Study On Optimal Design Of Water Utilization Network With Energy Integration

Effective utilization of water and energy is the key factor of sustainable development in process industries,it is also an important science and technology problem needed to be solved in systems engineering academic research．In this paper,the researches have been done as follows: 1．As to the multiple-objective optimization of water and energy in process industry,this article uses the stepwise design method which departs the optimal problem into two stages．In stage one,the water pinch method or mathematical programming method is used to minimize the freshwater flowrate．In stage two,the energy integration is carried out under the minimum freshwater flowrate．The method iS suitable both for single contaminant and multiple contaminants systems．The integration of energy Can be carried through total processsystem beyond the water utilization network． 2．Stepwise design method of minimum water and energy does not reach thesimultaneous minimization of water and energy in reality．Mathematical programming method is a powerful tool to perform simultaneous design because it has the advantage of simultaneous optimization and dealing with multiple objective together．As the research hot spot and difficult point,simultaneous design of optimization of water and energy is studied on the basis of stepwise design method．Sequential model method is used on the optimization of water and energy．The simultaneous minimum of water and energy is reached as the adaptivesimulated annealing genetic algorithm searches during a large region．The contrast of case study with stepwise design method indicates the simultaneous design method is efficient． 3．For the large non-convex nonlinear programming(NLP)or mixed integer nonlinear programming(MINLP)caused by optimization of water and energy,an adaptive simulated annealing genetic algorithm(ASAGA)is developed in this paper．The strategy of adjusting step size and temperature decreasing adaptively raises the speed and the ability to find global optimum with a higher probability of the hybrid algorithm．And genetic algorithm embed in the inner of adaptive simulated annealing algorithm compensates the deficiency that simulated annealing is difficult to perform global optimization because of its missing for ago information．Test functions of non．convex NLP show the hybrid algorithm has good capability in convergence speed and finding the global optimum．The combination of ASAGA and GASA of energy integration makes the simultaneous optimization of water and energy in process industries comes to reality．...