Frequency Control in PV-Integrated Microgrid Using Hybrid Optimization-Based ANFIS and Deep Learning Network

Abstract

Frequency variation in the network and severe impact of linked frequency-sensitive loads are the main concerns of integrating RESs with traditional power system networks. Because RESs are separated from the traditional grid by power electronic converters, they have zero or very little inertia, which is the primary source of frequency variation. If different electrical motors are connected with PV, the rotor speed frequency and the pulse of the PV panel are assorted. Therefore, this paper suggests an adaptive Neuro-fuzzy inference system (ANFIS) and Deep Neural Network (DNN) based controller for improving the performance of the power system. The developed approach’s primary goal is to regulate the output waveform, hence reducing the error among the control and reference signals. Moreover, the performance model is further enhanced by optimizing the ANFIS controller using the novel hybrid optimization algorithm, named Honey Badger-based grey wolf Optimization (HB-GWO) Algorithm. The performance of the implemented scheme is done in MATLAB and the results over various controllers concerning switching frequency and time analysis. Accordingly, the optimal parameter values obtained using the HB-GWO Algorithm are, the initial step size is 0.31258, the decrease rate of step size is 0.47177 and the increase rate of step size is 1.3754.

Keywords:

• distributed generator
• solar PV
• ANFIS
• DNN
• optimization
• switching frequency
• time analysis

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Deepesh Sharma

Deepesh Sharma received M. Tech. and Ph.D. from DCR University of Science and Technology, Murthal, Sonepat, India in 2011 and 2020, respectively. Presently, he is an Assistant Professor in the Department of Electrical Engineering, DCR University of Science and Technology, Murthal, Sonepat, India. He has more than 12 years of experience in teaching and research. He has published more than thirty papers in referred international journals and conferences. He is life member of ISTE. His research interests include power system restructuring, power system optimization & control, renewable energy and smart grid.