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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xin Fang Qiang Guo Dongxia Zhang Shuang Liang |
| Copyright Year | 2012 |
| Abstract | Photovoltaic (PV) generation is still considered to be an energy-replacement rather than capacity-replacement source for its intermittent and fluctuating nature. The power system reliability can be elevated after integrating a PV station to the system, so the PV generation should has a capacity credit of some degree. Evaluating this capacity credit is one of urgent problems when large-scare PV stations are planned to integrate into the traditional power system. This paper presents a new method for evaluating the capacity credit of a PV generation station. Firstly, an annual PV generation fluctuating model with weather random conditions considered including the probability of different weathers, the maximum proportion of solar radiation under various weathers, the radiation fluctuation range due to clouds mask and the temperature coefficient random variation range is presented. Secondly, established an object function based on the loss of load expectation before and after integrating the PV generation, and facilitated the particle swarm optimization to search the optimal combination of traditional generations which could maintain the original level of system reliability. Finally, the proposed model and algorithm are validated by an analysis of the RTS. |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 230632 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781457705458 |
| ISSN | 21574839 |
| e-ISBN | 9781457705472 |
| DOI | 10.1109/APPEEC.2012.6307182 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-03-27 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Temperature distribution Clouds Power system reliability Reliability Particle swarm optimization Meteorology |
| Content Type | Text |
| Resource Type | Article |
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