The unreasonable observation arrangements in the satellite operation control center(SOCC)may result in the observation data cannot be downloaded as scheduled.Meanwhile,if the operation instructions released by the sat...The unreasonable observation arrangements in the satellite operation control center(SOCC)may result in the observation data cannot be downloaded as scheduled.Meanwhile,if the operation instructions released by the satellite telemetry tracking center(STTC)for the on-board payloads are not injected on the specific satellites in time,the corresponding satellites cannot perform the observation operations as planned.Therefore,there is an urgent need to design an integrated instruction release,and observation task planning(I-IRO-TP)scheme by efficiently collaborating the SOCC and STTC.Motivated by this fact,we design an interaction mechanism between the SOCC and the STTC,where we first formulate the I-IRO-TP problem as a constraint satisfaction problem aiming at maximizing the number of completed tasks.Furthermore,we propose an interactive imaging task planning algorithm based on the analysis of resource distribution in the STTC during the previous planning periods to preferentially select the observation arcs that not only satisfy the requirements in the observation resource allocation phase but also facilitate the arrangement of measurement and control instruction release.We conduct extensive simulations to demonstrate the effectiveness of the proposed algorithm in terms of the number of completed tasks.展开更多
The limitations of the conventional master-slavesplitting(MSS)method,which is commonly applied to power flow and optimal power flow in integrated transmission and distribution(I-T&D)networks,are first analyzed.Con...The limitations of the conventional master-slavesplitting(MSS)method,which is commonly applied to power flow and optimal power flow in integrated transmission and distribution(I-T&D)networks,are first analyzed.Considering that the MSS method suffers from a slow convergence rate or even divergence under some circumstances,a least-squares-based iterative(LSI)method is proposed.Compared with the MSS method,the LSI method modifies the iterative variables in each iteration by solving a least-squares problem with the information in previous iterations.A practical implementation and a parameter tuning strategy for the LSI method are discussed.Furthermore,a LSI-PF method is proposed to solve I-T&D power flow and a LSIheterogeneous decomposition(LSI-HGD)method is proposed to solve optimal power flow.Numerical experiments demonstrate that the proposed LSI-PF and LSI-HGD methods can achieve the same accuracy as the benchmark methods.Meanwhile,these LSI methods,with appropriate settings,significantly enhance the convergence and efficiency of conventional methods.Also,in some cases,where conventional methods diverge,these LSI methods can still converge.展开更多
The efficient integration of satellite and terrestrial networks has become an important component for 6 G wireless architectures to provide highly reliable and secure connectivity over a wide geographical area.As the ...The efficient integration of satellite and terrestrial networks has become an important component for 6 G wireless architectures to provide highly reliable and secure connectivity over a wide geographical area.As the satellite and cellular networks are developed separately these years,the integrated network should synergize the communication,storage,computation capabilities of both sides towards an intelligent system more than mere consideration of coexistence.This has motivated us to develop double-edge intelligent integrated satellite and terrestrial networks(DILIGENT).Leveraging the boost development of multi-access edge computing(MEC)technology and artificial intelligence(AI),the framework is entitled with the systematic learning and adaptive network management of satellite and cellular networks.In this article,we provide a brief review of the state-of-art contributions from the perspective of academic research and standardization.Then we present the overall design of the proposed DILIGENT architecture,where the advantages are discussed and summarized.Strategies of task offloading,content caching and distribution are presented.Numerical results show that the proposed network architecture outperforms the existing integrated networks.展开更多
To satisfy the requirements of accurate operationalrisk assessment of integrated transmission and distribution networks (I-T&D), an integrated operational risk assessment (IORA) algorithm is proposed. Specific cas...To satisfy the requirements of accurate operationalrisk assessment of integrated transmission and distribution networks (I-T&D), an integrated operational risk assessment (IORA) algorithm is proposed. Specific cases demonstrate thatan I-ORA is necessary because it provides accurate handlingof the coupling between transmission and distribution networks,accurate analysis of power supply mode (PSM) changes ofimportant users and helps to improve security and stability ofpower grid operations. Two key technical requirements in theI-ORA algorithm are realized, i.e., integrated topology analysisand integrated power flow calculation. Under a certain contingency, integrated topology analysis is used to assess the risksof substation power cuts, network split and PSM changes ofimportant users, while the integrated power flow calculation,based on the self-adaptive Levenburg-Marquard method andNewton method, can be implemented to assess risks of heavyload/overload and voltage deviation. In addition, the graphicsprocessing unit is used to parallelly process some computationintensive steps. Numerical experiments show that the proposedI-ORA algorithm can realize accurate assessment for the entireI-T&D. In addition, the efficiency and convergence are satisfying,indicating the proposed I-ORA algorithm can significantly benefitreal practice in the coordination operation of I-T&D in the future.展开更多
随着大量分布式能源的接入,配电系统的运行与控制方式愈加复杂。针对配电网状态估计方法面临分布式电源波动数据辨识困难、估计精度低、鲁棒性与估计时效性差等问题,提出一种基于集成深度神经网络的配电网分布式状态估计方法。首先,利...随着大量分布式能源的接入,配电系统的运行与控制方式愈加复杂。针对配电网状态估计方法面临分布式电源波动数据辨识困难、估计精度低、鲁棒性与估计时效性差等问题,提出一种基于集成深度神经网络的配电网分布式状态估计方法。首先,利用量测数据相关性检验的数据辨识技术识别不良数据和新能源波动数据。在此基础上,利用时域卷积网络(temporal convolutional network,TCN)-双向长短期记忆网络(bidirectional long short term memory,BILSTM)对不良数据进行修正。然后,建立集成深度神经网络(deep neural network,DNN)状态估计模型,采用最大相关-最小冗余(maximum relevance-minimum redundancy,MRMR)的方法优化训练样本,从而提高状态估计的精度和鲁棒性。最后,建立分布式集成深度神经网络模型,弥补了集中式状态估计速度慢的不足,从而提高状态估计效率。基于IEEE123配电网的算例分析表明,所提方法能更准确地辨识分布式电源波动数据和不良数据,同时提高状态估计的精度和效率,且具有较高的鲁棒性。展开更多
随着智能电网的快速发展,配电网中信息物理耦合关系日益紧密。这种耦合性使得配电网更容易被多方面极端事件所影响,在通信网络发生故障时会降低系统的态势感知和控制能力,从而制约配电网的灾后负荷恢复能力,因此通信网络恢复对灾后配电...随着智能电网的快速发展,配电网中信息物理耦合关系日益紧密。这种耦合性使得配电网更容易被多方面极端事件所影响,在通信网络发生故障时会降低系统的态势感知和控制能力,从而制约配电网的灾后负荷恢复能力,因此通信网络恢复对灾后配电网负荷恢复至关重要。该文提出一种通信网络恢复和负荷恢复的协同优化决策方案,该方案将环网通信网络与软件定义网络(software defined networking,SDN)技术相结合,灵活恢复灾后的配电网通信网络,进而控制配电网拓扑重构形成以分布式电源为中心的微电网以恢复负荷电力供应,并进一步使用一种信息物理协同的启发式计算方法实现恢复方案的快速计算。最后,使用IEEE 33节点和IEEE 123节点测试系统验证所提出方法的优点和有效性。展开更多
为充分挖掘综合能源微网(integrated energy microgrid, IEM)的潜在价值,促进可再生能源消纳,针对同一配电网下的多个IEM协同管理问题进行研究,提出了一种基于双层博弈的配电网-多IEM协同优化模型。对于IEM模型的构建,考虑在热电联产机...为充分挖掘综合能源微网(integrated energy microgrid, IEM)的潜在价值,促进可再生能源消纳,针对同一配电网下的多个IEM协同管理问题进行研究,提出了一种基于双层博弈的配电网-多IEM协同优化模型。对于IEM模型的构建,考虑在热电联产机组中加入碳捕集系统以及电转气装置,用来获取低碳效益。同时,针对IEM中可再生能源与负荷不确定性问题,采用鲁棒区间规划进行处理。首先,构建配电网运营商(distribution system operator,DSO)与IEM联盟系统模型框架,分析其不同主体间的博弈关系。其次,对于双层博弈,分为主从博弈与合作博弈。DSO作为博弈领导者,以自身效益最大为目标制定电价引导IEM联盟响应。IEM联盟作为博弈跟随者,以自身运行成本最小为目标,通过成员间互相合作能源共享响应DSO的决策。同时采用纳什谈判理论解决IEM联盟的合作运行问题,使用二分法与交替方向乘子法结合求解模型。最后,在算例中验证所提模型与方法的可行性和有效性。展开更多
碳达峰碳中和的背景下、主动配电网(active distribution network,ADN)下多主体间能源共享有助于消纳弃风弃光。但随着各微网内风机光伏容量日益增加,每日微网净负荷峰谷趋势变化明显。传统分时电价逐渐很难发挥对微网的削峰填谷作用。...碳达峰碳中和的背景下、主动配电网(active distribution network,ADN)下多主体间能源共享有助于消纳弃风弃光。但随着各微网内风机光伏容量日益增加,每日微网净负荷峰谷趋势变化明显。传统分时电价逐渐很难发挥对微网的削峰填谷作用。提出考虑主动配电网下多主体能源共享调度策略,以主动配电网向下级微网的售电收益减去向主网购电成本所得净收益最大为目标函数,充分考虑下级多微网在电网议价下以微网自身运行成本最低为目标的调度自主性,运用卡罗需-库恩-塔克(Karush-Kuhn-Tucker,KKT)条件将下级多主体电能共享联盟运行成本最低的目标转化为上级目标的约束条件。引入KKT乘子,同时运用大M法对非线性约束进行线性化处理,提高模型求解速度。在MATLAB的Gurobi环境下,对连续的上下层耦合变量乘积进行离散化处理。最后,在IEEE33节点的主动配电网算例中验证所提模型的有效性。展开更多
基金supported by the Natural Science Foundation of China under Grants U19B2025,62121001,and 62001347in part by Key Research and Development Program of Shaanxi(ProgramNo.2022ZDLGY05-02)in part by Young Talent Support Program of Xi’an Association for Science and Technology(No.095920221337).
文摘The unreasonable observation arrangements in the satellite operation control center(SOCC)may result in the observation data cannot be downloaded as scheduled.Meanwhile,if the operation instructions released by the satellite telemetry tracking center(STTC)for the on-board payloads are not injected on the specific satellites in time,the corresponding satellites cannot perform the observation operations as planned.Therefore,there is an urgent need to design an integrated instruction release,and observation task planning(I-IRO-TP)scheme by efficiently collaborating the SOCC and STTC.Motivated by this fact,we design an interaction mechanism between the SOCC and the STTC,where we first formulate the I-IRO-TP problem as a constraint satisfaction problem aiming at maximizing the number of completed tasks.Furthermore,we propose an interactive imaging task planning algorithm based on the analysis of resource distribution in the STTC during the previous planning periods to preferentially select the observation arcs that not only satisfy the requirements in the observation resource allocation phase but also facilitate the arrangement of measurement and control instruction release.We conduct extensive simulations to demonstrate the effectiveness of the proposed algorithm in terms of the number of completed tasks.
基金supported by the National Natural Science Foundation of China(52077193).
文摘The limitations of the conventional master-slavesplitting(MSS)method,which is commonly applied to power flow and optimal power flow in integrated transmission and distribution(I-T&D)networks,are first analyzed.Considering that the MSS method suffers from a slow convergence rate or even divergence under some circumstances,a least-squares-based iterative(LSI)method is proposed.Compared with the MSS method,the LSI method modifies the iterative variables in each iteration by solving a least-squares problem with the information in previous iterations.A practical implementation and a parameter tuning strategy for the LSI method are discussed.Furthermore,a LSI-PF method is proposed to solve I-T&D power flow and a LSIheterogeneous decomposition(LSI-HGD)method is proposed to solve optimal power flow.Numerical experiments demonstrate that the proposed LSI-PF and LSI-HGD methods can achieve the same accuracy as the benchmark methods.Meanwhile,these LSI methods,with appropriate settings,significantly enhance the convergence and efficiency of conventional methods.Also,in some cases,where conventional methods diverge,these LSI methods can still converge.
基金supportedin part by the National Science Foundation of China(NSFC)under Grant 61631005,Grant 61771065,Grant 61901048in part by the Zhijiang Laboratory Open Project Fund 2020LCOAB01in part by the Beijing Municipal Science and Technology Commission Research under Project Z181100003218015。
文摘The efficient integration of satellite and terrestrial networks has become an important component for 6 G wireless architectures to provide highly reliable and secure connectivity over a wide geographical area.As the satellite and cellular networks are developed separately these years,the integrated network should synergize the communication,storage,computation capabilities of both sides towards an intelligent system more than mere consideration of coexistence.This has motivated us to develop double-edge intelligent integrated satellite and terrestrial networks(DILIGENT).Leveraging the boost development of multi-access edge computing(MEC)technology and artificial intelligence(AI),the framework is entitled with the systematic learning and adaptive network management of satellite and cellular networks.In this article,we provide a brief review of the state-of-art contributions from the perspective of academic research and standardization.Then we present the overall design of the proposed DILIGENT architecture,where the advantages are discussed and summarized.Strategies of task offloading,content caching and distribution are presented.Numerical results show that the proposed network architecture outperforms the existing integrated networks.
基金the State Grid Zhejiang Electric Power Co.,Ltd.(Science and Technology Project under Grant 5211JH180081:Research on security evaluation and control technology of smart platform based on dispatch cloud.)。
文摘To satisfy the requirements of accurate operationalrisk assessment of integrated transmission and distribution networks (I-T&D), an integrated operational risk assessment (IORA) algorithm is proposed. Specific cases demonstrate thatan I-ORA is necessary because it provides accurate handlingof the coupling between transmission and distribution networks,accurate analysis of power supply mode (PSM) changes ofimportant users and helps to improve security and stability ofpower grid operations. Two key technical requirements in theI-ORA algorithm are realized, i.e., integrated topology analysisand integrated power flow calculation. Under a certain contingency, integrated topology analysis is used to assess the risksof substation power cuts, network split and PSM changes ofimportant users, while the integrated power flow calculation,based on the self-adaptive Levenburg-Marquard method andNewton method, can be implemented to assess risks of heavyload/overload and voltage deviation. In addition, the graphicsprocessing unit is used to parallelly process some computationintensive steps. Numerical experiments show that the proposedI-ORA algorithm can realize accurate assessment for the entireI-T&D. In addition, the efficiency and convergence are satisfying,indicating the proposed I-ORA algorithm can significantly benefitreal practice in the coordination operation of I-T&D in the future.
文摘随着大量分布式能源的接入,配电系统的运行与控制方式愈加复杂。针对配电网状态估计方法面临分布式电源波动数据辨识困难、估计精度低、鲁棒性与估计时效性差等问题,提出一种基于集成深度神经网络的配电网分布式状态估计方法。首先,利用量测数据相关性检验的数据辨识技术识别不良数据和新能源波动数据。在此基础上,利用时域卷积网络(temporal convolutional network,TCN)-双向长短期记忆网络(bidirectional long short term memory,BILSTM)对不良数据进行修正。然后,建立集成深度神经网络(deep neural network,DNN)状态估计模型,采用最大相关-最小冗余(maximum relevance-minimum redundancy,MRMR)的方法优化训练样本,从而提高状态估计的精度和鲁棒性。最后,建立分布式集成深度神经网络模型,弥补了集中式状态估计速度慢的不足,从而提高状态估计效率。基于IEEE123配电网的算例分析表明,所提方法能更准确地辨识分布式电源波动数据和不良数据,同时提高状态估计的精度和效率,且具有较高的鲁棒性。
文摘随着智能电网的快速发展,配电网中信息物理耦合关系日益紧密。这种耦合性使得配电网更容易被多方面极端事件所影响,在通信网络发生故障时会降低系统的态势感知和控制能力,从而制约配电网的灾后负荷恢复能力,因此通信网络恢复对灾后配电网负荷恢复至关重要。该文提出一种通信网络恢复和负荷恢复的协同优化决策方案,该方案将环网通信网络与软件定义网络(software defined networking,SDN)技术相结合,灵活恢复灾后的配电网通信网络,进而控制配电网拓扑重构形成以分布式电源为中心的微电网以恢复负荷电力供应,并进一步使用一种信息物理协同的启发式计算方法实现恢复方案的快速计算。最后,使用IEEE 33节点和IEEE 123节点测试系统验证所提出方法的优点和有效性。
文摘为充分挖掘综合能源微网(integrated energy microgrid, IEM)的潜在价值,促进可再生能源消纳,针对同一配电网下的多个IEM协同管理问题进行研究,提出了一种基于双层博弈的配电网-多IEM协同优化模型。对于IEM模型的构建,考虑在热电联产机组中加入碳捕集系统以及电转气装置,用来获取低碳效益。同时,针对IEM中可再生能源与负荷不确定性问题,采用鲁棒区间规划进行处理。首先,构建配电网运营商(distribution system operator,DSO)与IEM联盟系统模型框架,分析其不同主体间的博弈关系。其次,对于双层博弈,分为主从博弈与合作博弈。DSO作为博弈领导者,以自身效益最大为目标制定电价引导IEM联盟响应。IEM联盟作为博弈跟随者,以自身运行成本最小为目标,通过成员间互相合作能源共享响应DSO的决策。同时采用纳什谈判理论解决IEM联盟的合作运行问题,使用二分法与交替方向乘子法结合求解模型。最后,在算例中验证所提模型与方法的可行性和有效性。
文摘碳达峰碳中和的背景下、主动配电网(active distribution network,ADN)下多主体间能源共享有助于消纳弃风弃光。但随着各微网内风机光伏容量日益增加,每日微网净负荷峰谷趋势变化明显。传统分时电价逐渐很难发挥对微网的削峰填谷作用。提出考虑主动配电网下多主体能源共享调度策略,以主动配电网向下级微网的售电收益减去向主网购电成本所得净收益最大为目标函数,充分考虑下级多微网在电网议价下以微网自身运行成本最低为目标的调度自主性,运用卡罗需-库恩-塔克(Karush-Kuhn-Tucker,KKT)条件将下级多主体电能共享联盟运行成本最低的目标转化为上级目标的约束条件。引入KKT乘子,同时运用大M法对非线性约束进行线性化处理,提高模型求解速度。在MATLAB的Gurobi环境下,对连续的上下层耦合变量乘积进行离散化处理。最后,在IEEE33节点的主动配电网算例中验证所提模型的有效性。