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Optimal dispatch of power system considering uncertainty of both source and load sides and N–1 security constraint
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Yanlin Yu1, Ping Yang1, 2, Kailin Zeng1, Xinyu Chen1
Renewable Energy Resources | 2024, 42(5) : 665 - 674
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Renewable Energy Resources | 2024, 42(5): 665-674
Optimal dispatch of power system considering uncertainty of both source and load sides and N–1 security constraint
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Yanlin Yu1, Ping Yang1, 2, Kailin Zeng1, Xinyu Chen1
Affiliations
  • 1 School of Electric Power South China University of Technology Guangzhou 510640 China
  • 2 Guangdong Key Laboratory of Clean Energy Technology Guangzhou 511458 China
Published: 2024-05-20
Outline
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Largescale wind power grid integration increases the uncertainties of system operation. It is urgent to use rapidly adjustable resources to smooth the power imbalance caused by wind power and load fluctuation and consider the impact of spinning reserve calling process on the system power flow. Firstly, the probability distribution model of wind power and load prediction error is analyzed. Then, the optimal dispatching model of power system with N1 network security opportunity constraint and spinning reserve opportunity constraint is established, and the unit output is optimized with the goal of minimizing the total dispatching cost. Finally, the Benders decomposition method based on the identification method of active integer variables is used to deal with the N1 network security constraints to improve the solving efficiency. Using the modified IEEE30node test system, it is verified that the proposed model can guarantee the reserve availability, economy and safety of the system, and fully excavate the fast adjustable capacity of pumped storage.

integration of wind power  /  N-1 security  /  spinning reserve  /  optimal dispatch
Yanlin Yu, Ping Yang, Kailin Zeng, Xinyu Chen. Optimal dispatch of power system considering uncertainty of both source and load sides and N–1 security constraint[J]. Renewable Energy Resources, 2024 , 42 (5) : 665 -674 .
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Year 2024 volume 42 Issue 5
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Article Info
  • Receive Date：2022-05-19
  • Online Date：2025-07-22
  • Published：2024-05-20
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  • Received：2022-05-19
Funding
Affiliations
    1 School of Electric Power South China University of Technology Guangzhou 510640 China
    2 Guangdong Key Laboratory of Clean Energy Technology Guangzhou 511458 China
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光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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