Hybrid Time-Scale Optimal Scheduling Considering Multi-Energy Complementary Characteristic

Evaluating the potential utilization of hybrid energy systems and determining the multi-scale optimal operation strategy is critical to power system planning in the context of energy structure adjustment, especially for large-scale hybrid energy systems. Considering the long-term and short-term comp...

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Veröffentlicht in:IEEE access 2021, Vol.9, p.94087-94098
Hauptverfasser: Wang, Songkai, Jia, Rong, Shi, Xiaoyu, An, Yuan, Huang, Qiang, Guo, Pengcheng, Luo, Chang
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Sprache:eng
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Zusammenfassung:Evaluating the potential utilization of hybrid energy systems and determining the multi-scale optimal operation strategy is critical to power system planning in the context of energy structure adjustment, especially for large-scale hybrid energy systems. Considering the long-term and short-term complementary characteristics, this paper puts forward a coordinated optimization framework for the integrated energy system in the world's largest multi-energy complementary base on Yellow River's upper reaches. The main procedures are as follows: 1) cross-correlation method is introduced for individually analyzing the long- and short-term complementary characteristics of wind power, photovoltaic, and hydropower in this multi-energy complementary base; 2) a double-layer model combining the long-term optimal operation model and short-term optimal operation model for determining the proportion of multiple energy and optimizing the maximum peak-shaving ability; 3) Large-Scale System Decomposition-Coordination Method is applied for solving the proposed double-layer operation model. The results show that wind power 23%, photovoltaic 35%, hydropower 42% can keep the most stable generation in the long-term complementary operation. This proportion results can improve the system peak regulation capacity with 50.8% (sunny day's morning peak) and 24.2% (rainy day's morning peak) in the optimal short-term operation.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2021.3093906