Abstract
One of the challenges brought about by the large wind portfolio in ERCOT is the presence of forced oscillations from wind generators driven by control systems with a bad setting. To address this, a study was undertaken to mine archived synchrophasor data from PMUs installed near wind farms for oscillations and identify location, frequency of oscillation, and minimum energy level for each mode. In this chapter, we present the results obtained from the study and the conclusions reached. The study utilized two metrics—Monthly Highest Energy (MHE) and Monthly Mode Occurrence (MMO)—to classify the identified oscillatory modes. The results of this study informed the configuration of real-time tools for monitoring of and alerting for these oscillations . The various modes were found to be associated with MW output and/or control system design and settings of wind farms. The results of the study also provided the needed information to validate models against specific oscillations events and determine plausible strategies for addressing these modes in real-time operations .
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Palayam, P.C., Rajagopalan, S., Blevins, B., Nuthalapati, S. (2019). Identification of Signature Oscillatory Modes in ERCOT by Mining of Synchrophasor Data. In: Nuthalapati, S. (eds) Power System Grid Operation Using Synchrophasor Technology . Power Electronics and Power Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-89378-5_6
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DOI: https://doi.org/10.1007/978-3-319-89378-5_6
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