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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. Noor Hussain & Mashood Nasir & Juan Carlos Vasquez & Josep M. Guerrero, 2020. "Recent Developments and Challenges on AC Microgrids Fault Detection and Protection Systems–A Review," Energies, MDPI, vol. 13(9), pages 1-31, May.
    2. Hu, Mian & Wang, Yan-Wu & Xiao, Jiang-Wen & Lin, Xiangning, 2019. "Multi-energy management with hierarchical distributed multi-scale strategy for pelagic islanded microgrid clusters," Energy, Elsevier, vol. 185(C), pages 910-921.
    3. Chen, J.J. & Qi, B.X. & Rong, Z.K. & Peng, K. & Zhao, Y.L. & Zhang, X.H., 2021. "Multi-energy coordinated microgrid scheduling with integrated demand response for flexibility improvement," Energy, Elsevier, vol. 217(C).
    4. Giaouris, Damian & Papadopoulos, Athanasios I. & Ziogou, Chrysovalantou & Ipsakis, Dimitris & Voutetakis, Spyros & Papadopoulou, Simira & Seferlis, Panos & Stergiopoulos, Fotis & Elmasides, Costas, 2013. "Performance investigation of a hybrid renewable power generation and storage system using systemic power management models," Energy, Elsevier, vol. 61(C), pages 621-635.
    5. Giaouris, Damian & Papadopoulos, Athanasios I. & Patsios, Charalampos & Walker, Sara & Ziogou, Chrysovalantou & Taylor, Phil & Voutetakis, Spyros & Papadopoulou, Simira & Seferlis, Panos, 2018. "A systems approach for management of microgrids considering multiple energy carriers, stochastic loads, forecasting and demand side response," Applied Energy, Elsevier, vol. 226(C), pages 546-559.
    6. Navid Rezaei & Abdollah Ahmadi & Mohammadhossein Deihimi, 2022. "A Comprehensive Review of Demand-Side Management Based on Analysis of Productivity: Techniques and Applications," Energies, MDPI, vol. 15(20), pages 1-28, October.
    7. Chicco, Gianfranco & Mancarella, Pierluigi, 2009. "Matrix modelling of small-scale trigeneration systems and application to operational optimization," Energy, Elsevier, vol. 34(3), pages 261-273.
    8. Silvente, Javier & Aguirre, Adrián M. & Zamarripa, Miguel A. & Méndez, Carlos A. & Graells, Moisès & Espuña, Antonio, 2015. "Improved time representation model for the simultaneous energy supply and demand management in microgrids," Energy, Elsevier, vol. 87(C), pages 615-627.
    9. Cagnano, A. & Caldarulo Bugliari, A. & De Tuglie, E., 2018. "A cooperative control for the reserve management of isolated microgrids," Applied Energy, Elsevier, vol. 218(C), pages 256-265.
    10. Luís Sousa Rodrigues & Daniel Lemos Marques & Jorge Augusto Ferreira & Vítor António Ferreira Costa & Nelson Dias Martins & Fernando José Neto Da Silva, 2022. "The Load Shifting Potential of Domestic Refrigerators in Smart Grids: A Comprehensive Review," Energies, MDPI, vol. 15(20), pages 1-36, October.
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    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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