BURO)框架。最后,通过GAMS软件将所提出的方案应用于19母线MV CIGRE基准网格,以研究模型的能力和效率。

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