【摘要】 针对分布式光伏发电的不确定性和设备整体利用率较低的特点，导致配电网规划面临成本上升的问题，文中提出一种考虑分布式光伏设备利用率的电网规划方法。通过使用信息熵对光伏出力数据进行场景提取，获得典型场景集。基于这些场景，文中建立分布式光伏储能运行-规划联合优化配置模型。在上层，以最小化投资建设费用和最大化分布式光伏利用率为目标，对分布式光伏及储能进行选址和定容；在下层，以最小化弃光费用，网损费用，运维费用，购电费用为目标，对分布式光伏以及储能功率进行优化，采用改进的粒子群算法做为规划模型求解的方法。最后，以IEEE 33节点系统为例进行场景算例分析，结果表明文中所提出的方法能够提高光伏设备利用率、改善配电网运行稳定性，并降低综合成本。更多还原

【Abstract】 Aiming at the uncertainty of distributed photovoltaic(PV) power generation and the overall low utilization rate of the equipment, which leads to the problem of rising cost faced by distribution network planning, a grid planning method considering the utilization rate of distributed PV equipment is proposed in the paper.By using information entropy to extract scenarios from PV output data, a set of typical scenarios is obtained.Based on these scenarios, a joint optimization model of distributed PV storage operation-planning is developed in the paper: at the upper level, the distributed PV and storage are selected and sited with the objective of minimizing the investment and construction cost and maximizing the utilization rate of distributed PV;at the lower level, the distributed PV power and storage are optimized with the objective of minimizing the cost of discarded light, network loss, operation and maintenance, and purchased power, and the planning model solves the optimization problem.In the lower layer, the distributed PV power and storage charging/discharging power in each time period are optimized with the objective of minimizing the abandoned light cost, network loss cost, operation and maintenance cost, and purchasing power cost, and a modified particle swarm algorithm is used as a method for solving the planning model.Finally, the IEEE 33 node system is used as an example for scenario analysis, and the results show that the proposed method can improve the utilization rate of PV equipment, improve the stability of distribution network operation, and reduce the comprehensive cost.更多还原