CN111199309A - Early warning management and control system of electric power material supply chain operation - Google Patents
Early warning management and control system of electric power material supply chain operation Download PDFInfo
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Abstract
An early warning management and control system for operation of an electric power material supply chain comprises an early warning management and control system, a service function system and a non-service function system. The operation of the power material supply chain can be used for analyzing the problems existing in the power material distribution process, and can be used for providing a feasible power material distribution optimization scheme based on the technology of the Internet of things; the method can be used for establishing a material distribution optimization model, and the model is improved through the technology of the Internet of things, so that the most appropriate electric power material distribution path selection method is obtained. The early warning management and control system can be used for formulating a reasonable distribution route; the system can be used for realizing the whole-process monitoring from a logistics distribution system to a demand point and preventing accidents; the method can be used for implementing an organization dispatching plan, collecting data in the transportation process, and adjusting and further optimizing the delivery route at any time; the method can be used for analyzing a large amount of historical data in actual operation and preparing for future transportation plans and transportation rationality plans.
Description
Technical Field
The invention relates to the technical field of operation of an electric power material supply chain, in particular to an early warning management and control system for operation of the electric power material supply chain.
Background
The electric power supplies have some characteristics different from common supplies due to the particularity of the industry. The method is mainly characterized in that:
(1) the timeliness requirement of the electric power materials is strict and the requirement is continuous. Because the power production has the characteristics of simultaneous production, supply and marketing, and the power product can not be stored, the requirements on timeliness and urgency of material guarantee are high, and accident emergency material storage is required. In order to maintain sufficient and timely power supply, power enterprises can never have the phenomenon of power interruption, and once materials such as fire coal and the like are insufficient, power plants can not normally supply power according to plans, so that normal operation of social production, operation and life is influenced, and adverse social results are caused. Thus, any out-of-stock is never allowed to occur.
(2) The demand of power enterprises for special materials is huge and has great fluctuation. Power generation enterprises generally carry out power production organization according to the power load requirements of the regions, power products change all the time along with random changes of users, and electric energy cannot be stored, so that the production activity plan of a power plant is determined to have great uncertainty. The demand of electric power has certain seasonal regularity, generally in summer and winter, because the utilization rate of the electric appliances for cooling and heating is too high, the two periods become the peak period of power utilization, the power generation load of a power plant is larger, correspondingly, more coal resources are needed to meet the power generation demand, the power generation load in spring and autumn is smaller, and the demand of coal is also reduced. This causes a certain imbalance in the demand of coal from power plants, which is characterized by seasonal fluctuations. While the annual power generation of power plants can remain a relatively steady growth trend, the supply of power plant fuel must also meet the different power outputs of the generating sets during off-season and peak periods. Even if reasonable planning and prediction are carried out according to a certain rule such as seasonality, volatility and the like, inaccuracy exists inevitably, and planning arrangement of purchasing and delivery of a power plant is influenced.
(3) Electric power materials are various in kind. The specialization of the use of electric power material divides the worker fine, and the variety is many, needs separately transport and store. Therefore, the power enterprises have high requirements on the management of material use, and objectively require a good material planning, storage, utilization and distribution process to ensure the efficiency of logistics links.
(4) Compared with other industrial materials, the cost of the electric power materials is very high. Activities such as technical improvement, maintenance and the like of power enterprises have burstiness and changeability, so most of stocks are emergency materials. In order to ensure that the power grid can recover to operate at the fastest speed when an emergency event occurs, the power material stock comprises various materials and various types of equipment. And many equipment models of the power grid are updated quickly, so that the inventory level of materials of the power enterprises is high due to a large amount of waste materials. Meanwhile, power enterprises pay more attention to response speed and social effect when the material demands occur, and lack planning on a logistics network system. For example, in companies such as national power grids, all external logistics are signed on power grid equipment suppliers, so that the workload of the power grid is reduced, core competitiveness of the power grid can be concerned more, and high-cost logistics transportation cost is brought. The cost is exchanged for efficiency, so that the cost of electric power materials is high.
The characteristics are caused by the particularity of the power industry, have important influence on establishing a material distribution decision analysis system, and determine that the existing distribution management method and mode cannot be completely and effectively implemented in power material distribution. Therefore, a set of new material distribution model must be established according to the actual operation of the power enterprise and the characteristics of the power materials, and the distribution strategy of the power materials must be analyzed and formulated.
However, current material logistics distribution systems lack integrated distribution capability. The logistics distribution system is lack of integration, allocation and transportation functions and poor in coordination, the distribution of materials is lack of matched technology and management, the situations that the purchasing period of electric power materials is long, repeated purchasing is carried out, the material supply is not timely and the like are easily caused, the requirements of electric power safety production and power grid construction cannot be timely met, large-scale economic loss is caused, and the power supply enterprise rush repair work is passively brought.
Therefore, it is urgent to establish an early warning management and control system for the operation of the power supply chain.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides an early warning management and control system for operation of an electric power material supply chain.
The technical scheme adopted by the invention for solving the technical problems is as follows: an early warning management and control system for operation of an electric power material supply chain comprises an early warning management and control system, a service function system and a non-service function system.
The early warning management and control system comprises a basic data module, an intelligent monitoring module, a data platform module and an intelligent decision module.
The basic data module comprises a quality safety unit, a goods arrival analysis unit, a storage analysis unit, a verification analysis unit, a delivery analysis unit and a comprehensive analysis unit.
The intelligent monitoring module comprises an equipment monitoring unit, an operation monitoring unit and an electronic billboard unit.
The data platform module comprises a data cleaning unit, a data analysis operation unit and a classification uploading unit.
The intelligent decision module comprises an automatic verification management unit, an intelligent warehouse management unit, a delivery supervision unit, an operation scheduling unit and an asset identification unit.
The service function system comprises a production maintenance module, a quality supervision management module and an auxiliary management module.
The production maintenance module comprises a maintenance management unit and a spare part management unit.
The quality supervision and management module comprises a promotion analysis unit, a sampling inspection supervision unit and a fault statistics unit.
The auxiliary management module comprises a security management unit, a material management unit, a logistics management unit and an intranet website unit.
The non-service function system comprises a permission management unit, an organization unit, a work flow table unit, a system parameter management unit, a message management unit, a task scheduling management unit, an application service monitoring unit, a self-defined report unit and a system log management unit.
Compared with the prior art, the invention has the advantages that:
the method has the advantages that (1) the operation of the power material supply chain can be used for analyzing the problems existing in the power material distribution process and can be used for providing a feasible power material distribution optimization scheme based on the technology of the Internet of things; the method can be used for establishing a material distribution optimization model, and the model is improved through the technology of the Internet of things, so that the most appropriate electric power material distribution path selection method is obtained.
The early warning management and control system has the advantages that (2) the early warning management and control system can be used for making a reasonable distribution route; the system can be used for realizing the whole-process monitoring from a logistics distribution system to a demand point and preventing accidents; the method can be used for implementing an organization dispatching plan, collecting data in the transportation process, and adjusting and further optimizing the delivery route at any time; the method can be used for analyzing a large amount of historical data in actual operation and preparing for future transportation plans and transportation rationality plans.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic view of the operation of the power supply chain of materials according to the present invention;
fig. 2 is a schematic structural diagram of the early warning management and control system according to the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings, in order that the present disclosure may be more fully understood and fully conveyed to those skilled in the art. While the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the invention is not limited to the embodiments set forth herein.
An early warning management and control system for electric power material supply chain operation is shown in fig. 1, and the electric power material supply chain operation comprises an early warning management and control system, a business function system and a non-business function system.
The early warning management and control system comprises a basic data module, an intelligent monitoring module, a data platform module and an intelligent decision module.
As shown in fig. 1, the basic data module includes a quality safety unit, an arrival analysis unit, a warehousing analysis unit, a verification analysis unit, a distribution analysis unit, and a comprehensive analysis unit.
As shown in fig. 1, the intelligent monitoring module includes an equipment monitoring unit, an operation monitoring unit, and an electronic billboard unit.
As shown in fig. 1, the data platform module includes a data cleaning unit, a data analysis operation unit, and a classification uploading unit.
As shown in fig. 1, the intelligent decision module includes an automatic verification management unit, an intelligent warehouse management unit, a delivery supervision unit, an operation scheduling unit, and an asset identification unit.
As shown in fig. 1, the service function system includes a production maintenance module, a quality supervision and management module, and an auxiliary management module.
As shown in fig. 1, the production maintenance module includes a maintenance management unit and a spare part management unit.
As shown in fig. 1, the quality supervision and management module includes a promotion analysis unit, a sampling inspection supervision unit, and a fault statistics unit.
As shown in fig. 1, the auxiliary management module includes a security management unit, a material management unit, a logistics management unit, and an intranet site unit.
As shown in fig. 1, the non-service function system includes a right management unit, an organization unit, a work flow table unit, a system parameter management unit, a message management unit, a task scheduling management unit, an application service monitoring unit, a custom report unit, and a system log management unit.
The basic data module is used for acquiring service data of a power material supply chain and on-site production, logistics and security video monitoring data; the method comprises the steps of collecting and summarizing the information data of the whole service process, the map, the inventory and the contract resource of the power material supply chain at regular time, and automatically collecting the data to a data platform module in an incremental or full mode through an Oracle task.
The intelligent monitoring module is used for visually displaying a monitoring picture for visually displaying the control indexes, the manufacturing real-time data, the video signals, the GPS and the 3D of the power material supply chain data through the large screen management system, and automatically acquiring the data to the data platform module for production scheduling personnel to make reasonable analysis, judgment and operation.
The large screen management system is used for monitoring pictures, displaying data analysis and prediction results, carrying out multi-dimensional, multi-type and multi-industry data information summary display, checking real-time alarm, safety basic data, alarm processing conditions and equipment data transmission real-time conditions, and presenting functions in real time according to a standard handling process of the intelligent decision module.
The data platform module is used for classifying, processing and storing the service data and the video data of the basic data module, cleaning the service data and the video data, and performing data analysis operations of unifying data formats, deleting repeated values, processing missing data and checking data accuracy; and the classification is uploaded to an intelligent decision module.
The intelligent decision module is used for classifying, processing, analyzing and calculating data of equipment operation indexes, energy environmental protection indexes and logistics indexes in the power material supply chain, providing a preset control strategy and obtaining a conclusion based on accurate statistical data analysis; setting an early warning threshold value for a key node for power material supply, carrying out corresponding processing through different business logics, actively sending a prompt to a user for the analyzed data of a business processing node close to the threshold value, and generating a corresponding chart in a large-screen management system through a Fusion-Chars chart component; and data support is provided for operation prediction, risk assessment and supply chain collaborative decision activities of users, and the accuracy and efficiency of decisions are improved.
All distribution vehicles are provided with RFID, sensors and clients provided with GPS (global positioning system); in the material transportation process, the logistics distribution system can monitor the states of the temperature, the position and the like of goods in real time through a sensor and a GPS technology, an upper limit value is set in the system, early warning can be given out once the dangerous value is close to the dangerous value, the emergency situation can be handled in time, and the safety of the whole transportation process is ensured; meanwhile, the logistics distribution system solves the optimal distribution route of the distribution vehicle through a GIS system, collects, processes, arranges and analyzes the data transported by the vehicle and then transmits the data to a decision maker, thereby providing real-time information for the selection of the distribution vehicle path; the other benefit of applying the technology of the internet of things is that a great deal of historical data of actual operation can be mastered, and the method has a great effect on subsequent transportation plan and transportation rationality planning.
The early warning control method of the early warning control system comprises the following steps:
establishing a shortest path model, and meeting the following short-circuit path objective function:
the shortest path model needs to satisfy the following constraints:
2) the total demand for vehicle delivery cannot exceed its load-bearing capacity, i.e.:
2) the number of vehicles departing from each logistics distribution system is equal to the number of vehicles returning to the logistics distribution system and does not exceed the number of vehicles owned by the logistics distribution system, namely:
3) the maximum value of the expression of the time function related to the qualitative coefficient cannot exceed the limit of the maximum time, namely:
step (2) cost analysis:
the total cost of material distribution is as follows:
1) vehicle fuel cost: assuming that the fuel cost per kilometer of the vehicle is positively correlated with the load capacity of the vehicle, the fuel cost per kilometer of the kth vehicle of the h logistics distribution system can be expressed as:
where λ, Δ are constants.
The total vehicle fuel cost is:
2) loss cost:
Then the vehicle material loss cost is:
3) time loss cost:
suppose that some materials must be matched for use among the n materials required for supply. Due to the uncertain supply, delayed delivery of the material may occur.
T1，T2，...，TkIndicating a delayed delivery time for vehicle k;
T’1，T’2，...，T’krepresents the lead time of the vehicle k:
C’krepresenting the waiting use cost of the materials carried by the vehicle k, such as inventory cost, loss cost and the like;
w represents the supply latency cost.
The time cost in the delivery of vehicles a, b can be expressed as:
although the embodiments have been described, once the basic inventive concept is obtained, other variations and modifications of these embodiments can be made by those skilled in the art, so that the above embodiments are only examples of the present invention, and not intended to limit the scope of the present invention, and all equivalent structures or equivalent processes using the contents of the present specification and drawings, or any other related technical fields, which are directly or indirectly applied thereto, are included in the scope of the present invention.
Claims (8)
1. An early warning management and control system for operation of an electric power material supply chain is characterized in that the operation of the electric power material supply chain comprises an early warning management and control system, a service function system and a non-service function system;
the early warning management and control system comprises a basic data module, an intelligent monitoring module, a data platform module and an intelligent decision module;
the basic data module comprises a quality safety unit, an arrival analysis unit, a storage analysis unit, a verification analysis unit, a delivery analysis unit and a comprehensive analysis unit;
the intelligent monitoring module comprises an equipment monitoring unit, an operation monitoring unit and an electronic billboard unit;
the data platform module comprises a data cleaning unit, a data analysis operation unit and a classification uploading unit;
the intelligent decision module comprises an automatic verification management unit, an intelligent warehouse management unit, a delivery supervision unit, an operation scheduling unit and an asset identification unit;
the business function system comprises a production maintenance module, a quality supervision management module and an auxiliary management module;
the production maintenance module comprises a maintenance management unit and a spare part management unit;
the quality supervision and management module comprises a promotion analysis unit, a sampling inspection supervision unit and a fault statistics unit;
the auxiliary management module comprises a security management unit, a material management unit, a logistics management unit and an intranet website unit;
the non-service function system comprises a permission management unit, an organization unit, a work flow table unit, a system parameter management unit, a message management unit, a task scheduling management unit, an application service monitoring unit, a self-defined report unit and a system log management unit.
2. The early warning management and control system of electric power material supply chain operation of claim 1, characterized in that: the basic data module is used for acquiring service data of a power material supply chain and on-site production, logistics and security video monitoring data; the method comprises the steps of collecting and summarizing the information data of the whole service process, the map, the inventory and the contract resource of the power material supply chain at regular time, and automatically collecting the data to a data platform module in an incremental or full mode through an Oracle task.
3. The early warning management and control system of electric power material supply chain operation of claim 1, characterized in that: the intelligent monitoring module is used for visually displaying a monitoring picture for visually displaying the control indexes, the manufacturing real-time data, the video signals, the GPS and the 3D of the power material supply chain data through the large screen management system, and automatically acquiring the data to the data platform module for production scheduling personnel to make reasonable analysis, judgment and operation.
4. The early warning management and control system of electric power material supply chain operation of claim 1, characterized in that: the large screen management system is used for monitoring pictures, displaying data analysis and prediction results, carrying out multi-dimensional, multi-type and multi-industry data information summary display, checking real-time alarm, safety basic data, alarm processing conditions and equipment data transmission real-time conditions, and presenting functions in real time according to a standard handling process of the intelligent decision module.
5. The early warning management and control system of electric power material supply chain operation of claim 1, characterized in that: the data platform module is used for classifying, processing and storing the service data and the video data of the basic data module, cleaning the service data and the video data, and performing data analysis operations of unifying data formats, deleting repeated values, processing missing data and checking data accuracy; and the classification is uploaded to an intelligent decision module.
6. The early warning management and control system of electric power material supply chain operation of claim 1, characterized in that: the intelligent decision module is used for classifying, processing, analyzing and calculating data of equipment operation indexes, energy environmental protection indexes and logistics indexes in the power material supply chain, providing a preset control strategy and obtaining a conclusion based on accurate statistical data analysis; setting an early warning threshold value for a key node for power material supply, carrying out corresponding processing through different business logics, actively sending a prompt to a user for the analyzed data of a business processing node close to the threshold value, and generating a corresponding chart in a large-screen management system through a Fusion-Chars chart component; and data support is provided for operation prediction, risk assessment and supply chain collaborative decision activities of users, and the accuracy and efficiency of decisions are improved.
7. The early warning management and control system of electric power material supply chain operation of claim 1, characterized in that: all distribution vehicles are provided with RFID, sensors and clients provided with GPS (global positioning system); in the material transportation process, the logistics distribution system can monitor the states of the temperature, the position and the like of goods in real time through a sensor and a GPS technology, an upper limit value is set in the system, early warning can be given out once the dangerous value is close to the dangerous value, the emergency situation can be handled in time, and the safety of the whole transportation process is ensured; meanwhile, the logistics distribution system solves the optimal distribution route of the distribution vehicle through a GIS system, collects, processes, arranges and analyzes the data transported by the vehicle and then transmits the data to a decision maker, thereby providing real-time information for the selection of the distribution vehicle path; the other benefit of applying the technology of the internet of things is that a great deal of historical data of actual operation can be mastered, and the method has a great effect on subsequent transportation plan and transportation rationality planning.
8. The early warning management and control system of electric power material supply chain operation of claim 1, characterized in that: the early warning control method of the early warning control system comprises the following steps:
establishing a shortest path model, and meeting the following short-circuit path objective function:
the shortest path model needs to satisfy the following constraints:
1) the total demand for vehicle delivery cannot exceed its load-bearing capacity, i.e.:
2) the number of vehicles departing from each logistics distribution system is equal to the number of vehicles returning to the logistics distribution system and does not exceed the number of vehicles owned by the logistics distribution system, namely:
3) the maximum value of the expression of the time function related to the qualitative coefficient cannot exceed the limit of the maximum time, namely:
step (2) cost analysis:
the total cost of material distribution is as follows:
1) vehicle fuel cost: assuming that the fuel cost per kilometer of the vehicle is positively correlated with the load capacity of the vehicle, the fuel cost per kilometer of the kth vehicle of the h logistics distribution system can be expressed as:
wherein λ, Δ are constants;
the total vehicle fuel cost is:
2) loss cost:
then the vehicle material loss cost is:
3) time loss cost:
supposing that some materials in the n materials required for supply must be matched for use; due to the influence of uncertain supply, the phenomenon of delayed delivery of materials can occur;
T1，T2，...，Tkindicating a delayed delivery time for vehicle k;
T′1，T′2，...，T′krepresents the lead time of the vehicle k:
C′krepresenting the waiting use cost of the materials carried by the vehicle k, such as inventory cost, loss cost and the like;
w represents the supply latency cost;
the time cost in the delivery of vehicles a, b can be expressed as:
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Cited By (12)
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|---|---|---|---|---|
| CN111861285A (en) * | 2020-08-07 | 2020-10-30 | 浙江华电器材检测研究所有限公司 | Power distribution network material quality data high-reliability real-time management and control method and system based on block chain technology |
| CN112630804A (en) * | 2020-12-15 | 2021-04-09 | 中铁第五勘察设计院集团有限公司 | Space-time application terminal, container positioning device and method |
| CN113095582A (en) * | 2021-04-21 | 2021-07-09 | 广东电网有限责任公司电力调度控制中心 | Safety monitoring and early warning method and system for electricity and coal supply chain |
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| CN114399133A (en) * | 2021-11-22 | 2022-04-26 | 国网浙江省电力有限公司 | Risk monitoring method and system based on power grid material supply chain operation |
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| CN116976770A (en) * | 2023-08-09 | 2023-10-31 | 江陵县金顺物流有限公司 | Logistics package distribution intelligent management system based on big data analysis |
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| CN112630804A (en) * | 2020-12-15 | 2021-04-09 | 中铁第五勘察设计院集团有限公司 | Space-time application terminal, container positioning device and method |
| CN113095582B (en) * | 2021-04-21 | 2023-09-29 | 广东电网有限责任公司电力调度控制中心 | Safety monitoring and early warning method and system for electric coal supply chain |
| CN113095582A (en) * | 2021-04-21 | 2021-07-09 | 广东电网有限责任公司电力调度控制中心 | Safety monitoring and early warning method and system for electricity and coal supply chain |
| CN113313331A (en) * | 2021-07-30 | 2021-08-27 | 深圳市城市交通规划设计研究中心股份有限公司 | Emergency material multi-cycle segmentation distribution method and device based on inventory gap risk |
| CN113342869A (en) * | 2021-08-06 | 2021-09-03 | 北京国电通网络技术有限公司 | Visualization path display method and device, electronic equipment and computer readable medium |
| CN114399133A (en) * | 2021-11-22 | 2022-04-26 | 国网浙江省电力有限公司 | Risk monitoring method and system based on power grid material supply chain operation |
| CN114529228A (en) * | 2022-04-24 | 2022-05-24 | 南京鼎研电力科技有限公司 | Risk early warning method and system for power monitoring system supply chain |
| CN114785832A (en) * | 2022-04-25 | 2022-07-22 | 北京兴竹同智信息技术股份有限公司 | Early warning data transmission method and system |
| CN114785832B (en) * | 2022-04-25 | 2024-01-23 | 北京兴竹同智信息技术股份有限公司 | Early warning data transmission method and system |
| CN115423381A (en) * | 2022-10-31 | 2022-12-02 | 国网浙江省电力有限公司金华供电公司 | Intelligent-chain-ID-code-based full-chain collaborative early warning method and platform for electric power materials |
| CN115423381B (en) * | 2022-10-31 | 2023-03-24 | 国网浙江省电力有限公司金华供电公司 | Intelligent-chain-ID-code-based full-chain collaborative early warning method and platform for electric power materials |
| CN116258430A (en) * | 2023-03-15 | 2023-06-13 | 国电南瑞南京控制***有限公司 | Electric power material storage and distribution method based on Internet of things |
| CN116258430B (en) * | 2023-03-15 | 2023-12-19 | 国电南瑞南京控制***有限公司 | Electric power material storage and distribution method based on Internet of things |
| CN116258431A (en) * | 2023-05-15 | 2023-06-13 | 成都运荔枝科技有限公司 | Cold chain transportation safety remote monitoring system based on internet |
| CN116258431B (en) * | 2023-05-15 | 2023-09-19 | 成都运荔枝科技有限公司 | Cold chain transportation safety remote monitoring system based on internet |
| CN116976770A (en) * | 2023-08-09 | 2023-10-31 | 江陵县金顺物流有限公司 | Logistics package distribution intelligent management system based on big data analysis |
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