Abstract:
A symbiotic multi-swarm coevolutionary optimization algorithm named SMSO(Symbiotic Multi-Species Optimization) is presented for multi-objective economic power dispatch problems such as environment protection and power cost. The effectiveness of SMSO is demonstrated with the IEEE 30-bus system, and the results demonstrate the better Pareto front, the computation complexity reduction and the convergence efficiency improvement of the proposed algorithm.
Key words:
Particle Swarm Optimization(PSO) algorithm,
symbiosis,
power dispatch
摘要: 为解决同时考虑环保要求、发电费用等多个目标的经济调度问题,基于生态系统中不同物种间的互利共生现象,提出一种多种群共生进化优化(SMSO)算法。对一个30节点IEEE系统进行计算,结果显示SMSO算法在获得最优Pareto解集、降低计算复杂度、提高收敛效率等方面具有较大的优越性。
关键词:
粒子群优化算法,
共生,
电力调度
CLC Number:
TUN Ying-Bin, MENG Xian-Meng, CHEN Han-Ning. Application of Multi-Species Coevolutionary Algorithm in Economic Dispatch[J]. Computer Engineering, 2010, 36(22): 173-174.
吴应斌, 孟宪明, 陈瀚宁. 多种群协同进化算法在经济调度中的应用[J]. 计算机工程, 2010, 36(22): 173-174.