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Robust Optimal Planning and Operation of Electrical Energy Systems pp 95–107Cite as

Optimal Robust Scheduling of Renewable Energy-Based Smart Homes Using Information-Gap Decision Theory (IGDT)

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Abstract

This chapter aims to study energy management of a renewable energy-based smart home, which contains of photovoltaic (PV) system for supplying a ratio of electrical demand of the considered home. Moreover, the plug-in electric vehicles (PEVs) are considered in obtaining optimal robust scheduling of the studied smart home. The main objective is minimizing the consumer’s bill as a smart home energy management scheduling problem. The controllable appliances are considered including washing machine, water heater, fridge, and electric vehicle. The robust self-scheduling of PV panel installed in the smart home is formulated, and the best suited set point of all suppliers is obtained. Information-gap decision theory (IGDT) is implemented in order to handle the uncertain PV power generation. The optimal robust scheduling of different appliance categories is provided considering economic optimal dispatch of the energy sources.

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Authors and Affiliations

  1. Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran

    Morteza Nazari-Heris, Parinaz Aliasghari, Behnam Mohammadi-ivatloo & Mehdi Abapour

Authors
  1. Morteza Nazari-Heris
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  2. Parinaz Aliasghari
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  3. Behnam Mohammadi-ivatloo
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  4. Mehdi Abapour
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Corresponding author

Correspondence to Parinaz Aliasghari .

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Editors and Affiliations

  1. Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran

    Behnam Mohammadi-ivatloo

  2. Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran

    Morteza Nazari-Heris

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Nazari-Heris, M., Aliasghari, P., Mohammadi-ivatloo, B., Abapour, M. (2019). Optimal Robust Scheduling of Renewable Energy-Based Smart Homes Using Information-Gap Decision Theory (IGDT). In: Mohammadi-ivatloo, B., Nazari-Heris, M. (eds) Robust Optimal Planning and Operation of Electrical Energy Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-04296-7_6

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  • DOI: https://doi.org/10.1007/978-3-030-04296-7_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04295-0

  • Online ISBN: 978-3-030-04296-7

  • eBook Packages: EngineeringEngineering (R0)

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