电力系统机组组合问题的改进粒子群优化算法

机组组合问题是一个大规模的非线性混合整数规划问题.文章首先对机组组合问题的0、1变量进行松弛,应用罚函数方法将此问题转化为一个非线性连续变量的规划问题,并应用改进粒子群优化算法求解.该算法在标准的粒子群优化算法的基础上,每个粒子速度和位置的更新不仅考虑自身个体极值和全局极值的信息,还考虑其它粒子所包含的信息.通过收敛性分析可知,若合适地选择算法的控制参数,该算法能较好地收敛到最优解.算例表明文章所提出的算法具有解的质量高、收敛速度快的优点.

AN IMPROVED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR POWER SYSTEM UNIT COMMITMENT

Unit commitment is a large scale non-linear hybrid integer programming problem. The authors at first relax the zero-one variables in unit commitment and transform this problem into a non-linear programming problem with continuous variable by penalty function, then this programming problem is solved by improved particle swarm optimization algorithm. On the basis of standard particle swarm optimization algorithm, for the renewal of speed and position of each particle not only the information of its own individual extremum and global extremum should be considered, but also the information of other particles. By means of convergence analysis, it is known that if the control parameter of this algorithm is properly chosen, the presented algorithm can converge to optimal solution. The results of calculation examples show that the solution of the presented algorithm possesses high quality and the high convergence speed.