Load Frequency Control Using Hybrid Intelligent Optimization Technique for Multi-Source Power Systems

Deepak Kumar Gupta, Amitkumar V. Jha, Bhargav Appasani, Avireni Srinivasulu, Nicu Bizon and Phatiphat Thounthong
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Deepak Kumar Gupta: School of Electrical Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar 751024, India
Amitkumar V. Jha: School of Electronics Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar 751024, India
Bhargav Appasani: School of Electronics Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar 751024, India
Avireni Srinivasulu: Department of Electronics Engineering, JECRC University, Jaipur 303905, India
Nicu Bizon: Faculty of Electronics, Communication and Computers, University of Pitesti, 110040 Pitesti, Romania
Phatiphat Thounthong: Renewable Energy Research Centre (RERC), Department of Teacher Training in Electrical Engineering, Faculty of Technical Education, King Mongkut’s University of Technology North Bangkok, 1518, Pracharat 1 Road, Wongsawang, Bangsue, Bangkok 10800, Thailand

Energies, 2021, vol. 14, issue 6, 1-16

Abstract: The automatic load frequency control for multi-area power systems has been a challenging task for power system engineers. The complexity of this task further increases with the incorporation of multiple sources of power generation. For multi-source power system, this paper presents a new heuristic-based hybrid optimization technique to achieve the objective of automatic load frequency control. In particular, the proposed optimization technique regulates the frequency deviation and the tie-line power in multi-source power system. The proposed optimization technique uses the main features of three different optimization techniques, namely, the Firefly Algorithm (FA), the Particle Swarm Optimization (PSO), and the Gravitational Search Algorithm (GSA). The proposed algorithm was used to tune the parameters of a Proportional Integral Derivative (PID) controller to achieve the automatic load frequency control of the multi-source power system. The integral time absolute error was used as the objective function. Moreover, the controller was also tuned to ensure that the tie-line power and the frequency of the multi-source power system were within the acceptable limits. A two-area power system was designed using MATLAB-Simulink tool, consisting of three types of power sources, viz., thermal power plant, hydro power plant, and gas-turbine power plant. The overall efficacy of the proposed algorithm was tested for two different case studies. In the first case study, both the areas were subjected to a load increment of 0.01 p.u. In the second case, the two areas were subjected to different load increments of 0.03 p.u and 0.02 p.u, respectively. Furthermore, the settling time and the peak overshoot were considered to measure the effect on the frequency deviation and on the tie-line response. For the first case study, the settling times for the frequency deviation in area-1, the frequency deviation in area-2, and the tie-line power flow were 8.5 s, 5.5 s, and 3.0 s, respectively. In comparison, these values were 8.7 s, 6.1 s, and 5.5 s, using PSO; 8.7 s, 7.2 s, and 6.5 s, using FA; and 9.0 s, 8.0 s, and 11.0 s using GSA. Similarly, for case study II, these values were: 5.5 s, 5.6 s, and 5.1 s, using the proposed algorithm; 6.2 s, 6.3 s, and 5.3 s, using PSO; 7.0 s, 6.5 s, and 10.0 s, using FA; and 8.5 s, 7.5 s, and 12.0 s, using GSA. Thus, the proposed algorithm performed better than the other techniques.

Keywords: optimization techniques; multisource power system; automatic generation control; controllers; load frequency control (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: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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