Taking geothermal heat as the heat source, KCS⁃11, KCS⁃34 and KSG⁃1 as the bottom cycles respectively, the thermodynamic and thermoeconomic performance of three systems combining flash⁃Kalina cycle and absorption refrigeration cycle (F⁃KCS11⁃ARC, F⁃KCS34⁃ARC, F⁃KSG1⁃ARC) were compared and analyzed. The results show that the total exergy loss of the F⁃KCS11⁃ARC system is 5.3% and 2.7% lower than that of the F⁃KCS34⁃ARC system and the F⁃KSG1⁃ARC system,respectively,and the component with the largest exergy loss is the heat exchanger 1. The F⁃KCS34⁃ARC system has the highest thermal efficiency, but the F⁃KCS11⁃ARC system has the highest heat recovery efficiency when the geothermal source temperature is in the range of 155～220 °C, and the smaller geothermal source temperature and flash pressure can make the system obtain higher heat recovery efficiency.Thermal economic analysis shows that pump 1 is the most expensive component in all three systems, the next is steam turbine 2. The F⁃KCS11⁃ARC system has the lowest cost, the highest annual net income, and the smallest investment recovery period, with values of 2.09×106 $, 6.61×105 $ and 3.72 years, respectively.

With the rapid advancement of ecological civilization construction in China, energy utilization methods such as recycling industrial waste heat and developing clean energy have gradually received widespread attention in the market. In this paper, a dual⁃loop cycle⁃kalina (DORC⁃KC) cogeneration system based on LNG cold energy utilization was designed. In addition, a new method for reducing acid gas emissions from industrial waste heat was proposed. Through the construction of the system thermodynamic model, the key thermodynamic parameters affecting the system carbon capture were analyzed in detail. The results show that the top cycle in the double cycle uses cyclopentane as the working fluid. By increasing the evaporation temperature and evaporation pressure, the maximum net output of the system is 367.9 kW,and the thermal efficiency is 33.29%. In the Kalina cycle, factors such as flux and concentration have a positive impact on system efficiency. The optimal thermal efficiency is 15.42% and the cold energy recovery efficiency is 20.65%. The reduction in compression pressure reduces the amount of circulating water but increase the quantity of the liquefaction of CO2. When the compression pressure is 472 kPa, the system has the highest exergy efficiency of 34.30%, carbon capture rate of 47.00%, and the amount of recycled water recovered is 167 616 t.

The intensification of the greenhouse effect has led to a gradual increase in people's awareness of carbon capture. Aiming at the carbon capture problem, combining the CO ₂ supercritical Rankine cycle with the organic Rankine cycle, the original gas turbine exhaust gas power generation system was improved,an LNG cold energy cascade utilization system combining exhaust gas power generation and CO ₂ capture was proposed. The thermodynamic simulation of the system was carried out using Aspen Plus software, the effects of evaporation pressure and evaporation temperature on the thermodynamic performance of the system were analyzed in detail. The results show that the increasing of the evaporation pressure and evaporation temperature of the CO ₂ supercritical Rankine cycle have a positive effect on the net output power and thermal efficiency of the system. After the evaporation temperature of the organic Rankine cycle reaches 250 ℃, the waste heat recovery rate reaches the maximum value and no longer changes with evaporation pressure. The net output power of the system can reach 251.6 kW, the recovery rate of waste heat is 92.00% and the exergy efficiency is 57.00%.The amount of CO ₂ liquefaction can reach 883.6 kg/h, which is equivalent to reducing CO ₂ emissions by 7.63 million tons per year, and is of great significance to environmental protection.

Aiming at the serious pollution caused by burning of the fossil fuel, to increase the proportion of clean energy in primary energy consumption in China, a new Organic Rankine Cycle system utilizing the solar energy and the cold energy of liquefied natural gas (LNG) was constructed to solve the problem of serious environmental pollution caused by fossil fuel combustion. The results showed that: the optimal net output power and thermal efficiency were obtained when the two cycle take the best evaporation pressure 2.8 MPa and the best evaporation temperature 371 K, the values are 81.46 kW and 20.88% respectively; when the evaporation pressure of two cycle is 3.0 MPa and the evaporation temperature is 371 K, the exergetic efficiency reaches the peak value 53.43%; the maximum exergy loss of the system is in the heat exchanger components, the exergy efficiency of solar collector is lower. According to 90% power generation efficiency and 1 yuan/(kW·h) electricity price, the system can bring economic benefits of more than RMB 530 000 per year. Compared with the same coal⁃fired power generation, it has the effect of SO2 emissions by 13 939 kg/a and CO2 emissions by 462 000 kg/a, which can achieve the effect of energy saving and emission reduction.

With the continuous development of gas transmission pipeline technology, application of computer simulation technology in the gas pipeline network is also increasing. The simulation model combined with the computer, can be effectively applied to the actual production, the true performance of the gas flow rule of gas in transmission line to ensure that natural gas pipeline reasonable optimization operation. Based on a comprehensive, systematic study of TGNET, SPS and other software ,useing the equation MBWRS equation of state the most accurate current gas properties calculation, and the fourth order RungeKutta method to solve the gas pipe network steady flow differential equations. And by means of C# software, combined with the advantages of related software, give full consideration to the initial and boundary conditions as well as the gas pipeline JouleThomson effect, etc. The simulation software is developed, and it's more suitable for compressors, pipes, valves, gas and other components of the source of arbitrary network. Compared with the TGNET software, the calculate results are reliable,and can be used as the initial value of the unsteady flow simulation,which has higher engineering application value.

Natural gas hydrate was becoming more and more important in Chinese energy structure, which had the advantages of high gas content, low pollution and large reserves. Therefore, it was necessary to study natural gas hydrate. Aiming at the common blockage problem in transmission pipeline for natural gas hydrate, on the background of subsea level pipelines and based on the multiphase flow model, the calculating and analyzing natural gas hydrate mathematical model was established in gassolid two phase flow based on finite volume method. And the relationship was obtained between the difference of the diameter (the diameter of the pipe and the through-flow diameter) and the distance from inlet. When the inlet flow velocity and the diameter of the pipe were fixed, the stack position of the gas hydrate in the pipeline was analyzed with the difference of the diameter. Calculation results showed that with the other conditions remaining unchanged, as the increase of the distance from the pipe inlet, the change rule of the difference of the diameter was in accord with Gauss curve. Then the change rule was fitted and Gauss function equation was obtained, which could calculate the difference of diameter under a given position of pipe. Finally, through changing the diameter size of pipeline, the simulation and analysis were carried out, whose results showed that Gauss function equation also applied in pipelines with different diameters. A theoretical basis for predicting the stack position was provided in the pipeline and improving the transport efficiency of natural gas hydrate.

      Long-term natural gas load forecasting can solve the problem of the imbalance between supply and demand of city gas and provide assistance for the city gas company's management and running. In order to improve the accuracy of predicting the longterm natural gas load，a forecasting model of natural gas longterm load was built based on SVM-GA(Support Vector MachinesGenetic Algorithm). The relevant factors influencing natural gas consumption was analyzed and determined. In order to improve prediction accuracy， the penalty factor c and the kernel parameter g of support vector machines were optimized using genetic algorithm and cross validation methods. Optimized parameters were inputted support vector machines model and long-term natural gas load forecasting was made. In a case study from a certain city，a comparative analysis was made of the forecasting results among SVM-GA，SVM and crossvalidation method combined prediction model and BP(Back Propagation) neural networks. The forecasting model based on SVM-GA was validated with a high prediction accuracy and the resulted relative mean square error，normalization mean square error，normalization absolute square error，normalization rootmean square error， maximum absolute error resulted from the SVM-GA were lower than those from SVM and crossvalidation method combined prediction model or BP neural networks by 0.58%，3.98%，2.99%，4.58%，8.64% and 6.13%，26.28%，19.71%，21.09%，31.48%. Therefore，the support vector machine and genetic algorithm combined model can accurately predict the long-term natural gas load.