Tracing spinning reserve inadequacy risk via hybrid importance sampling with an optimised partially collapsed Gibbs sampler
Abstract From the simulation perspective, spinning reserve risk evaluation of power system is commonly a rare‐event assessing issue, for which importance sampling is an appealing solution technique. This paper proposes a hybrid importance sampling method for tracing spinning reserve inadequacy risk...
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| Format: | Article |
| Language: | English |
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Wiley
2021-08-01
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| Series: | IET Renewable Power Generation |
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| Online Access: | https://doi.org/10.1049/rpg2.12180 |
| Summary: | Abstract From the simulation perspective, spinning reserve risk evaluation of power system is commonly a rare‐event assessing issue, for which importance sampling is an appealing solution technique. This paper proposes a hybrid importance sampling method for tracing spinning reserve inadequacy risk of power system integrating with renewables. The proposed method is oriented towards a generic high‐dimensional integral calculus, which allows for continuous and discrete random variables mixed together for casting kinds of risk indices. To improve the robustness in high‐dimensional applications, a partially collapsed Gibbs sampler is devised to help in exploring adaptive training samples which feature typical rare outage events. Interestingly, the originators engendering extreme spinning reserve inadequacy events can be traced using the sampling information of the proposed method. The performance of the proposed method is tested in an updated RTS‐79 system vis‐à‐vis several existing methods. Spinning reserve inadequacy risk tracing is explained by uncovering a scenario frequency distribution concerning the short‐term expected energy not supplied. |
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| ISSN: | 1752-1416 1752-1424 |