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Data-driven seasonal scenario generation-based static operation of hybrid energy systems

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  • Wang, Jinglong
  • Zheng, Yingying

Abstract

Integrating intermittent wind and solar energy into hybrid energy system has introduced significant operational uncertainties. This paper develops a static operation model incorporating biomass gasification-based combined heat and power as a coupling center based on conceptual utility grid-connected real data in Sacramento, California. This study involves generating typical scenarios with seasonal characteristics and demand correlations to capture key input parameters accurately. Subsequently, the Newton-Raphson method was developed to calculate the energy flow within these scenarios. Simulation results demonstrate the proposed method achieves over 70 % construction accuracy across different seasonal scenarios. The economic results that the winter electricity loads increased by 44.8 % compared to summer, with corresponding rises in gas and heat loads by 360.6 % and 372.3 %, respectively, resulting in the hybrid energy system economic cost increase of 58.9 %. These results confirm the model's robustness in effectively managing intermittent energy sources and addressing the economic impacts of seasonal demand variations.

Suggested Citation

  • Wang, Jinglong & Zheng, Yingying, 2024. "Data-driven seasonal scenario generation-based static operation of hybrid energy systems," Energy, Elsevier, vol. 309(C).
    • Handle: RePEc:eee:energy:v:309:y:2024:i:c:s0360544224028044
    DOI: 10.1016/j.energy.2024.133030
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    References listed on IDEAS

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    1. Liu, Xuezhi & Wu, Jianzhong & Jenkins, Nick & Bagdanavicius, Audrius, 2016. "Combined analysis of electricity and heat networks," Applied Energy, Elsevier, vol. 162(C), pages 1238-1250.
    2. Wu, Long & Yin, Xunyuan & Pan, Lei & Liu, Jinfeng, 2022. "Economic model predictive control of integrated energy systems: A multi-time-scale framework," Applied Energy, Elsevier, vol. 328(C).
    3. Li, Weiwei & Qian, Tong & Zhao, Wei & Huang, Wenwei & Zhang, Yin & Xie, Xuehua & Tang, Wenhu, 2023. "Decentralized optimization for integrated electricity–heat systems with data center based energy hub considering communication packet loss," Applied Energy, Elsevier, vol. 350(C).
    4. Zhang, Pan & Mansouri, Seyed Amir & Rezaee Jordehi, Ahmad & Tostado-Véliz, Marcos & Alharthi, Yahya Z. & Safaraliev, Murodbek, 2024. "An ADMM-enabled robust optimization framework for self-healing scheduling of smart grids integrated with smart prosumers," Applied Energy, Elsevier, vol. 363(C).
    5. Fu, Xueqian & Guo, Qinglai & Sun, Hongbin & Pan, Zhaoguang & Xiong, Wen & Wang, Li, 2017. "Typical scenario set generation algorithm for an integrated energy system based on the Wasserstein distance metric," Energy, Elsevier, vol. 135(C), pages 153-170.
    6. Zhang, Houwang & Wu, Qiuwei & Chen, Jian & Lu, Lina & Zhang, Jiangfeng & Zhang, Shuyi, 2023. "Multiple stage stochastic planning of integrated electricity and gas system based on distributed approximate dynamic programming," Energy, Elsevier, vol. 270(C).
    7. Yan, Rujing & Wang, Jiangjiang & Huo, Shuojie & Qin, Yanbo & Zhang, Jing & Tang, Saiqiu & Wang, Yuwei & Liu, Yan & Zhou, Lin, 2023. "Flexibility improvement and stochastic multi-scenario hybrid optimization for an integrated energy system with high-proportion renewable energy," Energy, Elsevier, vol. 263(PB).
    8. Dai, Yeming & Wang, Yanxin & Leng, Mingming & Yang, Xinyu & Zhou, Qiong, 2022. "LOWESS smoothing and Random Forest based GRU model: A short-term photovoltaic power generation forecasting method," Energy, Elsevier, vol. 256(C).
    9. Shen, Weijie & Zeng, Bo & Zeng, Ming, 2023. "Multi-timescale rolling optimization dispatch method for integrated energy system with hybrid energy storage system," Energy, Elsevier, vol. 283(C).
    10. Mansouri, Seyed Amir & Nematbakhsh, Emad & Jordehi, Ahmad Rezaee & Marzband, Mousa & Tostado-Véliz, Marcos & Jurado, Francisco, 2023. "An interval-based nested optimization framework for deriving flexibility from smart buildings and electric vehicle fleets in the TSO-DSO coordination," Applied Energy, Elsevier, vol. 341(C).
    11. 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.
    12. Zhang, Xuehan & Son, Yongju & Cheong, Taesu & Choi, Sungyun, 2022. "Affine-arithmetic-based microgrid interval optimization considering uncertainty and battery energy storage system degradation," Energy, Elsevier, vol. 242(C).
    13. Sun, Qiuye & Dong, Qianyu & You, Shi & Li, Zhibo & Wang, Rui, 2020. "A unified energy flow analysis considering initial guesses in complex multi-energy carrier systems," Energy, Elsevier, vol. 213(C).
    14. Ju, Liwei & Tan, Qinliang & Lin, Hongyu & Mei, Shufang & Li, Nan & Lu, Yan & Wang, Yao, 2020. "A two-stage optimal coordinated scheduling strategy for micro energy grid integrating intermittent renewable energy sources considering multi-energy flexible conversion," Energy, Elsevier, vol. 196(C).
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