考虑多重出力不确定性的风光装机容量优化

挖掘风电和光伏出力的日特性和月特性,构建基于日特性和月特性的风电/光伏序列模型,通过蒙特卡洛模拟方法,生成多条风电和光伏出力序列,以刻画风/光出力的多重不确定性。考虑风电和光伏多重不确定性出力约束、电力电量平衡约束、允许弃风弃光率约束等,构建风电和光伏收益最大模型,优化风电和光伏装机,保证风电和光伏运行的经济性,实现风电和光伏有序发展。仿真算例表明,在不同的允许弃风弃光率下,风电和光伏的最优装机差异较大,受光伏日特性和装机成本高的影响,只有在弃光率较小且光伏装机容量小的场景下,光伏发电才具有较好的经济效益。

Wind and PV installed capacity optimization with hybrid uncertainty of renewable energy

By mining the daily and monthly characteristics of renewable energy, a time series model of wind and PV was presented. Through the Monte Carlo method, several wind and PV time series were produced to depict the hybrid uncertainty of the wind and PV. Based on the hybrid uncertainty constraints of wind and PV, power balance constraint and allowed wind and PV curtailment rate, etc., the profit maximum model of renewable was proposed to optimize the installed capacities of wind power and PV, to ensure the operation economics of wind power and photovoltaic system. The simulations showed that under different allowed wind and PV curtailment rates, the optimal installation capacities of wind power and PV varied significantly. Due to the unique daily characteristics and high installation cost of PV system, the higher total revenue of PV could be achieved with lower curtailment rate and installation capacity of PV systems.