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Data-driven stochastic programming for energy storage system planning in high PV-penetrated distribution network
International Journal of Electrical Power & Energy Systems ( IF 5.0 ) Pub Date : 2020-12-01 , DOI: 10.1016/j.ijepes.2020.106326
Zhuoxin Lu , Xiaoyuan Xu , Zheng Yan

Abstract Energy storage systems (ESSs) facilitate the reliable and economic operation of distribution systems with high PV penetration. Establishing uncertainty models is the key to the optimal planning and operation of ESSs in distribution systems. Widely used parametric models cannot describe the variability of uncertainties thoroughly. In this paper, a data-driven method is designed for uncertainty modeling, and a distributionally robust optimization (DRO) model is developed to determine the optimal ESS planning strategy in distribution systems. First, a deterministic optimization model is established considering both ESS planning and distribution system operation. Then, the Wasserstein-metric-based ambiguity set is designed for the probability distributions of random variables. To hedge against the distributional ambiguity, the optimization problem is expanded into a two-stage DRO problem, of which the second-stage problem minimizes the expected operating cost under the worst-case probability distribution. Finally, the two-stage DRO model is reformulated as a mixed-integer second-order cone programming (MISOCP) problem, which is solved by optimization solvers. The proposed method is tested on modified 33-bus and 123-bus distribution systems with actual solar irradiance and load data. The influence of different strategies on ESS planning and operation is discussed. The ESS planning results obtained by DRO are compared with those of conventional stochastic optimization and deterministic optimization to verify the superiority of the proposed method.

中文翻译:

数据驱动的随机规划用于高光伏渗透配电网中的储能系统规划

摘要 储能系统 (ESS) 促进了具有高光伏渗透率的配电系统的可靠和经济运行。建立不确定性模型是配电系统中 ESS 优化规划和运行的关键。广泛使用的参数模型无法彻底描述不确定性的可变性。在本文中,为不确定性建模设计了一种数据驱动的方法,并开发了分布鲁棒优化 (DRO) 模型来确定配电系统中的最佳 ESS 规划策略。首先,建立考虑ESS规划和配电系统运行的确定性优化模型。然后,针对随机变量的概率分布设计了基于 Wasserstein 度量的模糊集。为了避免分布模糊,优化问题扩展为两阶段DRO问题,其中第二阶段问题最小化最坏情况概率分布下的预期运营成本。最后,两阶段 DRO 模型被重新表述为混合整数二阶锥规划 (MISOCP) 问题,由优化求解器解决。所提出的方法在修改后的 33 总线和 123 总线配电系统上进行了测试,该系统具有实际的太阳辐照度和负载数据。讨论了不同策略对 ESS 规划和运行的影响。将 DRO 获得的 ESS 规划结果与常规随机优化和确定性优化的结果进行比较,以验证所提出方法的优越性。其中第二阶段问题最小化了最坏情况概率分布下的预期运营成本。最后,两阶段 DRO 模型被重新表述为混合整数二阶锥规划 (MISOCP) 问题,由优化求解器解决。所提出的方法在改进的 33 总线和 123 总线配电系统上进行了测试,该系统具有实际的太阳辐照度和负载数据。讨论了不同策略对 ESS 规划和运行的影响。将 DRO 获得的 ESS 规划结果与常规随机优化和确定性优化的结果进行比较,以验证所提出方法的优越性。其中第二阶段问题最小化了最坏情况概率分布下的预期运营成本。最后,两阶段 DRO 模型被重新表述为混合整数二阶锥规划 (MISOCP) 问题,由优化求解器解决。所提出的方法在修改后的 33 总线和 123 总线配电系统上进行了测试,该系统具有实际的太阳辐照度和负载数据。讨论了不同策略对 ESS 规划和运行的影响。将 DRO 获得的 ESS 规划结果与常规随机优化和确定性优化的结果进行比较,以验证所提出方法的优越性。这是由优化求解器解决的。所提出的方法在修改后的 33 总线和 123 总线配电系统上进行了测试,该系统具有实际的太阳辐照度和负载数据。讨论了不同策略对 ESS 规划和运行的影响。将 DRO 获得的 ESS 规划结果与常规随机优化和确定性优化的结果进行比较,以验证所提出方法的优越性。这是由优化求解器解决的。所提出的方法在修改后的 33 总线和 123 总线配电系统上进行了测试,该系统具有实际的太阳辐照度和负载数据。讨论了不同策略对 ESS 规划和运行的影响。将 DRO 获得的 ESS 规划结果与常规随机优化和确定性优化的结果进行比较,以验证所提出方法的优越性。
更新日期:2020-12-01
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