Optimization And Design For Integrated System Of Seawater Desalination Based On The Genetic Algorithm

The lack of freshwater resources has become an important factor whichconstrains the social development and human life. And it has been a very importantissue to conserve water and to find a new fresh water resource today. The seawaterdesalination, which is a technology to obtain freshwater from the seawater, has beenrecognized as an effective measure to solve the freshwater shortage. However, thehigh energy consumption and high freshwater cost is the main bottleneck to restrictthe extending and application of the desalination technology. With the development oftechnology, the energy consumption of desalination has been greatly reduced, but it isstill not accepted by the public. Therefore, it is great significance to seek methods andtechniques to reduce the energy consumption of desalination.The optimization and design of the seawater desalination and its integrationsystem is investigated here to explore the main factors affecting the energyconsumption of desalination and then to get the techniques and methods to reduce theenergy consumption. The main works and conclusions are as follows:1Modified Genetic AlgorithmGenetic algorithm is an intelligent optimization algorithm imitating thebiological natural selection and genetic mechanisms. The difficulty of using geneticalgorithms to solve optimization problems, especially large-scale optimizationproblems, lies in the encoding of the variables. And it is inconvenient or difficult forsome problem that the binary encoding is adopted to represent the different kinds ofvariables simultaneously. To overcome the weakness, a modified genetic algorithmfeaturing mixed coding, in which the variable type being to code directly, is presented.The different crossover and mutation operators for different kinds of variables areproposed. The PMX crossover and inversion mutation is adopted for the sequencevariables. The direct cross and random mutation is used for an integer variable. Thearithmetic crossover and non-uniform mutation is adopted for continuous variables.The optimization results of an example using the proposed hybrid-coded geneticalgorithm are exactly the same as the literature values, which verifying that theimprovement of genetic algorithm in this paper is feasible and effective.2Optimization of Multi-Stage Flash (MSF)First, the structure of flash stage is analyzed. A single flash unit is decomposed into four compartments: the flash unit, the pre-heater, the steam room and the freshwater room. The mathematical models of MSF is presented and solved by improvedgenetic algorithm. The optimization of an example is performed and compared withthe literature values. The results are as follows:1) The stage number is16, the total heat transfer area is56046.3㎡(includingthe brine heater), and the performance ratio reaches10.7in the given example, whilein the literature, the stage number is21, the total heat transfer area is59008㎡andthe performance ratio is just8.29. It suggests that the mathematical model establishedand the optimization algorithm presented in the paper is feasible and effective.2) The distribution of temperature of fresh water, the flashing brine and thecirculating brine is approximately a straight line along stages in the multi-stage flashsystems. The overall heat transfer coefficient in the brine pre-heater shows a gradualdecline along the stages, while the logarithmic mean temperature difference increasesfirst and then decreases, and the quantity of heat transfer and fresh water productionstep-down.Secondly, the factors influencing the performance parameters of MSF, such asthe top brine temperature, feed temperature, feed concentration and fresh waterproduction, are explored in this paper. The results shown: with the increasing of feedconcentration, the number of flash stage is almost no change, the performance ratiodecreases gradually, and the recycle brine ratio increases slowly. The number of flashstage and performance ratio both increase when the freshwater production increased,but the brine recycle ratio just has a little change, almost a constant. Along with thetop brine temperature increasing, the number of flash stage and brine recycle ratioboth decrease gradually and the higher of the top brine temperature, the slower of thedecreasing. The performance ratio shows an increasing trend, and the higher of the topbrine temperature, the smaller of the increasing trend. As the feed temperatureincreasing, the performance ratio augments gradually and the number of flash stageand recycle brine flow rate are both decreased.3Optimal and Design of Hybrid RO and MSF Desalination PlantThe respective characteristics of the multi-stage flash and reverse osmosissystems, the coupling and advantages of hybrid RO and MSF system are analyzed.The concept of the separation stage, mixed nodes and distribution nodes is proposedhere: each separation stage includes one inlet stream and two outlet streams, mixednode could have multiply inlet streams but only one outlet stream, but distributionnode has only one inlet stream and could have multiply outlet streams. The freshwater cost of MSF and RO performing alone is investigated fordifferent seawater concentration and the results shown: the cost of MSF changessmaller than that of RO when the seawater concentration is increased. The MSFshould be adopted when the seawater concentration is greater than44000mg/L,otherwise RO should be used.Superstructure model of hybrid RO and MSF system is established based on theseparation stage and the concept of water production ratio is proposed as anoptimization variable of the hybrid system. The optimal structure of the integratedsystem and the corresponding operating conditions are obtained by solving the modelusing the improved genetic algorithm. For the given example, the water productionratio of RO with MSF is0.45.4Optimal Design of the Cogeneration for Water and ElectricityThe feasibility of the cogeneration for water and electricity is explored. Adetailed mathematical model of the cogeneration for water and electricity isestablished which is solved by hybrid-coded genetic algorithm. Three operatingstrategies of the integrated system are proposed: only meeting the demand of water,only meeting the demand of electricity and both meeting the demand of water and theelectricity. The results as follows:1) When only meeting the water demand, the optimal pattern of the cogenerationsystem is the integrated of power plant, MSF and RO, in which the power plant usesback pressure steam turbine. There is an optimal value of the production ratio forMSF and RO in the integrated system, and the water cost of the integrated system isless than the independent MSF and RO. The water cost of the integrated system andthe production ratio for MSF and RO decreased slowly with the increasing of waterdemand.2) When only meeting the electricity demand, the optimal pattern of thecogeneration system is the integrated of power plant and MSF, in which the powerplant uses back pressure steam turbine, the water production is decided by the powerand MSF is the first choice as the desalination.3) When simultaneously meeting water and electricity demand, the optimalpattern of the cogeneration system varies along the quantity of water demand: whenthe water demand is smaller, the integrated of power and MSF is adopted, in whichthe extraction turbine is used for the power plant, otherwise, power plant+MSF+ROis the optimal choice, in which back pressure steam turbine is used. In addition, thewater production of MSF is smaller than that of RO when just meeting the water demand, while it is opposite when meeting water and electricity demandsimultaneously.5Scheduling Problem of the Cogeneration SystemFirst, combining the characteristics of the cogeneration for water and electricity,the scheduling model for the cogeneration system is established in which the tank unitbeing introduced. The characteristics of water and electricity load demand areanalyzed. The research objectives and the corresponding time period of the long-term,medium-term and short-term scheduling problem is proposed. The interval timepartition and the time step selection of the medium-term and short-term scheduling isdiscussed.Secondly, the short-term scheduling problem is studied, which the schedulingperiod is one day and is divides into six time intervals. The maximum value of eachinterval is selected as the water and electricity demand. The results indicate that: themodel can obtain a larger income, in which, when the electricity demand is less,produce more water for storage, while in the period of higher demand for electricity,produce more electricity and less water, supplying the shortage of water using thestorage. At the same time, the load fluctuation of the power plant is reduced and theenergy efficiency is improved. The running time and production load of MSF and ROare different in different period, RO runs8hours in a scheduling period in summer orwinter, while12hours in spring or autumn.Finally, the medium-term scheduling problem is investigated with one year as thescheduling period and the season as the time step. The maximum value of eachinterval is selected as the water and electricity demand. The results showed: in ascheduling period, the power load of the cogeneration system could be met at anytime interval. The water production is different in the four scheduling intervals. It isfar greater than the demand in spring and autumn and less in summer and winter, butby adjusting the production load of water and electricity during the scheduling period,the coordination and complementarities of the demand of water and electricity indifferent seasons can be achieved and the fluctuations of the power load is reduced.