Title :
Probabilistic-Based Available Transfer Capability Assessment Considering Existing and Future Wind Generation Resources
Author :
Pengwei Du ; Weifeng Li ; Xinda Ke ; Ning Lu ; Ciniglio, Orlando A. ; Colburn, Mitchel ; Anderson, Phillip M.
Author_Institution :
Electr. Reliability Council of Texas (ERCOT), Taylor, TX, USA
Abstract :
This paper presents a probabilistic-based approach for available transfer capability (ATC) assessment. A composite algorithm is developed to generate ensembles of future wind generation scenarios for the existing and planned wind sites using both measured and model-produced wind data. Then, the ensembles of wind and load are used to calculate their respective probability density functions (pdfs), which are subsequently used to calculate the probabilistic-based ATC for a selected transmission corridor. The method has been tested and validated using historical and operational data provided by the Idaho Power Co. The results show that the method can effectively quantify the uncertainties in the ATC assessment introduced by variable generation resources and load variations. As a result, the grid planners will inform the likelihood for the transmission corridor to exceed its transfer capacity in any targeted future years as well as the duration of such events.
Keywords :
power generation planning; probability; wind power plants; ATC assessment; Idaho Power Co; PDF; available transfer capability assessment; load ensembles; planned wind sites; probability density functions; transmission corridor; wind ensembles; wind generation resources; Probabilistic logic; Time series analysis; Wind farms; Wind power generation; Wind speed; Available transfer capacity; composite methods; renewable integration; stochastic planning; transmission planning; uncertainty quantification; variable generation resources; wind scenario generation;
Journal_Title :
Sustainable Energy, IEEE Transactions on
DOI :
10.1109/TSTE.2015.2425354