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Comprehensive smart home energy management system using mixed-integer quadratic-programming

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  • Killian, M.
  • Zauner, M.
  • Kozek, M.

Abstract

Handling of varying energy sources and flexible connection to smart grids is a current challenge. Minimizing the overall monetary cost and maximizing the use of renewable energy sources are not the exclusive optimization goals, but also guaranteeing the thermal comfort is an important goal. This paper deals with a comprehensive approach of a mixed-integer quadratic-programming model predictive control scheme based on the thermal building model and the building energy management system. Calculating the global optima while handling continuous and binary constraints as well as variables and considering both the thermal and electrical part of a smart home are the key aspect of the proposed model predictive controller. By inclusion of disturbance forecasts, occupancy prediction, and individual user weights the control scheme is optimally suited for implementation in real buildings. Furthermore, the occupancy prediction in this research is based on an unsupervised method, which is useful for an effective implementation. This work demonstrates the optimal management of appliances such as heating, a battery storage, a freezer, a dishwasher, a photo-voltaic system, and the opportunities to buy from and sell to the smart grid. Optimal utilization of the building’s thermal storage capacity helps to minimize necessary battery capacity. Simulation results underline the efficient global optimization while demonstrating all proposed features of the complex control scheme.

Suggested Citation

  • Killian, M. & Zauner, M. & Kozek, M., 2018. "Comprehensive smart home energy management system using mixed-integer quadratic-programming," Applied Energy, Elsevier, vol. 222(C), pages 662-672.
    • Handle: RePEc:eee:appene:v:222:y:2018:i:c:p:662-672
    DOI: 10.1016/j.apenergy.2018.03.179
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    1. Ferracuti, Francesco & Fonti, Alessandro & Ciabattoni, Lucio & Pizzuti, Stefano & Arteconi, Alessia & Helsen, Lieve & Comodi, Gabriele, 2017. "Data-driven models for short-term thermal behaviour prediction in real buildings," Applied Energy, Elsevier, vol. 204(C), pages 1375-1387.
    2. Zhou, Bin & Li, Wentao & Chan, Ka Wing & Cao, Yijia & Kuang, Yonghong & Liu, Xi & Wang, Xiong, 2016. "Smart home energy management systems: Concept, configurations, and scheduling strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 30-40.
    3. Fiorentini, Massimo & Wall, Josh & Ma, Zhenjun & Braslavsky, Julio H. & Cooper, Paul, 2017. "Hybrid model predictive control of a residential HVAC system with on-site thermal energy generation and storage," Applied Energy, Elsevier, vol. 187(C), pages 465-479.
    4. Rastegar, Mohammad & Fotuhi-Firuzabad, Mahmud & Aminifar, Farrokh, 2012. "Load commitment in a smart home," Applied Energy, Elsevier, vol. 96(C), pages 45-54.
    5. Wu, Xiaohua & Hu, Xiaosong & Yin, Xiaofeng & Zhang, Caiping & Qian, Shide, 2017. "Optimal battery sizing of smart home via convex programming," Energy, Elsevier, vol. 140(P1), pages 444-453.
    6. Foucquier, Aurélie & Robert, Sylvain & Suard, Frédéric & Stéphan, Louis & Jay, Arnaud, 2013. "State of the art in building modelling and energy performances prediction: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 272-288.
    7. Haider, Haider Tarish & See, Ong Hang & Elmenreich, Wilfried, 2016. "A review of residential demand response of smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 166-178.
    8. Oldewurtel, Frauke & Sturzenegger, David & Morari, Manfred, 2013. "Importance of occupancy information for building climate control," Applied Energy, Elsevier, vol. 101(C), pages 521-532.
    9. Jin, Xin & Baker, Kyri & Christensen, Dane & Isley, Steven, 2017. "Foresee: A user-centric home energy management system for energy efficiency and demand response," Applied Energy, Elsevier, vol. 205(C), pages 1583-1595.
    10. Gottwalt, Sebastian & Ketter, Wolfgang & Block, Carsten & Collins, John & Weinhardt, Christof, 2011. "Demand side management—A simulation of household behavior under variable prices," Energy Policy, Elsevier, vol. 39(12), pages 8163-8174.
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