Intelligent power distribution system of coking equipment based on demand analysis

Abstract

The invention discloses a coking equipment intelligent power distribution system based on demand analysis, which relates to the technical field of intelligent power supply and distribution in the coking industry and comprises a sensing layer, a network layer, a platform layer and an application layer. The sensing layer is composed of an intelligent sensor and an intelligent electric meter which are deployed at key nodes of coking equipment, environment parameters and operation state parameters of the equipment are collected through the intelligent sensor, electric power parameters are metered through the intelligent electric meter, and data are uploaded in real time and sent to the network layer; the demand analysis of the coking electrical intelligent power distribution system can be carried out, based on the characteristics of the coking power supply and distribution system, an accurate and reliable data detection method is researched, a sensing layer data acquisition terminal is established and perfected, the processing, storage and transmission functions of mass data are realized, and the system has the functions of evaluating and analyzing the operation data of the intelligent power distribution system. And optimizing and adjusting the power demand prediction model, the fault diagnosis model and the intelligent power distribution strategy according to the actual operation condition and user feedback.

Description

Technical Field

[0001] This invention relates to the field of intelligent power supply and distribution technology in the coking industry, specifically to an intelligent power distribution system for coking equipment based on demand analysis. Background Technology

[0002] Traditional power distribution systems in coking plants suffer from numerous problems. Their monitoring of electrical parameters is limited, obtaining only basic voltage and current data, failing to provide a comprehensive understanding of the system's operational status. Fault detection and location rely on manual experience, resulting in low efficiency and poor accuracy; troubleshooting often consumes significant time, impacting production continuity. With the expansion of coking plants and the increase in electrical equipment, higher demands are placed on the intelligence, efficiency, and reliability of power distribution systems.

[0003] Furthermore, coking enterprises consume enormous amounts of energy during their production processes, making the task of achieving carbon peaking and carbon neutrality a challenging one. How to efficiently manage the safe operation of the power supply system in coking enterprises, and how to improve energy efficiency while ensuring the reliability of the power supply system to achieve carbon emission standards on schedule, have become primary concerns for managers of coking enterprises when planning, designing, and constructing their power grids. Based on the requirements for reducing energy efficiency and costs, coking enterprises have placed higher demands on their power supply systems: 1) The entire plant's power supply system achieves large-scale centralized control and unified operation; 2) To achieve intelligent centralized operation and maintenance, decentralized control must be fast, safe, stable, and reliable; 3) The electricity consumption of major production equipment is subject to precise metering, analysis, and optimization; 4) Requirements include data sharing, seamless connection, and integration with the intelligent chemical engineering system; 5) Achieve carbon peaking and carbon neutrality goals; 6) Develop from fossil energy to green energy.

[0004] Therefore, in view of this, the present invention proposes an intelligent power distribution system for coking equipment based on demand analysis to make up for and improve the shortcomings of the existing technology. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides an intelligent power distribution system for coking equipment based on demand analysis, thereby resolving the corresponding technical issues raised in the background section.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is: a smart power distribution system for coking equipment based on demand analysis, comprising a sensing layer, a network layer, a platform layer, and an application layer; The perception layer consists of smart sensors and smart meters deployed at key nodes of the coking equipment. The smart sensors collect environmental parameters and equipment operating status parameters, the smart meters measure power parameters, and the data is uploaded in real time and sent to the network layer. The network layer is used to acquire environmental parameters, operating status parameters, and power parameters, and uses communication technology to transmit the data to the platform layer, while the platform layer issues control commands to the execution device. The platform layer includes a data center, an intelligent analysis module, and a control decision module. The data center is used to store power parameters and operating status parameters. The intelligent analysis module is used to perform in-depth data mining and analysis based on big data analysis and artificial intelligence algorithms to achieve fault prediction and power quality assessment. The control decision module is used to generate corresponding control strategies based on the analysis results; The application layer is used to provide users with a functional interface, including real-time monitoring, fault alarms, energy management, and equipment maintenance.

[0007] Preferably, the environmental parameters include temperature, humidity, smoke, and gas concentration; the operating status parameters include vibration and partial discharge; and the electrical parameters include voltage, current, power, and electricity.

[0008] Preferably, in the perception layer, the setting of key nodes should meet the following requirements: Primary equipment in high-voltage power systems is required to have intelligent components, intelligent electronic devices, and online monitoring terminal functions. It should also be able to automatically collect, measure, and digitize the status information of primary equipment, and have the function of remote operation and control of primary equipment. Secondary equipment requires the configuration of smart meters, protection and control devices, secondary monitoring equipment, anti-misoperation locks, cameras, inspection robots, and sensor equipment. Each device is required to have network communication capabilities and reserved interfaces for access to the station's communication network via Ethernet or fiber optics. In accordance with the requirements of intelligent power supply and distribution for coking projects, in addition to smart meters, intelligent low-voltage circuit breakers are selected for low-voltage power distribution and motor circuits in each system and process unit power supply circuit. These circuit breakers have remote measurement, remote signaling, remote control and remote adjustment functions, and support Wi-Fi, 4G (5G) and RS485 communication functions. Furthermore, the intelligent low-voltage switches must have electric operation functions.

[0009] Preferably, in the platform layer, the data center should meet the following requirements: The collected data are processed, statistically analyzed, and calculated, and all results are saved to the database. Telemetry: Telemetry engineering conversion of primary side actual value, telemetry manual data setting, zero drift handling, telemetry over-limit alarm, various daily and monthly maximum, minimum and average statistics, and accident recall function; Remote signaling: Real-time processing of switch status, disconnector status, protection hard contact remote signaling, status quantity remote signaling, main transformer tap position and protection action items, protection alarm items, total fault remote signaling, and total warning remote signaling status changes to quickly generate change items, remote signaling inversion, remote signaling manual setting, maintenance or tagging settings, fault judgment, two-point remote signaling, remote control blocking and enabling, and statistics on the number of switch and protection actions; Electricity consumption: It can receive and process electricity meter code values ​​and pulse count values, perform scale conversion, manually set electricity consumption base code, calculate electricity consumption by integration, and provide daily, monthly, peak, valley, and average electricity consumption statistics; Statistical calculation functions: total active and reactive power summation, automatic calculation of safe days, transformer load rate and loss statistics, bus unbalance rate, bus voltage operating parameter non-compliance time and compliance rate statistics, capacitor and reactor input time, utilization rate and switching times, remote control adjustment times and success rate statistics, and users can define various formulas for calculation.

[0010] Preferably, in the platform layer, data is received through a cloud server, a large-screen display terminal, and a mobile device. The cloud server includes intelligent operation and maintenance management system software and database software to realize power monitoring and security management data mirroring, and to realize intelligent operation and maintenance data management, Web services, APP application interfaces, business flow management services, operation and maintenance report services, intelligent inspection management, and equipment management services.

[0011] Preferably, within the platform layer, an intelligent fault diagnosis system for coking equipment, an operation and maintenance management system, and a power monitoring system are constructed. These systems enable online monitoring and management of the operating status, event alarms, measurement data, and fault recording information of the primary and secondary power supply equipment in 110kV substations, 35kV substations, and various integrated electrical rooms and substations. By combining the power supply system operation mode and expert knowledge base, online analysis and intelligent diagnosis of power faults based on power operation expert knowledge are achieved. When a power supply system accident occurs, the cause of the accident is deduced, and an accident handling guidance report is provided to guide the on-duty personnel in handling the accident, providing managers or operators with a powerful and timely basis for decision-making.

[0012] Compared with the prior art, the beneficial effects of the present invention are: (1) Real-time monitoring function: Users can view power parameters, equipment operating status and environmental parameters in real time through the application layer interface, and fully grasp the operation of the power distribution system.

[0013] (2) Fault alarm function: Once the system detects a fault, it will immediately notify the maintenance personnel through SMS, sound and light alarms, etc., and display detailed fault information on the interface to facilitate the maintenance personnel to respond and handle the fault quickly.

[0014] (3) Energy management function: Statistical analysis of electricity consumption, generation of energy reports and energy consumption trend charts, providing data support for enterprises to formulate energy-saving measures and helping enterprises achieve energy conservation and emission reduction goals.

[0015] (4) Equipment maintenance management function: Based on the equipment operation status monitoring data and fault prediction results, formulate preventive maintenance plans, arrange equipment maintenance work in advance, reduce equipment failure rate, and ensure stable equipment operation. Attached Figure Description

[0016] Figure 1 This is a diagram of the intelligent power distribution system architecture shown in this invention; Figure 2 This is a structural diagram of a typical high-pressure system in a coking plant, as shown in this invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Embodiments of the present invention: Please refer to Figures 1 to 2 As shown, the intelligent power distribution system for coking equipment based on demand analysis includes a sensing layer, a network layer, a platform layer, and an application layer. The perception layer consists of smart sensors and smart meters deployed at key nodes of the coking equipment. The smart sensors collect environmental parameters and equipment operating status parameters, the smart meters measure power parameters, and the data is uploaded in real time and sent to the network layer. The network layer is used to acquire environmental parameters, operating status parameters, and power parameters, and uses a combination of wired and wireless communication technologies (fiber optic communication, industrial Ethernet, or wireless communication protocols) to transmit the data to the platform layer, while issuing control commands from the platform layer to the execution devices. The platform layer includes a data center, an intelligent analysis module, and a control decision module. The data center is used to clean and analyze the received data and store power parameters and operating status parameters. The intelligent analysis module is used to perform in-depth data mining and analysis based on big data analysis and artificial intelligence algorithms to achieve fault prediction and power quality assessment. The control decision module is used to generate corresponding control strategies based on the analysis results; The application layer provides users with a functional interface (visual operation interface), including real-time monitoring, fault alarm, energy management, and equipment maintenance, enabling remote monitoring, intelligent control, and report generation of the power distribution system.

[0019] Environmental parameters include temperature, humidity, smoke, and gas concentration; operating status parameters include vibration and partial discharge; and electrical parameters include voltage, current, power, and electrical quantity.

[0020] In the perception layer, the settings of key nodes should meet the following requirements: Primary equipment in high-voltage power systems is required to have intelligent components, intelligent electronic devices, and online monitoring terminal functions. It should also be able to automatically collect, measure, and digitize the status information of primary equipment, and have the function of remote operation and control of primary equipment. Secondary equipment requires the configuration of smart meters, protection and control devices, secondary monitoring equipment, anti-misoperation locks, cameras, inspection robots, and sensor equipment. Each device is required to have network communication capabilities and reserved interfaces for access to the station's communication network via Ethernet or fiber optics. In accordance with the requirements of intelligent power supply and distribution for coking projects, in addition to smart meters, intelligent low-voltage circuit breakers are selected for low-voltage power distribution and motor circuits in each system and process unit power supply circuit. These circuit breakers have remote measurement, remote signaling, remote control and remote adjustment functions, and support Wi-Fi, 4G (5G) and RS485 communication functions. Furthermore, the intelligent low-voltage switches must have electric operation functions.

[0021] At the platform layer, the data center should meet the following requirements: The collected data are processed, statistically analyzed, and calculated, and all results are saved to the database. Telemetry: Telemetry engineering conversion of primary side actual value, telemetry manual data setting, zero drift handling, telemetry over-limit alarm, various daily and monthly maximum, minimum and average statistics, and accident recall function; Remote signaling: Real-time processing of switch status, disconnector status, protection hard contact remote signaling, status quantity remote signaling, main transformer tap position and protection action items, protection alarm items, total fault remote signaling, and total warning remote signaling status changes to quickly generate change items, remote signaling inversion, remote signaling manual setting, maintenance or tagging settings, fault judgment, two-point remote signaling, remote control blocking and enabling, and statistics on the number of switch and protection actions; Electricity consumption: It can receive and process electricity meter code values ​​and pulse count values, perform scale conversion, manually set electricity consumption base code, calculate electricity consumption by integration, and provide daily, monthly, peak, valley, and average electricity consumption statistics; Statistical calculation functions: total active and reactive power summation, automatic calculation of safe days, transformer load rate and loss statistics, bus unbalance rate, bus voltage operating parameter non-compliance time and compliance rate statistics, capacitor and reactor input time, utilization rate and switching times, remote control adjustment times and success rate statistics, and users can define various formulas for calculation.

[0022] At the platform layer, data is received through cloud servers, large-screen display terminals, and mobile devices. The cloud server includes intelligent operation and maintenance management system software and database software to realize power monitoring and security management data mirroring, and realize intelligent operation and maintenance data management, Web services, APP application interfaces, business flow management services, operation and maintenance report services, intelligent inspection management, and equipment management services.

[0023] At the platform layer, an intelligent fault diagnosis system, an operation and maintenance management system, and a power monitoring system for coking equipment are constructed. These systems enable online monitoring and management of the operating status, event alarms, measurement data, and fault recording information of the primary and secondary power supply equipment in 110kV substations, 35kV substations, and various integrated electrical rooms and substations. By combining the power supply system operation mode and expert knowledge base, online analysis and intelligent diagnosis of power faults based on power operation expert knowledge are achieved. When a power supply system accident occurs, the cause of the accident is deduced, and an accident handling guidance report is provided to guide the on-duty personnel in handling the accident, providing managers or operators with strong and timely decision-making basis.

[0024] This application, through its established perception layer, network layer, platform layer, and application layer, enables demand analysis of a coking plant's intelligent power distribution system. Based on the characteristics of the coking plant's power supply and distribution system, it researches accurate and reliable data detection methods, establishes and improves the data acquisition terminal for the perception layer, and realizes the processing, storage, and transmission of massive amounts of data. It also has the capability to evaluate and analyze the operational data of the intelligent power distribution system, and optimize and adjust the power demand forecasting model, fault diagnosis model, and intelligent power allocation strategy based on actual operating conditions and user feedback. Simultaneously, it monitors the development of relevant technologies and upgrades the system in a timely manner to improve its performance and functionality.

[0025] Addressing the intelligent and automated power supply and distribution system requirements of coking enterprises, this paper innovatively applies cutting-edge technologies such as power electronics, sensing and measurement, mathematical computing architecture, big data decision-making, and information security to the entire process of coking enterprises, based on the Industrial Internet. By deploying intelligent equipment in enterprise-owned power plants, substations, control centers, and power distribution scenarios, various data are collected to achieve comprehensive perception of power facilities. Powerful cloud computing is used to collect, mine, and analyze big data, and strong execution capabilities enable real-time detection of anomalies, rapid elimination of various safety hazards, and dynamic adjustment of the power supply system to the optimal mode. This ensures the reliability of the coking enterprise's power supply and distribution system while reducing energy consumption, improving production efficiency, and promoting high-quality development of the enterprise. This application reconstructs a complete intelligent power supply and distribution management model for coking enterprises through a four-level system architecture. 1. System Architecture Design: This intelligent power distribution system adopts a layered distributed architecture, consisting of a perception layer, a network layer, a platform layer, and an application layer. The perception layer comprises various intelligent sensors and smart meters. Intelligent sensors collect environmental parameters such as temperature, humidity, smoke, and gas concentration, as well as operational status parameters such as equipment vibration and partial discharge. Smart meters accurately measure power parameters such as voltage, current, power, and electricity consumption, and upload the data in real time. The network layer utilizes various communication technologies, including fiber optic communication and wireless communication (such as 4G / 5G and Wi-Fi), to ensure high-speed and stable data transmission, accurately transmitting the data collected by the perception layer to the platform layer, and simultaneously issuing control commands from the platform layer to the execution devices. The platform layer includes a data center, an intelligent analysis module, and a control decision module. The data center stores massive amounts of power data and equipment operation data; the intelligent analysis module, based on big data analytics and artificial intelligence algorithms, performs in-depth data mining and analysis to achieve functions such as fault prediction and power quality assessment; the control decision module generates reasonable control strategies based on the analysis results. The application layer provides users with a rich set of functional interfaces, including real-time monitoring, fault alarms, energy management, and equipment maintenance, making it convenient for users to operate and manage.

[0026] 2. Application of key technologies: (1) Intelligent monitoring and fault diagnosis technology: Real-time collection of power parameters and equipment operating status data is carried out using intelligent sensors and smart meters. Fault prediction models are established through big data analysis and artificial intelligence algorithms. When the monitored data exceeds the normal range, the system automatically issues an early warning, accurately locates the fault location, quickly diagnoses the cause of the fault, greatly shortens the fault investigation time, and improves the reliability of power supply.

[0027] (2) Energy Management and Optimization Technology: Based on the production process and electricity demand of the coking project, a scientific and reasonable energy management strategy is formulated. By monitoring the power load in real time, the system dynamically adjusts the power allocation of the equipment to achieve optimal allocation of power resources. At the same time, in conjunction with the peak-valley electricity pricing policy, the operating time of the equipment is reasonably arranged to reduce electricity costs and improve energy utilization efficiency.

[0028] 3. System Function Implementation: (1) Real-time monitoring function: Users can view power parameters, equipment operating status and environmental parameters in real time through the application layer interface, and fully grasp the operation of the power distribution system.

[0029] (2) Fault alarm function: Once the system detects a fault, it will immediately notify the maintenance personnel through SMS, sound and light alarms, etc., and display detailed fault information on the interface to facilitate the maintenance personnel to respond and handle the fault quickly.

[0030] (3) Energy management function: Statistical analysis of electricity consumption, generation of energy reports and energy consumption trend charts, providing data support for enterprises to formulate energy-saving measures and helping enterprises achieve energy conservation and emission reduction goals.

[0031] (4) Equipment maintenance management function: Based on the equipment operation status monitoring data and fault prediction results, formulate preventive maintenance plans, arrange equipment maintenance work in advance, reduce equipment failure rate, and ensure stable equipment operation.

[0032] In this embodiment: like Figures 1 to 2As shown, the perception layer is deployed on primary equipment such as transformers, circuit breakers, disconnect switches, and current / voltage transformers, adopting a "primary equipment body + sensor + intelligent component" approach. The intelligent components include: intelligent terminals, merging units, status monitoring IEDs, online monitoring terminals, protection and control devices, secondary monitoring equipment, anti-misoperation locks, cameras, inspection robots, and sensors, realizing functions such as information collection, status monitoring, intelligent inspection, and operation control. They mainly realize the automatic collection, measurement, data digitization, and control of primary / secondary equipment status information. The network layer consists of communication management units, gateways, NVRs, switches, and communication cabinets, which poll and aggregate monitoring, control, alarm, and information data from all station equipment via the Modbus-RTU protocol, completing the Modbus-RTU to Modbus-TCP protocol conversion, and transmitting the data to the platform layer via an industrial Ethernet fiber optic ring network or wireless WIFI / 5G modules. The platform layer stores power data and equipment metadata through a time-series database server and a relational database server, respectively. The application layer receives data through cloud servers, large-screen display terminals, and mobile devices. The cloud server includes intelligent operation and maintenance management system software and database software, which realizes power monitoring and security management data mirroring, and realizes functions such as intelligent operation and maintenance data management, web services, APP application interface, business flow management services, operation and maintenance report services, intelligent inspection management, and equipment management services.

[0033] like Figure 1 As shown, the application-layer substation power monitoring system is a fully open SCADA system based on the UNIX / LINUX / WINDOWS operating system platform. The software adheres to the basic requirements of a unified model and platform, deeply integrating main and auxiliary equipment information in terms of functionality and interface to achieve functions such as monitoring, operation and control of all station equipment, intelligent applications, and main station support services. The system's configured remote communication units and monitoring workstations can connect to distributed or centralized integrated measurement and control devices and protection devices to complete the collection of information such as telemetry, remote signaling, electricity consumption, microcomputer protection information, and various records, collecting data periodically according to a scanning cycle. The system can perform engineering processing, statistics, and calculations on various collected data and save all results to the database.

[0034] It receives all status variables, measured values, electrical quantities, relay protection operating conditions and action information, etc., and monitors in real time the current, voltage, frequency, active power, reactive power, power factor, electrical quantity, remote signaling quantity, etc. of each line, bus, and main equipment, and classifies, counts, stores, displays, prints and alarms them.

[0035] It monitors fault alarms on various lines, the status and fault alarms of high-voltage switches and main low-voltage switches, transformer temperature monitoring and over-temperature alarms, etc. When the monitored values ​​exceed the allowable range or a fault occurs, the screen will automatically display text prompts and alarms. The alarm information includes alarm type, object of alarm, alarm content, specific time of alarm occurrence, confirmation status, etc., and can provide professional fault recovery guidance.

[0036] The computer in the power monitoring system can perform opening and closing operations on all high-voltage switchgear and intelligent low-voltage switchgear, except for 110kV substation equipment and high-voltage motor circuits. It also supports functions such as operation permission management, remote modification of settings, anti-misoperation interlocking, event sequence recording, dynamic real-time screen generation and display, report management and printing, time synchronization, system self-diagnosis and self-recovery.

[0037] It has statistical functions for daily, monthly, and annual load curves and load tables of the power load of the whole plant and each production unit, and provides data on the annual maximum load, annual average load, and annual maximum load utilization hours of the whole plant and each production unit. It has the functions of saving and querying historical data, and querying load curves, voltage and current bar charts.

[0038] It can perform comprehensive and accurate temperature monitoring of all connection points, busbars, equipment, etc., monitor equipment temperature in real time, and obtain fault alarm information in a timely manner. It can realize substation anomaly monitoring, abnormal sound monitoring, humidity monitoring, etc.

[0039] Establish a plant-wide electrical protection database. The protection settings, protection status, equipment parameters, and transformer parameters of each high- and low-voltage protection device and circuit breaker can be viewed through the primary power supply system diagram.

[0040] Status signals and fault signals from high- and low-voltage switchgear are transmitted to the DCS system.

[0041] Furthermore, to ensure long-term stable operation in the complex and harsh working environment of coking plants, expansion and dynamic reconfiguration are possible. The remote and local control of the computer monitoring system must have functions to prevent misoperation, and the communication network adopts a dual-network structure with redundant configuration; the communication front-end unit also employs a dual-machine redundant configuration.

[0042] like Figure 2As shown, taking the high-voltage system of a coking plant as an example, its intelligent power supply and distribution system is logically composed of an application layer, a network layer, and a sensing layer. The application layer consists of a host integrating operator stations, engineer stations, five-prevention workstations, and protection and fault information substations. It provides a human-machine interface for station operation, enabling management and control of equipment at the bay and process layers, forming a station-wide monitoring and management center, and can communicate with remote monitoring centers. The sensing layer consists of several secondary subsystems such as protection, measurement and control, metering, and waveform recording. Even in the event of application layer or network failure, it can still independently perform local monitoring functions for sensing layer equipment. The sensing layer also consists of instrument transformers, merging units, and intelligent terminals, performing functions related to primary equipment, including real-time acquisition of electrical quantities, monitoring of equipment operating status, and execution of control commands. The network layer structure uses dual Ethernet, and the application layer and bay layer communicate via fiber optic cables. Failure of any system or device connected to the data communication network will not paralyze the communication system or affect the operation of other networked systems and equipment. The network communication rate meets the system's real-time requirements and is no less than 100Mbps. When an error occurs in the data communication network, the system automatically takes safety measures, such as automatically requesting a retransmission of the data, disconnecting the faulty device, or switching to a redundant device. The main control layer network is scalable to interface with other devices.

[0043] The size of the interval and threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by those skilled in the art for each set of sample data; as long as it does not affect the ratio between the parameter and the quantized value.

[0044] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation. In the two embodiments provided in this application, it should be understood that the disclosed apparatus and system can be implemented in other ways; for example, the apparatus embodiments described above are merely illustrative, and the division of modules is merely a logical functional division. In actual implementation, there may be other division methods, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed; furthermore, the coupling or direct coupling or communication connection between the shown or discussed mutuals can be through some interfaces, and the indirect coupling or communication connection between the apparatus or modules can be electrical, mechanical or other forms. The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A smart power distribution system for coking equipment based on demand analysis, characterized in that, It includes the perception layer, network layer, platform layer, and application layer; The perception layer consists of smart sensors and smart meters deployed at key nodes of the coking equipment. The smart sensors collect environmental parameters and equipment operating status parameters, the smart meters measure power parameters, and the data is uploaded in real time and sent to the network layer. The network layer is used to acquire environmental parameters, operating status parameters, and power parameters, and uses communication technology to transmit the data to the platform layer, while the platform layer issues control commands to the execution device. The platform layer includes a data center, an intelligent analysis module, and a control decision module. The data center is used to store power parameters and operating status parameters. The intelligent analysis module is used to perform in-depth data mining and analysis based on big data analysis and artificial intelligence algorithms to achieve fault prediction and power quality assessment. The control decision module is used to generate corresponding control strategies based on the analysis results; The application layer is used to provide users with a functional interface, including real-time monitoring, fault alarms, energy management, and equipment maintenance.

2. The intelligent power distribution system for coking equipment based on demand analysis according to claim 1, characterized in that, The environmental parameters include temperature, humidity, smoke, and gas concentration; the operating status parameters include vibration and partial discharge; and the electrical parameters include voltage, current, power, and electricity.

3. The intelligent power distribution system for coking equipment based on demand analysis according to claim 1, characterized in that, In the perception layer, the settings of key nodes should meet the following requirements: Primary equipment in high-voltage power systems is required to have intelligent components, intelligent electronic devices, and online monitoring terminal functions. It should also be able to automatically collect, measure, and digitize the status information of primary equipment, and have the function of remote operation and control of primary equipment. Secondary equipment requires the configuration of smart meters, protection and control devices, secondary monitoring equipment, anti-misoperation locks, cameras, inspection robots, and sensor equipment. Each device is required to have network communication capabilities and reserved interfaces for access to the station's communication network via Ethernet or fiber optics. In accordance with the requirements of intelligent power supply and distribution for coking projects, in addition to smart meters, intelligent low-voltage circuit breakers are selected for low-voltage power distribution and motor circuits in each system and process unit power supply circuit. These circuit breakers have remote measurement, remote signaling, remote control and remote adjustment functions, and support Wi-Fi, 4G (5G) and RS485 communication functions. Furthermore, the intelligent low-voltage switches must have electric operation functions.

4. The intelligent power distribution system for coking equipment based on demand analysis according to claim 1, characterized in that, In the platform layer, the data center should meet the following requirements: The collected data are processed, statistically analyzed, and calculated, and all results are saved to the database. Telemetry: Telemetry engineering conversion of primary side actual value, telemetry manual data setting, zero drift handling, telemetry over-limit alarm, various daily and monthly maximum, minimum and average statistics, and accident recall function; Remote signaling: Real-time processing of switch status, disconnector status, protection hard contact remote signaling, status quantity remote signaling, main transformer tap position and protection action items, protection alarm items, total fault remote signaling, and total warning remote signaling status changes to quickly generate change items, remote signaling inversion, remote signaling manual setting, maintenance or tagging settings, fault judgment, two-point remote signaling, remote control blocking and enabling, and statistics on the number of switch and protection actions; Electricity consumption: It can receive and process electricity meter code values ​​and pulse count values, perform scale conversion, manually set electricity consumption base code, calculate electricity consumption by integration, and provide daily, monthly, peak, valley, and average electricity consumption statistics; Statistical calculation functions: total active and reactive power summation, automatic calculation of safe days, transformer load rate and loss statistics, bus unbalance rate, bus voltage operating parameter non-compliance time and compliance rate statistics, capacitor and reactor input time, utilization rate and switching times, remote control adjustment times and success rate statistics, and users can define various formulas for calculation.

5. The intelligent power distribution system for coking equipment based on demand analysis according to claim 1, characterized in that, In the platform layer, data is received through cloud servers, large-screen display terminals, and mobile devices. The cloud server includes intelligent operation and maintenance management system software and database software to realize power monitoring and security management data mirroring, and realize intelligent operation and maintenance data management, Web services, APP application interfaces, business flow management services, operation and maintenance report services, intelligent inspection management, and equipment management services.

6. The intelligent power distribution system for coking equipment based on demand analysis according to claim 1, characterized in that, Within the platform layer, an intelligent fault diagnosis system, an operation and maintenance management system, and a power monitoring system for coking equipment are constructed. These systems enable online monitoring and management of the operating status, event alarms, measurement data, and fault recording information of the primary and secondary power supply equipment in 110kV substations, 35kV substations, and various integrated electrical rooms and substations. By combining the power supply system operation mode and expert knowledge base, online analysis and intelligent diagnosis of power faults based on power operation expert knowledge are achieved. When a power supply system accident occurs, the cause of the accident is deduced, and an accident handling guidance report is provided to guide the on-duty personnel in handling the accident, providing managers or operators with strong and timely decision-making support.

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