布谷鸟搜索
经济调度
数学优化
布谷鸟
计算机科学
算法
功率(物理)
电力系统
数学
粒子群优化
动物
物理
量子力学
生物
作者
Jian Zhao,Shixin Liu,MengChu Zhou,Xiwang Guo,Liang Qi
标识
DOI:10.1109/jas.2018.7511138
摘要
A modified cuckoo search (CS) algorithm is proposed to solve economic dispatch (ED) problems that have nonconvex, non-continuous or non-linear solution spaces considering valve-point effects, prohibited operating zones, transmission losses and ramp rate limits. Comparing with the traditional cuckoo search algorithm, we propose a self-adaptive step size and some neighbor-study strategies to enhance search performance. Moreover, an improved lambda iteration strategy is used to generate new solutions. To show the superiority of the proposed algorithm over several classic algorithms, four systems with different benchmarks are tested. The results show its efficiency to solve economic dispatch problems, especially for large-scale systems.
科研通智能强力驱动
Strongly Powered by AbleSci AI