Principal Component Analysis (PCA)-Supported Underfrequency Load Shedding Algorithm

Tadej Skrjanc, Rafael Mihalic and Urban Rudez
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Tadej Skrjanc: Laboratory of Electric Power Supply, Faculty of Electrical Engineering, University of Ljubljana, Trzaska 25, 1000 Ljubljana, Slovenia
Rafael Mihalic: Laboratory of Electric Power Supply, Faculty of Electrical Engineering, University of Ljubljana, Trzaska 25, 1000 Ljubljana, Slovenia
Urban Rudez: Laboratory of Electric Power Supply, Faculty of Electrical Engineering, University of Ljubljana, Trzaska 25, 1000 Ljubljana, Slovenia

Energies, 2020, vol. 13, issue 22, 1-9

Abstract: This research represents a conceptual shift in the process of introducing flexibility into power system frequency stability-related protection. The existing underfrequency load shedding (UFLS) solution, although robust and fast, has often proved to be incapable of adjusting to different operating conditions. It triggers upon detection of frequency threshold violations, and functions by interrupting the electricity supply to a certain number of consumers, both of which values are decided upon beforehand. Consequently, it often does not comply with its main purpose, i.e., bringing frequency decay to a halt. Instead, the power imbalance is often reversed, resulting in equally undesirable frequency overshoots. Researchers have sought a solution to this shortcoming either by increasing the amount of available information (by means of wide-area communication) or through complex changes to all involved protection relays. In this research, we retain the existing concept of UFLS that performs so well for fast-occurring frequency events. The flexible rebalancing of power is achieved by a small and specialized group of intelligent electronic devices (IEDs) with machine learning functionalities. These IEDs interrupt consumers only when the need to do so is detected with a high degree of certainty. Their small number assures the fine-tuning of power rebalancing and, at the same time, poses no serious threat to system stability in cases of malfunction.

Keywords: machine learning; power system frequency stability; load shedding; power system protection (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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