Title :
Evaluation of Power System Flexibility
Author :
Lannoye, Eamonn ; Flynn, Damian ; O´Malley, Mark
Author_Institution :
Sch. of Electr., Electron. & Commun. Eng., Univ. Coll. Dublin, Dublin, Ireland
fDate :
5/1/2012 12:00:00 AM
Abstract :
As the penetration of variable renewable generation increases in power systems worldwide, planning for the effects of variability will become more important. Traditional capacity adequacy planning techniques have been supplemented with integration studies, which have been carried out in power systems with high targets for renewable generation. These have highlighted the increased variability that a system may experience in the future. As system generation planning techniques evolve with the challenge of integrating variable generation, the flexibility of a system to manage periods of high variability needs to be assessed. The insufficient ramping resource expectation (IRRE) metric is proposed to measure power system flexibility for use in long-term planning, and is derived from traditional generation adequacy metrics. Compared to existing generation adequacy metrics, flexibility assessment is more data intensive. A flexibility metric can identify the time intervals over which a system is most likely to face a shortage of flexible resources, and can measure the relative impact of changing operational policies and the addition of flexible resources. The flexibility of a test system with increasing penetrations of variable generation is assessed. The results highlight the time horizons of increased and decreased risk associated with the integration of VG.
Keywords :
distributed power generation; power generation planning; IRRE metric; adequacy planning techniques; insufficient ramping resource expectation metric; long-term planning; power system flexibility evaluation; system generation planning techniques; time intervals; variable renewable generation; Capacity planning; Load modeling; Measurement; Planning; Power systems; Time series analysis; Hydro power generation; power system modeling; power system planning; solar power generation; wind power generation;
Journal_Title :
Power Systems, IEEE Transactions on
DOI :
10.1109/TPWRS.2011.2177280