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A stochastic operational planning model for a zero emission building with emission compensation

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  • Thorvaldsen, Kasper Emil
  • Korpås, Magnus
  • Lindberg, Karen Byskov
  • Farahmand, Hossein

Abstract

The primary objective of Zero Emission Buildings (ZEBs) is to achieve net zero emission over the buildings’ lifetime. To achieve this goal, accurate cost-effective emission compensation is needed during the operational phase. This paper presents a stochastic planning model comprising an emission inventory for the operation of ZEBs. The operational planning methodology uses stochastic dynamic programming (SDP) to analyze and represent the expected future cost curve (EFCC) for operation based on the electricity price and accumulated CO2eq-inventory during the year. Failing to compensate for net zero emission makes the leftover amount subject to a penalty cost at the end of the year. This renders the overall problem multi-objective optimization including emission compensation and cost of operation. The model is applied to a case study of a Norwegian building, tested for a range of penalty costs for leftover CO2eq-inventory. The results show that, for a ZEB, including emission compensation demonstrates a significant impact on the operation of the building. The penalty cost puts a limit on how much the operational cost increase for additional compensation should be, influencing the end CO2eq-inventory. Increasing penalty costs decreases the end inventory, and a penalty cost of 10 EURkgCO2eq resulted in zero emission. The case achieving zero emission had an operational cost increase of 4.8% compared to operating without a penalty cost. This shows the importance of accounting for emissions during the operation of a ZEB, and the value of having an operational strategy that presents the future impact of operation.

Suggested Citation

  • Thorvaldsen, Kasper Emil & Korpås, Magnus & Lindberg, Karen Byskov & Farahmand, Hossein, 2021. "A stochastic operational planning model for a zero emission building with emission compensation," Applied Energy, Elsevier, vol. 302(C).
    • Handle: RePEc:eee:appene:v:302:y:2021:i:c:s0306261921008114
    DOI: 10.1016/j.apenergy.2021.117415
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    References listed on IDEAS

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    1. Suryakiran, B.V. & Nizami, Sohrab & Verma, Ashu & Saha, Tapan Kumar & Mishra, Sukumar, 2023. "A DSO-based day-ahead market mechanism for optimal operational planning of active distribution network," Energy, Elsevier, vol. 282(C).
    2. Ferahtia, Seydali & Rezk, Hegazy & Olabi, A.G. & Alhumade, Hesham & Bamufleh, Hisham S. & Doranehgard, Mohammad Hossein & Abdelkareem, Mohammad Ali, 2022. "Optimal techno-economic multi-level energy management of renewable-based DC microgrid for commercial buildings applications," Applied Energy, Elsevier, vol. 327(C).

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