ANNOUNCEMENTS
The project embodies in this dissertation aims to develop a MATLAB program for optimal design of Municipal Wastewater Treatment Plant (MWWTP) based on Activated Sludge Process (ASP). The objective function of optimization of ASP includes minimizing volume of biological reactor and energy consumption by aeration equipment and sludge recirculation pumps. Necessary raw effluent parameters like Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), pH, Total Suspended Solids (TSS) etc. are provided by the user from the program user interface. Based on these parameters the Decision Support System (DSS) developed suggest which treatment stage is required and which is not required. The treatment selection logics used in the algorithm follows the minimum discharge standards as prescribed in the CPHEEO manual. Non-Dominating Sorting Algorithm II (NSGA II) is used to generate Pareto optimal front. Based on the selected optimal pareto set, the program calculates the size of various treatment units and optimal design of biological reactor.
In developing countries, conventional technology is preferred to treat municipal wastewater in urban settlements because it is cost effective, easy to operate and effluent quality complies with minimum discharge standards. Lesser capital cost and operation cost is one of the primary decision criteria while choosing treatment technology. Activated sludge process fulfill almost all the criteria and is thus preferred as the first choice. The design process is often carried out by experts using simpler and manual tools which may or not generate an optimal design. The design process includes a number of design criteria like process capacity, rate of aeration, maintaining optimum MLSS. The program so developed can prove to be a foundation of an effective tool for quick and optimal design.
Keywords: Optimization, Municipal Wastewater Treatment Plant, Activated Sludge Process, Genetic Algorithm, MATLAB R2020, Design.
