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Design and Implementation of Demand Side Response Based on Binomial Distribution

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  • Ming Li

    (Department of Mechanical and Electrical Engineering, Yangjiang Polytechnic, Yangjiang 529500, China)

  • Jin Ye

    (School of Computer, Electronics and Information, Guangxi University, Nanning 530004, China)

Abstract

The application of microgrids (MG) is more and more extensive, therefore it is important to improve the system management method of microgrids. The intended costs can be further minimized when the energy management system is unified with demand side response (DSR) strategies. In this work, we propose a generic method of modeling the equipment in a microgrid including multiple stochastic loads. The microgrid model can be generated on a computer by converting the energy circuit diagram into a signal flow diagram. Then, a demand side response method based on binomial distribution is introduced, and loads are set to different probabilities according to importance. By applying the probability of loads and changing the return coefficient of loads, the problem of individual differences in demand side responses is solved, so as to improve consumer satisfaction. The proposed model is constructed as a mixed-integer linear program (MILP). Cases studies demonstrate feasibility of the proposed modeling method. The demand side response achieves the expected goal. The system management method reduces the operation cost of the energy system of microgrids.

Suggested Citation

  • Ming Li & Jin Ye, 2022. "Design and Implementation of Demand Side Response Based on Binomial Distribution," Energies, MDPI, vol. 15(22), pages 1-15, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:22:p:8431-:d:969530
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    References listed on IDEAS

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    1. Xuehua Wu & Qianqian Qian & Yuqing Bao, 2022. "Demand Response Using Disturbance Estimation-Based Kalman Filtering for the Frequency Control," Energies, MDPI, vol. 15(24), pages 1-14, December.
    2. Marian Kampik & Marcin Fice & Adam Pilśniak & Krzysztof Bodzek & Anna Piaskowy, 2023. "An Analysis of Energy Consumption in Small- and Medium-Sized Buildings," Energies, MDPI, vol. 16(3), pages 1-21, February.

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