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A two-step optimization model for quantifying the flexibility potential of power-to-heat systems in dwellings

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  • Oluleye, Gbemi
  • Allison, John
  • Hawker, Graeme
  • Kelly, Nick
  • Hawkes, Adam D.

Abstract

Coupling the electricity and heat sectors is receiving interest as a potential source of flexibility to help absorb surplus renewable electricity. The flexibility afforded by power-to-heat systems in dwellings has yet to be quantified in terms of time, energy and costs, and especially in cases where homeowners are heterogeneous prosumers. Flexibility quantification whilst accounting for prosumer heterogeneity is non-trivial. Therefore in this work a novel two-step optimization framework is proposed to quantify the potential of prosumers to absorb surplus renewable electricity through the integration of air source heat pumps and thermal energy storage. The first step is formulated as a multi-period mixed integer linear programming problem to determine the optimal energy system, and the quantity of surplus electricity absorbed. The second step is formulated as a linear programming problem to determine the price a prosumer will accept for absorbing surplus electricity, and thus the number of active prosumers in the market.

Suggested Citation

  • Oluleye, Gbemi & Allison, John & Hawker, Graeme & Kelly, Nick & Hawkes, Adam D., 2018. "A two-step optimization model for quantifying the flexibility potential of power-to-heat systems in dwellings," Applied Energy, Elsevier, vol. 228(C), pages 215-228.
    • Handle: RePEc:eee:appene:v:228:y:2018:i:c:p:215-228
    DOI: 10.1016/j.apenergy.2018.06.072
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    4. Li, Yanxue & Zhang, Xiaoyi & Gao, Weijun & Ruan, Yingjun, 2020. "Capacity credit and market value analysis of photovoltaic integration considering grid flexibility requirements," Renewable Energy, Elsevier, vol. 159(C), pages 908-919.
    5. Kim, Ju-Hee & Lim, Seul-Ye & Yoo, Seung-Hoon, 2021. "Public preferences for introducing a power-to-heat system in South Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    6. Lv, Chaoxian & Yu, Hao & Li, Peng & Wang, Chengshan & Xu, Xiandong & Li, Shuquan & Wu, Jianzhong, 2019. "Model predictive control based robust scheduling of community integrated energy system with operational flexibility," Applied Energy, Elsevier, vol. 243(C), pages 250-265.
    7. Klyapovskiy, Sergey & You, Shi & Michiorri, Andrea & Kariniotakis, George & Bindner, Henrik W., 2019. "Incorporating flexibility options into distribution grid reinforcement planning: A techno-economic framework approach," Applied Energy, Elsevier, vol. 254(C).
    8. Perera, A.T.D. & Nik, Vahid M. & Wickramasinghe, P.U. & Scartezzini, Jean-Louis, 2019. "Redefining energy system flexibility for distributed energy system design," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    9. Flower, Jack & Hawker, Graeme & Bell, Keith, 2020. "Heterogeneity of UK residential heat demand and its impact on the value case for heat pumps," Energy Policy, Elsevier, vol. 144(C).

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