Principal Component Analysis (PCA)-Supported Underfrequency Load Shedding Algorithm
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 co...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-11-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/13/22/5896 |
| _version_ | 1797548099164438528 |
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| author | Tadej Skrjanc Rafael Mihalic Urban Rudez |
| author_facet | Tadej Skrjanc Rafael Mihalic Urban Rudez |
| author_sort | Tadej Skrjanc |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T14:54:41Z |
| format | Article |
| id | doaj.art-2a4d21dcadf54a138e3a1dbe33811d1f |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T14:54:41Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-2a4d21dcadf54a138e3a1dbe33811d1f2023-11-20T20:41:57ZengMDPI AGEnergies1996-10732020-11-011322589610.3390/en13225896Principal Component Analysis (PCA)-Supported Underfrequency Load Shedding AlgorithmTadej Skrjanc0Rafael Mihalic1Urban Rudez2Laboratory of Electric Power Supply, Faculty of Electrical Engineering, University of Ljubljana, Trzaska 25, 1000 Ljubljana, SloveniaLaboratory of Electric Power Supply, Faculty of Electrical Engineering, University of Ljubljana, Trzaska 25, 1000 Ljubljana, SloveniaLaboratory of Electric Power Supply, Faculty of Electrical Engineering, University of Ljubljana, Trzaska 25, 1000 Ljubljana, SloveniaThis 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.https://www.mdpi.com/1996-1073/13/22/5896machine learningpower system frequency stabilityload sheddingpower system protection |
| spellingShingle | Tadej Skrjanc Rafael Mihalic Urban Rudez Principal Component Analysis (PCA)-Supported Underfrequency Load Shedding Algorithm Energies machine learning power system frequency stability load shedding power system protection |
| title | Principal Component Analysis (PCA)-Supported Underfrequency Load Shedding Algorithm |
| title_full | Principal Component Analysis (PCA)-Supported Underfrequency Load Shedding Algorithm |
| title_fullStr | Principal Component Analysis (PCA)-Supported Underfrequency Load Shedding Algorithm |
| title_full_unstemmed | Principal Component Analysis (PCA)-Supported Underfrequency Load Shedding Algorithm |
| title_short | Principal Component Analysis (PCA)-Supported Underfrequency Load Shedding Algorithm |
| title_sort | principal component analysis pca supported underfrequency load shedding algorithm |
| topic | machine learning power system frequency stability load shedding power system protection |
| url | https://www.mdpi.com/1996-1073/13/22/5896 |
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