Carbon capture and storage(CCS)systems can provide sufficient carbon raw materials for power-to-gas(P2G)systems to reduce the carbon emission of traditional coal-fired units,which helps to achieve low-carbon dispatch ...Carbon capture and storage(CCS)systems can provide sufficient carbon raw materials for power-to-gas(P2G)systems to reduce the carbon emission of traditional coal-fired units,which helps to achieve low-carbon dispatch of integrated energy systems(IESs).In this study,an extended carbon-emis-sion flow model that integrates CCS-P2G coordinated operation and low-carbon characteristics of an energy storage system(ESS)is proposed.On the energy supply side,the coupling rela-tionship between CCS and P2G systems is established to realize the low-carbon economic operation of P2G systems.On the en-ergy storage side,the concept of"state of carbon"is introduced to describe the carbon emission characteristics of the ESS to ex-ploit the potential of coordinated low-carbon dispatch in terms of both energy production and storage.In addition,a low-car-bon economic dispatch model that considers multiple uncertain-ties,including wind power output,electricity price,and load de-mands,is established.To solve the model efficiently,a parallel multidimensional approximate dynamic programming algo-rithm is adopted,while the solution efficiency is significantly im-proved over that of stochastic optimization without losing solu-tion accuracy under a multilayer parallel loop nesting frame-work.The low-carbon economic dispatch method of IESs is composed of the extended carbon emission flow model,low-car-bon economic dispatch model,and the parallel multidimension-al approximate dynamic programming algorithm.The effective-ness of the proposed method is verified on E14-H6-G6 and E57-H12-G12 systems.展开更多
It is well known that hierarchies of mathematical programming formulatlons with different numbers of variables and constraints have a considerable impact regarding the quality of solutions obtained once these formulat...It is well known that hierarchies of mathematical programming formulatlons with different numbers of variables and constraints have a considerable impact regarding the quality of solutions obtained once these formulations are fed to a commercial solver. In addition, even if dimensions are kept the same, changes in formulations may largely influence solvability and quality of results. This becomes evident especially if redundant constraints are used. We propose a related framework for information collection based on these constraints. We exemplify by means of a well-known combinatorial optimization problem from the knapsack problem family, i.e., the multidimensional multiple-choice knapsack problem （MMKP）. This incorporates a relationship of the MMKP to some generalized set partitioning problems. Moreover, we investigate an application in maritime shipping and logistics by means of the dynamic berth allocation problem （DBAP）, where optimal solutions are reached from the root node within the solver.展开更多
基金This work was supported by the Chinese Postdoctoral Science Foundation(No.2023M734092)National Natural Science Foundation of China(No.52107111)Shandong Provincial Natural Science Foundation of China(No.ZR2022ME219)。
文摘Carbon capture and storage(CCS)systems can provide sufficient carbon raw materials for power-to-gas(P2G)systems to reduce the carbon emission of traditional coal-fired units,which helps to achieve low-carbon dispatch of integrated energy systems(IESs).In this study,an extended carbon-emis-sion flow model that integrates CCS-P2G coordinated operation and low-carbon characteristics of an energy storage system(ESS)is proposed.On the energy supply side,the coupling rela-tionship between CCS and P2G systems is established to realize the low-carbon economic operation of P2G systems.On the en-ergy storage side,the concept of"state of carbon"is introduced to describe the carbon emission characteristics of the ESS to ex-ploit the potential of coordinated low-carbon dispatch in terms of both energy production and storage.In addition,a low-car-bon economic dispatch model that considers multiple uncertain-ties,including wind power output,electricity price,and load de-mands,is established.To solve the model efficiently,a parallel multidimensional approximate dynamic programming algo-rithm is adopted,while the solution efficiency is significantly im-proved over that of stochastic optimization without losing solu-tion accuracy under a multilayer parallel loop nesting frame-work.The low-carbon economic dispatch method of IESs is composed of the extended carbon emission flow model,low-car-bon economic dispatch model,and the parallel multidimension-al approximate dynamic programming algorithm.The effective-ness of the proposed method is verified on E14-H6-G6 and E57-H12-G12 systems.
文摘It is well known that hierarchies of mathematical programming formulatlons with different numbers of variables and constraints have a considerable impact regarding the quality of solutions obtained once these formulations are fed to a commercial solver. In addition, even if dimensions are kept the same, changes in formulations may largely influence solvability and quality of results. This becomes evident especially if redundant constraints are used. We propose a related framework for information collection based on these constraints. We exemplify by means of a well-known combinatorial optimization problem from the knapsack problem family, i.e., the multidimensional multiple-choice knapsack problem （MMKP）. This incorporates a relationship of the MMKP to some generalized set partitioning problems. Moreover, we investigate an application in maritime shipping and logistics by means of the dynamic berth allocation problem （DBAP）, where optimal solutions are reached from the root node within the solver.
