Research on Wind Power Optimization Scheduling Based on Improved Plant Growth Simulation Algorithm
To ensure the safety,stability and economic operation including wind power systems,the system constructed to minimize the operating cost of the spinning reserve capacity optimization target scheduling model.To enhance the computing speed for solving the model,an improved plant growth simulation algorithm is proposed to optimize this model.The reverse learning idea is introduced into the plant growth algorithm,and the growth point is inversely mutated to expand the search space of the algorithm; the intelligent variable step search is adopted and the variation mechanism of the elite set ensures fast optimization and improves the accuracy of the solution.Finally,the example verification is carried out on the IEEE30 bus system.Experimental results show that the proposed model can efficiently solve the wind farm containing spinning reserve capacity optimization scheduling problem,has broad application prospects.
Wind power system Optimized scheduling plant growth simulation algorithm Opposition-based learning Intelligent step change
Hexu Sun Hang Zhang Zhaoming Lei
Hebei University of Technology,Tianjin 300130,China
国际会议
江苏镇江
英文
473-481
2019-09-20（万方平台首次上网日期，不代表论文的发表时间）