A Wind Power Scenario Generation Method Based on Copula Functions and Forecast Errors
The scenario of renewable energy generation significantly affects the probabilistic distribution system analysis. To reflect the probabilistic characteristics of actual data, this paper proposed a scenario generation method that can reflect the spatiotemporal characteristics of wind power generation...
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| Veröffentlicht in: | Sustainability 2023-12, Vol.15 (23), p.16536 |
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| creator | Yoo, Jaehyun Son, Yongju Yoon, Myungseok Choi, Sungyun |
| description | The scenario of renewable energy generation significantly affects the probabilistic distribution system analysis. To reflect the probabilistic characteristics of actual data, this paper proposed a scenario generation method that can reflect the spatiotemporal characteristics of wind power generation and the probabilistic characteristics of forecast errors. The scenario generation method consists of a process of sampling random numbers and a process of inverse sampling using the cumulative distribution function. In sampling random numbers, random numbers that mimic the spatiotemporal correlation of power generation were generated using the copula function. Furthermore, the cumulative distribution functions of forecast errors according to power generation bins were used, thereby reflecting the probabilistic characteristics of forecast errors. The wind power generation scenarios in Jeju Island, generated by the proposed method, were analyzed through various indices that can assess accuracy. As a result, it was confirmed that by using the proposed scenario generation method, scenarios similar to actual data can be generated, which in turn allows for preparation of situations with a high probability of occurrence within the distribution system. |
| doi_str_mv | 10.3390/su152316536 |
| format | Article |
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| source | MDPI - Multidisciplinary Digital Publishing Institute; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
| subjects | Accuracy Alternative energy sources Distribution (Probability theory) Electric power production Electric vehicle charging stations Electric vehicles Energy resources Green technology Methods Probability distribution Random variables Renewable resources Systems analysis Wind power |
| title | A Wind Power Scenario Generation Method Based on Copula Functions and Forecast Errors |
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