柔性交流输电系统(flexible AC transmission system,FACTS)的并网位置对电力系统的安全运行具有重要影响。本文综合考虑故障发生后的暂态与稳态过程,提出兼顾暂稳态判据的选址打分方法,在单机等面积定则基础上,推导出FACTS元件等值系...柔性交流输电系统(flexible AC transmission system,FACTS)的并网位置对电力系统的安全运行具有重要影响。本文综合考虑故障发生后的暂态与稳态过程,提出兼顾暂稳态判据的选址打分方法,在单机等面积定则基础上,推导出FACTS元件等值系统的暂态裕度量化积分,将暂态稳定裕度近似灵敏度和稳态母线电压越限危险度作为选址依据。基于FACTS元件与储能相结合技术,将有功死区控制、电池荷电状态限制和逆变器容量限制考虑进FACTS元件建模中,利用PSASP/UD自定义模块搭建具有储能作用的FACTS模型。通过电力系统分析软件PSASP中CEPRI-36节点系统进行仿真,在得分高的母线处采取FACTS元件以注入电流源形式并网参与系统紧急控制,验证本文所提选址方法的准确性及FACTS元件对抑制电力系统连锁故障扩散的影响。展开更多
This work is part of the resolution of problems encountered on a 225 KV MANGOMBE-OYOMABANG line. This line is characterized by important technical losses, so that the voltage injected in the busbar is always lower tha...This work is part of the resolution of problems encountered on a 225 KV MANGOMBE-OYOMABANG line. This line is characterized by important technical losses, so that the voltage injected in the busbar is always lower than 200kV. The main objective of this work is to show the new solutions that can provide a combined FACTS-STATCOM and IPC 240 dual system on this line. Then to show the limitation of STATCOM compared to RPI 240. The results obtained allowed us to observe that in symmetrical operation the STATCOM improves the voltage profile on the busbar and in asymmetrical operation we found that it continues to regulate the voltage of each phase despite the unbalance. But the system remains too unbalanced because of the sequence current flow. The IPC 240 corrects this limitation, allowing asymmetrical operation of the line in an emergency while providing continuous service to the load.展开更多
Knowledge graph(KG)fact prediction aims to complete a KG by determining the truthfulness of predicted triples.Reinforcement learning(RL)-based approaches have been widely used for fact prediction.However,the existing ...Knowledge graph(KG)fact prediction aims to complete a KG by determining the truthfulness of predicted triples.Reinforcement learning(RL)-based approaches have been widely used for fact prediction.However,the existing approaches largely suffer from unreliable calculations on rule confidences owing to a limited number of obtained reasoning paths,thereby resulting in unreliable decisions on prediction triples.Hence,we propose a new RL-based approach named EvoPath in this study.EvoPath features a new reward mechanism based on entity heterogeneity,facilitating an agent to obtain effective reasoning paths during random walks.EvoPath also incorporates a new postwalking mechanism to leverage easily overlooked but valuable reasoning paths during RL.Both mechanisms provide sufficient reasoning paths to facilitate the reliable calculations of rule confidences,enabling EvoPath to make precise judgments about the truthfulness of prediction triples.Experiments demonstrate that EvoPath can achieve more accurate fact predictions than existing approaches.展开更多
文摘柔性交流输电系统(flexible AC transmission system,FACTS)的并网位置对电力系统的安全运行具有重要影响。本文综合考虑故障发生后的暂态与稳态过程,提出兼顾暂稳态判据的选址打分方法,在单机等面积定则基础上,推导出FACTS元件等值系统的暂态裕度量化积分,将暂态稳定裕度近似灵敏度和稳态母线电压越限危险度作为选址依据。基于FACTS元件与储能相结合技术,将有功死区控制、电池荷电状态限制和逆变器容量限制考虑进FACTS元件建模中,利用PSASP/UD自定义模块搭建具有储能作用的FACTS模型。通过电力系统分析软件PSASP中CEPRI-36节点系统进行仿真,在得分高的母线处采取FACTS元件以注入电流源形式并网参与系统紧急控制,验证本文所提选址方法的准确性及FACTS元件对抑制电力系统连锁故障扩散的影响。
文摘This work is part of the resolution of problems encountered on a 225 KV MANGOMBE-OYOMABANG line. This line is characterized by important technical losses, so that the voltage injected in the busbar is always lower than 200kV. The main objective of this work is to show the new solutions that can provide a combined FACTS-STATCOM and IPC 240 dual system on this line. Then to show the limitation of STATCOM compared to RPI 240. The results obtained allowed us to observe that in symmetrical operation the STATCOM improves the voltage profile on the busbar and in asymmetrical operation we found that it continues to regulate the voltage of each phase despite the unbalance. But the system remains too unbalanced because of the sequence current flow. The IPC 240 corrects this limitation, allowing asymmetrical operation of the line in an emergency while providing continuous service to the load.
基金the National Natural Science Foundation of China,Nos.62272480 and 62072470and the National Science Foundation of Hunan Province,Nos.2021JJ30881 and 2020JJ4758.
文摘Knowledge graph(KG)fact prediction aims to complete a KG by determining the truthfulness of predicted triples.Reinforcement learning(RL)-based approaches have been widely used for fact prediction.However,the existing approaches largely suffer from unreliable calculations on rule confidences owing to a limited number of obtained reasoning paths,thereby resulting in unreliable decisions on prediction triples.Hence,we propose a new RL-based approach named EvoPath in this study.EvoPath features a new reward mechanism based on entity heterogeneity,facilitating an agent to obtain effective reasoning paths during random walks.EvoPath also incorporates a new postwalking mechanism to leverage easily overlooked but valuable reasoning paths during RL.Both mechanisms provide sufficient reasoning paths to facilitate the reliable calculations of rule confidences,enabling EvoPath to make precise judgments about the truthfulness of prediction triples.Experiments demonstrate that EvoPath can achieve more accurate fact predictions than existing approaches.
