A Novel MPPT Controller Based on Mud Ring Optimization Algorithm for Centralized Thermoelectric Generator under Dynamic Thermal Gradients

Most industrial processes generate raw heat. To enhance the efficiency of operations, this heat is recovered. Thermoelectric generators (TEG), as solid state devices, provide an excellent application recovery in form most manageable electrical power. This work presents a novel MPPT controller based on Mud Ring Optimization algorithm for centralized Generator (TEG) under dynamic thermal gradients. The existing stochastic optimization Maximum Power Point Tracking (MPPT) control renewable energy systems exhibits several limitations that affect its performance control. convergence speed, local minima trap, hyper parameters’ sensitivity toward population size, acceleration coefficients, and stopping criterion all impact stability. In addition to these limitations, sensor noise measurement fluctuates system leading reduced performance. Therefore, careful design implementation MRO crucial overcome achieve satisfactory results study contribute developing more efficient TEG implementing technologies. effectively tracks maximum power point environments increases output compared conventional methods. findings illustrate efficacy proposed providing higher (Avg. 99.95%) faster response time (220 ms) conditions achieving 38–70% tracking GM operating conditions.