664 results about "Smart grid network" patented technology

The invention belongs to the field of dispatching automation systems and especially relates to a construction and application method of knowledge map of a dispatching automation system. The method comprises following steps: 1. the construction of knowledge map: the bottom-up and top-down combination method is used to construct the knowledge map of the basic platform and detailed business logic ofan intelligent grid dispatch control system; 2. the storage and maintenance of knowledge; 3. the display and application of the knowledge map: a front page shows the basic platform of the system and the detailed business knowledge map; the knowledge map of the basic platform shows the overall framework knowledge, and the knowledge map of the business logic shows the detailed logical relationship.The knowledge map constructed by the invention presents the abstract dispatching automation system business knowledge in a graphical manner, so that the user has an intuitive understanding of the business knowledge of the entire system. At the same time, users can operate the corresponding entities to selectively view the business knowledge they care about, with strong interactivity and availability.

Methods and articles of manufacture are provided. Some embodiments are directed to smart grid device authenticity verification. In an exemplary embodiment a method is provided that generates a firmware package image for a device. The method goes on to manufacture a microcontroller using the image. A ship file is then generated with unique data associated to the device. A board is then manufactured and a board ship file generated. The device is then authenticated on a network using the two ship files and the firmware image. This Abstract is provided for the sole purpose of complying with the Abstract requirement rules. This Abstract is submitted with the explicit understanding that it will not be used to interpret or to limit the scope or the meaning of the claims.

The invention relates to a multi-service real-time data integration processing system and method of an intelligent power grid. The multi-service real-time data integration processing system comprises a power control system, a power information management system and a visible platform database, and also comprises an information integration platform, wherein the information integration platform receives data of the power control and the power information management system, integrates the received data and transmits the integrated data to the visible platform database. The multi-service real-time data integration processing method is realized by a special program control module arranged on an information integration platform device, wherein the special program control module comprises a data collection module, a data filtering module, a data integrating module and a data processing module. The invention realizes a data integration service technology of a physical network-crossing and multi-service-crossing system in the field of intelligent grids, and realizes safe crossing between the power control system and the power information management system.

The invention discloses a smart power grid embedded device network detection assessment system which comprises a special network safety detection device, a shadow machine and a power system safety monitoring center. The special network safety detection device analyzes and filters various kinds of network data packs; the shadow machine detects the network state and changes of a host state of the embedded system when the embedded system is under network attack and sends the network state and host station information to the power system safety monitoring center; the power system safety monitoring center obtains a safety detection result by means of multi-dimensional property comprehensive measurement based on platform configuration property measurement, platform operation property measurement and user authentication property measurement. On the premise that normal work of the embedded system is not influenced, real-time and dynamic safety detection and assessment can be carried out on known or unknown power system network attacks quickly and accurately by means of the shadow machine.

The invention discloses a coud platform based non-intruding load monitoring system and identification method. The system comprises a hardware node, a cloud server and an intelligent terminal; the hardware node and the intelligent terminal communicate with the cloud server via a network communication module; the hardware node comprises a power supply management unit, a power metering unit, an optical coupler isolation unit, a digital pulse signal counting unit, a microcontroller and a wireless communication unit; the power supply management unit provides needed electric energy for the hardwarenode; and the power metering unit, the optical coupler isolation unit, the digital pulse signal counting unit, the microcontroller and the wireless communication unit are connected sequentially. According to the system and method, power data of a power load is collected in a non-intruding manner, the operation state of the power load is analyzed by means of the cloud server, the type of the powerload is identified, a user is guided to plan power utilization reasonably, energy saving and emission reduction can be realized, faults are eliminated timely, and the system and method become inevitable trend of development of smart grid.

The invention relates to a novel electricity consumption information acquisition system, comprising an intelligent electricity meter with an Ethernet interface, an Ethernet electricity meter concentrator, an Ethernet passive optical network (EPON) and an electricity consumption information acquisition master station, wherein the Ethernet interface of the intelligent electricity meter is connected with a first Ethernet interface of the Ethernet electricity meter concentrator; a second Ethernet interface of the Ethernet electricity meter concentrator is connected with an Ethernet interface of an optical network unit (ONU) in the Ethernet passive optical network; and an optical line unit (OLT) in the Ethernet passive optical network is connected with the electricity consumption information acquisition master station by optical fibers. By the novel electricity consumption information acquisition system, the problem that the traditional electricity consumption information acquisition mode cannot meet the development requirement of interactive service between smart electric grid and electricity consumption sectors can be solved, and the effects of high signal acquisition speed, short acquisition period and high stability can be achieved.

The invention discloses a safety control system and method applied to a smart power grid wireless sensor network and cloud computing. The safety control method comprises the steps that data are collected; whether the data are important data or unimportant data is judged; access control is performed to guarantee that the unimportant data are only transmitted to a user with access right; the important data are encrypted according to an encryption algorithm obtained through search, and therefore it is guaranteed that the important data are not illegally tampered or peeked at. According to the safety control system and method applied to the smart power grid wireless sensor network and cloud computing, an access control module is used for guaranteeing that the unimportant data are transmitted to the user with the access right; an access tree structure is adopted, so that complexity is low; the important data are encrypted through the encryption algorithm obtained through search, as a result, a third party can not know or tamper encrypted data content, it can be effectively avoided that sensing data are tampered and peeked at by the third party in the transmission process, and the integrity and confidentiality of the data are guaranteed. Due to the adoption of two safety strategies, the safety control system and method have the advantages of being high in flexibility and extendibility and the like.

The invention discloses a wireless test and data transmission system monitoring method. The method comprises the steps that a communication system which comprises a control center, a wireless data acquisition terminal and a wireless data transmission module is built, wherein the wireless data acquisition terminal can send data to the wireless data transmission module and receive data from the module; a safe communication channel is established; the wireless data acquisition terminal and the control center are in two-way connection; the control center processes and controls data into the wireless data acquisition terminal of the system; the control center completes safe verification of the wireless data acquisition terminal through the safe communication channel; if the acquisition terminal is not safe, the wireless data acquisition terminal is prevented from coming into the system for data encryption storage and exchange; and if the acquisition terminal is safe, the acquisition terminal is allowed to carry out data encryption storage and exchange. According to the monitoring method, wireless detection and transmission can be carried out on the power consumption information of an intelligent power grid user; detection continuity and accuracy of the power consumption data of the user can be ensured; and the confidentiality and the safety of power consumption information transmission can be ensured.

The invention discloses an intelligent home power consumption management system based on a smart power grid. The intelligent home power consumption management system based on the smart power grid comprises intelligent home equipment and an intelligent interaction terminal, wherein the intelligent home equipment comprises a power consumption monitoring device and a communication module, the power consumption monitoring device is electrically connected to the communication module and is used for monitoring power consumption data of electric equipment, the communication module is used for transmitting the power consumption data to the intelligent interaction terminal and receiving a control command of the intelligent interaction terminal, the intelligent home equipment operates according to the control command, and the intelligent interaction terminal generates the control command and sends the control command to the corresponding intelligent home equipment according to the power consumption data transmitted by the communication module. The intelligent home power consumption management system based on the smart power grid further comprises a rechargeable energy storage device, wherein the energy storage device is connected with the intelligent interaction terminal and the intelligent home equipment and can be charged and supply power to the intelligent home equipment, and the intelligent interaction terminal instructs the rechargeable energy storage device to be charged or supply power to the intelligent home equipment according to the power consumption condition of a user.

The invention requests to protect a privacy protection data aggregation method and system for a smart power grid. The method and system can protect the data privacy of a single user from being leakedand aggregates the sum of data in a certain area, and only a control center can read an aggregation result. The method comprises a system initialization step, a user registration step, an encrypted data generation step, a data aggregation step and a data decryption step. According to the invention, an intelligent electric meter and an aggregator negotiate a session key, and a BGN encryption algorithm based on an elliptic curve is used to encrypt the data. The method does not depend on a trusted third party, the system can still operate normally when the intelligent electric meter is missing, so that better reliability is achieved, the identity of the user is anonymous, and an attacker cannot obtain the real identity of the user. According to the method, the calculation efficiency is improved, the corresponding security requirements of confidentiality, integrity, certification and the like are met, and the security can be proved.

The invention discloses a virtual power plant economic dispatching method based on scenes and deep reinforcement learning, solves the problem of poor universality of an existing virtual power plant economic dispatching method, and belongs to the field of intelligent power grid economic dispatching. The method comprises the steps: S1, establishing a target function and corresponding constraint conditions of virtual power plant economic dispatch, so as to enable a power system to operate normally; s2, classifying the historical data into data of an extreme scene and data of a normal scene according to a set threshold value; s3, respectively expanding the data of the extreme scene and the data of the normal scene by using a generative adversarial network GAN to obtain an extreme scene data set and a normal scene data set; and S4, training the neural network by using a depth deterministic strategy gradient algorithm and taking the extreme scene data set and the normal scene data set as training sets, solving parameters of the target function, and determining an economic dispatching strategy of the virtual power plant. A virtual power plant (VPP) with energy storage and access to a power distribution network is operated stably under uncertain conditions.

The invention discloses a power grid equipment state information cloud storage system which comprises a plurality of computers and a cloud storage server cluster, wherein the computers are connected through the Internet and are arranged in all transformer substations to serve as client equipment, the cloud storage server cluster is arranged at an intelligent power grid center to serve as cloud storage end equipment, and all the computers are connected with fingerprint identification instruments. The invention further discloses a data uploading method of the power grid equipment state information cloud storage system. The uploading method includes the steps of (1) user registration, (2) file selection, (3) file transmission, (4) file receiving, (5) file encryption and (6) file storage. The invention further discloses a data downloading method of the power grid equipment state information cloud storage system. The downloading method includes the steps of (1) user certification, (2) file selection, (3) threshold restricting, (4) file decryption, (5) file transmission and (6) file receiving. By means of the power grid equipment state information cloud storage system and the data uploading and downloading methods of the power grid equipment state information cloud storage system, power grid information safety is improved, the integrity of the downloaded files is guaranteed, and the utilization rate of power grid information is increased.

The invention discloses a power terminal loophole attack detection method based on message features, and belongs to the technical field of intelligent power grid terminal equipment safety. The methodcomprises the following steps: S01, acquiring communication message data between power terminal equipment and a master station, and classifying the communication message data of the power terminal equipment in a normal working state and an attacked state into a positive sample and a negative sample; s02, performing feature extraction on the positive sample and the negative sample, and forming a sample feature vector; s03, based on the sample feature vector, selecting a classifier to perform deep neural network training, and generating a vulnerability attack detection model; s04, collecting real-time communication message data between the power terminal equipment and the main station in work; s05, performing feature extraction on the real-time communication message data, and forming a detection feature vector; and S06, inputting the detection feature vector into a vulnerability attack detection model to detect whether the power terminal is attacked or not and the attack type. Accordingto the method, the power terminal equipment is subjected to safety monitoring from a network layer, and the power grid safety is improved.

The invention relates to an intelligent distribution box which is applied to the field of power distribution in an electrical power system. The intelligent distribution box is mainly composed of a remote monitoring center, a general packet radio service (GPRS) wireless communication network and a remote terminal, wherein the a remote monitoring center is mainly composed of a personal computer (PC) and principle computer monitoring software, the GPRS wireless communication network is connected with a GPRS operator router through a service GPRS supporting node (SGSN) device, and the remote terminal is the main body of the intelligent distribution box and is mainly composed of a GPRS wireless transmission module, a collector, a control and protecting switch and a reactive compensation controller. The novel intelligent distribution box is capable of monitoring electric equipment in real time, transmitting real-time line information to the remote monitoring center through the GPRS wireless communication network, and controlling connection and disconnection of lines in real time according to commands of the remote monitoring center, and has the advantages of being simple in structure, powerful in function, capable of meeting requirements of the country for intelligent power grid construction, and the like.

The invention provides a random access method in smart power grid communication. Under the condition of not increasing additional signaling overheads, the random access collision probability is lowered, and system performance is improved. Due to the fact that multiple smart power grid devices exist and carry out data reporting frequently, the random access collision probability is greatly improved, and the random access process of a common user can be influenced. The random access process for the smart power grid scene is provided. Two different leader sequence sets are generated and used for the common user and a smart power grid respectively. One of MAC RARs is used for reserving bits for marking whether random access is from the common user or the smart power grid. Therefore, under the condition that no additional signaling overhead exists, the random access collision probability of the smart power grid can be reduced, and the random access of the common user cannot be influenced.

The invention provides single-channel TCP/ IP header compression method and system for an intelligent power grid. The method comprises the steps of respectively acquiring field information which is carried by a TCP construction message and remains unchanged in the current TCP connection life cycle through a sending end and a receiving end while constructing the TCP connection, and treating the field information as the context information for header compression; performing header compression for a TCP/ IP data packet to be transmitted through the sending end to obtain a compressed TCP/ IP data packet; sending the compressed TCP/ IP data packet to the receiving end by the sending end through a wireless link; recovering the received compressed TCP/ IP data packet into the complete TCP/ IP data packet by the receiving end according to the context information, the fixed value in the data packet, the remaining bit and the header checking method. According to the method, the header of the TCP/ IP data packet is compressed; the transmission of data messages without carrying service information in the link is avoided to the maximum; therefore, the waste of the wireless link resource is reduced, and the utilization efficiency of the wireless link is increased.

The invention relates to a digital model splicing method of an electric power setting calculating system. The digital model splicing method of the electric power setting calculating system is characterized by comprising the following steps of firstly unifying regulations of the whole grid device naming notations; secondly analyzing boundary equivalent data in each level of an power grid initial model; thirdly splitting and removing the boundary equivalent data in each level of the power grid initial model and retaining inner data in the initial model; fourthly merging the data, namely, merging the inner data in one of the power grid initial models and the actual boundary data in the adjacent power grid initial model; and fifthly exporting a splicing result to a setting calculating data center. The digital model splicing method of the electric power setting calculating system has the advantages that integration of setting calculating data and operation management is achieved and basic data unifying, model unifying, regulation unifying, standard unifying and platform unifying are achieved so that the requirements for 'source port maintenance and whole grid sharing' of an intelligent power grid are satisfied, model information setting and sharing among multi-level relay protection are achieved maximally and problems of 'information isolated island' and the like are solved.

The invention discloses a power line carrier and wireless dual-mode fusion communication method. The method adopts a communication protocol of a four-layer architecture during communication, and comprises the following steps: S1, after a communication service is generated, a physical layer performs diversity processing on input signals of a power line carrier communication channel and a wireless communication channel based on an OFDM modulation technology and outputs the input signals; S2, after receiving the data sending task, an MAC layer selects a power line carrier communication channel ora wireless communication channel to send data; S3, the network layer selects an optimal routing table path comprising a power line carrier communication channel and a wireless communication channel;and S4, an application layer collects data of the power line carrier communication channel and the wireless communication channel. The method of the power line carrier communication and wireless communication technology provided by the invention considers the advantages of the two technologies, realizes the heterogeneous converged network communication of the power line and the wireless, optimizesthe network performance, improves the collection success rate, and reduces the construction and use cost of a smart power grid.

The invention relates to a lattice implication reasoning algorithm of a bug in a partitioning protection system of a smart grid, comprising the steps of: building a lattice implication algebraic system model according to the experimental environment of the partitioning protection system of the smart grid; describing the bug in the model by a method of a concept lattice; building an automatic reasoning system of the lattice implication on the basis; reasoning and inspecting the bug of the system; and inspecting the reasoning efficiency by the experiment environment of the system. The automatic reasoning system of the boundary bug is built in the partitioning protection system of the smart grid by adopting a method that lattice implication is combined with concept lattice, so that the bug detection efficiency of the smart grid is improved.

The invention discloses a security data reporting system on the basis of Hash trees and anonymity technologies. The security data reporting system comprises four parties and seven modules. The four parties include a trusted authority (TA), a control center (CC), a gateway (GW) and a residential area (RA), and the gateway (GW) is connected with the trusted authority (TA) and the residential area (RA); the seven modules include a system initialization module, a session key agreement module, an autonomous aggregation forming module, an offline pre-computation module, an online power consumption data reporting module, a security data collecting module and a security data reading module. The security data reporting system has the advantages that the light-weight security data reporting system can be applied to intelligent power grids, accordingly, the privacy can be protected, and the integrity of communication data can be guaranteed.

The invention discloses a deep learning method for flow abnormity detection of an intelligent power grid server. According to the method, on the basis of the high-dimensional time sequence data information for monitoring the flow of a power grid server, an Encoder-Dector deep neural network based on two layers of LSTM neurons is utilized to construct the flow normal state estimation, and based onthe estimated normal flow behavior, the distribution condition of the residual error between the normal flow behavior and the measured value is analyzed, and finally a confidence interval is given asa control limit for judging the abnormal behavior, thereby realizing the detection of the abnormal flow behavior of the smart grid server. According to the method, the nonlinear relation between variables can be dynamically approximated in a self-adaptive mode, the manual intervention is not needed for selecting variable characteristics, the data dimension reduction is not needed, the certain universality is achieved, and the method has very important scientific significance and application value for preventing severe faults.