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Optimal electric-distribution-grid planning considering the demand-side flexibility of thermal building systems for a test case in Singapore

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Listed:
  • Troitzsch, Sebastian
  • Sreepathi, Bhargava Krishna
  • Huynh, Thanh Phong
  • Moine, Aurelie
  • Hanif, Sarmad
  • Fonseca, Jimeno
  • Hamacher, Thomas

Abstract

The planning of electric distribution grids aims at designing the most cost-efficient grid topology, while ensuring sufficient maximum capacity in the case of peak load conditions. With the advent of demand-side flexibility, there is the opportunity to reshape peak loads such that the investment cost of the electric grid decreases, in exchange for a minor increase in the operating cost. To this end, there exists a gap in formulating the trade-off between investment cost and operating cost, and a unsatisfactory understanding of the potential cost savings. This paper formulates a numerical optimization problem for the planning of the electric distribution grid, which incorporates the demand-side flexibility from thermal building systems, e.g., heating, ventilation and air-conditioning systems. The problem is formulated as a single-stage, mixed-integer quadratic program and aims at minimizing the investment cost for the grid along with the operating cost of the flexible loads. This is subject to the fixed electricity demand and thermal-comfort constraints of building occupants. The approach is tested on a district planning test case based in Singapore, where the results show reductions of up to 36.3% in investment cost and reductions of up to 0.81% in total annualized cost. Urban planning authorities, developers and utility companies can all benefit from the presented approach to make optimized investment decisions. For building operators, the results point to the need to adopt control systems for demand-side flexibility.

Suggested Citation

  • Troitzsch, Sebastian & Sreepathi, Bhargava Krishna & Huynh, Thanh Phong & Moine, Aurelie & Hanif, Sarmad & Fonseca, Jimeno & Hamacher, Thomas, 2020. "Optimal electric-distribution-grid planning considering the demand-side flexibility of thermal building systems for a test case in Singapore," Applied Energy, Elsevier, vol. 273(C).
  • Handle: RePEc:eee:appene:v:273:y:2020:i:c:s0306261920304293
    DOI: 10.1016/j.apenergy.2020.114917
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    References listed on IDEAS

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    1. Chua, K.J. & Chou, S.K. & Yang, W.M. & Yan, J., 2013. "Achieving better energy-efficient air conditioning – A review of technologies and strategies," Applied Energy, Elsevier, vol. 104(C), pages 87-104.
    2. Wolisz, Henryk & Schütz, Thomas & Blanke, Tobias & Hagenkamp, Markus & Kohrn, Markus & Wesseling, Mark & Müller, Dirk, 2017. "Cost optimal sizing of smart buildings' energy system components considering changing end-consumer electricity markets," Energy, Elsevier, vol. 137(C), pages 715-728.
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    Cited by:

    1. Xi, Yufei & Fang, Jiakun & Chen, Zhe & Zeng, Qing & Lund, Henrik, 2021. "Optimal coordination of flexible resources in the gas-heat-electricity integrated energy system," Energy, Elsevier, vol. 223(C).
    2. Krzysztof Zagrajek & Józef Paska & Łukasz Sosnowski & Konrad Gobosz & Konrad Wróblewski, 2021. "Framework for the Introduction of Vehicle-to-Grid Technology into the Polish Electricity Market," Energies, MDPI, vol. 14(12), pages 1-30, June.
    3. Wang, Chuyao & Ji, Jie & Yang, Hongxing, 2024. "Day-ahead schedule optimization of household appliances for demand flexibility: Case study on PV/T powered buildings," Energy, Elsevier, vol. 289(C).
    4. Utama, Christian & Troitzsch, Sebastian & Thakur, Jagruti, 2021. "Demand-side flexibility and demand-side bidding for flexible loads in air-conditioned buildings," Applied Energy, Elsevier, vol. 285(C).
    5. He, Shuaijia & Gao, Hongjun & Liu, Junyong & Zhang, Xi & Chen, Zhe, 2022. "Distribution system planning considering peak shaving of energy station," Applied Energy, Elsevier, vol. 312(C).
    6. Li, Haoran & Zhang, Chenghui & Sun, Bo, 2022. "Deep integration planning of sustainable energies in district energy system and distributed energy station," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).

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