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Optimal household energy management and economic analysis: from sizing to operation scheduling


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  • T.T. Ha Pham

    (G2ELAB - Grenoble Electrical Engineering - Institut National Polytechnique de Grenoble (INPG) - Université Joseph Fourier - Grenoble I)

  • Cédric Clastres

    (G2ELAB - Grenoble Electrical Engineering - Institut National Polytechnique de Grenoble (INPG) - Université Joseph Fourier - Grenoble I, LEPII - Laboratoire d'Économie de la Production et de l'Intégration Internationale - CNRS : FRE3389 - Université Pierre Mendès-France - Grenoble II)

  • F. Wurtz

    (G2ELAB - Grenoble Electrical Engineering - Institut National Polytechnique de Grenoble (INPG) - Université Joseph Fourier - Grenoble I)

  • S. Bacha

    (G2ELAB - Grenoble Electrical Engineering - Institut National Polytechnique de Grenoble (INPG) - Université Joseph Fourier - Grenoble I)

  • Eric Zamaï

    (G-SCOP - Laboratoire des sciences pour la conception, l'optimisation et la production - CNRS : UMR5272 - Institut National Polytechnique de Grenoble (INPG) - Université Joseph Fourier - Grenoble I)

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    The study presented in this paper takes part in a project aiming to increase the value of solar production for residential application with a medium-term vision where preferential solar energy subsidies will decrease before to disappear. This study is dedicated to propose and develop optimal energy architecture at supply side, a multi-source system based on photovoltaic (PV) solar energy connecting to main electrical network, taking further into account the effectiveness of intelligent demand side management. To investigate this issue, a method of optimal supplying system sizing and household energy management has been developed. This method, which has been formulated employing Mix Integer Linear Programming (MILP), enables the calculation of the appropriate configuration for power supply system and the optimal operation control to be applied. Using a Net Present Value (NPV) and Probability Index (P.I) basis, the economic analysis allows estimation of the viability of the proposed system under different factors of influence such as renewable energy policies, technology evolutions leading to cheaper installed PV module cost and deregulated electricity market. Simulation results show that, the solution makes it possible for PV power to be significantly valued by the customers without subsidized measures.

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    Bibliographic Info

    Paper provided by HAL in its series Post-Print with number halshs-00323581.

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    Date of creation: 2010
    Date of revision:
    Publication status: Published, Advances and Applications in Mechanical Engineering and Technology, 2010, 1, 1, 35-68
    Handle: RePEc:hal:journl:halshs-00323581

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    Keywords: connected-grid PV system ; battery storage ; sizing optimization ; energy management ; MILP;


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    1. Lise, Wietze & Kruseman, Gideon, 2008. "Long-term price and environmental effects in a liberalised electricity market," Energy Economics, Elsevier, vol. 30(2), pages 230-248, March.
    2. Bernal-Agustín, José L. & Dufo-López, Rodolfo, 2006. "Economical and environmental analysis of grid connected photovoltaic systems in Spain," Renewable Energy, Elsevier, vol. 31(8), pages 1107-1128.
    3. Sáenz de Miera, Gonzalo & del Ri­o González, Pablo & Vizcaino, Ignacio, 2008. "Analysing the impact of renewable electricity support schemes on power prices: The case of wind electricity in Spain," Energy Policy, Elsevier, vol. 36(9), pages 3345-3359, September.
    4. Fernández-Infantes, Alberto & Contreras, Javier & Bernal-Agustín, José L., 2006. "Design of grid connected PV systems considering electrical, economical and environmental aspects: A practical case," Renewable Energy, Elsevier, vol. 31(13), pages 2042-2062.
    5. Hernández, J.C. & Vidal, P.G. & Almonacid, G., 1998. "Photovoltaic in grid-connected buildings, sizing and economic analysis," Renewable Energy, Elsevier, vol. 15(1), pages 562-565.
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    Cited by:
    1. Morini, Mirko & Pinelli, Michele & Spina, Pier Ruggero & Venturini, Mauro, 2013. "Optimal allocation of thermal, electric and cooling loads among generation technologies in household applications," Applied Energy, Elsevier, vol. 112(C), pages 205-214.


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