Noninvasive control solution for energy efficiency in wastewater treatment plants

摘要

Improving energy efficiency in wastewater plants is an important goal for water distribution companies due to the high costs associated with wastewater treatment processes. Most of these costs are generated by the aeration process, respectively optimizing the oxygen control strategy and consequently affecting the ammonium and nitrate levels can lead to significant reduction in energy consumption. Most wastewater treatment plants are already implemented and functioning systems, respectively any interference in modifying invasively existing structures/algorithms is problematic. Following industrial internet of things principles in an Industry 4.0 context, the paper proposes an OPC UA client based model predictive control structure that will allow the solution development in a completely noninvasive manner for the functioning system. The solution is applied in a simulation environment with calibrated and validated model and using real input data. Also, a Node-red and Raspberry Pi platforms application is structured for future long-term testing and validation on real plant following the current research. The paper presents the results of current developments proving the efficiency of the concept.