Application of Machine Learning for Online Dynamic Security Assessment in Presence of System Variability and Additive Instrumentation Errors
| Autor: | Anamitra Pal, Reetam Sen Biswas, Anubhav Nath |
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| Rok vydání: | 2019 |
| Předmět: |
Scheme (programming language)
Observational error business.industry Computer science 020209 energy 020208 electrical & electronic engineering 02 engineering and technology Dynamic security assessment Systems and Control (eess.SY) Machine learning computer.software_genre Phasor measurement unit Electrical Engineering and Systems Science - Systems and Control Field (computer science) Grid security 0202 electrical engineering electronic engineering information engineering Renewable generation FOS: Electrical engineering electronic engineering information engineering Instrumentation (computer programming) Artificial intelligence business computer computer.programming_language |
| DOI: | 10.48550/arxiv.1909.04145 |
| Popis: | Large-scale blackouts that have occurred in the past few decades have necessitated the need to do extensive research in the field of grid security assessment. With the aid of synchrophasor technology, which uses phasor measurement unit (PMU) data, dynamic security assessment (DSA) can be performed online. However, existing applications of DSA are challenged by variability in system conditions and unaccounted for measurement errors. To overcome these challenges, this research develops a DSA scheme to provide security prediction in real-time for load profiles of different seasons in presence of realistic errors in the PMU measurements. The major contributions of this paper are: (1) develop a DSA scheme based on PMU data, (2) consider seasonal load profiles, (3) account for varying penetrations of renewable generation, and (4) compare the accuracy of different machine learning (ML) algorithms for DSA with and without erroneous measurements. The performance of this approach is tested on the IEEE-118 bus system. Comparative analysis of the accuracies of the ML algorithms under different operating scenarios highlights the importance of considering realistic errors and variability in system conditions while creating a DSA scheme. Comment: Accepted in the proceedings of the 51st North American Power Symposium (NAPS), Wichita, USA, Oct. 2019 |
| Databáze: | OpenAIRE |
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