With a heralded single photon source(HSPS), a measurement-device-independent quantum key distribution(MDIQKD) protocol is proposed, combined with a three-intensity decoy-state method. HSPS has the two-mode characteris...With a heralded single photon source(HSPS), a measurement-device-independent quantum key distribution(MDIQKD) protocol is proposed, combined with a three-intensity decoy-state method. HSPS has the two-mode characteristic, one mode is used as signal mode, and the other is used as heralded mode to reduce the influence of the dark count. The lower bound of the yield and the upper bound of the error rate are deduced and the performance of the MDI-QKD protocol with an HSPS is analyzed. The simulation results show that the MDI-QKD protocol with an HSPS can achieve a key generation rate and a secure transmission distance which are close to the theoretical limits of the protocol with a single photon source(SPS). Moreover, the key generation rate will improve with the raise of the senders' detection efficiency. The key generation rate of the MDI-QKD protocol with an HSPS is a little less than that of the MDI-QKD protocol with a weak coherent source(WCS) in the close range, but will exceed the latter in the far range. Furthermore, a farther transmission distance is obtained due to the two-mode characteristic of HSPS.展开更多
In order to reduce the risk of commutation failure(CF)in the AC/DC hybrid power system,the quantitative analysis on CF is required for on-line assessment and optimal control.This paper presents an accurate and reliabl...In order to reduce the risk of commutation failure(CF)in the AC/DC hybrid power system,the quantitative analysis on CF is required for on-line assessment and optimal control.This paper presents an accurate and reliable method to quantify the commutation security based on the trajectory due to the complexity of the high-voltage direct current(HVDC)model.Firstly,the characteristics of the extinction angle trajectory are analyzed under both commutation success and failure conditions.The commutation security margin index(CSMI)is then proposed for the HVDC systems.Moreover,a search strategy for parameter limits is put forward based on the sensitivity analysis of CSMI to accelerate the search speed with a guaranteed accuracy level.A modified IEEE 39-bus power system and an actual large-scale power system with 46 generators and 821 buses are utilized to verify the validity and robustness of the proposed index and strategy.展开更多
This paper develops a real-time control method based on deep reinforcement learning aimed to determine the optimal control actions to maintain a sufficient secure operating limit.The secure operating limit refers to t...This paper develops a real-time control method based on deep reinforcement learning aimed to determine the optimal control actions to maintain a sufficient secure operating limit.The secure operating limit refers to the limit to the most stressed pre-contingency operating point of an electric power system that can withstand a set of credible contingencies without violating stability criteria.The developed deep reinforcement learning method uses a hybrid control scheme that is capable of simultaneously adjusting both discrete and continuous action variables.The performance is evaluated on a modified version of the Nordic32 test system.The results show that the developed deep reinforcement learning method quickly learns an effective control policy to ensure a sufficient secure operating limit for a range of different system scenarios.The performance is also compared to a control based on a rule-based look-up table and a deep reinforcement learning control adapted for discrete action spaces.The hybrid deep reinforcement learning control managed to achieve significantly better on all of the defined test sets,indicating that the possibility of adjusting both discrete and continuous action variables resulted in a more flexible and efficient control policy.展开更多
基金supported by the National Natural Science Foundation of China(No.61302099)
文摘With a heralded single photon source(HSPS), a measurement-device-independent quantum key distribution(MDIQKD) protocol is proposed, combined with a three-intensity decoy-state method. HSPS has the two-mode characteristic, one mode is used as signal mode, and the other is used as heralded mode to reduce the influence of the dark count. The lower bound of the yield and the upper bound of the error rate are deduced and the performance of the MDI-QKD protocol with an HSPS is analyzed. The simulation results show that the MDI-QKD protocol with an HSPS can achieve a key generation rate and a secure transmission distance which are close to the theoretical limits of the protocol with a single photon source(SPS). Moreover, the key generation rate will improve with the raise of the senders' detection efficiency. The key generation rate of the MDI-QKD protocol with an HSPS is a little less than that of the MDI-QKD protocol with a weak coherent source(WCS) in the close range, but will exceed the latter in the far range. Furthermore, a farther transmission distance is obtained due to the two-mode characteristic of HSPS.
文摘In order to reduce the risk of commutation failure(CF)in the AC/DC hybrid power system,the quantitative analysis on CF is required for on-line assessment and optimal control.This paper presents an accurate and reliable method to quantify the commutation security based on the trajectory due to the complexity of the high-voltage direct current(HVDC)model.Firstly,the characteristics of the extinction angle trajectory are analyzed under both commutation success and failure conditions.The commutation security margin index(CSMI)is then proposed for the HVDC systems.Moreover,a search strategy for parameter limits is put forward based on the sensitivity analysis of CSMI to accelerate the search speed with a guaranteed accuracy level.A modified IEEE 39-bus power system and an actual large-scale power system with 46 generators and 821 buses are utilized to verify the validity and robustness of the proposed index and strategy.
文摘This paper develops a real-time control method based on deep reinforcement learning aimed to determine the optimal control actions to maintain a sufficient secure operating limit.The secure operating limit refers to the limit to the most stressed pre-contingency operating point of an electric power system that can withstand a set of credible contingencies without violating stability criteria.The developed deep reinforcement learning method uses a hybrid control scheme that is capable of simultaneously adjusting both discrete and continuous action variables.The performance is evaluated on a modified version of the Nordic32 test system.The results show that the developed deep reinforcement learning method quickly learns an effective control policy to ensure a sufficient secure operating limit for a range of different system scenarios.The performance is also compared to a control based on a rule-based look-up table and a deep reinforcement learning control adapted for discrete action spaces.The hybrid deep reinforcement learning control managed to achieve significantly better on all of the defined test sets,indicating that the possibility of adjusting both discrete and continuous action variables resulted in a more flexible and efficient control policy.
