Oxygen consumption is an important index of coal oxidation.In order to explore the coal-oxygen reaction,we developed an experimental system of coal spontaneous combustion and tested oxygen consumption of differently r...Oxygen consumption is an important index of coal oxidation.In order to explore the coal-oxygen reaction,we developed an experimental system of coal spontaneous combustion and tested oxygen consumption of differently ranked coals at programmed temperatures.The size of coal samples ranged from 0.18~0.42 mm and the system heat-rate was 0.8℃/min.The results show that, for high ranked coals,oxygen consumption rises with coal temperature as a piecewise non-linear process.The critical coal temperature is about 50℃.Below this temperature,oxygen consumption decreases with rising coal temperatures and reached a minimum at 50℃,approximately.Subsequently,it begins to increase and the rate of growth clearly increased with temperature.For low ranked coals,this characteristic is inconspicuous or even non-existent.The difference in oxygen consumption at the same temperatures varies for differently ranked coals.The results show the difference in oxygen consumption of the coals tested in our study reached 78.6%at 100℃.Based on the theory of coal-oxygen reaction,these phenomena were analyzed from the point of view of physical and chemical characteristics,as well as the appearance of the coal-oxygen complex.From theoretical analyses and our experiments,we conclude that the oxygen consumption at programmed temperatures reflects the oxidation ability of coals perfectly.展开更多
Oil and gas pipeline networks are a key link in the coordinated development of oil and gas both upstream and downstream.To improve the reliability and safety of the oil and gas pipeline network, inspections are implem...Oil and gas pipeline networks are a key link in the coordinated development of oil and gas both upstream and downstream.To improve the reliability and safety of the oil and gas pipeline network, inspections are implemented to minimize the risk of leakage, spill and theft, as well as documenting actual incidents. In recent years, unmanned aerial vehicles have been recognized as a promising option for inspection due to their high efficiency. However, the integrated optimization of unmanned aerial vehicle inspection for oil and gas pipeline networks, including physical feasibility, the performance of mission, cooperation, real-time implementation and three-dimensional(3-D) space, is a strategic problem due to its large-scale,complexity as well as the need for efficiency. In this work, a novel mixed-integer nonlinear programming model is proposed that takes into account the constraints of the mission scenario and the safety performance of unmanned aerial vehicles. To minimize the total length of the inspection path, the model is solved by a two-stage solution method. Finally, a virtual pipeline network and a practical pipeline network are set as two examples to demonstrate the performance of the optimization schemes. Moreover, compared with the traditional genetic algorithm and simulated annealing algorithm, the self-adaptive genetic simulated annealing algorithm proposed in this paper provides strong stability.展开更多
In this paper, a new class of three term memory gradient method with non-monotone line search technique for unconstrained optimization is presented. Global convergence properties of the new methods are discussed. Comb...In this paper, a new class of three term memory gradient method with non-monotone line search technique for unconstrained optimization is presented. Global convergence properties of the new methods are discussed. Combining the quasi-Newton method with the new method, the former is modified to have global convergence property. Numerical results show that the new algorithm is efficient.展开更多
Refineries often need to find similar crude oil to replace the scarce crude oil for stabilizing the feedstock property. We introduced the method for calculation of crude blended properties firstly, and then created a ...Refineries often need to find similar crude oil to replace the scarce crude oil for stabilizing the feedstock property. We introduced the method for calculation of crude blended properties firstly, and then created a crude oil selection and blending optimization model based on the data of crude oil property. The model is a mixed-integer nonlinear programming(MINLP) with constraints, and the target is to maximize the similarity between the blended crude oil and the objective crude oil. Furthermore, the model takes into account the selection of crude oils and their blending ratios simultaneously, and transforms the problem of looking for similar crude oil into the crude oil selection and blending optimization problem. We applied the Improved Cuckoo Search(ICS) algorithm to solving the model. Through the simulations, ICS was compared with the genetic algorithm, the particle swarm optimization algorithm and the CPLEX solver. The results show that ICS has very good optimization efficiency. The blending solution can provide a reference for refineries to find the similar crude oil. And the method proposed can also give some references to selection and blending optimization of other materials.展开更多
The renewable portfolio standard has been promoted in parallel with the reform of the electricity market,and the flexibility requirement of the power system has rapidly increased.To promote renewable energy consumptio...The renewable portfolio standard has been promoted in parallel with the reform of the electricity market,and the flexibility requirement of the power system has rapidly increased.To promote renewable energy consumption and improve power system flexibility,a bi-level optimal operation model of the electricity market is proposed.A probabilistic model of the flexibility requirement is established,considering the correlation between wind power,photovoltaic power,and load.A bi-level optimization model is established for the multi-markets;the upper and lower models represent the intra-provincial market and inter-provincial market models,respectively.To efficiently solve the model,it is transformed into a mixed-integer linear programming model using the Karush–Kuhn–Tucker condition and Lagrangian duality theory.The economy and flexibility of the model are verified using a provincial power grid as an example.展开更多
Oil depots along products pipelines are important components of the pipeline transportation system and down-stream markets.The operating costs of oil depots account for a large proportion of the total system’s operat...Oil depots along products pipelines are important components of the pipeline transportation system and down-stream markets.The operating costs of oil depots account for a large proportion of the total system’s operating costs.Meanwhile,oil depots and pipelines form an entire system,and each operation in a single oil depot may have influence on others.It is a tough job to make a scheduling plan when considering the factors of delivering contaminated oil and batches migration.So far,studies simultaneously considering operating constraints and contaminated oil issues are rare.Aiming at making a scheduling plan with the lowest operating costs,the paper establishes a mixed-integer linear programming model,considering a sequence of operations,such as delivery, export, blending,fractionating and exchanging operations,and batch property differences of the same oil as well as influence of batch migration on contaminated volume.Moreover,the paper verifies the linear relationship between oil concentration and blending capability by mathematical deduction.Finally,the model is successfully applied to one of the product pipelines in China and proved to be practical.展开更多
In contrast to most existing works on robust unit commitment(UC),this study proposes a novel big-M-based mixed-integer linear programming(MILP)method to solve security-constrained UC problems considering the allowable...In contrast to most existing works on robust unit commitment(UC),this study proposes a novel big-M-based mixed-integer linear programming(MILP)method to solve security-constrained UC problems considering the allowable wind power output interval and its adjustable conservativeness.The wind power accommodation capability is usually limited by spinning reserve requirements and transmission line capacity in power systems with large-scale wind power integration.Therefore,by employing the big-M method and adding auxiliary 0-1 binary variables to describe the allowable wind power output interval,a bilinear programming problem meeting the security constraints of system operation is presented.Furthermore,an adjustable confidence level was introduced into the proposed robust optimization model to decrease the level of conservatism of the robust solutions.This can establish a trade-off between economy and security.To develop an MILP problem that can be solved by commercial solvers such as CPLEX,the big-M method is utilized again to represent the bilinear formulation as a series of linear inequality constraints and approximately address the nonlinear formulation caused by the adjustable conservativeness.Simulation studies on a modified IEEE 26-generator reliability test system connected to wind farms were performed to confirm the effectiveness and advantages of the proposed method.展开更多
This paper reviews alternative market equilibrium models for policy analysis. The origin of spatial equilibrium models and their application to wood and wood-processing industries are described. Three mathematical pro...This paper reviews alternative market equilibrium models for policy analysis. The origin of spatial equilibrium models and their application to wood and wood-processing industries are described. Three mathematical programming models commonly applied to solve spatial problems - namely linear programming, non-linear programming and mixed complementary programming - are reviewed in terms of forms of objective functions and constraint equalities and inequalities. These programming are illustrated with numerical examples. Linear programming is only applied in transportation problems to solve quantities trans, ported between regions when quantities supplied and demanded in each region are already known. It is argued that linear programming can be applied in broader context to transportation problems where supply and demand quantities are unknown and are linear. In this context, linear programming is seen as a more convenient method for modelers because it has a simpler objective function and does not require as strict conditions, for instance the equal numbers of variables and equations required in mixed complementary programming. Finally, some critical insights are provided on the interpretation of optimal solutions generated by solving spatial equilibrium models.展开更多
The superstructure optimization of biomass to biomethane system through digestion is conducted in this work. The system encompasses biofeedstock collection and transportation, anaerobic digestion, biogas upgrading, an...The superstructure optimization of biomass to biomethane system through digestion is conducted in this work. The system encompasses biofeedstock collection and transportation, anaerobic digestion, biogas upgrading, and digestate recycling. We propose a multicriteria mixed integer nonlinear programming(MINLP) model that seeks to minimize the energy consumption and maximize the green degree and the biomethane production constrained by technology selection, mass balance, energy balance, and environmental impact. A multi-objective MINLP model is proposed and solved with a fast nondominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ). The resulting Pareto-optimal surface reveals the trade-off among the conflicting objectives. The optimal results indicate quantitatively that higher green degree and biomethane production objectives can be obtained at the expense of destroying the performance of the energy consumption objective.展开更多
基金Financial support for this research from the National Natural Science Foundation of China(Nos. 50674088 and 50927403)
文摘Oxygen consumption is an important index of coal oxidation.In order to explore the coal-oxygen reaction,we developed an experimental system of coal spontaneous combustion and tested oxygen consumption of differently ranked coals at programmed temperatures.The size of coal samples ranged from 0.18~0.42 mm and the system heat-rate was 0.8℃/min.The results show that, for high ranked coals,oxygen consumption rises with coal temperature as a piecewise non-linear process.The critical coal temperature is about 50℃.Below this temperature,oxygen consumption decreases with rising coal temperatures and reached a minimum at 50℃,approximately.Subsequently,it begins to increase and the rate of growth clearly increased with temperature.For low ranked coals,this characteristic is inconspicuous or even non-existent.The difference in oxygen consumption at the same temperatures varies for differently ranked coals.The results show the difference in oxygen consumption of the coals tested in our study reached 78.6%at 100℃.Based on the theory of coal-oxygen reaction,these phenomena were analyzed from the point of view of physical and chemical characteristics,as well as the appearance of the coal-oxygen complex.From theoretical analyses and our experiments,we conclude that the oxygen consumption at programmed temperatures reflects the oxidation ability of coals perfectly.
基金part of the Program of "Study on Optimization and Supply-side Reliability of Oil Product Supply Chain Logistics System" funded under the National Natural Science Foundation of China, Grant Number 51874325
文摘Oil and gas pipeline networks are a key link in the coordinated development of oil and gas both upstream and downstream.To improve the reliability and safety of the oil and gas pipeline network, inspections are implemented to minimize the risk of leakage, spill and theft, as well as documenting actual incidents. In recent years, unmanned aerial vehicles have been recognized as a promising option for inspection due to their high efficiency. However, the integrated optimization of unmanned aerial vehicle inspection for oil and gas pipeline networks, including physical feasibility, the performance of mission, cooperation, real-time implementation and three-dimensional(3-D) space, is a strategic problem due to its large-scale,complexity as well as the need for efficiency. In this work, a novel mixed-integer nonlinear programming model is proposed that takes into account the constraints of the mission scenario and the safety performance of unmanned aerial vehicles. To minimize the total length of the inspection path, the model is solved by a two-stage solution method. Finally, a virtual pipeline network and a practical pipeline network are set as two examples to demonstrate the performance of the optimization schemes. Moreover, compared with the traditional genetic algorithm and simulated annealing algorithm, the self-adaptive genetic simulated annealing algorithm proposed in this paper provides strong stability.
文摘In this paper, a new class of three term memory gradient method with non-monotone line search technique for unconstrained optimization is presented. Global convergence properties of the new methods are discussed. Combining the quasi-Newton method with the new method, the former is modified to have global convergence property. Numerical results show that the new algorithm is efficient.
基金supported by the National Natural Science Foundation of China(No.21365008)the Science Foundation of Guangxi province of China(No.2012GXNSFAA053230)
文摘Refineries often need to find similar crude oil to replace the scarce crude oil for stabilizing the feedstock property. We introduced the method for calculation of crude blended properties firstly, and then created a crude oil selection and blending optimization model based on the data of crude oil property. The model is a mixed-integer nonlinear programming(MINLP) with constraints, and the target is to maximize the similarity between the blended crude oil and the objective crude oil. Furthermore, the model takes into account the selection of crude oils and their blending ratios simultaneously, and transforms the problem of looking for similar crude oil into the crude oil selection and blending optimization problem. We applied the Improved Cuckoo Search(ICS) algorithm to solving the model. Through the simulations, ICS was compared with the genetic algorithm, the particle swarm optimization algorithm and the CPLEX solver. The results show that ICS has very good optimization efficiency. The blending solution can provide a reference for refineries to find the similar crude oil. And the method proposed can also give some references to selection and blending optimization of other materials.
基金supported by the National Key R&D Program of China(2018YFA0702200)Science and Technology Project of State Grid Shandong Electric Power Corporation(52062518000Q)。
文摘The renewable portfolio standard has been promoted in parallel with the reform of the electricity market,and the flexibility requirement of the power system has rapidly increased.To promote renewable energy consumption and improve power system flexibility,a bi-level optimal operation model of the electricity market is proposed.A probabilistic model of the flexibility requirement is established,considering the correlation between wind power,photovoltaic power,and load.A bi-level optimization model is established for the multi-markets;the upper and lower models represent the intra-provincial market and inter-provincial market models,respectively.To efficiently solve the model,it is transformed into a mixed-integer linear programming model using the Karush–Kuhn–Tucker condition and Lagrangian duality theory.The economy and flexibility of the model are verified using a provincial power grid as an example.
基金part of the Program of ‘‘Study of the mechanism of complex heat and mass transfer during batch transport process in product pipelines’’ funded under the National Natural Science Foundation of China, Grant Number 51474228
文摘Oil depots along products pipelines are important components of the pipeline transportation system and down-stream markets.The operating costs of oil depots account for a large proportion of the total system’s operating costs.Meanwhile,oil depots and pipelines form an entire system,and each operation in a single oil depot may have influence on others.It is a tough job to make a scheduling plan when considering the factors of delivering contaminated oil and batches migration.So far,studies simultaneously considering operating constraints and contaminated oil issues are rare.Aiming at making a scheduling plan with the lowest operating costs,the paper establishes a mixed-integer linear programming model,considering a sequence of operations,such as delivery, export, blending,fractionating and exchanging operations,and batch property differences of the same oil as well as influence of batch migration on contaminated volume.Moreover,the paper verifies the linear relationship between oil concentration and blending capability by mathematical deduction.Finally,the model is successfully applied to one of the product pipelines in China and proved to be practical.
基金State Grid Jiangsu Electric Power Co.,Ltd(JF2020001)National Key Technology R&D Program of China(2017YFB0903300)State Grid Corporation of China(521OEF17001C).
文摘In contrast to most existing works on robust unit commitment(UC),this study proposes a novel big-M-based mixed-integer linear programming(MILP)method to solve security-constrained UC problems considering the allowable wind power output interval and its adjustable conservativeness.The wind power accommodation capability is usually limited by spinning reserve requirements and transmission line capacity in power systems with large-scale wind power integration.Therefore,by employing the big-M method and adding auxiliary 0-1 binary variables to describe the allowable wind power output interval,a bilinear programming problem meeting the security constraints of system operation is presented.Furthermore,an adjustable confidence level was introduced into the proposed robust optimization model to decrease the level of conservatism of the robust solutions.This can establish a trade-off between economy and security.To develop an MILP problem that can be solved by commercial solvers such as CPLEX,the big-M method is utilized again to represent the bilinear formulation as a series of linear inequality constraints and approximately address the nonlinear formulation caused by the adjustable conservativeness.Simulation studies on a modified IEEE 26-generator reliability test system connected to wind farms were performed to confirm the effectiveness and advantages of the proposed method.
文摘This paper reviews alternative market equilibrium models for policy analysis. The origin of spatial equilibrium models and their application to wood and wood-processing industries are described. Three mathematical programming models commonly applied to solve spatial problems - namely linear programming, non-linear programming and mixed complementary programming - are reviewed in terms of forms of objective functions and constraint equalities and inequalities. These programming are illustrated with numerical examples. Linear programming is only applied in transportation problems to solve quantities trans, ported between regions when quantities supplied and demanded in each region are already known. It is argued that linear programming can be applied in broader context to transportation problems where supply and demand quantities are unknown and are linear. In this context, linear programming is seen as a more convenient method for modelers because it has a simpler objective function and does not require as strict conditions, for instance the equal numbers of variables and equations required in mixed complementary programming. Finally, some critical insights are provided on the interpretation of optimal solutions generated by solving spatial equilibrium models.
基金the financial support from the National Basic Research Program of China(No.2013CB733506)the National Natural Science Fund for Distinguished Young Scholars(No.21425625)National Natural Science Foundation of China(No.21576269,21576262)
文摘The superstructure optimization of biomass to biomethane system through digestion is conducted in this work. The system encompasses biofeedstock collection and transportation, anaerobic digestion, biogas upgrading, and digestate recycling. We propose a multicriteria mixed integer nonlinear programming(MINLP) model that seeks to minimize the energy consumption and maximize the green degree and the biomethane production constrained by technology selection, mass balance, energy balance, and environmental impact. A multi-objective MINLP model is proposed and solved with a fast nondominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ). The resulting Pareto-optimal surface reveals the trade-off among the conflicting objectives. The optimal results indicate quantitatively that higher green degree and biomethane production objectives can be obtained at the expense of destroying the performance of the energy consumption objective.
