A Bio-inspired Meta-heuristic Optimization approach for Economic Load Dispatch

Rishabh Bhargava, Manas Dixit, Ishan Gupta,T. Nageswara Prasad,Rajeshkumar Muthu,Rani Chinnappa Naidu

2022 7th International Conference on Environment Friendly Energies and Applications (EFEA)(2022)

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摘要
Scarcity of energy resources, rising electricity generating costs, environmental impacts, and ever-increasing demand for electrical power need optimal economic dispatch in the modern scenario. The expense of generator fuel determines the percentage of a power plant's operating costs, which are minimized via optimal load dispatch (OLD). The OLD problem is determining the best and cheapest power generating strategy among a set of on-line producing units to supply the whole power requirements at a particular period. This paper presents bio-inspired meta-heuristic Ant Lion Optimizer (ALO) techniques to solve the economic load dispatch problem. The main objective of this paper is to reduce the generation fuel cost while meeting equality and inequality requirements. The obtained results demonstrate that the proposed approach can significantly reduce generating expenses even while satisfying the constraints (Power Stability as well as Generation Limit).
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关键词
Ant Lion Optimization,Fuel Cost,Generators,Load Dispatch
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