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The cost of providing operational flexibility from distributed energy resources

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  • Harder, Nick
  • Qussous, Ramiz
  • Weidlich, Anke

Abstract

Flexible household devices, such as heat pumps combined with thermal energy storage or battery energy storage units, can provide flexibility to the electricity sector. However, to make flexibility available to the market, it has to be correctly quantified, and its cost has to be estimated. In this work, a methodology for generic flexibility quantification is proposed and developed in a Python environment using model predictive control. The chosen methodology allows to quantify the adjustable power, and also to determine the corresponding cost of the flexibility provision. It was observed that the available flexibility and its cost is influenced by many factors such as system components, human behavior, building thermal parameters, and price signals. Also, the inclusion of even a low share of households with batteries or electric vehicles smoothens the aggregated flexibility profile, and a considerable amount of flexibility is available at almost any point in time.

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  • Harder, Nick & Qussous, Ramiz & Weidlich, Anke, 2020. "The cost of providing operational flexibility from distributed energy resources," Applied Energy, Elsevier, vol. 279(C).
    • Handle: RePEc:eee:appene:v:279:y:2020:i:c:s030626192031268x
    DOI: 10.1016/j.apenergy.2020.115784
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    References listed on IDEAS

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    Cited by:

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    3. Zhou, Yuan & Wang, Jiangjiang & Dong, Fuxiang & Qin, Yanbo & Ma, Zherui & Ma, Yanpeng & Li, Jianqiang, 2021. "Novel flexibility evaluation of hybrid combined cooling, heating and power system with an improved operation strategy," Applied Energy, Elsevier, vol. 300(C).
    4. Salgado, Marcelo & Negrete-Pincetic, Matias & Lorca, Álvaro & Olivares, Daniel, 2021. "A low-complexity decision model for home energy management systems," Applied Energy, Elsevier, vol. 294(C).
    5. Li, Yanxue & Zhang, Xiaoyi & Gao, Weijun & Xu, Wenya & Wang, Zixuan, 2022. "Operational performance and grid-support assessment of distributed flexibility practices among residential prosumers under high PV penetration," Energy, Elsevier, vol. 238(PB).
    6. Zhang, Zhaoyan & Jiang, Ping & Liu, Zhibin & Fu, Lei & Wang, Peiguang, 2023. "Capacity optimal configuration and collaborative planning of multi-region integrated energy system," Energy, Elsevier, vol. 278(PB).
    7. Xiaoyi Zhang & Weijun Gao & Yanxue Li & Zixuan Wang & Yoshiaki Ushifusa & Yingjun Ruan, 2021. "Operational Performance and Load Flexibility Analysis of Japanese Zero Energy House," IJERPH, MDPI, vol. 18(13), pages 1-19, June.
    8. Wanapinit, Natapon & Thomsen, Jessica & Weidlich, Anke, 2022. "Integrating flexibility provision into operation planning: A generic framework to assess potentials and bid prices of end-users," Energy, Elsevier, vol. 261(PB).

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