This study addresses a new charging station network planning problem for smart connected electric vehicles.We embed a charging station choice model into a charging network planning model that explicitly considers the ...This study addresses a new charging station network planning problem for smart connected electric vehicles.We embed a charging station choice model into a charging network planning model that explicitly considers the heterogeneity of the charging behavior in a data-driven manner.To cope with the deficiencies from a small size and sparse behavioral data,we propose a robust charging demand prediction method that can significantly reduce the impact of sample errors and missing data.On the basis of these two building blocks,we form and solve a new optimal charging station location and capacity problem by minimizing the construction and charging costs while considering the charging service level,construction budget,and limit to the number of chargers.We use a case study of planning charging stations in Shanghai to validate our contributions and provide managerial insight in this area.展开更多
The accelerated global adoption of electric vehicles(EVs)is driving significant expansion and increasing complexity within the EV charging infrastructure,consequently presenting novel and pressing cybersecurity challe...The accelerated global adoption of electric vehicles(EVs)is driving significant expansion and increasing complexity within the EV charging infrastructure,consequently presenting novel and pressing cybersecurity challenges.While considerable effort has focused on preventative cybersecurity measures,a critical deficiency persists in structured methodologies for digital forensic analysis following security incidents,a gap exacerbated by system heterogeneity,distributed digital evidence,and inconsistent logging practices which hinder effective incident reconstruction and attribution.This paper addresses this critical need by proposing a novel,data-driven forensic framework tailored to the EV charging infrastructure,focusing on the systematic identification,classification,and correlation of diverse digital evidence across its physical,network,and application layers.Our methodology integrates open-source intelligence(OSINT)with advanced system modeling based on a three-layer cyber-physical system architecture to comprehensively map potential evidentiary sources.Key contributions include a comprehensive taxonomy of cybersecurity threats pertinent to EV charging ecosystems,detailed mappings between these threats and the resultant digital evidence to guide targeted investigations,the formulation of adaptable forensic investigation workflows for various incident scenarios,and a critical analysis of significant gaps in digital evidence availability within current EV charging systems,highlighting limitations in forensic readiness.The practical application and utility of this method are demonstrated through illustrative case studies involving both empirically-derived and virtual incident scenarios.The proposed datadriven approach is designed to significantly enhance digital forensic capabilities,support more effective incident response,strengthen compliance with emerging cybersecurity regulations,and ultimately contribute to bolstering the overall security,resilience,and trustworthiness of this increasingly vital critical infrastructure.展开更多
The surge of distributed renewable energy resources has given rise to the emergence of prosumers,facilitating the low-carbon transition of distribution networks.However,flexible prosumers introduce bidirectional power...The surge of distributed renewable energy resources has given rise to the emergence of prosumers,facilitating the low-carbon transition of distribution networks.However,flexible prosumers introduce bidirectional power and carbon interaction,increasing the complexity of practical decision-making in distribution networks.To address these challenges,this paper presents a carbon-coupled network charge-guided bi-level interactive optimization method between the distribution system operator and prosumers.In the upper level,a carbon-emission responsibility settlement method that incorporates the impact of peer-to-peer(P2P)trading is proposed,based on a carbon-emission flow model and optimal power flow model,leading to the formulation of carbon-coupled network charges.In the lower level,a decentralized P2P trading mechanism is developed to achieve the clearing of energy and carbon-emission rights.Furthermore,an alternating direction method of multipliers with an adaptive penalty factor is introduced to address the equilibrium of the P2P electricity–carbon coupled market,and an improved bisection method is employed to ensure the convergence of the bi-level interaction.A case study on the modified IEEE 33-bus system demonstrates the effectiveness of the proposed model and methodology.展开更多
For the suppliers of concerned services, theories about infrastructure pricing： SAT （Stand Alone economists such as Laffont, Tirole, etc. developed Test）, ECPR （Efficient Component Pricing Rule）. Especially, Sida...For the suppliers of concerned services, theories about infrastructure pricing： SAT （Stand Alone economists such as Laffont, Tirole, etc. developed Test）, ECPR （Efficient Component Pricing Rule）. Especially, Sidak, Spulber, put forward M-ECPR （Market Efficient Component Pricing Rule） method for bottleneck infrastructures. In this article, we bring the M-ECPR principles into the study of Chinese railways pricing of its network infrastructures. Combined with our Engineer Model and Opportunity Cost Model, we analyzed the special conditions faced by Chinese railways, and developed a model for sharing infrastructure fees among freight and passenger transportations. Engineer Model split Variable Cost （VC） and Fixed Cost （FC） into freight and passenger activities, and Opportunity Cost Model take the insufficient supply of infrastructure capacity into consideration. Of course, the subsidy from the government greatly affected the price standard for bottleneck facilities, or so-called network infrastructures.展开更多
More electricity utilities will participate in the investment and operation of private distributed generations(DGs)while the local power company is responsible for the reinforcement of lines and DGs,as well.How to ach...More electricity utilities will participate in the investment and operation of private distributed generations(DGs)while the local power company is responsible for the reinforcement of lines and DGs,as well.How to achieve the maximum benefits among various utilities,including the power company,is a task in the expansion planning of distribution networks.To solve the market-oriented planning problem,virtual peer to peer(P2P)trading is integrated and modeled in the new expansion planning of distribution networks.First,virtual market transaction optimization among prosumers is formulated.Second,the distributed regional marginal price(DLMP)is calculated by the optimal operation model,which contributed to the network usage charge(NUC)and then integrated in the expansion planning model.Case studies are performed and indicate the integrated P2P transaction strategy could improve local load consumption,while reducing the load rate of lines,as well as the electricity cost of users.Besides,the total planning cost paid by the power company could be saved via prosumers’investment and P2P transactions and the factors affecting power company’s profit are also classified in multi-investor planning of distribution networks.展开更多
Amorphous and non-stoichiometric hafnium oxide(a-HfO_(x))systems are essential for advanced electronic applications due to their superior electrical properties.Simulating their atomic behaviors under electric fields(E...Amorphous and non-stoichiometric hafnium oxide(a-HfO_(x))systems are essential for advanced electronic applications due to their superior electrical properties.Simulating their atomic behaviors under electric fields(Efield)is critical but challenging.Ab-initio molecular dynamics(AIMD)offer high accuracy but is computationally expensive,while classical MD lacks precision.To address this,we develop a charge equilibration integrated graph neural network(CIGNN)model that predicts atomic charge,energy,and force under Efield conditions.Using the CIGNN model and AIMD datasets,we develop a CIGNN-based machine learning potential(CNMP)optimized for a-HfO_(x)systems.The CNMP achieves quantum mechanical accuracy and effectively captures the atomic behaviors and dynamic properties of these systems across varying temperatures,densities,and E_(field)conditions.We expect the CNMP to serve as a valuable tool for studying field-induced phenomena in complex systems and to provide a foundation for advancing innovations in electronic applications.展开更多
The emergence of prosumers in distribution systems has enabled competitive electricity markets to transition from traditional hierarchical structures to more decentralized models such as peer-to-peer(P2P)and community...The emergence of prosumers in distribution systems has enabled competitive electricity markets to transition from traditional hierarchical structures to more decentralized models such as peer-to-peer(P2P)and community-based(CB)energy transaction markets.However,the network usage charge(NUC)that prosumers pay to the electric power utility for network services is not adjusted to suit these energy transactions,which causes a reduction in revenue streams of the utility.In this study,we propose an NUC calculation method for P2P and CB transactions to address holistically economic and technical issues in transactive energy markets and distribution system operations,respectively.Based on the Nash bargaining(NB)theory,we formulate an NB problem for P2P and CB transactions to solve the conflicts of interest among prosumers,where the problem is further decomposed into two convex subproblems of social welfare maximization and payment bargaining.We then build the NUC calculation model by coupling the NB model and AC optimal power flow model.We also employ the Shapley value to allocate the NUC to consumers fairly for the NUC model of CB transactions.Finally,numerical studies on IEEE 15-bus and 123-bus distribution systems demonstrate the effectiveness of the proposed NUC calculation method for P2P and CB transactions.展开更多
Asymmetry has been demonstrated an effective approach in recent years to tune the structural and energetic orders of nonfullerene electron acceptors(NFAs)to prepare efficient organic solar cells(OSCs).In this article,...Asymmetry has been demonstrated an effective approach in recent years to tune the structural and energetic orders of nonfullerene electron acceptors(NFAs)to prepare efficient organic solar cells(OSCs).In this article,five asymmetric NFAs,namely C9BTP-BO-Th Cl-2F,C9BTP-BO-Cl-2F,C9BTP-BO-2Cl-2F,C7BTP-BO-2Cl-2F and C5BTP-BO-2Cl-2F possessing varied asymmetric end-groups and alkyl chains are synthesized to tune the charge transport networks formed within these NFAs.We found that the enhanced planarity in the asymmetric NFA can facilitate closerπ-πstacking distance in either the A-to-A or A-toD type NFA dimers,whilst the larger dipole moment can promote the formation of three-dimensional(3D)charge transport networks among NFAs.Taking those advantages,C7BTP-BO-2Cl-2F exhibit a compact 3D honeycomb network with a high packing coefficient of 72.1%and molecular packing density of 0.48 g/cm^(3),contributing to a superior power conversion efficiency of 18.0%when employing PM6 as the donor,with an open-circuit voltage of 0.85 V,short-circuit current of26.7 m A cm^(-2)and fill factor of 79.3%.Our work provides guidelines in engineering the end group and side chains of asymmetric NFAs to achieve compact charge transport networks for high efficiency OSCs.展开更多
Scholars and practitioners believe that the large-scale deployment of charging piles is imperative to our future electric transportation systems.Major economies ambitiously install charging pile networks,with massive ...Scholars and practitioners believe that the large-scale deployment of charging piles is imperative to our future electric transportation systems.Major economies ambitiously install charging pile networks,with massive construction spending,maintenance costs,and urban space occupation.However,recent developments in technology may significantly reduce the necessary charging capacity required by the system.This paper develops a linear programming model to characterize the effects of likely scenarios where vehicle-to-vehicle(V2V)charging is available via vehicle modularization or wireless charging.Specifically,we consider scenarios in which vehicles can transmit energy to each other(coordinated by a central platform)while traveling closely on the same road.We first estimate the number of charging piles needed for completing the travel plan of 73 cars from data,assuming a battery capacity of 400 km’s range and no V2V charging.Our results show that once V2V charging technologies with an efficiency of 50%are available,more than 2/3 of the charging piles investment would be wasted.Additionally,if the efficiency of V2V charging increases to 75%,we can easily reduce the battery capacity of vehicles to 200 km,which will reduce production costs and improve energy efficiency.These results may reveal us an alternative pathway towards transportation electrification.展开更多
Peer-to-peer(P2P)energy trading is an emerging energy supply paradigm where customers with distributed energy resources(DERs)are allowed to directly trade and share electricity with each other.P2P energy trading can f...Peer-to-peer(P2P)energy trading is an emerging energy supply paradigm where customers with distributed energy resources(DERs)are allowed to directly trade and share electricity with each other.P2P energy trading can facilitate local power and energy balance,thus being a potential way to manage the rapidly increasing number of DERs in net zero transition.It is of great importance to explore P2P energy trading via public power networks,to which most DERs are connected.Despite the extensive research on P2P energy trading,there has been little large-scale commercial deployment in practice across the world.In this paper,the practical challenges of conducting P2P energy trading via public power networks are identified and presented,based on the analysis of a practical Local Virtual Private Networks(LVPNs)case in North Wales,UK.The ongoing efforts and emerging solutions to tackling the challenges are then summarized and critically reviewed.Finally,the way forward for facilitating P2P energy trading via public power networks is proposed.展开更多
基金the National Natural Science Founda-tion of China(Nos.72171175,and 72021102)。
文摘This study addresses a new charging station network planning problem for smart connected electric vehicles.We embed a charging station choice model into a charging network planning model that explicitly considers the heterogeneity of the charging behavior in a data-driven manner.To cope with the deficiencies from a small size and sparse behavioral data,we propose a robust charging demand prediction method that can significantly reduce the impact of sample errors and missing data.On the basis of these two building blocks,we form and solve a new optimal charging station location and capacity problem by minimizing the construction and charging costs while considering the charging service level,construction budget,and limit to the number of chargers.We use a case study of planning charging stations in Shanghai to validate our contributions and provide managerial insight in this area.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2023-00242528,50%)supported by a grant from the Korea Electric Power Corporation(R24XO01-4,50%)for basic research and development projects starting in 2024.
文摘The accelerated global adoption of electric vehicles(EVs)is driving significant expansion and increasing complexity within the EV charging infrastructure,consequently presenting novel and pressing cybersecurity challenges.While considerable effort has focused on preventative cybersecurity measures,a critical deficiency persists in structured methodologies for digital forensic analysis following security incidents,a gap exacerbated by system heterogeneity,distributed digital evidence,and inconsistent logging practices which hinder effective incident reconstruction and attribution.This paper addresses this critical need by proposing a novel,data-driven forensic framework tailored to the EV charging infrastructure,focusing on the systematic identification,classification,and correlation of diverse digital evidence across its physical,network,and application layers.Our methodology integrates open-source intelligence(OSINT)with advanced system modeling based on a three-layer cyber-physical system architecture to comprehensively map potential evidentiary sources.Key contributions include a comprehensive taxonomy of cybersecurity threats pertinent to EV charging ecosystems,detailed mappings between these threats and the resultant digital evidence to guide targeted investigations,the formulation of adaptable forensic investigation workflows for various incident scenarios,and a critical analysis of significant gaps in digital evidence availability within current EV charging systems,highlighting limitations in forensic readiness.The practical application and utility of this method are demonstrated through illustrative case studies involving both empirically-derived and virtual incident scenarios.The proposed datadriven approach is designed to significantly enhance digital forensic capabilities,support more effective incident response,strengthen compliance with emerging cybersecurity regulations,and ultimately contribute to bolstering the overall security,resilience,and trustworthiness of this increasingly vital critical infrastructure.
基金supported by Institutional Research Fund from Sichuan University(0-1 Innovation Research Project,2023SCUH0002)the Sichuan Science and Technology Program(2024YFHZ0312)+1 种基金the Chengdu Science and Technology Program(2024YF0600012HZ)the National Natural Science Foundation of China(U2166211 and 52177103).
文摘The surge of distributed renewable energy resources has given rise to the emergence of prosumers,facilitating the low-carbon transition of distribution networks.However,flexible prosumers introduce bidirectional power and carbon interaction,increasing the complexity of practical decision-making in distribution networks.To address these challenges,this paper presents a carbon-coupled network charge-guided bi-level interactive optimization method between the distribution system operator and prosumers.In the upper level,a carbon-emission responsibility settlement method that incorporates the impact of peer-to-peer(P2P)trading is proposed,based on a carbon-emission flow model and optimal power flow model,leading to the formulation of carbon-coupled network charges.In the lower level,a decentralized P2P trading mechanism is developed to achieve the clearing of energy and carbon-emission rights.Furthermore,an alternating direction method of multipliers with an adaptive penalty factor is introduced to address the equilibrium of the P2P electricity–carbon coupled market,and an improved bisection method is employed to ensure the convergence of the bi-level interaction.A case study on the modified IEEE 33-bus system demonstrates the effectiveness of the proposed model and methodology.
文摘For the suppliers of concerned services, theories about infrastructure pricing： SAT （Stand Alone economists such as Laffont, Tirole, etc. developed Test）, ECPR （Efficient Component Pricing Rule）. Especially, Sidak, Spulber, put forward M-ECPR （Market Efficient Component Pricing Rule） method for bottleneck infrastructures. In this article, we bring the M-ECPR principles into the study of Chinese railways pricing of its network infrastructures. Combined with our Engineer Model and Opportunity Cost Model, we analyzed the special conditions faced by Chinese railways, and developed a model for sharing infrastructure fees among freight and passenger transportations. Engineer Model split Variable Cost （VC） and Fixed Cost （FC） into freight and passenger activities, and Opportunity Cost Model take the insufficient supply of infrastructure capacity into consideration. Of course, the subsidy from the government greatly affected the price standard for bottleneck facilities, or so-called network infrastructures.
基金supported by the National Natural Science Foundation of China(52177103).
文摘More electricity utilities will participate in the investment and operation of private distributed generations(DGs)while the local power company is responsible for the reinforcement of lines and DGs,as well.How to achieve the maximum benefits among various utilities,including the power company,is a task in the expansion planning of distribution networks.To solve the market-oriented planning problem,virtual peer to peer(P2P)trading is integrated and modeled in the new expansion planning of distribution networks.First,virtual market transaction optimization among prosumers is formulated.Second,the distributed regional marginal price(DLMP)is calculated by the optimal operation model,which contributed to the network usage charge(NUC)and then integrated in the expansion planning model.Case studies are performed and indicate the integrated P2P transaction strategy could improve local load consumption,while reducing the load rate of lines,as well as the electricity cost of users.Besides,the total planning cost paid by the power company could be saved via prosumers’investment and P2P transactions and the factors affecting power company’s profit are also classified in multi-investor planning of distribution networks.
基金supported by the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning No. NRF-2020R1A6C101A202 and NRF-2024M3A7C2045166 and NRF-2021M3I3A1084940 and RS-2023-00257666 and RS-2024-00446683 and RS-2024-00450836.
文摘Amorphous and non-stoichiometric hafnium oxide(a-HfO_(x))systems are essential for advanced electronic applications due to their superior electrical properties.Simulating their atomic behaviors under electric fields(Efield)is critical but challenging.Ab-initio molecular dynamics(AIMD)offer high accuracy but is computationally expensive,while classical MD lacks precision.To address this,we develop a charge equilibration integrated graph neural network(CIGNN)model that predicts atomic charge,energy,and force under Efield conditions.Using the CIGNN model and AIMD datasets,we develop a CIGNN-based machine learning potential(CNMP)optimized for a-HfO_(x)systems.The CNMP achieves quantum mechanical accuracy and effectively captures the atomic behaviors and dynamic properties of these systems across varying temperatures,densities,and E_(field)conditions.We expect the CNMP to serve as a valuable tool for studying field-induced phenomena in complex systems and to provide a foundation for advancing innovations in electronic applications.
基金supported in part by the Foundation of State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(No.LAPS22015)in part by Shanghai Science and Technology Development Funds(No.22YF1429500)。
文摘The emergence of prosumers in distribution systems has enabled competitive electricity markets to transition from traditional hierarchical structures to more decentralized models such as peer-to-peer(P2P)and community-based(CB)energy transaction markets.However,the network usage charge(NUC)that prosumers pay to the electric power utility for network services is not adjusted to suit these energy transactions,which causes a reduction in revenue streams of the utility.In this study,we propose an NUC calculation method for P2P and CB transactions to address holistically economic and technical issues in transactive energy markets and distribution system operations,respectively.Based on the Nash bargaining(NB)theory,we formulate an NB problem for P2P and CB transactions to solve the conflicts of interest among prosumers,where the problem is further decomposed into two convex subproblems of social welfare maximization and payment bargaining.We then build the NUC calculation model by coupling the NB model and AC optimal power flow model.We also employ the Shapley value to allocate the NUC to consumers fairly for the NUC model of CB transactions.Finally,numerical studies on IEEE 15-bus and 123-bus distribution systems demonstrate the effectiveness of the proposed NUC calculation method for P2P and CB transactions.
基金supported by the National Natural Science Foundation of China(52073221,52273196)。
文摘Asymmetry has been demonstrated an effective approach in recent years to tune the structural and energetic orders of nonfullerene electron acceptors(NFAs)to prepare efficient organic solar cells(OSCs).In this article,five asymmetric NFAs,namely C9BTP-BO-Th Cl-2F,C9BTP-BO-Cl-2F,C9BTP-BO-2Cl-2F,C7BTP-BO-2Cl-2F and C5BTP-BO-2Cl-2F possessing varied asymmetric end-groups and alkyl chains are synthesized to tune the charge transport networks formed within these NFAs.We found that the enhanced planarity in the asymmetric NFA can facilitate closerπ-πstacking distance in either the A-to-A or A-toD type NFA dimers,whilst the larger dipole moment can promote the formation of three-dimensional(3D)charge transport networks among NFAs.Taking those advantages,C7BTP-BO-2Cl-2F exhibit a compact 3D honeycomb network with a high packing coefficient of 72.1%and molecular packing density of 0.48 g/cm^(3),contributing to a superior power conversion efficiency of 18.0%when employing PM6 as the donor,with an open-circuit voltage of 0.85 V,short-circuit current of26.7 m A cm^(-2)and fill factor of 79.3%.Our work provides guidelines in engineering the end group and side chains of asymmetric NFAs to achieve compact charge transport networks for high efficiency OSCs.
基金support from the Ministry of Education China and NSFC through the CJJX scheme(20221710034).
文摘Scholars and practitioners believe that the large-scale deployment of charging piles is imperative to our future electric transportation systems.Major economies ambitiously install charging pile networks,with massive construction spending,maintenance costs,and urban space occupation.However,recent developments in technology may significantly reduce the necessary charging capacity required by the system.This paper develops a linear programming model to characterize the effects of likely scenarios where vehicle-to-vehicle(V2V)charging is available via vehicle modularization or wireless charging.Specifically,we consider scenarios in which vehicles can transmit energy to each other(coordinated by a central platform)while traveling closely on the same road.We first estimate the number of charging piles needed for completing the travel plan of 73 cars from data,assuming a battery capacity of 400 km’s range and no V2V charging.Our results show that once V2V charging technologies with an efficiency of 50%are available,more than 2/3 of the charging piles investment would be wasted.Additionally,if the efficiency of V2V charging increases to 75%,we can easily reduce the battery capacity of vehicles to 200 km,which will reduce production costs and improve energy efficiency.These results may reveal us an alternative pathway towards transportation electrification.
文摘Peer-to-peer(P2P)energy trading is an emerging energy supply paradigm where customers with distributed energy resources(DERs)are allowed to directly trade and share electricity with each other.P2P energy trading can facilitate local power and energy balance,thus being a potential way to manage the rapidly increasing number of DERs in net zero transition.It is of great importance to explore P2P energy trading via public power networks,to which most DERs are connected.Despite the extensive research on P2P energy trading,there has been little large-scale commercial deployment in practice across the world.In this paper,the practical challenges of conducting P2P energy trading via public power networks are identified and presented,based on the analysis of a practical Local Virtual Private Networks(LVPNs)case in North Wales,UK.The ongoing efforts and emerging solutions to tackling the challenges are then summarized and critically reviewed.Finally,the way forward for facilitating P2P energy trading via public power networks is proposed.
