An improved quantum particle swarm optimization algorithm for environmental economic dispatch

作者：

Highlights：

• We consider both fuel costs and emissions, and find the best compromise value.

• We introduce differential evolution operator into quantum particle swarm optimization (QPSO).

• We introduce crossover operator into quantum particle swarm optimization (QPSO).

• Adaptive control is adopted for crossover probability.

摘要

•We consider both fuel costs and emissions, and find the best compromise value.•We introduce differential evolution operator into quantum particle swarm optimization (QPSO).•We introduce crossover operator into quantum particle swarm optimization (QPSO).•Adaptive control is adopted for crossover probability.

论文关键词：Environmental economic dispatch,Carbon emission reduction,Quantum particle swarm optimization,Differential evolution operator,Crossover operator,Adaptive control

论文评审过程：Received 31 May 2019, Revised 5 March 2020, Accepted 8 March 2020, Available online 9 March 2020, Version of Record 30 April 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113370