Renewable Energy Based Economic Emission Load Dispatch Using Grasshopper Optimization Algorithm

Sunanda Hazra, Tapas Pal and Provas Kumar Roy
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Sunanda Hazra: Department of Electrical Engineering, Central Institute of Plastics Engineering and Technology, Haldia, West Bengal, India
Tapas Pal: Department of Electrical Engineering, Kalyani Government Engineering College, Kalyani, West Bengal, India
Provas Kumar Roy: Kalyani Government Engineering College, India

International Journal of Swarm Intelligence Research (IJSIR), 2019, vol. 10, issue 1, 38-57

Abstract: This article presents an integrated approach towards the economical operation of a hybrid system which consists of conventional thermal generators and renewable energy sources like windmills using a grasshopper optimization algorithm (GOA). This is based on the social interaction nature of the grasshopper, considering a carbon tax on the emissions from the thermal unit and uncertainty in wind power availability. The Weibull distribution is used for nonlinearity of wind power availability. A standard system, containing six thermal units and two wind farms, is used for testing the dispatch model of three different loads. The GOA results are compared with those obtained using a recently developed quantum-inspired particle swarm optimization (QPSO) optimization technique available in the literature. The simulation results demonstrate the efficacy and ability of GOA over the QPSO algorithm in terms of convergence rate and minimum fitness value. Performance analysis under wind power integration and emission minimization further confirms the supremacy of the GOA algorithm.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jsir00:v:10:y:2019:i:1:p:38-57

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