SINCE 2015,17 Sustainable Development Goals(SDGs)have been understood as more promising blueprints for a peaceful,prosperous,and sustainable future[1]which are formulated to seek a framework to address global challeng...SINCE 2015,17 Sustainable Development Goals(SDGs)have been understood as more promising blueprints for a peaceful,prosperous,and sustainable future[1]which are formulated to seek a framework to address global challenging issues such as poverty,inequality,and pollution.展开更多
As location-based techniques and applications have become ubiquitous in emerging wireless networks, the verification of location information has become more important. In recent years, there has been an explosion of a...As location-based techniques and applications have become ubiquitous in emerging wireless networks, the verification of location information has become more important. In recent years, there has been an explosion of activity related to lo- cation-verification techniques in wireless networks. In particular, there has been a specific focus on intelligent transport systems because of the mission-critical nature of vehicle location verification. In this paper, we review recent research on wireless location verification related to vehicular networks. We focus on location verification systems that rely on for- mal mathematical classification frameworks and show how many systems are either partially or fully encompassed by such frameworks.展开更多
With serious cybersecurity situations and frequent network attacks,the demands for automated pentests continue to increase,and the key issue lies in attack planning.Considering the limited viewpoint of the attacker,at...With serious cybersecurity situations and frequent network attacks,the demands for automated pentests continue to increase,and the key issue lies in attack planning.Considering the limited viewpoint of the attacker,attack planning under uncertainty is more suitable and practical for pentesting than is the traditional planning approach,but it also poses some challenges.To address the efficiency problem in uncertainty planning,we propose the APU-D*Lite algorithm in this paper.First,the pentest framework is mapped to the planning problem with the Planning Domain Definition Language(PDDL).Next,we develop the pentest information graph to organize network information and assess relevant exploitation actions,which helps to simplify the problem scale.Then,the APU-D*Lite algorithm is introduced based on the idea of incremental heuristic searching.This method plans for both hosts and actions,which meets the requirements of pentesting.With the pentest information graph as the input,the output is an alternating host and action sequence.In experiments,we use the attack success rate to represent the uncertainty level of the environment.The result shows that APU-D*Lite displays better reliability and efficiency than classical planning algorithms at different attack success rates.展开更多
With the increasing penetration of renewables,power systems have to operate with greater flexibility to address the uncertainties of renewable output.This paper develops an uncertainty locational marginal price(ULMP)m...With the increasing penetration of renewables,power systems have to operate with greater flexibility to address the uncertainties of renewable output.This paper develops an uncertainty locational marginal price(ULMP)mechanism to price these uncertainties.They are denoted as box deviation intervals as suggested by the market participants.The ULMP model solves a robust optimal power flow(OPF)problem to clear market bids,aiming to minimize the system cost as a prerequisite that the reserve margin can address all the relevant uncertainties.The ULMP can be obtained as a by-product of the optimization problem from the Lagrange multipliers.Under the ULMP mechanism,renewables and consumers with uncertainty will make extra payments,and the thermals and financial transmission right(FTR)holders will be compensated.It is further shown that the proposed mechanism has preferable properties,such as social efficiency,budget balance and individual rationality.Numerical tests are conducted on the modified IEEE 5-bus and 118-bus systems to demonstrate the merits and applicability of the proposed mechanism.展开更多
Wind power has been proven to have the ability to participate in the frequency modulation(FM)market.Using batteries to improve wind power stability can better aid wind farms participating in the FM market.Battery ener...Wind power has been proven to have the ability to participate in the frequency modulation(FM)market.Using batteries to improve wind power stability can better aid wind farms participating in the FM market.Battery energy storage system(BESS)has a promising future in applying regulation and load management in the power grid.For regulation services,normally,the regulation power prediction is estimated based on the required maximum regulation capacity;the power needed for the specific regulation service is unknown to the BESS owner.However,this information is needed in the regulation model when formulating the linearised BESS model with a constraint on the state of charge(SoC).This compromises the accuracy of the model greatly when it is applied for regulation service.Moreover,different control strategies can be employed by BESS.However,the current depth of discharge(DoD)based models have difficulties in being used in a linearization problem.Due to the consideration of the control strategy,the model becomes highly nonlinear and cannot be solved.In this paper,a charging rate(C-rate)based model is introduced,which can consider different control strategies of a BESS for cooperation with wind farms to participate in wind farm estimation error compensation,load management,energy bid,and regulation bid.First,the limitation of conventional BESS models are listed,and a new C-rate-based model is introduced.Then the C-rate-based BESS model is adopted in a wind farm and BESS cooperation scheme.Finally,experimental studies are carried out,and the DoD model and C-rate model optimization results are compared to prove the rationality of the C-rate model.展开更多
基金supported by the Australian Research Council(DE210100274)。
文摘SINCE 2015,17 Sustainable Development Goals(SDGs)have been understood as more promising blueprints for a peaceful,prosperous,and sustainable future[1]which are formulated to seek a framework to address global challenging issues such as poverty,inequality,and pollution.
基金supported by the University of New South Wales and the Australian Research Council under grant No.DP120102607
文摘As location-based techniques and applications have become ubiquitous in emerging wireless networks, the verification of location information has become more important. In recent years, there has been an explosion of activity related to lo- cation-verification techniques in wireless networks. In particular, there has been a specific focus on intelligent transport systems because of the mission-critical nature of vehicle location verification. In this paper, we review recent research on wireless location verification related to vehicular networks. We focus on location verification systems that rely on for- mal mathematical classification frameworks and show how many systems are either partially or fully encompassed by such frameworks.
文摘With serious cybersecurity situations and frequent network attacks,the demands for automated pentests continue to increase,and the key issue lies in attack planning.Considering the limited viewpoint of the attacker,attack planning under uncertainty is more suitable and practical for pentesting than is the traditional planning approach,but it also poses some challenges.To address the efficiency problem in uncertainty planning,we propose the APU-D*Lite algorithm in this paper.First,the pentest framework is mapped to the planning problem with the Planning Domain Definition Language(PDDL).Next,we develop the pentest information graph to organize network information and assess relevant exploitation actions,which helps to simplify the problem scale.Then,the APU-D*Lite algorithm is introduced based on the idea of incremental heuristic searching.This method plans for both hosts and actions,which meets the requirements of pentesting.With the pentest information graph as the input,the output is an alternating host and action sequence.In experiments,we use the attack success rate to represent the uncertainty level of the environment.The result shows that APU-D*Lite displays better reliability and efficiency than classical planning algorithms at different attack success rates.
基金supported in part by the National Natural Science Foundation of China(No.51620105007)in part the UNSW(University of New South Wales)&Tsinghua University Collaborative Research Fund(RG193827/2018Z)。
文摘With the increasing penetration of renewables,power systems have to operate with greater flexibility to address the uncertainties of renewable output.This paper develops an uncertainty locational marginal price(ULMP)mechanism to price these uncertainties.They are denoted as box deviation intervals as suggested by the market participants.The ULMP model solves a robust optimal power flow(OPF)problem to clear market bids,aiming to minimize the system cost as a prerequisite that the reserve margin can address all the relevant uncertainties.The ULMP can be obtained as a by-product of the optimization problem from the Lagrange multipliers.Under the ULMP mechanism,renewables and consumers with uncertainty will make extra payments,and the thermals and financial transmission right(FTR)holders will be compensated.It is further shown that the proposed mechanism has preferable properties,such as social efficiency,budget balance and individual rationality.Numerical tests are conducted on the modified IEEE 5-bus and 118-bus systems to demonstrate the merits and applicability of the proposed mechanism.
文摘Wind power has been proven to have the ability to participate in the frequency modulation(FM)market.Using batteries to improve wind power stability can better aid wind farms participating in the FM market.Battery energy storage system(BESS)has a promising future in applying regulation and load management in the power grid.For regulation services,normally,the regulation power prediction is estimated based on the required maximum regulation capacity;the power needed for the specific regulation service is unknown to the BESS owner.However,this information is needed in the regulation model when formulating the linearised BESS model with a constraint on the state of charge(SoC).This compromises the accuracy of the model greatly when it is applied for regulation service.Moreover,different control strategies can be employed by BESS.However,the current depth of discharge(DoD)based models have difficulties in being used in a linearization problem.Due to the consideration of the control strategy,the model becomes highly nonlinear and cannot be solved.In this paper,a charging rate(C-rate)based model is introduced,which can consider different control strategies of a BESS for cooperation with wind farms to participate in wind farm estimation error compensation,load management,energy bid,and regulation bid.First,the limitation of conventional BESS models are listed,and a new C-rate-based model is introduced.Then the C-rate-based BESS model is adopted in a wind farm and BESS cooperation scheme.Finally,experimental studies are carried out,and the DoD model and C-rate model optimization results are compared to prove the rationality of the C-rate model.