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Optimal management of multiple heat sources in a residential area by an energy management system

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  • Aki, Hirohisa
  • Wakui, Tetsuya
  • Yokoyama, Ryohei
  • Sawada, Kento

Abstract

An energy management system (EMS) that achieves optimal operation by combining heat sources with different characteristics and using energy interchanges between residential dwellings was developed. Commercial fuel cell combined heat and power (FC-CHP) systems and CO2 heat pump water heaters (CO2HP) with high generation efficiencies have penetrated the Japanese residential market. In this real environment, the types or models of the installed heat sources vary between residential dwellings, and their energy demand is unknown. The EMS predicts energy generation and consumption and develops an optimum operational strategy that it uses to control energy equipment. It also continually revises the strategy and adjusts equipment controls to reflect actual conditions. The EMS is evaluated using a case study of a group of four residential dwellings with two different heat sources. Subsequent quantitative analysis shows that the EMS reduced energy costs by 10%. A sensitivity analysis also confirmed that it operates optimally even when energy prices are changed.

Suggested Citation

  • Aki, Hirohisa & Wakui, Tetsuya & Yokoyama, Ryohei & Sawada, Kento, 2018. "Optimal management of multiple heat sources in a residential area by an energy management system," Energy, Elsevier, vol. 153(C), pages 1048-1060.
    • Handle: RePEc:eee:energy:v:153:y:2018:i:c:p:1048-1060
    DOI: 10.1016/j.energy.2018.03.181
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    References listed on IDEAS

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    2. Wakui, Tetsuya & Sawada, Kento & Yokoyama, Ryohei & Aki, Hirohisa, 2019. "Predictive management for energy supply networks using photovoltaics, heat pumps, and battery by two-stage stochastic programming and rule-based control," Energy, Elsevier, vol. 179(C), pages 1302-1319.
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    5. Ou, Kai & Yuan, Wei-Wei & Kim, Young-Bae, 2021. "Development of optimal energy management for a residential fuel cell hybrid power system with heat recovery," Energy, Elsevier, vol. 219(C).
    6. Tushar, Wayes & Yuen, Chau & Saha, Tapan K. & Morstyn, Thomas & Chapman, Archie C. & Alam, M. Jan E. & Hanif, Sarmad & Poor, H. Vincent, 2021. "Peer-to-peer energy systems for connected communities: A review of recent advances and emerging challenges," Applied Energy, Elsevier, vol. 282(PA).
    7. Kwan, Trevor Hocksun & Shen, Yongting & Yao, Qinghe, 2019. "An energy management strategy for supplying combined heat and power by the fuel cell thermoelectric hybrid system," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    8. Wakui, Tetsuya & Hashiguchi, Moe & Sawada, Kento & Yokoyama, Ryohei, 2019. "Two-stage design optimization based on artificial immune system and mixed-integer linear programming for energy supply networks," Energy, Elsevier, vol. 170(C), pages 1228-1248.
    9. Ferrari, Simone & Blázquez, Teresa & Dall'O', Giuliano, 2021. "Energy performance indexes based on monitored data of social housing buildings in Northern Italy," Applied Energy, Elsevier, vol. 298(C).

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