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Demand response in smart electricity grids equipped with renewable energy sources: A review

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  • Aghaei, Jamshid
  • Alizadeh, Mohammad-Iman

Abstract

Dealing with Renewable Energy Resources (RERs) requires sophisticated planning and operation scheduling along with state of art technologies. Among many possible ways for handling RERs, Demand Response (DR) is investigated in the current review. Because of every other year modifications in DR definition and classification announced by Federal Energy Regulatory Commission (FERC), the latest DR definition and classification are scrutinized in the present work. Moreover, a complete benefit and cost assessment of DR is added in the paper. Measurement and evolution methods along with the effects of DR in electricity prices are discussed. Next comes DR literature review of the recent papers majorly published after 2008. Eventually, successful DR implementations, around the world, are analyzed.

Suggested Citation

  • Aghaei, Jamshid & Alizadeh, Mohammad-Iman, 2013. "Demand response in smart electricity grids equipped with renewable energy sources: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 18(C), pages 64-72.
    • Handle: RePEc:eee:rensus:v:18:y:2013:i:c:p:64-72
    DOI: 10.1016/j.rser.2012.09.019
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    References listed on IDEAS

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    1. Moura, Pedro S. & de Almeida, Aníbal T., 2010. "Multi-objective optimization of a mixed renewable system with demand-side management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(5), pages 1461-1468, June.
    2. Baños, R. & Manzano-Agugliaro, F. & Montoya, F.G. & Gil, C. & Alcayde, A. & Gómez, J., 2011. "Optimization methods applied to renewable and sustainable energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(4), pages 1753-1766, May.
    3. Chao, Hung-po, 2010. "Price-Responsive Demand Management for a Smart Grid World," The Electricity Journal, Elsevier, vol. 23(1), pages 7-20, January.
    4. Wang, Jianhui & Bloyd, Cary N. & Hu, Zhaoguang & Tan, Zhongfu, 2010. "Demand response in China," Energy, Elsevier, vol. 35(4), pages 1592-1597.
    5. Yousefi, Shaghayegh & Moghaddam, Mohsen Parsa & Majd, Vahid Johari, 2011. "Optimal real time pricing in an agent-based retail market using a comprehensive demand response model," Energy, Elsevier, vol. 36(9), pages 5716-5727.
    6. Kwag, Hyung-Geun & Kim, Jin-O, 2012. "Optimal combined scheduling of generation and demand response with demand resource constraints," Applied Energy, Elsevier, vol. 96(C), pages 161-170.
    7. Aalami, H.A. & Moghaddam, M. Parsa & Yousefi, G.R., 2010. "Demand response modeling considering Interruptible/Curtailable loads and capacity market programs," Applied Energy, Elsevier, vol. 87(1), pages 243-250, January.
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