An Improved Dual Particle Swarm Optimization Algorithm for Unit Commitment Problem

作者：Jinlei Qin · 发表于：Proceedings of the CSEE · 年份：2012 · 被引用次数：10 · 研究领域：Power Systems and Renewable Energy、Power Systems and Technologies、Smart Grid and Power Systems

To solve the unit commitment problem economically and quickly,an improved dual particle swarm optimization(PSO) algorithm including both discrete and continuous parts was proposed.The starting and shutdown state of units were optimized according to different period of time using discrete PSO,and a pair of critical operators was added into the algorithm;in addition,the criterion condition of feasible solution was modified,where the sum of each unit's lowest value must be smaller than the load to some extent.The inheritance from earlier state and constraints to later period of time for running time and shutdown time were considered.The continuous PSO was used in units' load dispatch during the process of deciding starting-stopping states and after the solution,where constraints of power balance,spinning reserve and lower and upper limits were considered.While solving the economic load dispatch,penalty function was adopted to satisfy the ramp rate constraints,and the minimum coal consumptions could be gained.Two examples including 24 period of time were simulated,the experimental results of which showed the proposed approach decreased amount of effort during search and improved convergence rate.In addition,the new method suggests new thinking for unit commitment problem.