Open Access

ARTICLE

Robust Load Frequency Control in Hybrid Power Systems Using QOSCA-Tuned PID with EV Loads

Pralay Roy¹, Pabitra Kumar Biswas¹, Chiranjit Sain^2,*, Taha Selim Ustun^3,*

1 Department of Electrical Engineering, National Institute of Technology Mizoram, Mizoram, 796012, India
2 Department of Electrical Engineering, Ghani Khan Choudhury Institute of Engineering & Technology, Malda, 732141, India
3 Fukushima Renewable Energy Institute, AIST, Koriyama, 963-0298, Japan

* Corresponding Authors: Chiranjit Sain. Email: ; Taha Selim Ustun. Email:

(This article belongs to the Special Issue: Low-Carbon Situational Awareness and Dispatch Decision of New-Type Power System Operation)

Energy Engineering 2025, 122(10), 4035-4060. https://doi.org/10.32604/ee.2025.068989

Received 11 June 2025; Accepted 15 August 2025; Issue published 30 September 2025

Abstract

This study presents the use of an innovative population-based algorithm called the Sine Cosine Algorithm and its metaheuristic form, Quasi Oppositional Sine Cosine Algorithm, to automatic generation control of a multiple-source-based interconnected power system that consists of thermal, gas, and hydro power plants. The Proportional-Integral-Derivative controller, which is utilized for automated generation control in an interconnected hybrid power system with a DC link connecting two regions, has been tuned using the proposed optimization technique. An Electric Vehicle is taken into consideration only as an electrical load. The Quasi Oppositional Sine Cosine method’s performance and efficacy have been compared to the Sine Cosine Algorithm and optimal output feedback controller tuning performance. Applying the QOSCA optimization technique, which has only been shown in this study in the context of an LFC research thus far, makes this paper unique. The main objective has been used to assess and compare the dynamic performances of the recommended controller along with QOSCA optimisation technic. The resilience of the controller is examined using two different system parameters: B (frequency bias parameter) and R (governor speed regulation). The sensitivity analysis results demonstrate the high reliability of the QOSCA algorithm-based controller. Once optimal controller gains are established for nominal conditions, step load perturbations up to ±10% & ±25% in the nominal values of the system parameters and operational load condition do not require adjustment of the controller. Ultimately, a scenario is examined whereby EVs are used for area 1, and a single PID controller is used rather than three.

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Keywords

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