中国电机工程学报2012，Vol.32Issue(25)：189-195,7.
一种用于机组组合问题的改进双重粒子群算法
An Improved Dual Particle Swarm Optimization Algorithm for Unit Commitment Problem
摘要
Abstract
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.关键词
机组组合/双重粒子群优化/分时段/临界算子/罚函数Key words
unit commitment/ dual particle swarm optimization/ divided period/ critical operator/ penalty function分类
信息技术与安全科学引用本文复制引用
李整,谭文,秦金磊..一种用于机组组合问题的改进双重粒子群算法[J].中国电机工程学报,2012,32(25):189-195,7.基金项目
河北省自然科学基金项目(F2011502069) （F2011502069）
北京市自然科学基金项目(4122075). （4122075）
