@inproceedings{61ee03024b1641929a2538cb49812b52,
title = "Modeling of the CPS1 for the Frequency Constrained Unit Commitment",
abstract = "Frequency is an important index to reflect stability of the power system. NERC's Control Performance Standard 1 (CPSI) is to assess control area's ability in maintaining frequency quality. This paper proposes a stepwise regression method to identify important frequency-control correlation factors for developing a CPSI model. The CPSI model is constructed by the Long Short-Term Memory (LSTM) neural network. The well trained CPSI model is then integrated into a unit commitment (UC) program to realize a CPSI compliant UC (UC-CPSI). The performance of the proposed UC-CPSI is validated by simulation case and is compared with the case without the frequency constrained UC.",
author = "Chiu, {Hsin Wei} and Lin, {Yu Lin} and Chang-Chien, {Le Ren} and Wu, {Chin Chung}",
note = "Funding Information: ACKNOWLEDGMENT This research was partially supported by Taiwan Power Company under Grant TPC-5460300124. Funding Information: Under normal operation, the continuous load-generation balance is kept by PFC supported by speed-droop governors, and SFC supported by automatic generation control (AGC). AGC sends signal every 4 seconds to adjust generating units for maintaining frequency stability at satisfied level. Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE PES Asia-Pacific Power and Energy Engineering Conference, APPEEC 2019 ; Conference date: 01-12-2019 Through 04-12-2019",
year = "2019",
month = dec,
doi = "10.1109/APPEEC45492.2019.8994656",
language = "English",
series = "Asia-Pacific Power and Energy Engineering Conference, APPEEC",
publisher = "IEEE Computer Society",
booktitle = "2019 IEEE PES Asia-Pacific Power and Energy Engineering Conference, APPEEC 2019",
address = "United States",
}