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Article
Article
| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wang, S. Baran, M.E. |
| Copyright Year | 2010 |
| Description | Author affiliation: Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, 27695 USA (Baran, M.E.) || ABB Grid Systems, Raleigh, North Carolina 27606, USA (Wang, S.) |
| Abstract | The paper focuses on reliability assessment of power systems with wind power generation. A Monte Carlo based production cost simulation model is introduced in the paper. The model closely simulates actual system operation processes and takes system random behaviors into account. A simplified unit commitment method is created to fit the simulation for reliability evaluation purpose. The effects of wind forecast error is addressed in the model by applying forecasted value in day-ahead unit commitment and actual value in real-time operation. An Auto-Regressive Moving Average (ARMA) based process is designed to automatically perform day-ahead hourly wind generation forecasting through the simulation period. Numerical results of a 50-unit system case study are presented. |
| Starting Page | 1 |
| Ending Page | 8 |
| File Size | 515473 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424465491 |
| ISSN | 19449925 |
| e-ISBN | 9781424465514 |
| e-ISBN | 9781424483570 |
| DOI | 10.1109/PES.2010.5590079 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-07-25 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Wind forecasting Biological system modeling Power system reliability Reliability Monte Carlo methods Generators Wind power generation Wind Power Generation Auto-Regressive Moving Average Monte Carlo Simulation Power System Reliability Unit Commitment |
| Content Type | Text |
| Resource Type | Article |
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