Abstract—As the demand for power increases, the need for harmonic state estimation (HSE) has been increasing as well. Harmonics, injected by the non-linear equipments along the distribution networks, causes several power quality issues. Therefore, HSE plays an important role in harmonics monitoring and control. Various HSE techniques and algorithms have been developed since 1989, which would be reviewed and discussed in this paper. The author outlines the role of artificial intelligence (AI) in the field and the process overview of neural network and also a hybrid algorithm which combines particle swarm optimization (PSO) and gradient descent (GD) to train the weights of neural network (NN).
Index Terms—Artificial intelligence, gradient descent, harmonics state estimation, neural network, power quality.
The authors are with the Department of Electrical and Electronics Engineering, Universiti Teknologi PETRONAS, 31750 Tronoh, Perak, Malaysia(e-mail:ugasciny@gmail.com),(e-mail:nursyarizal_mnor@petrona s.com.my), (e-mail: mfaris_abdullah@petronas.com.my).
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Cite: U. Arumugam, N. M. Nor, and M. F. Abdullah, "A Brief Review on Advances of Harmonic State Estimation Techniques in Power Systems," International Journal of Information and Electronics Engineering vol. 1, no. 3, pp. 217-222, 2011.
