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A multi-level Demand-Side Management algorithm for offgrid multi-source systems

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  • Roy, Anthony
  • Auger, François
  • Dupriez-Robin, Florian
  • Bourguet, Salvy
  • Tran, Quoc Tuan

Abstract

The use of renewable sources for electricity supply of islands is faced with technical and economic constraints. To ensure that demand is fully met in the event of low generated power, batteries and gensets are often used and these can be expensive due to fuel import and battery costs. To provide more degrees of freedom for these offgrid networks, a multi-level algorithm based on several Demand Side Management strategies is proposed in this paper. The simulated case study concerns an island supplied by a multi-source system including solar, wind, tidal, wave energies and a battery storage solution. To limit the inconvenience for users, a hierarchical application of the proposed strategies is studied, according to a day-ahead forecast. Strategies based on anticipation are firstly applied for electric room heaters and water heaters in order to use the excess of generated power. For the most critical situations, strategies based on load shifting and load shedding are studied. In these cases, the best solution is found using a genetic algorithm. The application of the proposed Demand Side Management algorithm was found to help reduce the unmet load demand rate and adapt load demand according to the power generated.

Suggested Citation

  • Roy, Anthony & Auger, François & Dupriez-Robin, Florian & Bourguet, Salvy & Tran, Quoc Tuan, 2020. "A multi-level Demand-Side Management algorithm for offgrid multi-source systems," Energy, Elsevier, vol. 191(C).
    • Handle: RePEc:eee:energy:v:191:y:2020:i:c:s0360544219322315
    DOI: 10.1016/j.energy.2019.116536
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    Cited by:

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    2. Anthony Roy & François Auger & Jean-Christophe Olivier & Emmanuel Schaeffer & Bruno Auvity, 2020. "Design, Sizing, and Energy Management of Microgrids in Harbor Areas: A Review," Energies, MDPI, vol. 13(20), pages 1-24, October.
    3. Groppi, Daniele & Pfeifer, Antun & Garcia, Davide Astiaso & Krajačić, Goran & Duić, Neven, 2021. "A review on energy storage and demand side management solutions in smart energy islands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    4. Zhang, Yin & Qian, Tong & Tang, Wenhu, 2022. "Buildings-to-distribution-network integration considering power transformer loading capability and distribution network reconfiguration," Energy, Elsevier, vol. 244(PB).
    5. Su, Huai & Chi, Lixun & Zio, Enrico & Li, Zhenlin & Fan, Lin & Yang, Zhe & Liu, Zhe & Zhang, Jinjun, 2021. "An integrated, systematic data-driven supply-demand side management method for smart integrated energy systems," Energy, Elsevier, vol. 235(C).
    6. Ng, Rong Wang & Begam, K.M. & Rajkumar, Rajprasad Kumar & Wong, Yee Wan & Chong, Lee Wai, 2022. "A novel dynamic two-stage controller of battery energy storage system for maximum demand reductions," Energy, Elsevier, vol. 248(C).
    7. Wang, Xinlin & Wang, Hao & Ahn, Sung-Hoon, 2021. "Demand-side management for off-grid solar-powered microgrids: A case study of rural electrification in Tanzania," Energy, Elsevier, vol. 224(C).
    8. Mughees, Neelam & Jaffery, Mujtaba Hussain & Mughees, Anam & Ansari, Ejaz Ahmad & Mughees, Abdullah, 2023. "Reinforcement learning-based composite differential evolution for integrated demand response scheme in industrial microgrids," Applied Energy, Elsevier, vol. 342(C).

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