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A new perspective for sizing of distributed generation and energy storage for smart households under demand response

Author

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  • Erdinc, Ozan
  • Paterakis, Nikolaos G.
  • Pappi, Iliana N.
  • Bakirtzis, Anastasios G.
  • Catalão, João P.S.

Abstract

As a recently increasing trend among different applications of smart grid vision, smart households as a new implementation area of demand response (DR) strategies have drawn more attention both in research and in engineering practice. On the other hand, optimum sizing of renewable energy based small scale hybrid systems is also a topic that is widely covered by the existing literature. In this study, the sizing of additional distributed generation (DG) and energy storage systems (ESSs) to be applied in smart households, that due to DR activities have a different daily demand profile compared with normal household profiles, is investigated. To the best knowledge of the authors this is the first attempt in the literature to investigate this issue, also including step-wise decreasing cost functions for DG and ESS, varying load and DG production profiles seasonally, and weekday–weekend horizons for a long-term analysis period. The study is conducted using a mixed-integer linear programming (MILP) framework for home energy management system (HEM) modeling and techno-economical sizing. Also, different sensitivity analyses considering the impacts of variation of economic inputs on the provided model are realized.

Suggested Citation

  • Erdinc, Ozan & Paterakis, Nikolaos G. & Pappi, Iliana N. & Bakirtzis, Anastasios G. & Catalão, João P.S., 2015. "A new perspective for sizing of distributed generation and energy storage for smart households under demand response," Applied Energy, Elsevier, vol. 143(C), pages 26-37.
    • Handle: RePEc:eee:appene:v:143:y:2015:i:c:p:26-37
    DOI: 10.1016/j.apenergy.2015.01.025
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    References listed on IDEAS

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    1. Erdinc, O. & Uzunoglu, M., 2012. "Optimum design of hybrid renewable energy systems: Overview of different approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1412-1425.
    2. Matallanas, E. & Castillo-Cagigal, M. & Gutiérrez, A. & Monasterio-Huelin, F. & Caamaño-Martín, E. & Masa, D. & Jiménez-Leube, J., 2012. "Neural network controller for Active Demand-Side Management with PV energy in the residential sector," Applied Energy, Elsevier, vol. 91(1), pages 90-97.
    3. Erdinc, Ozan, 2014. "Economic impacts of small-scale own generating and storage units, and electric vehicles under different demand response strategies for smart households," Applied Energy, Elsevier, vol. 126(C), pages 142-150.
    4. Bartusch, Cajsa & Alvehag, Karin, 2014. "Further exploring the potential of residential demand response programs in electricity distribution," Applied Energy, Elsevier, vol. 125(C), pages 39-59.
    5. Broeer, Torsten & Fuller, Jason & Tuffner, Francis & Chassin, David & Djilali, Ned, 2014. "Modeling framework and validation of a smart grid and demand response system for wind power integration," Applied Energy, Elsevier, vol. 113(C), pages 199-207.
    6. 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.
    7. Zhao, Jiayun & Kucuksari, Sadik & Mazhari, Esfandyar & Son, Young-Jun, 2013. "Integrated analysis of high-penetration PV and PHEV with energy storage and demand response," Applied Energy, Elsevier, vol. 112(C), pages 35-51.
    8. Shen, Bo & Ghatikar, Girish & Lei, Zeng & Li, Jinkai & Wikler, Greg & Martin, Phil, 2014. "The role of regulatory reforms, market changes, and technology development to make demand response a viable resource in meeting energy challenges," Applied Energy, Elsevier, vol. 130(C), pages 814-823.
    9. Rastegar, Mohammad & Fotuhi-Firuzabad, Mahmud & Aminifar, Farrokh, 2012. "Load commitment in a smart home," Applied Energy, Elsevier, vol. 96(C), pages 45-54.
    10. Li, Xiao Hui & Hong, Seung Ho, 2014. "User-expected price-based demand response algorithm for a home-to-grid system," Energy, Elsevier, vol. 64(C), pages 437-449.
    11. Wissner, Matthias, 2011. "The Smart Grid - A saucerful of secrets?," Applied Energy, Elsevier, vol. 88(7), pages 2509-2518, July.
    12. Joung, Manho & Kim, Jinho, 2013. "Assessing demand response and smart metering impacts on long-term electricity market prices and system reliability," Applied Energy, Elsevier, vol. 101(C), pages 441-448.
    13. Fadaee, M. & Radzi, M.A.M., 2012. "Multi-objective optimization of a stand-alone hybrid renewable energy system by using evolutionary algorithms: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3364-3369.
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