JOURNAL ARTICLE

A Hybrid With Cross-Entropy Method and Sequential Quadratic Programming to Solve Economic Load Dispatch Problem

M. S. P. SubathraEaster S. SuviseshamuthuT. Aruldoss Albert VictoireHepzibah A. ChristinalUmberto Amato

Year: 2014 Journal:   IEEE Systems Journal Vol: 9 (3)Pages: 1031-1044   Publisher: Institute of Electrical and Electronics Engineers

Abstract

This paper presents a new hybrid approach integrating the cross-entropy (CE) algorithm and the sequential quadratic programming (SQP) technique to solve the economic load dispatch (ELD) problem related to electrical power generating units. Due to the introduction of the valve-point effect in the ELD objective function, the optimization task requires tools appropriate for a nonconvex optimization landscape. In this respect, we employ the CE approach, which constructs a random sequence of solutions probabilistically converging to a near-optimal solution and, thus, facilitating the exploration capability. Additionally, to fine-tune the solution in promising basins of attraction, the SQP algorithm is invoked, which performs a local search. Despite its reliance on a global heuristic scheme, CE-SQP is vested with fast convergence capability, which may entail its use for online power dispatch. The effectiveness and the robustness of the proposed method in comparison with several state-of-the-art approaches have been demonstrated with four standard test systems that are widely reported in the ELD literature.

Keywords:
Sequential quadratic programming Mathematical optimization Economic dispatch Computer science Quadratic programming Robustness (evolution) Entropy (arrow of time) Linear programming Electric power system Mathematics Power (physics)

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122
Cited By
4.25
FWCI (Field Weighted Citation Impact)
81
Refs
0.96
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Citation History

Topics

Electric Power System Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Optimal Power Flow Distribution
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Smart Grid Energy Management
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
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