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Energy Flexibility as Additional Energy Source in Multi-Energy Systems with District Cooling

Author

Listed:
  • Alice Mugnini

    (Dipartimento di Ingegneria Industriale e Scienze Matematiche, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy)

  • Gianluca Coccia

    (Dipartimento di Ingegneria Industriale e Scienze Matematiche, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy)

  • Fabio Polonara

    (Dipartimento di Ingegneria Industriale e Scienze Matematiche, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy
    Consiglio Nazionale delle Ricerche, Istituto per le Tecnologie della Costruzione, Viale Lombardia 49, San Giuliano Milanese, 20098 Milan, Italy)

  • Alessia Arteconi

    (Dipartimento di Ingegneria Industriale e Scienze Matematiche, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy
    Department of Mechanical Engineering, KU Leuven, B-3000 Leuven, Belgium)

Abstract

The integration of multi-energy systems to meet the energy demand of buildings represents one of the most promising solutions for improving the energy performance of the sector. The energy flexibility provided by the building is paramount to allowing optimal management of the different available resources. The objective of this work is to highlight the effectiveness of exploiting building energy flexibility provided by thermostatically controlled loads (TCLs) in order to manage multi-energy systems (MES) through model predictive control (MPC), such that energy flexibility can be regarded as an additional energy source in MESs. Considering the growing demand for space cooling, a case study in which the MPC is used to satisfy the cooling demand of a reference building is tested. The multi-energy sources include electricity from the power grid and photovoltaic modules (both of which are used to feed a variable-load heat pump), and a district cooling network. To evaluate the varying contributions of energy flexibility in resource management, different objective functions—namely, the minimization of the withdrawal of energy from the grid, of the total energy cost and of the total primary energy consumption—are tested in the MPC. The results highlight that using energy flexibility as an additional energy source makes it possible to achieve improvements in the energy performance of an MES building based on the objective function implemented, i.e., a reduction of 53% for the use of electricity taken from the grid, a 43% cost reduction, and a 17% primary energy reduction. This paper also reflects on the impact that the individual optimization of a building with a multi-energy system could have on other users sharing the same energy sources.

Suggested Citation

  • Alice Mugnini & Gianluca Coccia & Fabio Polonara & Alessia Arteconi, 2021. "Energy Flexibility as Additional Energy Source in Multi-Energy Systems with District Cooling," Energies, MDPI, vol. 14(2), pages 1-30, January.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:2:p:519-:d:483316
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    References listed on IDEAS

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    1. Mancarella, Pierluigi, 2014. "MES (multi-energy systems): An overview of concepts and evaluation models," Energy, Elsevier, vol. 65(C), pages 1-17.
    2. Heendeniya, Charitha Buddhika & Sumper, Andreas & Eicker, Ursula, 2020. "The multi-energy system co-planning of nearly zero-energy districts – Status-quo and future research potential," Applied Energy, Elsevier, vol. 267(C).
    3. Fontenot, Hannah & Dong, Bing, 2019. "Modeling and control of building-integrated microgrids for optimal energy management – A review," Applied Energy, Elsevier, vol. 254(C).
    4. Ren, Hongbo & Zhou, Weisheng & Nakagami, Ken'ichi & Gao, Weijun & Wu, Qiong, 2010. "Multi-objective optimization for the operation of distributed energy systems considering economic and environmental aspects," Applied Energy, Elsevier, vol. 87(12), pages 3642-3651, December.
    5. Aste, Niccolò & Caputo, Paola & Del Pero, Claudio & Ferla, Giulio & Huerto-Cardenas, Harold Enrique & Leonforte, Fabrizio & Miglioli, Alessandro, 2020. "A renewable energy scenario for a new low carbon settlement in northern Italy: Biomass district heating coupled with heat pump and solar photovoltaic system," Energy, Elsevier, vol. 206(C).
    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. Gianluca Serale & Massimo Fiorentini & Alfonso Capozzoli & Daniele Bernardini & Alberto Bemporad, 2018. "Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities," Energies, MDPI, vol. 11(3), pages 1-35, March.
    8. Gabrielli, Paolo & Gazzani, Matteo & Martelli, Emanuele & Mazzotti, Marco, 2018. "Corrigendum to “Optimal design of multi-energy systems with seasonal storage” [Appl. Energy (2017)]," Applied Energy, Elsevier, vol. 212(C), pages 720-720.
    9. Aoun, Nadine & Bavière, Roland & Vallée, Mathieu & Aurousseau, Antoine & Sandou, Guillaume, 2019. "Modelling and flexible predictive control of buildings space-heating demand in district heating systems," Energy, Elsevier, vol. 188(C).
    10. Lo Cascio, Ermanno & De Schutter, Bart & Schenone, Corrado, 2018. "Flexible energy harvesting from natural gas distribution networks through line-bagging," Applied Energy, Elsevier, vol. 229(C), pages 253-263.
    11. Alice Mugnini & Gianluca Coccia & Fabio Polonara & Alessia Arteconi, 2020. "Performance Assessment of Data-Driven and Physical-Based Models to Predict Building Energy Demand in Model Predictive Controls," Energies, MDPI, vol. 13(12), pages 1-18, June.
    12. Gabrielli, Paolo & Gazzani, Matteo & Martelli, Emanuele & Mazzotti, Marco, 2018. "Optimal design of multi-energy systems with seasonal storage," Applied Energy, Elsevier, vol. 219(C), pages 408-424.
    13. Alice Mugnini & Gianluca Coccia & Fabio Polonara & Alessia Arteconi, 2019. "Potential of District Cooling Systems: A Case Study on Recovering Cold Energy from Liquefied Natural Gas Vaporization," Energies, MDPI, vol. 12(15), pages 1-13, August.
    14. Vandermeulen, Annelies & van der Heijde, Bram & Helsen, Lieve, 2018. "Controlling district heating and cooling networks to unlock flexibility: A review," Energy, Elsevier, vol. 151(C), pages 103-115.
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    1. Saletti, Costanza & Morini, Mirko & Gambarotta, Agostino, 2022. "Smart management of integrated energy systems through co-optimization with long and short horizons," Energy, Elsevier, vol. 250(C).

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