Principal component analysis (PCA)-supported underfrequency load shedding algorithm

Tadej Škrjanc (Author), Rafael Mihalič (Author), Urban Rudež (Author)

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

strojno učenje;frekvenčna stabilnost elektroenergetskega sistema;razbremenjevanje bremen;zaščita elektroenergetskega sistema;machine learning;power system frequency stability;load shedding;power system protection;

Data

Language:	English
Year of publishing:	2020
Typology:	1.01 - Original Scientific Article
Organization:	UL FE - Faculty of Electrical Engineering
UDC:	621.31:004
COBISS:	37324291
ISSN:	1996-1073
Views:	132
Downloads:	145
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	Slovenian
Secondary keywords:	strojno učenje;frekvenčna stabilnost elektroenergetskega sistema;razbremenjevanje;zaščita elektroenergetskega sistema;
Type (COBISS):	Article
Pages:	str. 1-9
Volume:	ǂno. ǂ22
Issue:	5896
Chronology:	2020
DOI:	10.3390/en13225896
ID:	14271469