计及风险系数的含风电场电力系统多目标动态优化调度  

Multi-objective Dynamic Dispatching of Power Grid with Wind Farms by Considering Risk Index

作　　者：李晨[1] 胡志坚[1] 董骥[2] 仉梦林[1] 

机构地区：[1]武汉大学电气工程学院,湖北武汉430072 [2]宜昌供电公司,湖北宜昌443000

出　　处：《现代电力》2015年第5期56-65,共10页Modern Electric Power

基　　金：高等学校博士学科点专项科研基金项目(20110141110032);西安交通大学电力设备电气绝缘国家重点实验室资助(EIPE13205)

摘　　要：随着风电并网容量的不断增加,传统的确定性优化调度方法已难以满足电力系统安全运行要求。本文建立了计及风险系数的含风电场电力系统多目标动态优化调度模型,模型包括风险系数、燃料成本及污染排放量最小3个目标,将风电场出力及负荷的不确定性纳入模型综合考虑。为了对模型中的随机变量进行处理,引入概率性序列理论,并对其运算空间进行扩展,然后提出了一种改进的多目标教与学优化算法对模型进行求解。含风电场的10机系统算例验证了本文模型及算法的可行性和有效性。With the increasing of wind capacity integrated into grid, the traditional deterministic optimization method can hardly meet the requirements for the safe operation of the power system. A multi-objective dynamic dispatch model for power grid with wind farms is presented by considering risk index, which includes such three objectives as minimum fuel cost, minimum emissions and minimum risk index, and also takes the uncertainty of load and the power output of wind farms into consideration. To deal with random varia- bles in this model, probabilistic sequence theory is intro- duced and its operational space is extended. Then, an im- proved multi-objective teaching-learning-based optimization （IMOTLBO） algorithm is proposed to solve the model. In the end, the validity and effectiveness of proposed model and algorithm are verified through a 10-gnerators test systemwith wind farms.

关 键 词：多目标动态优化调度 风险系数 概率性序列理论 教与学算法 帕累托最优解 

分 类 号：TM731[电气工程—电力系统及自动化]