Energy management optimization of open-pit mine solar photothermal-photoelectric membrane distillation using a support vector machine and a non-dominated genetic algorithm
AffiliationXi'an University of Architecture and Technology
Hong Kong University of Science and Technology
University of Bedfordshire
Northeastern State University
Subjectsenvironmental technology portfolio
environmental management practices
Subject Categories::F851 Applied Environmental Sciences
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AbstractAs a distributed energy source, open-pit mine solar photothermal-photoelectric membrane distillation can convert solar energy into heat and electrical energy to provide power for membrane distillation water purification system. In mine sewage treatment, the solar membrane distillation system has the advantages of high desalination rate, good water quality and low cost. However, this system has not been widely promoted and applied because of its high energy consumption and low membrane flux. Different operating parameters have a greater impact on the operating efficiency of the solar membrane distillation system. In this study, a natural cooling film distillation system was built, and the response surface method was used to analyze it, and a multi-objective optimization algorithm was used to optimize the operating conditions and improve the energy efficiency of the system. In our experiment, the hot end feed temperature, hot end feed flow rate, cold end cooling water flow rate, and membrane area were used as variables, and the membrane flux, thermal efficiency, and energy consumption values were investigated as target values. We used a support vector machine (SVM) with improved fitting, and substituted the fitting rediction model into the response surface method for the relationship between the variable and the target value collaborative analysis was followed by substituting the model into a non-dominated sorting genetic algorithm-II (NSGA-II). After the optimization operation, the optimal working conditions were obtained to improve the operating efficiency of the solar membrane distillation system, which will enable open-pit mine prosumers to realize intelligent management of solar energy generation, storage and consumption simultaneously.
CitationZhang S, Lu C, Jiang S, Lu S, Crabbe MJC, Xiong N (2020) 'Energy management optimization of open-pit mine solar photothermal-photoelectric membrane distillation using a support vector machine and a non-dominated genetic algorithm', IEEE Access, 8, pp.155766 -155782.
SponsorsThis work was supported in part by the Natural Science Foundation of China, title: “Research on Intelligent Fusion and situation assessment of multi-source heterogeneous flow data of rock failure in underground metal mines”, under Grant 51974223, title: “Research on 5D refined mining production scheduling model and collaborative optimization method in metal open pit under constraints of Grade-Price-Cost”, under Grant 51774228, and title: “Experimental theory and method of time-varying calculation for fully mechanized mining process under artificial system environment in Yushen mining area”, under Grant 51864046, and in part by the Natural Science Foundation of Shaanxi Province, title: “Research and development of key technologies for intelligent production control and intelligent decision-making of open pit coal mine under cloud service”, under Grant 2019JLP-16, title: “Integrated intelligent scheduling model of driverless multi vehicle cooperation in metal open pit under time and space road conditions”, unde
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