摘要
考虑到风电功率本身的随机波动特性,在制定日前市场经济预调度方案过程中,需要将风电功率不确定性因素考虑进来。因此,利用机会约束规划方法来建立包含风电场在内的日前经济调度随机优化模型,并选用改进的引力搜索算法来求解所建立的模型。最后,选用具体算例,结合IEEE-30节点网络调试系统进行模型仿真,并利用仿真结果探讨了负荷水平对系统所容纳的风电容量的影响、风电功率预测偏差对预调度惩罚成本的影响、风电预测功率下不同成本系数对日前市场的影响。研究结果表明,利用改进引力搜索算法进行优化仿真的收敛速度比粒子群算法和遗传算法的收敛速度快,可靠性高。研究所得成果为日前市场经济下风电功率短期预测研究提供参考。
Considering the random fluctuation characteristics of wind power itself, the uncertainty factors of wind power are necessary to be taken into account in the process of making pre-day market economic pre-scheduling. Therefore, a pre-day economic scheduling stochastic optimization model consisting of wind farm is established herein with the chance constrained programming method, and then the improved gravitational search algorithm is selected to solve the established model. Finally, the model simulation is carried out with specific calculation case in combination with the IEEE-30 node network debugging system, while the influence from the load level on the system containing wind power capacity, the influence from the predictive deviation of wind power on the penalty cost of pre-scheduling and the influences from different cost coefficients under predicted wind powerare discussed with the simulated result. The study result shows that the rate of convergence optimally simulated by the improved gravitational search algorithm is faster than those from the particle swarm optimization and genetic algorithm with high reliability. The study result provides reference for the study on the short-term prediction of wind power under pre-day market economy.
作者
寇建涛
KOU Jiantao(State Grid Customer Service Center,Tianjin 750021,China)
出处
《水利水电技术》
北大核心
2019年第3期201-206,共6页
Water Resources and Hydropower Engineering
关键词
风电
日前市场
优化调度
引力搜索算法
机会约束规划法
短期预测
wind power
pre-day market
optimal scheduling
gravitational search algorithm
chance constrained programming method
short-term prediction
