The design and building of new alternative fuel plants is an increasing necessity to replace old technology and non-renewable fossil fuels. To optimize the performance of these plants and to obtain an economically fea...The design and building of new alternative fuel plants is an increasing necessity to replace old technology and non-renewable fossil fuels. To optimize the performance of these plants and to obtain an economically feasible production of these types of fuels, it is necessary to have a total control of each variable involved in the process of production and how these factors affect the yield of fuel production. In this paper it is proposed a model of a digester to generate gas using a Vensim software designed to generate simulations in dynamic state. This simulation was developed using differential equations to model the behavior at each stage of the process and auxiliary conditions to complement the mathematical description of the model. The main factors in the biogas production are the retention time and the methanogen mortality ratio. For retention time lower than 10 h the process loses effectiveness due to bacterial growth is not completed efficiently, but a high retention time involves a bigger reactor and the yield of production decreases considerably for retention time higher than 40 h. The best yields were obtained for a mortality ratio in methanogen and acidogenic bacteria lower than 0.2 and a retention time of 30 h with a final production of 3.33 L by each kilogram of biomass.展开更多
The numerical solution of the differential-algebraic equations(DAEs) involved in time domain simulation(TDS) of power systems requires the solution of a sequence of large scale and sparse linear systems.The use of ite...The numerical solution of the differential-algebraic equations(DAEs) involved in time domain simulation(TDS) of power systems requires the solution of a sequence of large scale and sparse linear systems.The use of iterative methods such as the Krylov subspace method is imperative for the solution of these large and sparse linear systems.The motivation of the present work is to develop a new algorithm to efficiently precondition the whole sequence of linear systems involved in TDS.As an improvement of dishonest preconditioner(DP) strategy,updating preconditioner strategy(UP) is introduced to the field of TDS for the first time.The idea of updating preconditioner strategy is based on the fact that the matrices in sequence of the linearized systems are continuous and there is only a slight difference between two consecutive matrices.In order to make the linear system sequence in TDS suitable for UP strategy,a matrix transformation is applied to form a new linear sequence with a good shape for preconditioner updating.The algorithm proposed in this paper has been tested with 4 cases from real-life power systems in China.Results show that the proposed UP algorithm efficiently preconditions the sequence of linear systems and reduces 9%-61% the iteration count of the GMRES when compared with the DP method in all test cases.Numerical experiments also show the effectiveness of UP when combined with simple preconditioner reconstruction strategies.展开更多
文摘The design and building of new alternative fuel plants is an increasing necessity to replace old technology and non-renewable fossil fuels. To optimize the performance of these plants and to obtain an economically feasible production of these types of fuels, it is necessary to have a total control of each variable involved in the process of production and how these factors affect the yield of fuel production. In this paper it is proposed a model of a digester to generate gas using a Vensim software designed to generate simulations in dynamic state. This simulation was developed using differential equations to model the behavior at each stage of the process and auxiliary conditions to complement the mathematical description of the model. The main factors in the biogas production are the retention time and the methanogen mortality ratio. For retention time lower than 10 h the process loses effectiveness due to bacterial growth is not completed efficiently, but a high retention time involves a bigger reactor and the yield of production decreases considerably for retention time higher than 40 h. The best yields were obtained for a mortality ratio in methanogen and acidogenic bacteria lower than 0.2 and a retention time of 30 h with a final production of 3.33 L by each kilogram of biomass.
基金supported by the National Natural Science Foundation of China (Grant Nos. 60703055 and 60803019)the National High-Tech Research & Development Program of China ("863" Program) (Grant No. 2009AA01A129)+1 种基金State Key Development Program of Basic Research of China (Grant No. 2010CB951903)Tsinghua National Laboratory for Information Science and Technology (THList) Cross-discipline Foundation
文摘The numerical solution of the differential-algebraic equations(DAEs) involved in time domain simulation(TDS) of power systems requires the solution of a sequence of large scale and sparse linear systems.The use of iterative methods such as the Krylov subspace method is imperative for the solution of these large and sparse linear systems.The motivation of the present work is to develop a new algorithm to efficiently precondition the whole sequence of linear systems involved in TDS.As an improvement of dishonest preconditioner(DP) strategy,updating preconditioner strategy(UP) is introduced to the field of TDS for the first time.The idea of updating preconditioner strategy is based on the fact that the matrices in sequence of the linearized systems are continuous and there is only a slight difference between two consecutive matrices.In order to make the linear system sequence in TDS suitable for UP strategy,a matrix transformation is applied to form a new linear sequence with a good shape for preconditioner updating.The algorithm proposed in this paper has been tested with 4 cases from real-life power systems in China.Results show that the proposed UP algorithm efficiently preconditions the sequence of linear systems and reduces 9%-61% the iteration count of the GMRES when compared with the DP method in all test cases.Numerical experiments also show the effectiveness of UP when combined with simple preconditioner reconstruction strategies.
