梯级电站群短期水火联合经济调度优化方法  

Optimization method of short-term hydro and thermal power system combined economic dispatching in cascade hydropower stations

作　　者：林艺城 孟安波[1] 陈云龙[1] LIN Yicheng;MENG Anbo;CHEN Yunlong(School of Automation, Guangdong University of Technology. Guangzhou Guangdong 510006, China)

机构地区：[1]广东工业大学自动化学院,广东省广州市510006

出　　处：《宁夏电力》2017年第5期1-10,共10页Ningxia Electric Power

基　　金：广东省科技计划项目(2016A010104016);广东电网公司科技项目(CCDKJQQ20152066)

摘　　要：针对多约束、非线性、不可微的梯级电站群短期水火联合经济调度优化问题,在标准灰狼算法的基础上,提出了一种基于改进灰狼算法的梯级电站群短期水火联合经济调度优化方法以处理该复杂优化问题。该算法通过融入纵向交叉操作以修正狼群前进方向,改善算法的全局收敛性;采用一种新型约束处理方法,解决传统差额约束处理方式无法处置的强耦合关系变量的违约问题,提高算法的计算效率。仿真结果表明:该优化方法不仅克服了标准GWO的缺陷,且在求解质量、精度、收敛性和稳定性等方面较其它算法具有明显优势。Aiming at the problem of short-term hydro and thermal power system combined economic scheduling optimization for multi-constraint,nonlinear and non-differentiable cascade power station groups,on the basis of the standard gray wolf optimizer(GWO)algorithm,puts forward the optimization method of short-term hydro and thermal power system combined economic dispatching for cascade power station groups based on an improved gray wolf algorithm to deal with this complex optimization problem.The algorithm corrects the forward direction of the wolves by integrating the longitudinal cross operation to improve the global convergence.Using a new constraint processing method solves the strong coupling relation variable default problem which the traditional balance constraint cannot deal with,improves the computational efficiency of the algorithm.The simulation result shows that this optimization method not only overcomes the defects of standard GWO,but also has obvious advantages in solving the quality,precision,convergence and stability.

关 键 词：梯级电站群 短期水火联合经济调度 改进灰狼算法 计数淘汰 纵向交叉 

分 类 号：TM727[电气工程—电力系统及自动化]