考虑风电的电力系统机组组合两阶段优化方法

Two-stage optimization method for unit commitment of power system considering wind power

电的随机性和波动性给电力系统的安全经济运行带来了严峻的挑战,合理的风电不确定性模型及机组组合优化方法是保证电力系统日前调度安全性和经济性的关键。为此,提出一种考虑风电的电力系统机组组合两阶段随机优化方法。根据风电出力历史数据的非参数经验分布,生成符合风电随机性和波动性的风电动态场景。考虑到场景削减过程中容易忽略的一些极端边界场景会增加系统的弃风或切负荷风险,提出以削减后的场景和极端边界场景为输入的机组组合两阶段优化模型。同时,为求解机组组合这一非线性混合整数优化问题,提出一种混合遗传纵横交叉算法的优化方法。通过实验仿真结果证明了所提模型和方法用于求解考虑风电的电力系统机组组合问题时的合理性和有效性。

The randomness and volatility of wind power bring serious challenges to the safe and economical operation of power system.Reasonable wind power uncertainty model and unit commitment optimization method are the key to ensure the safety and economy of dispatching in power system.A two-stage stochastic optimization method for unit commitment of power system considering wind power is proposed in this paper.According to the nonparametric empirical distribution of wind power output history data,wind power dynamic scenarios are produced accorded with wind power randomness and volatility.Considering that some extreme boundary scenarios that are easily overlooked in the process of scenarios reduction will increase the risk of wind or load shedding,a two-stage optimization model of unit commitment with reduced scenarios and extreme boundary scenarios is proposed.Meanwhile,in order to solve the nonlinear mixed integer optimization problem of unit commitment,a hybrid genetic and crisscross optimization algorithm is proposed.The simulation results show that the proposed model and method are effective when solving the problem of unit commitment with wind power system.