Interrelated Solar and Thermal Plant Autonomous Generation Control Utilizing Metaheuristic Optimization

Sanjiv Kumar Jain (), Sandeep Bhongade, Shweta Agrawal, Abolfazl Mehbodniya (), Bhisham Sharma, Subrata Chowdhury and Julian L. Webber
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Sanjiv Kumar Jain: Electrical Engineering Department, Medi-Caps University, Indore 453331, Madhya Pradesh, India
Sandeep Bhongade: Electrical Engineering Department, Shri G. S. Institute of Technology and Science, Indore 452001, Madhya Pradesh, India
Shweta Agrawal: Institute of Advance Computing, Sage University, Indore 452020, Madhya Pradesh, India
Abolfazl Mehbodniya: Department of Electronics and Communication Engineering, Kuwait College of Science and Technology (KCST), Doha 20185145, Kuwait
Bhisham Sharma: Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura 140401, Punjab, India
Subrata Chowdhury: Department of Computer Science and Engineering, Sreenivasa Institute of Technology and Management Studies, Chittoor 517127, Andhra Pradesh, India
Julian L. Webber: Department of Electronics and Communication Engineering, Kuwait College of Science and Technology (KCST), Doha 20185145, Kuwait

Energies, 2023, vol. 16, issue 8, 1-21

Abstract: In this study, the load frequency control of a two-area thermal generation system based on renewable energy sources is considered. When solar generation is used in one of the control areas, the system becomes nonlinear and complicated. Zero deviations in the frequencies and the flow of power through the tie lines are achieved by considering load disturbances. A novel grey wolf optimizer, which is a metaheuristic algorithm motivated by grey wolves is utilized for tuning the controller gains. The proportional, integral, and derivative gains values are optimized for the two-area Solar integrated Thermal Plant (STP). As the load connected to the system varies continuously with time, random load variation is also applied to observe the effectiveness of the proposed optimization method. Sensitivity analyses have also been adopted with the deviation in the time constants of different systems. Inertia constant variations of both areas are considered from −25% to +25%, with or without STP. The proposed algorithm shows good dynamic performance as shown from the simulation results in terms of settling time, overshoot values, and undershoot values. The power in the tie line achieves zero deviation quite rapidly in solar-based cases compared to those without STP.

Keywords: frequency control; grey wolf optimization; solar plant; thermal plant; control area error; gain optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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