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An integrated smart home energy management model based on a pyramid taxonomy for residential houses with photovoltaic-battery systems

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  • Zheng, Zhuang
  • Sun, Zhankun
  • Pan, Jia
  • Luo, Xiaowei

Abstract

Smart home energy management (SHEM) with residential photovoltaic (PV)-battery systems is a complicated issue with different facets. An integrated SHEM model covering the essential functions is missing. Meanwhile, residential PV-battery systems' optimal operations with renewable energy exchanges and imperfect forecasts are still open challenges. In this study, the research activities in SHEM are firstly organized by a pyramid with four functional layers: (i) Monitoring; (ii) Analyzing and forecasting; (iii) Scheduling; and (iv) Coordinating, which can serve as a standard pathway for developing SHEM. Second, guided by the pyramid taxonomy, an integrated SHEM model is developed for residential houses with PV-battery systems. Assuming a perfect Monitoring layer, we obtain the probabilistic load/PV forecasts and user preference vectors of shiftable appliances based on historical data. Then, we develop a two-stage stochastic programming model for optimal scheduling of single houses with a grid-connected PV-battery system, incorporating the probabilistic forecasts and user preference vectors. A retail electricity market with day-ahead (DA) and real-time (RT) markets is employed for leveraging imperfect forecasts. Finally, we design a distributed coordinating algorithm - Asynchronous Scheduling and Iterative Pricing for PV power-sharing among multiple prosumers based on the single-house scheduling model. Numerical simulations based on realistic loads and PV generation data validated the two-stage stochastic programming model's economic superiority and the distributed PV power-sharing approach compared with the rule-based dispatching and selfish scheduling strategies. We concluded that 1) the modeling of load/PV forecast uncertainties is valuable than averaging or ignoring them, 2) the two-stage stochastic programming model and the DA-RT retail electricity market are beneficial for utilizing imperfect forecasts, and 3) coordinating multiple prosumers could benefit each household by sharing PV and battery investments for revenue or trading with local small prosumers for cost reductions.

Suggested Citation

  • Zheng, Zhuang & Sun, Zhankun & Pan, Jia & Luo, Xiaowei, 2021. "An integrated smart home energy management model based on a pyramid taxonomy for residential houses with photovoltaic-battery systems," Applied Energy, Elsevier, vol. 298(C).
    • Handle: RePEc:eee:appene:v:298:y:2021:i:c:s0306261921005936
    DOI: 10.1016/j.apenergy.2021.117159
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    References listed on IDEAS

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    Cited by:

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    2. Chong, Cheng Tung & Fan, Yee Van & Lee, Chew Tin & Klemeš, Jiří Jaromír, 2022. "Post COVID-19 ENERGY sustainability and carbon emissions neutrality," Energy, Elsevier, vol. 241(C).
    3. Zheng, Zhuang & Pan, Jia & Huang, Gongsheng & Luo, Xiaowei, 2022. "A bottom-up intra-hour proactive scheduling of thermal appliances for household peak avoiding based on model predictive control," Applied Energy, Elsevier, vol. 323(C).
    4. Liu, Yinyan & Ma, Jin & Xing, Xinjie & Liu, Xinglu & Wang, Wei, 2022. "A home energy management system incorporating data-driven uncertainty-aware user preference," Applied Energy, Elsevier, vol. 326(C).
    5. Zheng, Zhuang & Shafique, Muhammad & Luo, Xiaowei & Wang, Shengwei, 2024. "A systematic review towards integrative energy management of smart grids and urban energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    6. Luan, Wenpeng & Tian, Longfei & Zhao, Bochao, 2023. "Leveraging hybrid probabilistic multi-objective evolutionary algorithm for dynamic tariff design," Applied Energy, Elsevier, vol. 342(C).
    7. Isaías Gomes & Karol Bot & Maria Graça Ruano & António Ruano, 2022. "Recent Techniques Used in Home Energy Management Systems: A Review," Energies, MDPI, vol. 15(8), pages 1-41, April.
    8. Li, Heng & Liu, Zheng & Yang, Yingze & Yang, Huihui & Shu, Boyu & Liu, Weirong, 2024. "A proactive energy management strategy for battery-powered autonomous systems," Applied Energy, Elsevier, vol. 363(C).
    9. Tostado-Véliz, Marcos & Kamel, Salah & Aymen, Flah & Jurado, Francisco, 2022. "A novel hybrid lexicographic-IGDT methodology for robust multi-objective solution of home energy management systems," Energy, Elsevier, vol. 253(C).
    10. Jun Dong & Xihao Dou & Dongran Liu & Aruhan Bao & Dongxue Wang & Yunzhou Zhang & Peng Jiang, 2023. "Benefit Sharing of Power Transactions in Distributed Energy Systems with Multiple Participants," Sustainability, MDPI, vol. 15(11), pages 1-23, June.
    11. Lu, Qing & Guo, Qisheng & Zeng, Wei, 2022. "Optimization scheduling of integrated energy service system in community: A bi-layer optimization model considering multi-energy demand response and user satisfaction," Energy, Elsevier, vol. 252(C).

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