Improved Immune Genetic Algorithm And Its Application In Wastewater Treatment

Wastewater treatment system is an important department of environmental protection industry, including municipal wastewater, industrial wastewater and rural wastewater. Along with the increasing emphasis on environmental management and energy conservation, effectively reducing the power consumption of wastewater treatment plants become more and more important.In the field of wastewater treatment, Benchmark Simulation Model No.1(BSM1) is widely used model in this field. BSM1 is composed of activated sludge biochemical reaction tank model and the secondary sedimentation tank model. Both of the models are benchmark in the field of wastewater treatment. In this paper, BSM1 is used as the simulation object, and the performance evaluation standard and conventional control strategy of BSM1 are defined. Taking the water quality as the constraint, the aeration energy consumption and pumping energy consumption are used as the optimization objective. Moreover, this paper puts up with optimal strategy of the BSM1’s PI controller in the different climatic conditions.In the study of energy saving optimization of wastewater treatment system by using immune genetic algorithm, the process of BSM1 requires the accuracy of the optimization. Therefore, in this paper, the gradient descent method is proposed to accelerate the iteration speed of the antibody and the local search ability of the immune genetic algorithm is enhanced to improve the accuracy of convergence. The Markov chain model is used in the algorithm, and then gives the mathematical proof. The simulation results of standard test functions shows that the improved immune genetic algorithm can achieve high precision and high accuracy while keeping the fast convergence rate.In the process of MATLAB simulation experiment, MATLAB can’t run parallel in the Windows operation system. Besides, the speed of computation has not reached acceptable level. This dissertation rewrites the immune genetic algorithm in LINUX operation system. The algorithm uses shared memory to achieve communication between different processes, binds processor to eliminate resource waste of processor scheduling, and improves the computational performance by Multi-threading technology. The simulation results show that the improved parallel immune algorithm not only can improve the speed of calculation, but also can improve the accuracy of calculation.