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Energy Optimization and Management of Demand Response Interactions in a Smart Campus

Author

Listed:
  • Antimo Barbato

    (Deparment of Electronics, Information, and Bioengineering, Polytechnic University of Milan, Piazza Leonardo da Vinci 32, Milano 20133, Italy)

  • Cristiana Bolchini

    (Deparment of Electronics, Information, and Bioengineering, Polytechnic University of Milan, Piazza Leonardo da Vinci 32, Milano 20133, Italy)

  • Angela Geronazzo

    (Deparment of Electronics, Information, and Bioengineering, Polytechnic University of Milan, Piazza Leonardo da Vinci 32, Milano 20133, Italy)

  • Elisa Quintarelli

    (Deparment of Electronics, Information, and Bioengineering, Polytechnic University of Milan, Piazza Leonardo da Vinci 32, Milano 20133, Italy)

  • Andrei Palamarciuc

    (Deparment of Electronics, Information, and Bioengineering, Polytechnic University of Milan, Piazza Leonardo da Vinci 32, Milano 20133, Italy)

  • Alessandro Pitì

    (Deparment of Electronics, Information, and Bioengineering, Polytechnic University of Milan, Piazza Leonardo da Vinci 32, Milano 20133, Italy)

  • Cristina Rottondi

    (Dalle Molle Institute for Artificial Intelligence (IDSIA), University of Lugano (USI)—University of Applied Science and Arts of Southern Switzerland (SUPSI), Manno 6928, Switzerland)

  • Giacomo Verticale

    (Deparment of Electronics, Information, and Bioengineering, Polytechnic University of Milan, Piazza Leonardo da Vinci 32, Milano 20133, Italy)

Abstract

The proposed framework enables innovative power management in smart campuses, integrating local renewable energy sources, battery banks and controllable loads and supporting Demand Response interactions with the electricity grid operators. The paper describes each system component: the Energy Management System responsible for power usage scheduling, the telecommunication infrastructure in charge of data exchanging and the integrated data repository devoted to information storage. We also discuss the relevant use cases and validate the framework in a few deployed demonstrators.

Suggested Citation

  • Antimo Barbato & Cristiana Bolchini & Angela Geronazzo & Elisa Quintarelli & Andrei Palamarciuc & Alessandro Pitì & Cristina Rottondi & Giacomo Verticale, 2016. "Energy Optimization and Management of Demand Response Interactions in a Smart Campus," Energies, MDPI, vol. 9(6), pages 1-20, May.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:6:p:398-:d:70758
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    References listed on IDEAS

    as
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    Cited by:

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    6. Jihoon Moon & Sungwoo Park & Seungmin Rho & Eenjun Hwang, 2019. "A comparative analysis of artificial neural network architectures for building energy consumption forecasting," International Journal of Distributed Sensor Networks, , vol. 15(9), pages 15501477198, September.
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    9. Kai Ma & Yege Bai & Jie Yang & Yangqing Yu & Qiuxia Yang, 2017. "Demand-Side Energy Management Based on Nonconvex Optimization in Smart Grid," Energies, MDPI, vol. 10(10), pages 1-17, October.
    10. Flah Aymen & Chokri Mahmoudi, 2019. "A Novel Energy Optimization Approach for Electrical Vehicles in a Smart City," Energies, MDPI, vol. 12(5), pages 1-22, March.
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