The comprehensive optimization of thermodynamic and economic performances is significant for the engineering application of ocean thermal energy conversion(OTEC).Motivated by this,this paper develops a thermo-economic...The comprehensive optimization of thermodynamic and economic performances is significant for the engineering application of ocean thermal energy conversion(OTEC).Motivated by this,this paper develops a thermo-economic OTEC model and conducts a sensitivity analysis of the OTEC system concerning its thermodynamic and economic performances.Specifically,the impact of warm-seawater temperature and cold-seawater pumping depth on the net thermal efficiency and the total investment cost are investigated.The results indicate that,an increase in warm-seawater temperature and cold-seawater pumping depth can improve the net thermal efficiency and a higher installed capacity is beneficial to the system economics.Building on these,a design optimization method with considering the on-design and off-design conditions is proposed in this paper,and the dynamic variation of warm-seawater temperature are considered in this method.In multi-objective optimization procedure,with the objective functions being the average net thermal efficiency and unit power cost within the operational cycle,the non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ) is employed to maximize the net thermal efficiency and minimize the unit power investment cost,resulting in the Pareto front.The net thermal efficiencies of OTEC systems using ammonia and R245fa as working fluids are 4.13% and 3.8%,respectively.This represents an improvement of 19.4% and 57.0%,respectively,compared to traditional optimization methods that do not account for off-design conditions.展开更多
In model-based climate sensitivity studies, model errors may grow during continuous long-term inte- grations in both the ＂reference＂ and ＂perturbed＂ states and hence the climate sensitivity （defined as the differ...In model-based climate sensitivity studies, model errors may grow during continuous long-term inte- grations in both the ＂reference＂ and ＂perturbed＂ states and hence the climate sensitivity （defined as the difference between the two states）. To reduce the errors, we propose a piecewise modeling approach that splits the continuous long-term simulation into subintervals of sequential short-term simulations, and updates the modeled states through re-initialization at the end of each subinterval. In the re-initialization processes, this approach updates the reference state with analysis data and updates the perturbed states with the sum of analysis data and the difference between the perturbed and the reference states, thereby improving the credibility of the modeled climate sensitivity. We conducted a series of experiments with a shallow-water model to evaluate the advantages of the piecewise approach over the conventional continuous modeling approach. We then investigated the impacts of analysis data error and subinterval length used in the piecewise approach on the simulations of the reference and perturbed states as well as the resulting climate sensitivity. The experiments show that the piecewise approach reduces the errors produced by the conventional continuous modeling approach, more effectively when the analysis data error becomes smaller and the subinterval length is shorter. In addition, we employed a nudging assimilation technique to solve possible spin-up problems caused by re-initializations by using analysis data that contain inconsistent errors between mass and velocity. The nudging technique can effectively diminish the spin-up problem, resulting in a higher modeling skill.展开更多
An optimal tracking control （OTC） problem for linear time-delay large-scale systems affected by external persistent disturbances is investigated. Based on the internal model principle, a disturbance compensator is c...An optimal tracking control （OTC） problem for linear time-delay large-scale systems affected by external persistent disturbances is investigated. Based on the internal model principle, a disturbance compensator is constructed. The system with persistent disturbances is transformed into an augmented system without persistent disturbances. The original OTC problem of linear time-delay system is transformed into a sequence of linear two- point boundary value （TPBV） problems by introducing a sensitivity parameter and expanding Maclaurin series around it. By solving an OTC law of the augmented system, the OTC law of the original system is obtained. A numerical simulation is provided to illustrate the effectiveness of the proposed method.展开更多
This paper studies the optimal control with zero steady-state error problem for nonlinear large-scale systems affected by external persistent disturbances.The nonlinear large-scale system is transformed into N nonline...This paper studies the optimal control with zero steady-state error problem for nonlinear large-scale systems affected by external persistent disturbances.The nonlinear large-scale system is transformed into N nonlinear subsystems with interconnect terms.Based on the internal model principle,a disturbance compensator is constructed such that the ith subsystem with external persistent disturbances is transformed into an augmented subsystem without disturbances.According to the sensitivity approach,the optimal tracking control law for the ith nonlinear subsystem can be obtained.The optimal tracking control law for the nonlinear large-scale systems can be obtained.A numerical simulation shows that the method is effective.展开更多
Within the framework of building energy assessment,this article proposes to use a derivative based sensitivity analysis of heat transfer models in a building envelope.Two,global and local,estimators are obtained at lo...Within the framework of building energy assessment,this article proposes to use a derivative based sensitivity analysis of heat transfer models in a building envelope.Two,global and local,estimators are obtained at low computational cost,to evaluate the influence of the parameters on the model outputs.Ranking of these estimators values allows to reduce the number of model unknown parameters by excluding non-significant parameters.A comparison with variance and regression-based methods is carried out and the results highlight the satisfactory accuracy of the continuous-based approach.Moreover,for the carried investigations the approach is 100 times faster compared to the variance-based methods.A case study applies the method to a real-world building wall.The sensitivity of the thermal loads to local or global variations of the wall thermal properties is investigated.Additionally,a case study of wall with window is analyzed.展开更多
基金supported by National Key R&D Program of China(No.2019YFB1504301).
文摘The comprehensive optimization of thermodynamic and economic performances is significant for the engineering application of ocean thermal energy conversion(OTEC).Motivated by this,this paper develops a thermo-economic OTEC model and conducts a sensitivity analysis of the OTEC system concerning its thermodynamic and economic performances.Specifically,the impact of warm-seawater temperature and cold-seawater pumping depth on the net thermal efficiency and the total investment cost are investigated.The results indicate that,an increase in warm-seawater temperature and cold-seawater pumping depth can improve the net thermal efficiency and a higher installed capacity is beneficial to the system economics.Building on these,a design optimization method with considering the on-design and off-design conditions is proposed in this paper,and the dynamic variation of warm-seawater temperature are considered in this method.In multi-objective optimization procedure,with the objective functions being the average net thermal efficiency and unit power cost within the operational cycle,the non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ) is employed to maximize the net thermal efficiency and minimize the unit power investment cost,resulting in the Pareto front.The net thermal efficiencies of OTEC systems using ammonia and R245fa as working fluids are 4.13% and 3.8%,respectively.This represents an improvement of 19.4% and 57.0%,respectively,compared to traditional optimization methods that do not account for off-design conditions.
基金Supported by the National Natural Science Foundation of China(41330527 and 41275102)Fundamental Research Funds for the Central Universities(lzujbky-2013-k16)Program for New Century Excellent Talents in Universities(NCET-11-0213)
文摘In model-based climate sensitivity studies, model errors may grow during continuous long-term inte- grations in both the ＂reference＂ and ＂perturbed＂ states and hence the climate sensitivity （defined as the difference between the two states）. To reduce the errors, we propose a piecewise modeling approach that splits the continuous long-term simulation into subintervals of sequential short-term simulations, and updates the modeled states through re-initialization at the end of each subinterval. In the re-initialization processes, this approach updates the reference state with analysis data and updates the perturbed states with the sum of analysis data and the difference between the perturbed and the reference states, thereby improving the credibility of the modeled climate sensitivity. We conducted a series of experiments with a shallow-water model to evaluate the advantages of the piecewise approach over the conventional continuous modeling approach. We then investigated the impacts of analysis data error and subinterval length used in the piecewise approach on the simulations of the reference and perturbed states as well as the resulting climate sensitivity. The experiments show that the piecewise approach reduces the errors produced by the conventional continuous modeling approach, more effectively when the analysis data error becomes smaller and the subinterval length is shorter. In addition, we employed a nudging assimilation technique to solve possible spin-up problems caused by re-initializations by using analysis data that contain inconsistent errors between mass and velocity. The nudging technique can effectively diminish the spin-up problem, resulting in a higher modeling skill.
基金supported by the National Natural Science Foundation of China(60574023)the Natural Science Foundation of Shandong Province(Z2005G01).
文摘An optimal tracking control （OTC） problem for linear time-delay large-scale systems affected by external persistent disturbances is investigated. Based on the internal model principle, a disturbance compensator is constructed. The system with persistent disturbances is transformed into an augmented system without persistent disturbances. The original OTC problem of linear time-delay system is transformed into a sequence of linear two- point boundary value （TPBV） problems by introducing a sensitivity parameter and expanding Maclaurin series around it. By solving an OTC law of the augmented system, the OTC law of the original system is obtained. A numerical simulation is provided to illustrate the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(No.60574023)the Natural Science Foundation of Shandong Province(No.Z2005G01)
文摘This paper studies the optimal control with zero steady-state error problem for nonlinear large-scale systems affected by external persistent disturbances.The nonlinear large-scale system is transformed into N nonlinear subsystems with interconnect terms.Based on the internal model principle,a disturbance compensator is constructed such that the ith subsystem with external persistent disturbances is transformed into an augmented subsystem without disturbances.According to the sensitivity approach,the optimal tracking control law for the ith nonlinear subsystem can be obtained.The optimal tracking control law for the nonlinear large-scale systems can be obtained.A numerical simulation shows that the method is effective.
文摘Within the framework of building energy assessment,this article proposes to use a derivative based sensitivity analysis of heat transfer models in a building envelope.Two,global and local,estimators are obtained at low computational cost,to evaluate the influence of the parameters on the model outputs.Ranking of these estimators values allows to reduce the number of model unknown parameters by excluding non-significant parameters.A comparison with variance and regression-based methods is carried out and the results highlight the satisfactory accuracy of the continuous-based approach.Moreover,for the carried investigations the approach is 100 times faster compared to the variance-based methods.A case study applies the method to a real-world building wall.The sensitivity of the thermal loads to local or global variations of the wall thermal properties is investigated.Additionally,a case study of wall with window is analyzed.
