A Probabilistic Reserve Decision-Making Method Based on Cumulative Probability Approximation for High-Penetration Renewable Energy Power System
Probabilistic modeling of net load forecast errors is an important approach for reserve decision-making in power systems with a high penetration of renewable energy. However, existing probabilistic modeling methods face issues such as insufficient estimation accuracy in the small probability interva...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/10/2658 |
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| author | Yun Yang Zichao Meng Guobing Wu Zhanxin Yang Ruipeng Guo |
| author_facet | Yun Yang Zichao Meng Guobing Wu Zhanxin Yang Ruipeng Guo |
| author_sort | Yun Yang |
| collection | DOAJ |
| description | Probabilistic modeling of net load forecast errors is an important approach for reserve decision-making in power systems with a high penetration of renewable energy. However, existing probabilistic modeling methods face issues such as insufficient estimation accuracy in the small probability interval of the tails or increased complexity in probability decision-making problems. A probabilistic reserve decision-making method based on cumulative probability approximation is proposed. By using key points on the cumulative probability distribution curve of net load forecast error samples, this method enhances the fitting accuracy of the normal distribution model in the small probability interval of the tail, resulting in an optimal reserve outcome with the desired comprehensive expected profit. Using relevant renewable energy output and load data from actual transmission networks in Guangdong Province, China, the proposed method demonstrates good practical value. |
| format | Article |
| id | doaj-art-d7496546de724f329e8a5c7b3e181f94 |
| institution | OA Journals |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-d7496546de724f329e8a5c7b3e181f942025-08-20T01:56:16ZengMDPI AGEnergies1996-10732025-05-011810265810.3390/en18102658A Probabilistic Reserve Decision-Making Method Based on Cumulative Probability Approximation for High-Penetration Renewable Energy Power SystemYun Yang0Zichao Meng1Guobing Wu2Zhanxin Yang3Ruipeng Guo4Power Dispatching and Control Center Guangdong Power Grid Corporation, Guangzhou 510335, ChinaPower Dispatching and Control Center Guangdong Power Grid Corporation, Guangzhou 510335, ChinaPower Dispatching and Control Center Guangdong Power Grid Corporation, Guangzhou 510335, ChinaCollege of Electrical Engineering, Zhejiang University, Hangzhou 310027, ChinaCollege of Electrical Engineering, Zhejiang University, Hangzhou 310027, ChinaProbabilistic modeling of net load forecast errors is an important approach for reserve decision-making in power systems with a high penetration of renewable energy. However, existing probabilistic modeling methods face issues such as insufficient estimation accuracy in the small probability interval of the tails or increased complexity in probability decision-making problems. A probabilistic reserve decision-making method based on cumulative probability approximation is proposed. By using key points on the cumulative probability distribution curve of net load forecast error samples, this method enhances the fitting accuracy of the normal distribution model in the small probability interval of the tail, resulting in an optimal reserve outcome with the desired comprehensive expected profit. Using relevant renewable energy output and load data from actual transmission networks in Guangdong Province, China, the proposed method demonstrates good practical value.https://www.mdpi.com/1996-1073/18/10/2658reserve decision-makingnet load forecast errorcumulative probability distributionnormal distribution modelkey pointssmall probability interval of the tail |
| spellingShingle | Yun Yang Zichao Meng Guobing Wu Zhanxin Yang Ruipeng Guo A Probabilistic Reserve Decision-Making Method Based on Cumulative Probability Approximation for High-Penetration Renewable Energy Power System Energies reserve decision-making net load forecast error cumulative probability distribution normal distribution model key points small probability interval of the tail |
| title | A Probabilistic Reserve Decision-Making Method Based on Cumulative Probability Approximation for High-Penetration Renewable Energy Power System |
| title_full | A Probabilistic Reserve Decision-Making Method Based on Cumulative Probability Approximation for High-Penetration Renewable Energy Power System |
| title_fullStr | A Probabilistic Reserve Decision-Making Method Based on Cumulative Probability Approximation for High-Penetration Renewable Energy Power System |
| title_full_unstemmed | A Probabilistic Reserve Decision-Making Method Based on Cumulative Probability Approximation for High-Penetration Renewable Energy Power System |
| title_short | A Probabilistic Reserve Decision-Making Method Based on Cumulative Probability Approximation for High-Penetration Renewable Energy Power System |
| title_sort | probabilistic reserve decision making method based on cumulative probability approximation for high penetration renewable energy power system |
| topic | reserve decision-making net load forecast error cumulative probability distribution normal distribution model key points small probability interval of the tail |
| url | https://www.mdpi.com/1996-1073/18/10/2658 |
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