The increasing integration of variable wind generation has aggravated the imbalance between electricity supply and demand. Power-to-hydrogen(P2H) is a promising solution to balance supply and demand in a variable powe...The increasing integration of variable wind generation has aggravated the imbalance between electricity supply and demand. Power-to-hydrogen(P2H) is a promising solution to balance supply and demand in a variable power grid, in which excess wind power is converted into hydrogen via electrolysis and stored for later use. In this study, an energy hub(EH) with both a P2H facility(electrolyzer) and a gas-to-power(G2P) facility(hydrogen gas turbine) is proposed to accommodate a high penetration of wind power. The EH is modeled and integrated into a security-constrained unit commitment(SCUC) problem, and this optimization problem is solved by a mixed-integer linear programming(MILP) method with the Benders decomposition technique. Case studies are presented to validate the proposed model and elaborate on the technological potential of integrating P2H into a power system with a high level of wind penetration(HWP).展开更多
Nanogrids are expected to play a significant role in managing the ever-increasing distributed renewable energy sources. If an off-grid nanogrid can supply fullycharged batteries to a battery swapping station(BSS)servi...Nanogrids are expected to play a significant role in managing the ever-increasing distributed renewable energy sources. If an off-grid nanogrid can supply fullycharged batteries to a battery swapping station(BSS)serving regional electric vehicles(EVs), it will help establish a structure for implementing renewable-energyto-vehicle systems. A capacity planning problem is formulated to determine the optimal sizing of photovoltaic(PV) generation and battery-based energy storage system(BESS) in such a nanogrid. The problem is formulated based on the mixed-integer linear programming(MILP)and then solved by a robust optimization approach. Flexible uncertainty sets are employed to adjust the conservativeness of the robust optimization, and Monte Carlo simulations are carried out to compare the performance of the solutions. Case studies demonstrate the merits of the proposed applications and verify the approach.展开更多
Insufficiencies in charging facilities limit the broad application of electric vehicles(EVs).In addition,EV can hardly represent a green option if its electricity primarily depends on fossil energy.Considering these t...Insufficiencies in charging facilities limit the broad application of electric vehicles(EVs).In addition,EV can hardly represent a green option if its electricity primarily depends on fossil energy.Considering these two problems,this paper studies a battery swapping-charging system based on wind farms(hereinafter referred to as W-BSCS).In a W-BSCS,the wind farms not only supply electricity to the power grid but also cooperate with a centralized charge station(CCS),which can centrally charge EV batteries and then distribute them to multiple battery swapping stations(BSSs).The operational framework of the W-BSCS is analyzed,and some preprocessing technologies are developed to reduce complexity in modeling.Then,a joint optimal scheduling model involving a wind power generation plan,battery swapping demand,battery charging and discharging,and a vehicle routing problem(VRP)is established.Then a heuristic method based on the exhaustive search and the Genetic Algorithm is employed to solve the formulated NP-hard problem.Numerical results verify the effectiveness of the joint optimal scheduling model,and they also show that the W-BSCS has great potential to promote EVs and wind power.展开更多
The usage of each private electric vehicle(PrEV)is a repeating behavior process composed by driving,parking,discharging and charging,in which PrEV shows obvious procedural characteristics.To analyze the procedural cha...The usage of each private electric vehicle(PrEV)is a repeating behavior process composed by driving,parking,discharging and charging,in which PrEV shows obvious procedural characteristics.To analyze the procedural characteristics,this paper proposes a procedural simulation method.The method aggregates the behavior process regularity of the PrEV cluster to model the cluster’s charging load.Firstly,the basic behavior process of each PrEV is constructed by referring the statistical datasets of the traditional private non-electric vehicles.Secondly,all the basic processes are set as a simulation starting point,and they are dynamically reconstructed by several constraints.The simulation continues until the steady state of charge(SOC)distribution and behavior regularity of the PrEV cluster are obtained.Lastly,based on the obtained SOC and behavior regularity information,the PrEV cluster’s behavior processes are simulated again to make the aggregating charging load model available.Examples for several scenarios show that the proposed method can improve the reliability of modeling by grasping the PrEV cluster’s procedural characteristics.展开更多
基金supported by National Natural Science Foundation of China(No.51377035)NSFC-RCUK_EPSRC(No.51361130153)
文摘The increasing integration of variable wind generation has aggravated the imbalance between electricity supply and demand. Power-to-hydrogen(P2H) is a promising solution to balance supply and demand in a variable power grid, in which excess wind power is converted into hydrogen via electrolysis and stored for later use. In this study, an energy hub(EH) with both a P2H facility(electrolyzer) and a gas-to-power(G2P) facility(hydrogen gas turbine) is proposed to accommodate a high penetration of wind power. The EH is modeled and integrated into a security-constrained unit commitment(SCUC) problem, and this optimization problem is solved by a mixed-integer linear programming(MILP) method with the Benders decomposition technique. Case studies are presented to validate the proposed model and elaborate on the technological potential of integrating P2H into a power system with a high level of wind penetration(HWP).
基金jointly supported by the National Natural Science Foundation of China (No. 51377035)the China-UK NSFC/EPSRC EV project (No. 51361130153)
文摘Nanogrids are expected to play a significant role in managing the ever-increasing distributed renewable energy sources. If an off-grid nanogrid can supply fullycharged batteries to a battery swapping station(BSS)serving regional electric vehicles(EVs), it will help establish a structure for implementing renewable-energyto-vehicle systems. A capacity planning problem is formulated to determine the optimal sizing of photovoltaic(PV) generation and battery-based energy storage system(BESS) in such a nanogrid. The problem is formulated based on the mixed-integer linear programming(MILP)and then solved by a robust optimization approach. Flexible uncertainty sets are employed to adjust the conservativeness of the robust optimization, and Monte Carlo simulations are carried out to compare the performance of the solutions. Case studies demonstrate the merits of the proposed applications and verify the approach.
基金This work was supported by the Fundamental Research Funds for the Central Universities(2572020BF04).
文摘Insufficiencies in charging facilities limit the broad application of electric vehicles(EVs).In addition,EV can hardly represent a green option if its electricity primarily depends on fossil energy.Considering these two problems,this paper studies a battery swapping-charging system based on wind farms(hereinafter referred to as W-BSCS).In a W-BSCS,the wind farms not only supply electricity to the power grid but also cooperate with a centralized charge station(CCS),which can centrally charge EV batteries and then distribute them to multiple battery swapping stations(BSSs).The operational framework of the W-BSCS is analyzed,and some preprocessing technologies are developed to reduce complexity in modeling.Then,a joint optimal scheduling model involving a wind power generation plan,battery swapping demand,battery charging and discharging,and a vehicle routing problem(VRP)is established.Then a heuristic method based on the exhaustive search and the Genetic Algorithm is employed to solve the formulated NP-hard problem.Numerical results verify the effectiveness of the joint optimal scheduling model,and they also show that the W-BSCS has great potential to promote EVs and wind power.
基金This work is jointly supported by the National Natural Science Foundation of China(No.51377035)NSFCRCUK_EPSRC(No.51361130153).
文摘The usage of each private electric vehicle(PrEV)is a repeating behavior process composed by driving,parking,discharging and charging,in which PrEV shows obvious procedural characteristics.To analyze the procedural characteristics,this paper proposes a procedural simulation method.The method aggregates the behavior process regularity of the PrEV cluster to model the cluster’s charging load.Firstly,the basic behavior process of each PrEV is constructed by referring the statistical datasets of the traditional private non-electric vehicles.Secondly,all the basic processes are set as a simulation starting point,and they are dynamically reconstructed by several constraints.The simulation continues until the steady state of charge(SOC)distribution and behavior regularity of the PrEV cluster are obtained.Lastly,based on the obtained SOC and behavior regularity information,the PrEV cluster’s behavior processes are simulated again to make the aggregating charging load model available.Examples for several scenarios show that the proposed method can improve the reliability of modeling by grasping the PrEV cluster’s procedural characteristics.