基于云模型粒子群算法的海岛交直流混合微网鲁棒优化运行

Robust Optimization Operation of Island AC-DC Hybrid Micro-grid Based on Cloud Model Particle Swarm Optimization

针对海岛交直流混合微网系统区域电能交换方式复杂、系统运行安全稳定性要求高的问题,在综合考虑交直流混合微网系统结构和微源出力特性的基础上,以最大净负荷波动量作为满足最坏运行条件下系统储备容量要求的替代方案,建立以系统综合运行成本最低、净负荷波动量最大为上、下层优化目标的海岛交直流混合微网鲁棒双层优化模型,并分别基于云模型理论改进的粒子群算法和CPLEX求解器对双层优化模型进行求解.仿真结果可知,所提的海岛交直流混合微网鲁棒优化方法可有效提高系统的优化水平,使微网在满足最恶劣环境的安全约束前提下,可获取更好的经济效益.

Island AC-DC hybrid micro-grid systems are characterized by complex power exchange modes and high requirements on the system security and stability. To solve these problems, based on a comprehensive consideration of AC-DC hybrid micro-grid system structures and micro-source output characteristics, we use the maximum load volatility to replace the system reserve capacity requirements under the worst operating conditions. We construct a robust bilevel optimization model for island hybrid AC-DC hybrid micro-grid with minimum system operating cost and maximum load fluctuation for both upper and lower layers, and solve the bilevel optimization model using an improved particle swarm optimization algorithm and CPLEX solver. The simulation result shows that the proposed method can effectively improve the system's optimal operation level and make the micro-grid realize better economic benefits under the premise of meeting the security constraints of the harshest environments.