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Optimal scheduling algorithm for residential building distributed energy source systems using Levy flight and chaos-assisted artificial rabbits optimizer

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submitted on 2023-05-21, 11:58 and posted on 2023-05-22, 05:09 authored by M. Premkumar, D. Sathish Kumar, C. Kumar, S.M. Muyeen

The increase in demand for MicroGrids (MGs) is a significant factor in the provision of electricity in the future, mainly due to the use of renewable energy sources, which reduces the release of hazardous gases. The grid-connected MG operation is the most cost-effective and reliable because it actively involves the grid buying and selling power, lowering the electricity cost of the MG. This study describes a residential thermal/electrical home energy system comprising a battery energy storage system and a combined heat and power fuel cell. The optimal planning of various energy resources is scheduled by a new optimization algorithm called Levy Flight and Chaos-assisted Artificial Rabbits Optimization (LFCARO), resulting in the lowest operational cost of this combined power system. The operating cost of a residential building is reduced by using a day-ahead scheduling process for controlling multiple energy sources to create a reliable look-up table that estimates the best schedule for the distributed energy sources at each time frame. The impact of various electricity prices for obtaining energy from the primary grid on the system’s operating costs is examined. The efficiency of LFCARO is compared with other algorithms, and the results show that LFCARO performs better than other algorithms. The execution time of the proposed LFCARO is less than 1 sec. for 10 numerical problems and less than 1.5 sec. for the resource scheduling of residential distribution systems. Based on the average Friedman’s ranking test values, the proposed algorithm stands first with 1.82 for numerical and real-world scheduling problems. 

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Published in: Energy Reports
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Open Access funding provided by the Qatar National Library.



  • English



Publication Year

  • 2023

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This Item is licensed under the Creative Commons Attribution 4.0 International License

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  • Qatar University
  • College of Engineering - QU

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