考虑微网源荷不确定性的旋转备用容量优化

电力市场环境下，为应对微网源荷波动和可控机组随机故障，提升其供电可靠性，提出了一种考虑微网源荷不确定性的旋转备用容量优化方法。计及日前预测误差，采用序列理论对源荷随机概率性序列以及可控机组随机故障序列进行离散化处理，生成微网综合不确定性离散分布模型；在此基础上，以微网运行成本、备用成本和停电损失的总成本最小为目标函数，建立旋转备用容量优化模型，并结合蒙特卡罗与粒子群算法对该模型进行求解，获得各时段的旋转备用优化配置容量。以某地微网系统为例，仿真验证了所提方法的有效性和合理性。

Spinning Reserve Capacity Optimization Considering Microgrid Source Load Uncertainty

A method for optimizing the spinning reserve capacity considering the uncertainty of the microgrid source load is proposed in order to cope with the fluctuation of microgrid source load and random failure of conventional unit，improve its power supply reliability under the power market environment. The discrete uncertainty distribution model of microgrid power is generated by considering day-ahead forecast error，using sequence operation theory to discrete source load and conventional unit fault outage. A spinning reserve capacity optimization model is established with the goal of minimizing the total cost of microgrid operating costs，reserve costs and outage costs. The model is solved by combining Monte Carlo and particle swarm algorithm to obtain optimal amount of spinning reserve capacity for each period. Taking a microgrid system as an example，the simulation validates the effectiveness and rationality of the proposed method.