Abstract
Economic Dispatch (ED) is one of the important problems among numerous vital operational problems of power economics. ED is a non-convex, non-drivable, and non-linear optimization issue along with diverse constraints. In this research work, a neoteric natural influential optimization tool Multi-verse Optimizer (MVO) hybridized with sequential quadratic programming (SQP) termed as Hybrid MVO (MVO-SQP) is proposed for the solution of multi-constrained ED problem. This contemporary effort contemplates on ED problem in the milieu of convergence features, numerical proficiency, and stoutness.The non-convex ED problem is encrypted at Hybrid Multi-verse Optimizer (HMVO) framework and employed in MATLAB for 30 trials, 300 iterations, and 30 exploration universes. The presented mechanism is verified on typical standard test systems comprising of 6, 13, 15, and 40 unit test systems, and experimental outcomes are juxtaposed with the reported approaches in the literature. The statistical analysis shows that the proposed approach saves 2.927 $/h for 6 units test system, 9.0618 $/h for 13 units test system, 1.831 $/h for 15 units test system, and 113.515 $/hr for 40 units test system with losses. It is envisioned that this work will equip the researchers with an improved tool to solve ED problem.
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