An enhanced multi‐objective differential evolution algorithm for dynamic environmental economic dispatch of power system with wind power

Dynamic environmental economic dispatch (DEED) with wind power is an important extension of the classical environmental economic dispatch (EED) problem, which could provide reasonable scheduling scheme to minimize the pollution emission and economic cost at the same time. In this study, the combined...

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Bibliographic Details
Published in:Energy science & engineering Vol. 9; no. 3; pp. 316 - 329
Main Authors: Bai, Yingjie, Wu, Xuedong, Xia, Aiming
Format: Journal Article
Language:English
Published: London John Wiley & Sons, Inc 01.03.2021
Wiley
Subjects:
Algorithms
dynamic environmental economic dispatch
Economic impact
Economics
Emission analysis
Emissions
enhanced multi‐objective differential evolution algorithm
Evolutionary algorithms
Evolutionary computation
Fossil fuels
Methods
Optimization
Optimization algorithms
Penalty function
Pollutants
Power dispatch
Scheduling
selection strategies
Thermal power
Wind power
ISSN:2050-0505, 2050-0505
Online Access:Get full text
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Summary:Dynamic environmental economic dispatch (DEED) with wind power is an important extension of the classical environmental economic dispatch (EED) problem, which could provide reasonable scheduling scheme to minimize the pollution emission and economic cost at the same time. In this study, the combined dynamic scheduling of thermal power and wind power is carried out with pollutant emission and economic cost as optimization objectives; meanwhile, the valve‐point effect, power balance, ramp rate, and other constraints are taken into consideration. In order to solve the DEED problem, an enhanced multi‐objective differential evolution algorithm (EMODE) is proposed, which adopts the superiority of feasible solution (SF) and nondominated sorting (NDS) two selection strategies to improve the optimization effect. The suggested algorithm combines the total constraint violation and penalty function to deal with various constraints, due to different constraint techniques could be effective during different stages of searching process, and this method could ensure that each individual in the Pareto front (PF) is feasible. The results show that the proposed algorithm can deal with DEED problem with wind power effectively, and provide better dynamic scheduling scheme for power system. For the problem of power system dynamic dispatch with wind power, an enhanced multi‐objective differential evolution algorithm is proposed in this paper, which adopts two selection strategies and different constraint handling process techniques. The suggested method has strong ability for the problem of dispatch, and from the simulation results, we can obtain that this method could provide better dispatch scheme for decision‐makers.
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ISSN:2050-0505
2050-0505
DOI:10.1002/ese3.827