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The application of the Jellyfish search algorithm for solving Modified economic load dispatch under the consideration of prohibited operation zones, varied load demand, and renewable energy sources

Thu Quach Minh, Minh Nghia Pham

Abstract


In this research, an expanded version of the original economic load dispatch problem (EELD) is concerned to optimize operation of power plants in power systems. While solving the problem, the power supplied from solar energy is considered in addition to the conventional thermal power plants. The main objective function of the research is to minimize the entire electricity generating cost (EEGC) of all thermal power plants in the systems. On top of that, the unactive operating areas belonging to thermal generators and the fluctuating load demand throughout 24 hours are also validated. Moreover, the power supplied by the unique solar power plant is also varied within 24 hours. Two meta-heuristic algorithms, including the artificial hummingbird algorithm (AHA) and the jellyfish swarm algorithm (JFSA) are applied to solve the EELD problem. Both AHA and JFSA are tested for finding the raw performance on the power system with six thermal power plants and one solar power plant. The results obtained by the two applied algorithms indicate that JSFA is completely superior to AHA in all comparing criteria. Hence, JFSA is acknowledged as an effective computing method, and it is highly recommended to be used for the EELD.


Keywords


Modified economic load dispatch (MELD); Jellyfish optimization; Salp swarm optimization; thermal generator; wind and solar energies; load demand variation.

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References


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