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Stochastic energy optimization of residential heat pumps in uncertain electricity markets

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  • Golmohamadi, Hessam

Abstract

The penetration of renewable energy sources is increasing in power systems all over the world. Due to the intermittency and volatility of renewable energies, demand-side management is a practical solution to overcome the problem. This paper proposes a stochastic model predictive control for heat pumps to supply space heating and domestic hot water consumption of residential buildings. Continuous-Time Stochastic Model is coded in R language to address the model identification approach. The approach uses the sensor data of households to extract the thermal dynamics of the building. The controller participates in three floors of power markets with high renewable power penetration. The three-stage stochastic programming is suggested to unlock power-to-heat flexibility in the day-ahead, intraday, and balancing markets on long, mid, and short advance notices, respectively. Regarding the close correlation between renewable power availability and electricity price, the price data is modeled as probabilistic scenarios through Auto-Regressive Integrated Moving Average. The ambient temperature, as well as the domestic hot water consumption, are addressed as envelope-bounds with upper and lower thresholds. Finally, the operational strategies of the controller are examined on a 150 m2 test house under uncertain electricity prices, weather variables, and occupancy patterns.

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  • Golmohamadi, Hessam, 2021. "Stochastic energy optimization of residential heat pumps in uncertain electricity markets," Applied Energy, Elsevier, vol. 303(C).
    • Handle: RePEc:eee:appene:v:303:y:2021:i:c:s0306261921009971
    DOI: 10.1016/j.apenergy.2021.117629
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    1. Le Dréau, J. & Heiselberg, P., 2016. "Energy flexibility of residential buildings using short term heat storage in the thermal mass," Energy, Elsevier, vol. 111(C), pages 991-1002.
    2. Zhang, Shudong & Wang, Zhenyang, 2018. "Thermodynamics behavior of phase change latent heat materials in micro-/nanoconfined spaces for thermal storage and applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2319-2331.
    3. Kuboth, Sebastian & Heberle, Florian & König-Haagen, Andreas & Brüggemann, Dieter, 2019. "Economic model predictive control of combined thermal and electric residential building energy systems," Applied Energy, Elsevier, vol. 240(C), pages 372-385.
    4. Dengiz, Thomas & Jochem, Patrick & Fichtner, Wolf, 2019. "Demand response with heuristic control strategies for modulating heat pumps," Applied Energy, Elsevier, vol. 238(C), pages 1346-1360.
    5. Daryabari, Mohamad K. & Keypour, Reza & Golmohamadi, Hessam, 2020. "Stochastic energy management of responsive plug-in electric vehicles characterizing parking lot aggregators," Applied Energy, Elsevier, vol. 279(C).
    6. Tang, Rui & Wang, Shengwei, 2019. "Model predictive control for thermal energy storage and thermal comfort optimization of building demand response in smart grids," Applied Energy, Elsevier, vol. 242(C), pages 873-882.
    7. Francesco Neirotti & Michel Noussan & Stefano Riverso & Giorgio Manganini, 2019. "Analysis of Different Strategies for Lowering the Operation Temperature in Existing District Heating Networks," Energies, MDPI, vol. 12(2), pages 1-17, January.
    8. Powell, Kody M. & Kim, Jong Suk & Cole, Wesley J. & Kapoor, Kriti & Mojica, Jose L. & Hedengren, John D. & Edgar, Thomas F., 2016. "Thermal energy storage to minimize cost and improve efficiency of a polygeneration district energy system in a real-time electricity market," Energy, Elsevier, vol. 113(C), pages 52-63.
    9. Nie, Binjian & Palacios, Anabel & Zou, Boyang & Liu, Jiaxu & Zhang, Tongtong & Li, Yunren, 2020. "Review on phase change materials for cold thermal energy storage applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    10. Moallemi, A. & Arabkoohsar, A. & Pujatti, F.J.P. & Valle, R.M. & Ismail, K.A.R., 2019. "Non-uniform temperature district heating system with decentralized heat storage units, a reliable solution for heat supply," Energy, Elsevier, vol. 167(C), pages 80-91.
    11. Hessam Golmohamadi & Amin Asadi, 2020. "Integration of Joint Power-Heat Flexibility of Oil Refinery Industries to Uncertain Energy Markets," Energies, MDPI, vol. 13(18), pages 1-25, September.
    12. Romero Rodríguez, Laura & Brennenstuhl, Marcus & Yadack, Malcolm & Boch, Pirmin & Eicker, Ursula, 2019. "Heuristic optimization of clusters of heat pumps: A simulation and case study of residential frequency reserve," Applied Energy, Elsevier, vol. 233, pages 943-958.
    13. Golmohamadi, Hessam & Asadi, Amin, 2020. "A multi-stage stochastic energy management of responsive irrigation pumps in dynamic electricity markets," Applied Energy, Elsevier, vol. 265(C).
    14. Finck, Christian & Li, Rongling & Kramer, Rick & Zeiler, Wim, 2018. "Quantifying demand flexibility of power-to-heat and thermal energy storage in the control of building heating systems," Applied Energy, Elsevier, vol. 209(C), pages 409-425.
    15. Ignacio Blanco & Daniela Guericke & Anders N. Andersen & Henrik Madsen, 2018. "Operational Planning and Bidding for District Heating Systems with Uncertain Renewable Energy Production," Energies, MDPI, vol. 11(12), pages 1-26, November.
    16. Dahash, Abdulrahman & Ochs, Fabian & Janetti, Michele Bianchi & Streicher, Wolfgang, 2019. "Advances in seasonal thermal energy storage for solar district heating applications: A critical review on large-scale hot-water tank and pit thermal energy storage systems," Applied Energy, Elsevier, vol. 239(C), pages 296-315.
    17. Saloux, E. & Candanedo, J.A., 2019. "Modelling stratified thermal energy storage tanks using an advanced flowrate distribution of the received flow," Applied Energy, Elsevier, vol. 241(C), pages 34-45.
    18. Kitapbayev, Yerkin & Moriarty, John & Mancarella, Pierluigi, 2015. "Stochastic control and real options valuation of thermal storage-enabled demand response from flexible district energy systems," Applied Energy, Elsevier, vol. 137(C), pages 823-831.
    19. Dominković, Dominik Franjo & Junker, Rune Grønborg & Lindberg, Karen Byskov & Madsen, Henrik, 2020. "Implementing flexibility into energy planning models: Soft-linking of a high-level energy planning model and a short-term operational model," Applied Energy, Elsevier, vol. 260(C).
    20. De Schepper, Guillaume & Paulus, Claire & Bolly, Pierre-Yves & Hermans, Thomas & Lesparre, Nolwenn & Robert, Tanguy, 2019. "Assessment of short-term aquifer thermal energy storage for demand-side management perspectives: Experimental and numerical developments," Applied Energy, Elsevier, vol. 242(C), pages 534-546.
    21. Yan, T. & Wang, R.Z. & Li, T.X. & Wang, L.W. & Fred, Ishugah T., 2015. "A review of promising candidate reactions for chemical heat storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 13-31.
    22. Tschopp, Daniel & Tian, Zhiyong & Berberich, Magdalena & Fan, Jianhua & Perers, Bengt & Furbo, Simon, 2020. "Large-scale solar thermal systems in leading countries: A review and comparative study of Denmark, China, Germany and Austria," Applied Energy, Elsevier, vol. 270(C).
    23. Meesenburg, Wiebke & Ommen, Torben & Thorsen, Jan Eric & Elmegaard, Brian, 2020. "Economic feasibility of ultra-low temperature district heating systems in newly built areas supplied by renewable energy," Energy, Elsevier, vol. 191(C).
    24. Wang, Dan & Zhi, Yun-qiang & Jia, Hong-jie & Hou, Kai & Zhang, Shen-xi & Du, Wei & Wang, Xu-dong & Fan, Meng-hua, 2019. "Optimal scheduling strategy of district integrated heat and power system with wind power and multiple energy stations considering thermal inertia of buildings under different heating regulation modes," Applied Energy, Elsevier, vol. 240(C), pages 341-358.
    25. Vandermeulen, Annelies & van der Heijde, Bram & Helsen, Lieve, 2018. "Controlling district heating and cooling networks to unlock flexibility: A review," Energy, Elsevier, vol. 151(C), pages 103-115.
    26. Vivian, Jacopo & Quaggiotto, Davide & Zarrella, Angelo, 2020. "Increasing the energy flexibility of existing district heating networks through flow rate variations," Applied Energy, Elsevier, vol. 275(C).
    27. Daryabari, Mohamad K. & Keypour, Reza & Golmohamadi, Hessam, 2021. "Robust self-scheduling of parking lot microgrids leveraging responsive electric vehicles," Applied Energy, Elsevier, vol. 290(C).
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    Cited by:

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    2. Chen, Minghao & Xie, Zhiyuan & Sun, Yi & Zheng, Shunlin, 2023. "The predictive management in campus heating system based on deep reinforcement learning and probabilistic heat demands forecasting," Applied Energy, Elsevier, vol. 350(C).
    3. Golmohamadi, Hessam & Larsen, Kim Guldstrand & Jensen, Peter Gjøl & Hasrat, Imran Riaz, 2022. "Integration of flexibility potentials of district heating systems into electricity markets: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
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    5. Huang, Bowen & Huang, Sen & Ma, Xu & Katipamula, Srinivas & Wu, Di & Lutes, Robert, 2023. "Stochastic scheduling for commercial building cooling systems: considering uncertainty in zone temperature prediction," Applied Energy, Elsevier, vol. 346(C).

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