Control technologies of wastewater treatment plants: The state-of-the-art, current challenges, and future directions

Existing pieces of literature on previous studies advocate the research focus by various researchers to reach the benchmark of energy efficiency of Wastewater Treatment Plants (WWTPs). The driving factors to improve the energy efficiency and mitigate the energy self-sufficiency of WWTP have been identified as the increase in population growth, rising energy costs, and tightening effluent discharge requirements. WWTP economy is directly related to energy consumption and thus affects smart grid economy. There has been limited research on energy self-sufficiency and optimizing the energy demand and cost of WWTP, where the significant contributing factors are in development an optimal pumping system and advanced motor technologies. Moreover, high quality WWTP's effluent depends on the concentration level of biochemical oxygen demand (BOD) and total kjedhal nitrogen (TKN). Even so, WWTPs are always subject to evident nonlinearities and uncertainties, making it difficult to define proper optimization objectives. Besides, controllers and control systems have a strong influence on the performance of the plants. Therefore, existing research gaps to achieve optimal efficiency with minimized energy consumption and costs are the design of the WWTP plant, pumping system, motors, selection of suitable controllers and control systems, and their parameter optimizations to get the optimal output from the plant, switching techniques, challenges and uncertainties associated with plant are highlighted in this paper. Thus, as a novel contribution to the literature, this study aims to review and analyze the history, current issues, and future directions of WWTP control technologies in the context of sustainable development. The rigorous study by the authors in this paper will definitely lead the academic researchers and industry partners toward the development of optimal WWTP technologies with improved efficiency and minimized energy consumption and costs.