The rapid development of Internet Plus Smart Energy requires further strengthening of three kinds of interconnections based on traditional power systems: physical interconnection, information interconnection, and comm...The rapid development of Internet Plus Smart Energy requires further strengthening of three kinds of interconnections based on traditional power systems: physical interconnection, information interconnection, and commercial interconnection. Due to the integration of renewable energy, the reform of the electricity market, and the deployment of the Smart Grid, a large amount of data will be generated. Thus, it is necessary to establish a Ubiquitous Power Internet of Things (UPIoT) to realize connections among people and things, things and things, and people and people in power systems. This paper studies the concept and architecture of the UPIoT and indicates the deployment of the perception layer and network layer as the key to building UPIoT in the initial stage. As UPIoT tends to cover a wide area and produce massive and distributed data, signal processing and data analytics theories and techniques are needed to handle the data and observe the state of the large-scale system. Further studies on distributed sensing and cooperative estimation theories and techniques of UPIoT are also required. Finally, the application prospects of UPIoT and the directions for future research are discussed.展开更多
In order to have an accurate knowledge of system-wide operation states,it is necessary to perform state estimation for the integrated energy system(IES)as the basis of energy man-agement and control.Centralized state ...In order to have an accurate knowledge of system-wide operation states,it is necessary to perform state estimation for the integrated energy system(IES)as the basis of energy man-agement and control.Centralized state estimation is practically infeasible for IES due to the unreliability of communication,the barrier on privacy,and the large scale of integrated systems.This paper proposes a distributed state estimation algorithm based on the alternating direction method of multipliers(ADMM)for IES containing electricity,heat,and natural gas.Various coupling units are taken into full consideration in modeling of IES state estimation to reflect the harmonization of multi energy.On the basis of bilinear measurement model,the state estimation considering nonlinear measurements can be replaced by an equivalent three-stage problem containing two linear state estimations and an intermediate transformation to avoid non-convex optimization.The three-stage procedure for IES state estimation can be further decoupled over three sub-systems with coordination on coupling units,yielding a fully distributed scheme based on ADMM.A modified ADMM with the self-adjusting penalty parameter is also adopted to enhance the convergence.Simulation results demonstrate the validity and superiority of the proposed algorithm.展开更多
Geographic location of nodes is very useful in a sensor network. Previous localization algorithms assume that there exist some anchor nodes in this kind of network, and then other nodes are estimated to create their c...Geographic location of nodes is very useful in a sensor network. Previous localization algorithms assume that there exist some anchor nodes in this kind of network, and then other nodes are estimated to create their coordinates. Once there are not anchors to be deployed, those localization algorithms will be invalidated. Many papers in this field focus on anchor-based solutions. The use of anchors introduces many limitations, since anchors require external equipments such as global position system, cause additional power consumption. A novel positioning algorithm is proposed to use a virtual coordinate system based on a new concept--virtual anchor. It is executed in a distributed fashion according to the connectivity of a node and the measured distances to its neighbors. Both the adjacent member information and the ranging distance result are combined to generate the estimated position of a network, one of which is independently adopted for localization previously. At the position refinement stage the intermediate estimation of a node begins to be evaluated on its reliability for position mutation; thus the positioning optimization process of the whole network is avoided falling into a local optimal solution. Simulation results prove that the algorithm can resolve the distributed localization problem for anchor-free sensor networks, and is superior to previous methods in terms of its positioning capability under a variety of circumstances.展开更多
基金Supported by National Key Research and DevelopmentProgram of China(2016YFB0900100).
文摘The rapid development of Internet Plus Smart Energy requires further strengthening of three kinds of interconnections based on traditional power systems: physical interconnection, information interconnection, and commercial interconnection. Due to the integration of renewable energy, the reform of the electricity market, and the deployment of the Smart Grid, a large amount of data will be generated. Thus, it is necessary to establish a Ubiquitous Power Internet of Things (UPIoT) to realize connections among people and things, things and things, and people and people in power systems. This paper studies the concept and architecture of the UPIoT and indicates the deployment of the perception layer and network layer as the key to building UPIoT in the initial stage. As UPIoT tends to cover a wide area and produce massive and distributed data, signal processing and data analytics theories and techniques are needed to handle the data and observe the state of the large-scale system. Further studies on distributed sensing and cooperative estimation theories and techniques of UPIoT are also required. Finally, the application prospects of UPIoT and the directions for future research are discussed.
文摘In order to have an accurate knowledge of system-wide operation states,it is necessary to perform state estimation for the integrated energy system(IES)as the basis of energy man-agement and control.Centralized state estimation is practically infeasible for IES due to the unreliability of communication,the barrier on privacy,and the large scale of integrated systems.This paper proposes a distributed state estimation algorithm based on the alternating direction method of multipliers(ADMM)for IES containing electricity,heat,and natural gas.Various coupling units are taken into full consideration in modeling of IES state estimation to reflect the harmonization of multi energy.On the basis of bilinear measurement model,the state estimation considering nonlinear measurements can be replaced by an equivalent three-stage problem containing two linear state estimations and an intermediate transformation to avoid non-convex optimization.The three-stage procedure for IES state estimation can be further decoupled over three sub-systems with coordination on coupling units,yielding a fully distributed scheme based on ADMM.A modified ADMM with the self-adjusting penalty parameter is also adopted to enhance the convergence.Simulation results demonstrate the validity and superiority of the proposed algorithm.
基金the National Natural Science Foundation of China (60673054, 60773129)theExcellent Youth Science and Technology Foundation of Anhui Province of China.
文摘Geographic location of nodes is very useful in a sensor network. Previous localization algorithms assume that there exist some anchor nodes in this kind of network, and then other nodes are estimated to create their coordinates. Once there are not anchors to be deployed, those localization algorithms will be invalidated. Many papers in this field focus on anchor-based solutions. The use of anchors introduces many limitations, since anchors require external equipments such as global position system, cause additional power consumption. A novel positioning algorithm is proposed to use a virtual coordinate system based on a new concept--virtual anchor. It is executed in a distributed fashion according to the connectivity of a node and the measured distances to its neighbors. Both the adjacent member information and the ranging distance result are combined to generate the estimated position of a network, one of which is independently adopted for localization previously. At the position refinement stage the intermediate estimation of a node begins to be evaluated on its reliability for position mutation; thus the positioning optimization process of the whole network is avoided falling into a local optimal solution. Simulation results prove that the algorithm can resolve the distributed localization problem for anchor-free sensor networks, and is superior to previous methods in terms of its positioning capability under a variety of circumstances.
