The main technologies for reducing flue gas heat loss of pulverized coal-fired boilers are introduced, and the suitability of these technologies for boiler operation and the principles for selection of these technolog...The main technologies for reducing flue gas heat loss of pulverized coal-fired boilers are introduced, and the suitability of these technologies for boiler operation and the principles for selection of these technologies are explored. The main conclusions are： 1） the non-equilibrium control over flue gas flow rates at the inlet of the air heater and the reversal rotation of the air heater rotator should be popularized as regular technologies in large boilers; 2） increasing the area of the air heater to reduce the flue gas heat loss in pulverized coal-fired boilers should be the top option and increasing the area of the economizer be the next choice; 3） low- pressure economizer technology could save energy under special conditions and should be compared with the technology of increasing economizer area in terms of technical economics when the latter is feasible; 4） the hot primary air heater is only suitable to the pnlvefizing system with a large amount of cold air mixed.展开更多
Optimizing operational parameters for syngas production of Texaco coal-water slurry gasifier studied in this paper is a complicated nonlinear constrained problem concerning 3 BP(Error Back Propagation) neural networks...Optimizing operational parameters for syngas production of Texaco coal-water slurry gasifier studied in this paper is a complicated nonlinear constrained problem concerning 3 BP(Error Back Propagation) neural networks. To solve this model, a new 3-layer cultural evolving algorithm framework which has a population space, a medium space and a belief space is firstly conceived. Standard differential evolution algorithm(DE), genetic algorithm(GA), and particle swarm optimization algorithm(PSO) are embedded in this framework to build 3-layer mixed cultural DE/GA/PSO(3LM-CDE, 3LM-CGA, and 3LM-CPSO) algorithms. The accuracy and efficiency of the proposed hybrid algorithms are firstly tested in 20 benchmark nonlinear constrained functions. Then, the operational optimization model for syngas production in a Texaco coal-water slurry gasifier of a real-world chemical plant is solved effectively. The simulation results are encouraging that the 3-layer cultural algorithm evolving framework suggests ways in which the performance of DE, GA, PSO and other population-based evolutionary algorithms(EAs) can be improved,and the optimal operational parameters based on 3LM-CDE algorithm of the syngas production in the Texaco coalwater slurry gasifier shows outstanding computing results than actual industry use and other algorithms.展开更多
文摘The main technologies for reducing flue gas heat loss of pulverized coal-fired boilers are introduced, and the suitability of these technologies for boiler operation and the principles for selection of these technologies are explored. The main conclusions are： 1） the non-equilibrium control over flue gas flow rates at the inlet of the air heater and the reversal rotation of the air heater rotator should be popularized as regular technologies in large boilers; 2） increasing the area of the air heater to reduce the flue gas heat loss in pulverized coal-fired boilers should be the top option and increasing the area of the economizer be the next choice; 3） low- pressure economizer technology could save energy under special conditions and should be compared with the technology of increasing economizer area in terms of technical economics when the latter is feasible; 4） the hot primary air heater is only suitable to the pnlvefizing system with a large amount of cold air mixed.
基金Supported by the National Natural Science Foundation of China(61174040,U1162110,21206174)Shanghai Commission of Nature Science(12ZR1408100)
文摘Optimizing operational parameters for syngas production of Texaco coal-water slurry gasifier studied in this paper is a complicated nonlinear constrained problem concerning 3 BP(Error Back Propagation) neural networks. To solve this model, a new 3-layer cultural evolving algorithm framework which has a population space, a medium space and a belief space is firstly conceived. Standard differential evolution algorithm(DE), genetic algorithm(GA), and particle swarm optimization algorithm(PSO) are embedded in this framework to build 3-layer mixed cultural DE/GA/PSO(3LM-CDE, 3LM-CGA, and 3LM-CPSO) algorithms. The accuracy and efficiency of the proposed hybrid algorithms are firstly tested in 20 benchmark nonlinear constrained functions. Then, the operational optimization model for syngas production in a Texaco coal-water slurry gasifier of a real-world chemical plant is solved effectively. The simulation results are encouraging that the 3-layer cultural algorithm evolving framework suggests ways in which the performance of DE, GA, PSO and other population-based evolutionary algorithms(EAs) can be improved,and the optimal operational parameters based on 3LM-CDE algorithm of the syngas production in the Texaco coalwater slurry gasifier shows outstanding computing results than actual industry use and other algorithms.
