Solution of the Multi-objective Economic and Emission Load Dispatch Problem Using Adaptive Real Quantum Inspired Evolutionary Algorithm

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Published: Jan 16, 2023
DOI: https://doi.org/10.17762/ijritcc.v11i1s.5989
Keywords:
power system, meta-heuristics, multi-objective, economic load dispatch, Quantum inspired Evolutionary Algorithms

Main Article Content

Jitender Singh
Ph.D. Scholar, EEE Department Amity University, Noida,Uttar pradesh, India
Ashish Mani
Professor, EEE Department, Amity University, Noida,Uttar pradesh, India
H.P. Singh
Professor, EEE Department, Amity University, Noida,Uttar pradesh, India
Dinesh Singh Rana
Professor, Department of Instrumentation, U.S.I.C., Kurukshetra University, Kurukshetra, Haryana, India

Abstract

Economic load dispatch is a complex and significant problem in power generation. The inclusion of emission with economic operation makes it a Multi-objective economic emission load dispatch (MOEELD) problem. So it is a tough task to resolve a constrained MOEELD problem with antagonistic multiple objectives of emission and cost. Evolutionary Algorithms (EA) have been widely used for solving such complex multi-objective problems. However, the performance of EAs on such problems is dependent on the choice of the operators and their parameters, which becomes a complex issue to solve in itself. The present work is carried out to solve a Multi-objective economic emission load dispatch problem using a Multi-objective adaptive real coded quantum-inspired evolutionary algorithm (MO-ARQIEA) with gratifying all the constraints of unit and system. A repair-based constraint handling and adaptive quantum crossover operator (ACO) are used to satisfy the constraints and preserve the diversity of the suggested approach. The suggested approach is evaluated on the IEEE 30-Bus system consisting of six generating units. These results obtained for different test cases are compared with other reputed and well-known techniques.

Article Details

How to Cite
Singh, J. ., Mani, A. ., Singh, H. ., & Rana, D. S. . (2023). Solution of the Multi-objective Economic and Emission Load Dispatch Problem Using Adaptive Real Quantum Inspired Evolutionary Algorithm. International Journal on Recent and Innovation Trends in Computing and Communication, 11(1s), 01–12. https://doi.org/10.17762/ijritcc.v11i1s.5989
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Vol. 11 No. 1s (2023): Advances in Communication and Computing Paradigms
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Articles

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