并网型风电场扩展光伏互补发电容量优化配置

风、光资源具有天然的互补性,在已建成的风电场中扩展光伏发电,组建互补发电系统,有利于平抑出力波动并提高运行经济性。提出一种并网型风电场扩展光伏容量优化配置方法。基于风速和太阳辐射在时间尺度上的互补性,建立修正的气象概率分布模型。以电气设备利用率最大,输出功率波动性和弃风、弃光电量最小为目标构建多目标优化模型,充分考虑3个目标之间的矛盾以及不同升压主变容量的影响。采用蒙特卡罗方法仿真生成风、光气象数据,基于多目标粒子群算法求取Pareto最优解集合,结合工程要求和经济性指标从集合中确定最终方案。结合算例,对本研究方法的有效性进行了验证。

Optimal complementary photovoltaic capacity configuration for grid-connected wind farms expansion

According to the complementarity of wind and solar energy sources, expanding photovoltaic panels in wind farms into wind-PV hybrid generation systems was helpful to smooth power fluctuation and improve operation economy. An approach to solve the optimization of the PV capacity for grid-connected wind farm was presented. Based on the complementarity of wind speed and solar radiation in time scales, modified meteorological probability models were established. A multi-objective optimization model was proposed with three objectives: maximizing the utilization of electrical equipment, minimizing the power fluctuation and the loss of renewable energy. The contradiction of three objectives and influence of the step-up transformer were incorporated. Meteorological data were simulated based on the Monte Carlo method. And the multi-objective particle swarm optimization was used to search the Pareto optimal solution set, from which an ultimate planning scheme was selected considering the engineering requirements and economic index. A numerical example was provided to validate the effectiveness of proposed approach.