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Multiobjective Economic/Environmental Dispatch Using Harris Hawks Optimization Algorithm

T. Mahalekshmi1,*, P. Maruthupandi2

1 Jansons Institute of Technology, Coimbatore, 641659, Tamilnadu, India
2 Government College of Technology, Coimbatore, 641013, Tamilnadu, India

* Corresponding Author: T. Mahalekshmi. Email:

Intelligent Automation & Soft Computing 2023, 36(1), 445-460.


The eminence of Economic Dispatch (ED) in power systems is significantly high as it involves in scheduling the available power from various power plants with less cost by compensating equality and inequality constrictions. The emission of toxic gases from power plants leads to environmental imbalance and so it is highly mandatory to rectify this issues for obtaining optimal performance in the power systems. In this present study, the Economic and Emission Dispatch (EED) problems are resolved as multi objective Economic Dispatch problems by using Harris Hawk’s Optimization (HHO), which is capable enough to resolve the concerned issue in a wider range. In addition, the clustering approach is employed to maintain the size of the Pareto Optimal (PO) set during each iteration and fuzzy based approach is employed to extricate compromise solution from the Pareto front. To meet the equality constraint effectively, a new demand-based constraint handling mechanism is adopted. This paper also includes Wind energy conversion system (WECS) in EED problem. The conventional thermal generator cost is taken into account while considering the overall cost functions of wind energy like overestimated, underestimated and proportional costs. The quality of the non-dominated solution set is measured using quality metrics such as Set Spacing (SP) and Hyper-Volume (HV) and the solutions are compared with other conventional algorithms to prove its efficiency. The present study is validated with the outcomes of various literature papers.


Cite This Article

T. Mahalekshmi and P. Maruthupandi, "Multiobjective economic/environmental dispatch using harris hawks optimization algorithm," Intelligent Automation & Soft Computing, vol. 36, no.1, pp. 445–460, 2023.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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