Application of modified multi-verse optimization for temperature control in thermal power plant condensers

The surface condenser exhibits nonlinear dynamics and inherent time delays, making precise temperature regulation essential for stable operation in thermal power systems. In this study, a Modified Multi-Verse Optimizer (MMVO) is employed to tune the parameters of a PID controller for improved temperature control of a shell-and-tube condenser. The methodology involves formulating the PID tuning task as an optimization problem, applying MMVO with defined search bounds, and evaluating its performance using 23 standard benchmark functions and repeated simulation runs. Statistical indicators including best, worst, average, and standard deviation values across 30 independent executions are used to assess robustness. Comparative analyses with Ziegler-Nichols (ZN), Genetic Algorithm (GA), and the original Multi-Verse Optimizer (MVO) demonstrate that the modified approach achieves lower integral error indices and reduced overshoot, while providing more consistent performance across trials. The results indicate that MMVO-based PID tuning offers enhanced control capability for systems with strong nonlinearities and delay characteristics.