含大规模风电场的电力系统动态经济调度

Dynamic economic dispatch of power system containing large-scale wind farm

电力系统动态经济调度(DED)问题是一个高维、非凸、多约束的优化难题,风电场并网进一步增加了问题的难度。针对风功率波动性和随机性的特点,模型中引入了风电场出力爬坡约束条件,考虑了含风电场的系统上、下旋转备用量。在大规模风电场并网的基础上,根据电力系统所能提供的最大备用容量,适时优化风机出力,既满足了系统可靠运行,又实现风电最大化利用。为了更好地优化DED问题,增强算法的收敛性能,在二进制微分进化算法的基础上,加入了自适应调整控制参数、共享适应度等改进措施。运用旋转备用、最小启停时间、爬坡等修正策略来处理约束条件,大大提高寻优能力。经典算例分析表明,该方法能快速、有效地求解动态经济调度问题。

Dynamic economic dispatch（DED） is a high-dimensional,non-convex,multi-constrained optimization problem.With the increase of wind power integration into power system,the DED problem becomes more difficult.In the mathematical model the constraints of wind farm output and spinning reserve are proposed to deal with the random and unpredictable nature of wind power.In the power system with large-scale wind farm integration,wind power should be adjusted according to the available spinning reserve capacity.To improve the searching capability of binary differential evolution（BDE） algorithm,sharing fitness and adaptive control parameters are adopted.At the same time,the constraints are sloved by some new strategies including rotating reserve,minimum start/stop time,and climbing,which can make all the particles feasible and the searching efficiency greatly improved.The presented method proves to be effective and fast in solving dynamic economic dispatch problem by some examples.