考虑农业设施负荷特性的农村配电网与储能分布鲁棒协同优化规划

Distributionally Robust Cooperative Optimization Planning of Rural Distribution Networks and Energy Storage

  • 摘要: 如何高效承载规模化分布式资源,保障电力安全可靠,是当前和未来一段时期内农村配电网建设必须要面对的重大问题。在此背景下,提出考虑农业设施负荷特性的农村配电网与储能分布鲁棒协同优化规划方法。首先,分析农业设施负荷特性并构建农业大棚负荷、农业灌溉负荷和农业生产负荷的数学模型。其次,提出以最小化投资费用和运行费用之和为目标函数且考虑农业设施负荷特性的农村配电网与储能协同优化规划模型。为了有效应对光伏出力的不确定性,提出农村配电网与储能协同规划的分布鲁棒优化模型,并提出基于列和约束生成(Column and constraint generation,C&CG)算法的求解方法。最后,以改进的IEEE 33节点系统为算例验证所提规划方法的有效性。算例结果表明,通过配电网与储能协同规划可有助于减少投资和运行费用,采用所提分布鲁棒优化方法可兼顾规划方案的经济性与鲁棒性。

     

    Abstract: How to efficiently accommodate scaled distributed resources and ensure the security and reliability of power systems is a major issue that the construction of rural distribution networks must face in the current and future periods. In this background, a distributionally robust cooperative optimization planning method of rural distribution networks and energy storage is proposed considering the coordination of agricultural facilities. First, the characteristics of agricultural loads are analyzed and mathematical models of agricultural greenhouse loads, agricultural irrigation loads and agricultural production loads are built. Then, a cooperative planning model of rural distribution networks and energy storage is proposed to minimize the sum of investment cost and operation cost, taking the agricultural facilities into account. In order to effectively deal with the uncertainty of the generation outputs of the PV, a distributionally robust optimization model for cooperative planning of rural distribution networks and energy storage is proposed, and a solution method based on the column and constraint generation(C&CG) algorithm is proposed. Finally, an improved IEEE 33-bus system is employed as an example to verify the effectiveness of the proposed planning method. Simulation results show that the coordinated planning of the distribution network and the energy storage can help reduce investment and operating costs. The distributed robust optimization method proposed can balance the economic efficiency and robustness of the planning scheme.

     

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