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Review Articles

Utilizing Electric Vehicles and Renewable Energy Sources for Load Frequency Control in Deregulated Power System Using Emotional Controller

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Pages 1500-1511 | Published online: 29 Aug 2019
 

Abstract

Modern day power system comprises of distributed power generation sources (DGs), distributed energy storage devices and loads. Control of these systems is more tedious than ordinary power systems since energy in these systems is provided by renewable energy sources which have intermittent and varying nature. These fluctuations in the generated power may cause some problems in the function of conventional controllers. As a result, the present-day power systems require increased intelligence and flexibility in control to ensure generation–load balance. In this paper, emotional controller (Brain Emotional Learning-Based Intelligent Controller, BELBIC) is used for load frequency control of two area hybrid power system in deregulated environment. The power system is integrated with DG sources like solar and biomass. Electric vehicles are used to handle intermittency of solar power. To make it more realistic, effect of nonlinearity constraints and time delay in communication channel is also considered. The proposed controller based on the emotional learning process of the human brain provides a suitable control action against system imperfections and occurrence of uncertainties. The special feature of this controller that makes it effective is its flexibility; its five gain parameters that give freedom to choose the desired response. To evaluate the performance of the proposed controller, the results are compared with the conventional proportional integral derivative (PID) and fractional order PID controller. Simulation results show the effectiveness of the emotional controller. Also, the parameters of the BELBIC are tuned by using Sugeno fuzzy inference system. Lyapunov stability analysis is used to prove the convergence of the designed control signals and to ensure the stability of the system.

ACKNOWLEDGMENTS

The authors would like to thank the authorities of Thapar Institute of Engineering and Technology for their continuous support.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Ankush Dutta

Ankush Dutta received the BE degree in electrical engineering from SUSCET, Tangori, India, in 2007, ME degree (Power Systems and Electric Drives) from Thapar Institute of Engineering and Technology, Patiala in 2009. He is currently pursuing PhD from Thapar Institute of Engineering and Technology, Patiala. His research interests include power system control under deregulated environment, renewable energy systems, distributed generation, vehicle-to-grid, and intelligent control techniques. Corresponding author. Email: [email protected]; [email protected]

Surya Prakash

Surya Prakash received the BE degree in electrical engineering from the Institution of Engineers (India) in 2003, MTech degree (Power Systems) from KNIT, Sultanpur, UP, India in 2009 and obtained his PhD from SSET, SHIATS (Formerly Allahabad Agriculture Institute, Allahabad, India) in 2014. Currently, working as assistant professor in the Electrical and Instrumentation Engineering Department, Thapar Institute of Engineering and Technology, Patiala. Dr Prakash has about 18 years of industry and 6 years of teaching experience. His research interests include power system operation and control, artificial intelligence control. Email: [email protected]

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