Optimal Scheduling of Wind Farm with Storage and Forecasting Based on Improved Genetic Algorithms
The optimal Operation Scheduling for power output of a wind farm with storage units and forecasting system has been studied in this paper. Genetic algorithm(GA) is used to achieve the optimal scheduling of wind farm output power which maximize revenue and minimize costs over a required period. However, the Traditional Genetic Algorithm(TGA) has the characteristics of premature phenomenon and slow convergence; it cannot get the desirable result on such a multi-step scheduling scenario. An Improved Genetic Algorithm(IGA) is presented in this paper by modifying the fitness function, choice strategy and crossover strategy. Simulation shows that IGA has the advantages of fast convergence speed and strong capability of global search over traditional genetic algorithm. Finally, a method for optimal scheduling of wind farm with storage and forecasting based on improved genetic algorithms is presented and the experiments validate its feasibility and effectiveness.
Wind power optimal generation schedule storage units forecasting system improved genetic algorithm
Juncheng Liu Chongliang Huang Pengfei Li
School Of Control and Computer Engineering, North China Electric Power University, Changping, Beijing 102206
国际会议
长沙
英文
80-85
2014-05-31（万方平台首次上网日期，不代表论文的发表时间）