Artificial Intelligence-Based State Estimation in Power System and Phasor Measurement Units

Abstract

In the dynamically varying modern power system, it is challenging to monitor and estimate state variables of the network. In this work, state variables such as voltage magnitude and phasor angle are estimated using artificial intelligence (AI) techniques such as machine learning (ML) and deep learning (DL) methods. Among various ML models available, the few models considered in the proposed work for the state estimation (SE) in power system are decision tree, support vector machine, Ensemble boost, Ensemble bag (Eboost/bag), and artificial neural network (ANN). Similarly, DL models such as gate recurrent unit (GRU), long short-term memory (LSTM), and bidirectional LSTM are proposed for the SE. Among all these AI techniques, ANN and GRU gives better results than other models. Among them, the performance of GRU, a DL tool is found as best when compared to ANN, the ML. The accuracy of AI techniques are measured using evaluation metrics. The obtained results from AI compared to conventional techniques, weighted least square, and regularized least square method. Phasor measurement units is contributing more to minimize the SE errors based on its maximum observability and proved by using IEEE 14 and 30 bus systems.

Keywords:

• deep learning
• machine learning
• phasor measurement units
• state estimation
• weighted least square estimation

Authors’ contributions

Conceptualization and Supervision contributed by [Koperundevi Ganesan], Methodology and article preparation contributed by [Saravanakumar Ramasamy], Formal analysis and investigation contributed by [Banumalar Koodalsamy]. All authors read and approved the final manuscript.

Research involving human participants and/or animals

This research does not involve human participant and animals.

DATA AVAILABILITY

Data available based on request.

Acknowledgment

The authors would like to express their sincere gratitude to the National Institute of Technology Puducherry for providing research facility in this area.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

There is no funding for this research.

Notes on contributors

Saravanakumar Ramasamy

Saravanakumar Ramasamy received his B.E. degree in Electrical and Electronics Engineering from PSNA College of engineering & technology, Dindigul, Anna University, Chennai, India in 2010 and M.E. degree in Power systems engineering from Anna University Trichy, India in 2013. He is currently doing Ph. D in Department of Electrical and Electronics Engineering, National Institute of Technology, Puducherry, India. His research interest includes phasor measurement units, power system pricing, smart grid, demand response programme and power system optimization.

Koperundevi Ganesan

Koperundevi Ganesan received her B.Tech. degree in Electrical and Electronics Engineering from Pondicherry Engineering College, Pondicherry University, India in 2001. She obtained her M.E. degree in Electrical Drives and Control from Pondicherry Engineering College, Pondicherry University, India in 2004. Ph.D. degree in High Voltage Engineering from Indian Institute of Technology Madras, Chennai, India in the year 2011. She is currently serving as Associate Professor with the Department of Electrical and Electronics Engineering, National Institute of Technology, Puducherry, India. Her research interests include Condition Monitoring of Insulation structures in Power Apparatus, Nano Dielectric Liquids, Power Electronics application in Power System, Power Converters, Drives & Control for Electric Vehicle, Smart Technology in Agriculture.

Banumalar Koodalsamy

Banumalar Koodalsamy received her B.E. degree in Electrical and Electronics Engineering from Madurai Kamaraj University, India in 1999. She obtained her M.E. degree in Applied Electronics and Ph.D. degree in Information and Communication Engineering from Anna University, Chennai, India in the year 2008 and 2018, respectively. She is currently serving as Associate Professor with the Department of Electrical and Electronics Engineering, Mepco Schlenk Engineering College, Sivakasi, India. Her research interests include power system scheduling problems, optimal placement of distributed generation & phasor measurement units and optimization techniques.