CAJ | 학술논문

针对配电网中分布式电源(distributed generation,DG)的选址和定容问题,在研究标准粒子群优化算法的基础上建立有功网损和DG运行费用最小的目标函数。考虑运行中的约束条件,利用旋转门更新的量子粒子群算法(quantum particle swarm optimization,QPSO)分析DG接入位置、容量不确定的情况下将目标函数和约束条件转换为综合目标函数,并求得最优解。对 IEEE14节点配电测试系统进行算例仿真,比较仿真结果与粒子群算法优化结果,验证了QPSO在分布式电源规划上的收敛性和适应性。
침대배전망중분포식전원(distributed generation,DG)적선지화정용문제,재연구표준입자군우화산법적기출상건립유공망손화DG운행비용최소적목표함수。고필운행중적약속조건,이용선전문경신적양자입자군산법(quantum particle swarm optimization,QPSO)분석DG접입위치、용량불학정적정황하장목표함수화약속조건전환위종합목표함수,병구득최우해。대 IEEE14절점배전측시계통진행산례방진,비교방진결과여입자군산법우화결과,험증료QPSO재분포식전원규화상적수렴성화괄응성。
Aiming at problems of site selection and constant volume of distributed generation in power distribution network, this paper discusses establishment of minimum objective functions of power loss and DG running cost on the basis of studying standard particle swarm optimization algorithm.Considering constraint condition in operation and using updated quantum particle swarm optimization algorithm of rotation gate,this paper analyzes transformation of objective functions and con-straint condition into generalized objective functions under conditions of uncertain DG connecting position and capacities and acquires optimal solutions.Example simulation on IEEE 1 4 node power distribution testing system was conducted and simula-tion result was compared with result of particle swarm optimization algorithm.Astringency and adaptability of QPSO in DG planning was verified.