Water Science and Technology (Nov 2022)
Heterogeneous multi-population competitive algorithm and its application in ASM1 parameter estimation
Abstract
Activated sludge model 1 (ASM1) is a biokinetic model of the activated sludge wastewater treatment process, which has several uncertain parameters and complex chemical reaction processes. This model is often used in simulations to assess whether the effluent quality of wastewater meets discharge standards. Accurate and rapid estimation of the parameters of ASM1 is a necessary prerequisite for its successful application in industrial practice. However, ASM1-based parameter estimation is difficult to implement in practical operations due to the slow convergence rate and low convergence accuracy of most parameter estimation algorithms as well as the non-uniqueness of parameter estimation. In view of this, a novel metaheuristic optimization algorithm combining Legendre function network and dynamic partitioning strategy, named heterogeneous multi-group competitive algorithm (HMCA), is proposed to overcome the problem of low algorithmic efficiency and poor practicality in parameter estimation. The performance of the algorithm in terms of convergence speed, convergence accuracy and applicability is verified by two sets of test functions and eight state-of-the-art comparison algorithms. The superior performance of the algorithm in parameter estimation is then validated in conjunction with Benchmark Simulation Model no. 1 (BSM1) and four sets of operational data. HIGHLIGHTS A novel algorithm (HMCA) is proposed for parameter estimation.; HMCA is tested by 20 classical benchmark test functions and performance is superior in most cases.; Four wastewater treatment processes under different conditions were modeled using the HMCA-estimated parameters.; Experimental results show that HMCA is able to effectively simulate the activated sludge wastewater treatment process in different conditions.;
Keywords
