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Combined heat and power economic dispatch using an adaptive cuckoo search with differential evolution mutation

Lookup NU author(s): Professor Qiangda Yang, Peng Liu, Dr Jie ZhangORCiD



This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


In power system operation, the combined heat and power economic dispatch (CHPED) is an attractive and momentous optimization problem where the major objective is to find an optimal generation schedule of heat and power to meet the heat and power demands with the minimum cost, while satisfying various practical operation constraints. This paper puts forward an adaptive cuckoo search with differential evolution mutation (ACS-DEM) for solving the CHPED problem. Compared with the basic cuckoo search (CS), there are three main improvements in the proposed ACS-DEM. The first improvement is that adaptive parameters are employed and therefore no parameter adjustment is required. The second is the incorporation of a Gaussian sampling strategy into the global search phase of the algorithm to increase the exploration capability. The third is the introduction of an improved differential evolution mutation strategy into the local search phase to replace the simple biased random walk in the basic CS, thus discouraging the blindness and enhancing the exploitation capability. The outstanding performance of ACS-DEM is first confirmed through the test suite from the 2017 Conference on Evolutionary Computation and then demonstrated on several CHPED problems. The obtained dispatch schedules from ACS-DEM are feasible and in most cases exhibit a distinct improvement over the results offered by six other CS-based algorithms, one state-of-the-art differential evolution algorithm, as well as recent works in this field.

Publication metadata

Author(s): Yang Q, Liu P, Zhang J, Dong N

Publication type: Article

Publication status: Published

Journal: Applied Energy

Year: 2022

Volume: 307

Print publication date: 01/02/2022

Online publication date: 10/11/2021

Acceptance date: 11/10/2021

Date deposited: 20/10/2021

ISSN (print): 0306-2619

ISSN (electronic): 1872-9118

Publisher: Elsevier Ltd


DOI: 10.1016/j.apenergy.2021.118057


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