CN112562286A - Cloud computing-based power grid material management system - Google Patents

Cloud computing-based power grid material management system Download PDF

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CN112562286A
CN112562286A CN202011424173.8A CN202011424173A CN112562286A CN 112562286 A CN112562286 A CN 112562286A CN 202011424173 A CN202011424173 A CN 202011424173A CN 112562286 A CN112562286 A CN 112562286A
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power grid
storage environment
material management
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CN112562286B (en
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俞容江
张睿
计建仁
诸吉祥
杨先进
应雪正
魏俊
胡健
朱小燕
何云
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Hangzhou Electric Power Design Institute Co ltd
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/18—Status alarms
    • G08B21/24—Reminder alarms, e.g. anti-loss alarms
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
    • H—ELECTRICITY
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    • H—ELECTRICITY
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    • H04W—WIRELESS COMMUNICATION NETWORKS
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
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    • H04W40/24—Connectivity information management, e.g. connectivity discovery or connectivity update
    • H04W40/32—Connectivity information management, e.g. connectivity discovery or connectivity update for defining a routing cluster membership
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

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Abstract

The invention provides a cloud computing-based power grid material management system, which comprises a data acquisition module, a data transmission module, a cloud platform and a user terminal, wherein the data acquisition module is used for acquiring data; the data acquisition module is used for acquiring storage environment data of the electric power materials; the data transmission module is used for transmitting the storage environment data to the cloud platform; the cloud platform is used for judging whether the storage environment data exceeds a preset threshold range to obtain a judgment result and sending the judgment result to the user terminal; and the user terminal is used for displaying the judgment result to power grid material management personnel and sending an alarm prompt to the power grid material management personnel when the judgment result shows that the storage environment data exceeds a preset threshold range. According to the invention, while traditional management is carried out on materials, monitoring on the storage environment of the materials is realized, and the damage to the materials of the power grid caused by deterioration of the storage environment is avoided.

Description

Cloud computing-based power grid material management system
Technical Field
The invention relates to the field of management, in particular to a power grid material management system based on cloud computing.
Background
In the prior art, a system for managing power grid materials in a warehouse is generally only suitable for management such as warehouse-out and warehouse-in, the environment for storing the power grid materials is not correspondingly monitored, the deterioration of the storage environment cannot be timely found and corresponding management measures cannot be taken, and the power grid materials are easily damaged due to the deterioration of the storage environment.
Disclosure of Invention
In view of the above problems, the present invention aims to provide a power grid material management system based on cloud computing.
The invention provides a cloud computing-based power grid material management system, which comprises a data acquisition module, a data transmission module, a cloud platform and a user terminal, wherein the data acquisition module is used for acquiring data;
the data acquisition module is used for acquiring storage environment data of the electric power materials and transmitting the storage environment data to the data transmission module;
the data transmission module is used for transmitting the storage environment data to the cloud platform;
the cloud platform is used for judging whether the storage environment data exceeds a preset threshold range to obtain a judgment result and sending the judgment result to the user terminal;
and the user terminal is used for displaying the judgment result to power grid material management personnel and sending an alarm prompt to the power grid material management personnel when the judgment result shows that the storage environment data exceeds a preset threshold range.
Preferably, the data acquisition module comprises an in-warehouse data acquisition unit, an out-warehouse data acquisition unit and a storage environment data acquisition unit;
the warehousing data acquisition unit is used for acquiring warehousing data of the warehoused power grid materials and transmitting the warehousing data to the data transmission module;
the ex-warehouse data acquisition unit is used for acquiring warehousing data of ex-warehouse power grid materials and transmitting the warehousing data to the data transmission module;
the storage environment data acquisition unit is used for acquiring storage environment data of the electric power materials and transmitting the storage environment data to the data transmission module.
Preferably, the warehousing data comprises the type, the quantity and the storage position of the warehoused power grid materials;
the ex-warehouse data comprises the types and the quantity of the electric power grid materials to be ex-warehouse;
the storage environment data comprises temperature, humidity and dangerous gas concentration in a warehouse for storing power grid materials.
Preferably, the data transmission module is further configured to send the warehousing data and the ex-warehouse data to the cloud platform.
Preferably, the cloud platform comprises a storage unit, a material management unit and an environment monitoring unit;
the storage unit is used for storing the warehousing data, the ex-warehouse data and the storage environment data;
the material management unit is used for updating corresponding warehousing data in the storage unit according to the ex-warehouse data;
the environment monitoring unit is used for judging whether the storage environment data exceeds a preset threshold range to obtain a judgment result and sending the judgment result to the user terminal.
Preferably, the user terminal comprises a display module and an alarm prompt module;
the display module is used for displaying the judgment result to power grid material management personnel;
and the alarm prompt module is used for sending an alarm prompt to the power grid material management personnel when the judgment result shows that the storage environment data exceeds a preset threshold range.
Compared with the prior art, the invention has the advantages that:
according to the invention, while traditional management is carried out on materials, monitoring of the storage environment of the materials is realized, and an alarm prompt is sent to power grid material management personnel when the storage environment data is abnormal, so that the power grid material management personnel can conveniently make corresponding treatment measures in time, and further the damage of the power grid material due to the deterioration of the storage environment is prevented.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
Fig. 1 is a diagram of an exemplary embodiment of a cloud computing-based power grid material management system according to the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
The invention provides a cloud computing-based power grid material management system, which comprises a data acquisition module, a data transmission module, a cloud platform and a user terminal, wherein the data acquisition module is used for acquiring data;
the data acquisition module is used for acquiring storage environment data of the electric power materials and transmitting the storage environment data to the data transmission module;
the data transmission module is used for transmitting the storage environment data to the cloud platform;
the cloud platform is used for judging whether the storage environment data exceeds a preset threshold range to obtain a judgment result and sending the judgment result to the user terminal;
and the user terminal is used for displaying the judgment result to power grid material management personnel and sending an alarm prompt to the power grid material management personnel when the judgment result shows that the storage environment data exceeds a preset threshold range.
Because the cloud platform is not local, a data transmission module is needed to forward the storage environment data and remotely transmit the storage environment data to the cloud platform.
Preferably, the data acquisition module comprises an in-warehouse data acquisition unit, an out-warehouse data acquisition unit and a storage environment data acquisition unit;
the warehousing data acquisition unit is used for acquiring warehousing data of the warehoused power grid materials and transmitting the warehousing data to the data transmission module;
the ex-warehouse data acquisition unit is used for acquiring warehousing data of ex-warehouse power grid materials and transmitting the warehousing data to the data transmission module;
the storage environment data acquisition unit is used for acquiring storage environment data of the electric power materials and transmitting the storage environment data to the data transmission module.
Preferably, the warehousing data comprises the type, the quantity and the storage position of the warehoused power grid materials;
the ex-warehouse data comprises the types and the quantity of the electric power grid materials to be ex-warehouse;
the storage environment data comprises temperature, humidity and dangerous gas concentration in a warehouse for storing power grid materials.
Hazardous gases including methane, hydrogen, and the like.
Preferably, the data transmission module is further configured to send the warehousing data and the ex-warehouse data to the cloud platform.
Preferably, the cloud platform comprises a storage unit, a material management unit and an environment monitoring unit;
the storage unit is used for storing the warehousing data, the ex-warehouse data and the storage environment data;
the material management unit is used for updating corresponding warehousing data in the storage unit according to the ex-warehouse data;
the environment monitoring unit is used for judging whether the storage environment data exceeds a preset threshold range to obtain a judgment result and sending the judgment result to the user terminal.
Updating the corresponding warehousing data in the storage unit according to the ex-warehouse data, wherein the updating comprises the following steps: for example, for the same type of material with the same storage location, the warehouse-in quantity is subtracted from the warehouse-out quantity, so as to obtain the existing inventory quantity, that is, the updated warehouse-in data.
Preferably, the user terminal comprises a display module and an alarm prompt module;
the display module is used for displaying the judgment result to power grid material management personnel;
and the alarm prompt module is used for sending an alarm prompt to the power grid material management personnel when the judgment result shows that the storage environment data exceeds a preset threshold range.
The alarm prompt comprises a pop-up window prompt, an alarm sound prompt and the like, wherein the alarm sound is a recorded sound in advance.
Preferably, the storage environment data acquisition unit comprises a wireless sensor node and a base station; the wireless sensor node is used for acquiring the storage environment data and sending the storage environment data to the base station;
the base station is used for receiving the storage environment data sent by all the wireless sensor nodes and sending the storage environment data to the data transmission module.
The wireless sensor nodes are distributed in a warehouse for storing electric power grid materials.
Preferably, the base station is further configured to divide the wireless sensor nodes into cluster head nodes and member nodes, and send the division result to each wireless sensor node in a broadcast manner.
Preferably, dividing the wireless sensor node into a cluster head node and a member node includes:
calculating the total number numofNode of cluster head nodes;
and calculating the advantage value of each wireless sensor node to become a cluster head node, sequencing the advantage values from high to low, and taking the wireless sensor nodes corresponding to the advantage values of the numofNode before ranking as the cluster head nodes.
Preferably, the calculating the total number numofNode of cluster head nodes includes:
calculating the total number of cluster head nodes numofNode by the following method:
Figure BDA0002824047630000041
Figure BDA0002824047630000042
in the formula, numfN represents the total number of wireless sensor nodes, frek represents the system loss factor of the free space model, slk represents the average transmission power of the wireless sensor nodes, malongtb represents the maximum number of communication hops between the wireless sensor nodes and the base station, milongtb represents the minimum number of communication hops between the wireless sensor nodes and the base station, S represents the area of the monitoring range of all the wireless sensor nodes, midnum represents an integer-type intermediate parameter, if the number of midnum values is multiple, the minimum value is taken, and jznnum represents the preset reference number.
The traditional clustering mode, such as a leach protocol, obtains cluster head nodes in a mode of generating random numbers, and the mode does not consider the number, coverage area and the like of the nodes at all, so that the number of the generated cluster head nodes is easily too large or too small.
Preferably, the reference number is calculated by:
Figure BDA0002824047630000051
in the formula, blvaRepresenting the average communication radius of all wireless sensor nodes.
Preferably, calculating the dominance value of each wireless sensor node to become a cluster head node comprises:
Figure BDA0002824047630000052
in the formula csNodeaThe dominance value of the wireless sensor node a becoming a cluster head node is shown, and the numB shows the communication radius bl of the aaTotal number of wireless sensor nodes in, longa,bTo representa and the wireless sensor nodes b within the communication radius of the wireless sensor nodes a are stored in the set UaIf U is presentaA wireless sensor node c is internally present, such that
Figure BDA0002824047630000053
If true, qza＝mi(longa,b) Otherwise, qza＝ma(longa,b) Where numD denotes a communication radius bl of ccTotal number of wireless sensor nodes in, longc,dDenotes the Euclidean distance, mi (long), between c and the wireless sensor node d within its communication radiusa,b) Indicating the fetching of Longa,bMinimum value of, mi (long)a,b)＝min{longa,b|b∈Ua}，ma(longa,b) Indicating the fetching of Longa,bMaximum value of, ma (long)a,b)＝max{longa,b|b∈Ua}，senaRepresenting the remaining power, csen, of the wireless sensor node aaRepresents the initial power of the wireless sensor node a, plcsen represents the average initial power of all wireless sensor nodes, longa,bsRepresents the average number of communication hops between a and the base station, plongbsRepresenting the average of the average number of communication hops between all wireless sensor nodes and the base station.
When the advantage value is calculated, parameters such as the relation between the distance and the number of the wireless sensor nodes in the communication radius of the wireless sensor nodes, the residual electric quantity, the initial electric quantity, the hop count between the wireless sensor nodes and the base station and the like are mainly considered, so that the advantage value is obtained comprehensively. Especially, the hop count is a true reflection of the spatial distribution between the cluster head node and the base station compared to the distance, because the cluster head nodes are not all able to communicate with the base station directly, the superiority calculated by the above method is more accurate.
Preferably, the cluster head node adopts two central modes of communication between base stations, namely direct communication and indirect communication, and the cluster head node selects a communication mode with the base station through the following modes:
the cluster head node compares the average hop count of the cluster head node communicating with the base station with a hop count threshold value sent by the base station, if the average hop count is smaller than the hop count threshold value, the cluster head node communicates with the base station in a direct-transmission communication mode, otherwise, the cluster head node communicates with the base station in an indirect-transmission communication mode;
the average hop count is calculated as follows:
Figure BDA0002824047630000061
where avjunum represents the average hop count, numG represents the total number of cluster heads communicating with the base station within a time period T, junum representsgIndicating the hop count of the g-th communication between the cluster head and the base station in the time period T;
the hop count threshold is calculated as follows:
Figure BDA0002824047630000062
where jumthre denotes the hop count threshold, k1And k2Denotes the proportionality coefficient, k1And k is2Is 1, zdibsRepresenting the maximum number of hops, mdi, of a wireless sensor node communicating with a base stationbsIndicating the minimum number of hops for communication with the base station, longtbsRepresenting the average number of hops that all wireless sensor nodes are communicating with the base station.
The cluster head nodes select a proper communication mode in a self-adaptive mode according to actual conditions, and the cluster head nodes with overlarge communication hops with the base station can be prevented from communicating with the base station in a direct communication mode, so that the purposes of saving the energy of the cluster head nodes and balancing the energy consumption of the cluster head nodes are achieved. The method is beneficial to prolonging the service life of the cluster head node, and further prolonging the monitoring range of a monitoring network formed by the cluster head node and the member nodes.
Preferably, the direct communication includes: the cluster head communicates directly with the base station.
Preferably, the indirect communication includes: the cluster head node selects another cluster head node which is closest to the base station in the communication range of the cluster head node as a forwarding node, and the cluster head node communicates with the base station through the forwarding node.
While embodiments of the invention have been shown and described, it will be understood by those skilled in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims (6)

1. A cloud computing-based power grid material management system is characterized by comprising a data acquisition module, a data transmission module, a cloud platform and a user terminal;
the data acquisition module is used for acquiring storage environment data of the electric power materials and transmitting the storage environment data to the data transmission module;
the data transmission module is used for transmitting the storage environment data to the cloud platform;
the cloud platform is used for judging whether the storage environment data exceeds a preset threshold range to obtain a judgment result and sending the judgment result to the user terminal;
and the user terminal is used for displaying the judgment result to power grid material management personnel and sending an alarm prompt to the power grid material management personnel when the judgment result shows that the storage environment data exceeds a preset threshold range.
2. The cloud-computing-based power grid material management system of claim 1, wherein the data acquisition module comprises an in-store data acquisition unit, an out-of-store data acquisition unit and a storage environment data acquisition unit;
the warehousing data acquisition unit is used for acquiring warehousing data of the warehoused power grid materials and transmitting the warehousing data to the data transmission module;
the ex-warehouse data acquisition unit is used for acquiring warehousing data of ex-warehouse power grid materials and transmitting the warehousing data to the data transmission module;
the storage environment data acquisition unit is used for acquiring storage environment data of the electric power materials and transmitting the storage environment data to the data transmission module.
3. The cloud-computing-based power grid material management system according to claim 2, wherein the warehousing data includes types, amounts, and storage locations of warehoused power grid materials;
the ex-warehouse data comprises the types and the quantity of the electric power grid materials to be ex-warehouse;
the storage environment data comprises temperature, humidity and dangerous gas concentration in a warehouse for storing power grid materials.
4. The cloud-computing-based power grid material management system of claim 2, wherein the data transmission module is further configured to send the warehousing data and the ex-warehouse data to the cloud platform.
5. The cloud computing-based power grid material management system of claim 4, wherein the cloud platform comprises a storage unit, a material management unit and an environment monitoring unit;
the storage unit is used for storing the warehousing data, the ex-warehouse data and the storage environment data;
the material management unit is used for updating corresponding warehousing data in the storage unit according to the ex-warehouse data;
the environment monitoring unit is used for judging whether the storage environment data exceeds a preset threshold range to obtain a judgment result and sending the judgment result to the user terminal.
6. The cloud-computing-based power grid material management system of claim 5, wherein the user terminal comprises a display module and an alarm prompt module;
the display module is used for displaying the judgment result to power grid material management personnel;
and the alarm prompt module is used for sending an alarm prompt to the power grid material management personnel when the judgment result shows that the storage environment data exceeds a preset threshold range.
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