Optimization of Control Structures in Wastewater Treatment Plants for Enhanced Efficiency

: Wastewater Treatment Plants are crucial because they are ensuring environmental sustainability through effective wastewater treatment before discharge or reuse. Nevertheless, the power of these plants is compromised by aspects such as high energy usage, operational costs, and environmental problems like greenhouse gas production and sludge toxicity. This study will address optimization in the WWTP control structure by strengthening efficiency while observing minimum effluent quality compliant with regulatory necessities. By employing advanced control strategies such as real-time monitoring, artificial intelligence, and MPC, the work determines how the process automation might decrease energy use and increase removal efficiency of pollutant. Simulation-based model MATLAB with the utilization of GA, is used by the study, optimizing the operation of WWTP control systems against influent varied conditions such as dry and wet weather. The results show that the proposed AI-driven optimization method significantly improves pH stability, BOD, COD, and ammonia removal while reducing aeration energy consumption. The study concludes that the implementation of advanced control strategies in WWTP operations can lead to cost-effective and environmentally friendly wastewater treatment. Future research should focus on validating these optimization models in real-world settings to support large-scale implementation.