Enhancing Voltage Regulation in Synchronous Generators: A Novel Approach With Fractional-Order PID Controllers and Wound Healing Algorithm

• Published in: IEEE access Vol. 12; pp. 167404 - 167412
• Main Author: Cinar, Mehmet
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Antibodies; Automatic voltage regulator; Cloning; Configuration management; Control systems design; Controllers; Effectiveness; Evolutionary computation; FOPID; Graphical user interface; Heuristic methods; Optimization; Parameter estimation; Particle swarm optimization; Peak values; Power system stability; Programming languages; Proportional integral derivative; Regulators; Reliability; Settling; Stability analysis; Step response; Synchronous generators; Synchronous machines; Transient response; Tuning; Voltage control; Voltage regulators; Water waves; Wound healing; wound healing algorithm; Wounds
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2024.3496820

Voltage regulation in automatic voltage regulator (AVR) systems has been one of the most challenging engineering problems owing to uncertain load conditions. One of the primary study topics is to obtain an effective and reliable control mechanism for attaining a specific voltage level in AVR systems. Especially with the method proposed in the study, parameters such as overshoot percentage, peak value, and settling time of the system are optimized and the system is made more stable. In this study, a fractional-order PID controller (FOPID) was used to achieve an optimal design for an automatic voltage regulator. The developed wound healing algorithm (WHA) was used to estimate the tuning parameters of the FOPID controller to achieve the ideal transient response and boost the stability of the AVR system. The terminal voltage of the synchronous generator's maximum percent overshoot in the step response, the rising time, the settling time, and the steady state error have all been attempted to be decreased utilizing the configuration parameters that have been supplied. Software that performed this was produced using the graphical user interface (GUI) of Matlab's programming language. Comparisons are made using several metaheuristic algorithms to determine this recommended technique's results and advantages. The proposed algorithm-based FOPID tuning technique provides 62.01%, 71.61%, 12.2%, 26.6%, 65.23%, 26.32%, 30.36%, 44.37%, and 0.17% reduced overshoot than the Particle Swarm Optimization (PSO), Water Cycle (WCA), Grey Wolf Optimization (GWO), Local Unimodal Sampling (LUS), Differential Evolution (DE), Salp Swarm Optimization (SSA), Water Wave Optimization (WWO), Grasshopper Optimization (GOA), and Sine-Cosine Optimization (SCA) algorithms, respectively, thus validating its competence and effectiveness.