Economic and Green Dispatch in Multi-Area Power Systems: An Approach of using NDSGA-II

This paper introduces an improved strategy for multi-area economic and environmental dispatch (MAEED) utilizing the Non-Dominated Sorting Genetic Algorithm II (NSGA-II).As the global push for sustainable energy solutions intensifies, optimizing power distribution to minimize both cost and emissions has become essential.This work formulates MAEED as a bi-goal nonlinear constrained optimization problem incorporating power balance, generation capacity, and tie-line limits.The proposed NSGA-II is benchmarked against Strength Pareto Evolutionary Algorithm II (SPEA-II) and other contemporary methods.Simulation results on a four-area power system illustrate that NSGA-II consistently outperforms alternatives by offering superior trade-offs between cost and emissions.Recent studies support these findings, highlighting the robustness of evolutionary approaches in multi-goal dispatch problems.I.

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Publication Details

Journal
International Journal of Communication Science and Technology
Published
2025-01-01
DOI
https://doi.org/10.70965/ijcst.vol.1.issue3.12
Primary Topic
Renewable energy and sustainable power systems
Type
article
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article

Economic and Green Dispatch in Multi-Area Power Systems: An Approach of using NDSGA-II

Manpreet Singh Manna, Arnab Ganguly, Amartya Roy, Abhik Hazra et al.
1 links
International Journal of Communication Science and Technology
Renewable energy and sustainable power systems
article

Economic and Green Dispatch in Multi-Area Power Systems: An Approach of using NDSGA-II

Manpreet Singh Manna, Arnab Ganguly, Amartya Roy, Abhik Hazra, Rakesh Naskar
article en

Abstract

This paper introduces an improved strategy for multi-area economic and environmental dispatch (MAEED) utilizing the Non-Dominated Sorting Genetic Algorithm II (NSGA-II).As the global push for sustainable energy solutions intensifies, optimizing power distribution to minimize both cost and emissions has become essential.This work formulates MAEED as a bi-goal nonlinear constrained optimization problem incorporating power balance, generation capacity, and tie-line limits.The proposed NSGA-II is benchmarked against Strength Pareto Evolutionary Algorithm II (SPEA-II) and other contemporary methods.Simulation results on a four-area power system illustrate that NSGA-II consistently outperforms alternatives by offering superior trade-offs between cost and emissions.Recent studies support these findings, highlighting the robustness of evolutionary approaches in multi-goal dispatch problems.I.

International Journal of Communication Science and TechnologyVol. 1(3)
Memorial Foundation (US)
Openalex Percentile: Top 91%
Renewable energy and sustainable power systems
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