Comprehensive energy scheduling system based on distributed edge intelligence

Abstract

The invention discloses a comprehensive energy scheduling system based on distributed edge intelligence, which comprises a lower automatic control management layer and an upper edge adjustment management layer, and is characterized in that the lower automatic control management layer comprises a power distribution unit and a gas distribution unit; the upper edge adjustment management layer further comprises an edge data acquisition layer, a fault early warning diagnosis module, an energy monitoring and evaluation module, an energy scheduling management layer, an energy scheduling decision module and a centralized scheduling module. The edge energy data acquisition layer comprises intelligent collectors 1-4. The electric power distribution unit and the gas distribution unit are directly applied between the regional users and the power supply main body and the gas supply main body, so that edge-type autonomous distribution is realized, real-time data processing and decision making can be performed at edge nodes, the delay of data transmission is reduced, the scheduling efficiency and the response speed are improved, and the service life is prolonged. And an energy storage station and a gas storage station are arranged near each regional user, so that the energy supply guarantee of the sampling user can be improved, and the time delay of energy dispatching distribution is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of energy scheduling, and in particular to an integrated energy scheduling system based on distributed edge intelligence. Background Art

[0002] The existing energy dispatching system is a complex system built on advanced computer technology, information technology and automation technology. Although it can realize intelligent, efficient and sustainable energy dispatching, these systems usually integrate data collection, real-time monitoring, prediction analysis, optimization dispatching and other functions. They can monitor the production, transmission, distribution and consumption of energy in real time, and automatically adjust the energy dispatching strategy according to the real-time data and prediction results to ensure the stability and reliability of energy supply.

[0003] Traditional centralized dispatching systems need to collect and process a large amount of data before issuing dispatching instructions to each node. This process may cause large delays. At the same time, when supplying and allocating energy to regional users, it is impossible to achieve temporary energy supply guarantees for regional users and to quickly coordinate energy replenishment between regional users. Moreover, with the continuous expansion and complexity of energy systems, centralized dispatching systems may find it difficult to cope with large-scale data processing and dispatching needs. Summary of the invention

[0004] The purpose of the present invention is to provide a comprehensive energy scheduling system based on distributed edge intelligence, which can effectively solve the problems in the background technology.

[0005] To achieve the above object, the technical solution adopted by the present invention is:

[0006] A comprehensive energy dispatching system based on distributed edge intelligence, comprising a lower automatic control management layer and an upper edge calculation management layer, wherein the lower automatic control management layer comprises a power distribution unit and a gas distribution unit, and the upper edge calculation management layer further comprises an edge data collection layer, a fault warning / diagnosis module, an energy monitoring and evaluation module, an energy dispatching management layer, an energy dispatching decision module, and a centralized dispatching module, wherein the edge energy data collection layer comprises intelligent collectors 1-4, wherein the intelligent collector 1 is arranged on the lines between thermal power, solar energy, wind energy, geothermal energy and each substation and is respectively connected to the power distribution power supply and the edge gateway, the intelligent collector 3 is arranged on the line between the energy storage station and the end user and is connected to the edge gateway, the intelligent collector 2 is arranged on the pipeline between the natural gas main supply and the gas distribution unit and is connected to the edge gateway, and the intelligent collector 4 is arranged on the pipeline between the gas storage station and the end user and is connected to the edge gateway.

[0007] As a further optimization scheme of the present invention, the thermal power, solar power, wind power and geothermal power generation are respectively equipped with subsidiary substations, a plurality of the substations are connected to a power distribution unit, and the power distribution power supply is connected to an edge data collection layer.

[0008] As a further optimization scheme of the present invention, the shunt lines of the power distribution unit are respectively connected to multiple energy storage stations and regional users, and the lines between the power distribution unit and the energy storage stations are interconnected to reduce the delay of power regulation. The intelligent collector 3 collects the total input power of the power distribution unit, the power consumption of users in each region, and the power status of each energy storage station including the remaining power, charging power, discharging power, etc. in real time, monitors the power consumption patterns and peak power consumption periods of regional users in order to better predict demand, and simultaneously uploads the data to the upper edge computing layer for data collection and data processing.

[0009] As a further optimization scheme of the present invention, the power distribution unit firstly supplies power to users in multiple regions, and stores excess power in energy storage stations near users in each region. During peak power consumption periods, the power of the energy storage station is preferentially called to meet the needs of regional users to reduce the pressure on the power distribution unit. The power of the energy storage station is allocated in sequence according to the priority of regional users to ensure that key users are given priority protection. When the power of the regional energy storage station is insufficient, the input power of the power distribution unit is reasonably allocated. When the power consumption of users in a certain region suddenly increases, power is allocated from nearby energy storage stations in priority. If the power of the energy storage station is insufficient, more power is obtained from the power distribution unit to reduce the power control delay between regional users with high and low power demand. If a certain energy storage station fails or runs out of power, the distribution strategy is adjusted in time to allocate the regional users originally served by it to other energy storage stations or directly supply power to the power distribution unit.

[0010] During periods of low electricity consumption, energy storage stations are given priority for charging to reserve energy. For regional users with lower electricity consumption, the power supply can be appropriately reduced and the excess electricity can be allocated to charging energy storage stations. If there is excess power generation from solar, wind, and geothermal energy, it will be used first to charge energy storage stations and meet regional user needs.

[0011] As a further optimization scheme of the present invention, the total gas intake of the gas distribution unit, the gas consumption of users in each area, and the gas status of each gas storage station including the remaining gas volume, inflation rate, deflation rate, etc. are collected in real time, the gas consumption patterns and peak gas consumption periods of regional users are monitored, and external environmental information is collected, such as temperature changes, gas supply stability, etc.

[0012] As a further optimization scheme of the present invention, during peak gas consumption periods, the gas volume of the gas storage station is preferentially called upon to meet the needs of regional users to reduce the pressure on the gas distribution unit. The gas volume of the gas storage station is allocated in turn according to the priority of regional users to ensure stable supply for high-priority important public facilities and key industrial users. During low gas consumption periods, the gas storage station is preferentially charged to reserve energy. For regional users with smaller gas consumption, the gas supply pressure can be appropriately reduced and the excess gas can be allocated to the gas storage station for charging. Important public facilities such as schools, hospitals, and nursing homes are set as the highest priority to ensure the stability of their gas supply. For industrial users, their production is prioritized according to the importance of their production to the economy and society.

[0013] As a further optimization scheme of the present invention, the distribution strategy is dynamically adjusted according to the real-time monitored changes in gas consumption of regional users and the gas status of gas storage stations. When the gas consumption of users in a certain area suddenly increases, gas is allocated from nearby gas storage stations first. If the gas storage station is insufficient, more gas is obtained from the gas distribution unit. When a gas storage station fails or runs out of gas, the distribution strategy is adjusted in time to allocate users in the area originally served to other gas storage stations or directly supply gas from the gas distribution unit.

[0014] As a further optimization scheme of the present invention, data from the data acquisition layer is received and stored, analyzed and processed. The edge server analyzes the supply data of electricity and gas, and evaluates the electricity demand and gas demand of terminal users with the help of the energy monitoring and evaluation module, analyzes the electricity and gas consumption patterns of regional users, identifies peak and valley time periods, establishes an energy demand prediction model, predicts future energy demand based on historical data and environmental parameters, and predicts the demand change trend in the future. At the same time, the capacity utilization, charging and discharging and charging and discharging efficiency of energy storage stations and gas storage stations, as well as the health status of the equipment are evaluated. Among regional users, the energy consumption patterns of users in different regions are compared to draw time series curves of electricity and gas consumption, and peak and valley time periods are found. According to historical data and industry standards, a reasonable energy consumption benchmark value is determined. For different types of regional users and equipment, a reference range of average electricity consumption and gas consumption is set, and the actual energy consumption is compared with the benchmark value to find regional users that exceed the benchmark range.

[0015] As a further optimization scheme of the present invention, the energy scheduling decision module issues instructions to the centralized scheduling module, and adjusts the power distribution unit and the gas distribution unit through the centralized scheduling module, so as to adaptively and uniformly manage and schedule the energy storage station and the gas storage station, realize the storage and allocation of energy across time periods, improve the stability and reliability of the entire energy system, continuously optimize the algorithms and models of the energy monitoring and evaluation module and the energy scheduling decision module, and improve the prediction accuracy and decision-making efficiency.

[0016] Compared with the prior art, the present invention has the following beneficial effects:

[0017] In the present invention, an electricity distribution unit and a gas distribution unit are set up and directly used between regional users and power supply entities and gas supply entities, so as to realize edge-type autonomous distribution, enable real-time data processing and decision-making at edge nodes, reduce data transmission delays, improve scheduling efficiency and response speed, and set up energy storage stations and gas storage stations near each regional user, which can improve the energy supply security of sampling users and reduce the delay of energy scheduling and distribution. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a detailed diagram of the main system of the present invention;

[0019] Figure 2 This is a flow chart of the upper edge computing layer of the present invention. DETAILED DESCRIPTION

[0020] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0021] like Figure 1-Figure 2 As shown, the present invention provides an integrated energy dispatching system based on distributed edge intelligence, including a lower automatic control management layer and an upper edge settlement management layer, the lower automatic control management layer includes a power distribution unit and a gas distribution unit, the upper edge settlement management layer also includes an edge data acquisition layer, a fault warning\diagnosis module, an energy monitoring and evaluation module, an energy dispatching management layer, an energy dispatching decision module, and a centralized dispatching module. The edge energy data acquisition layer includes intelligent collectors 1-4, and the intelligent collector 1 is arranged on the line between thermal power, solar energy, wind energy, geothermal energy and each substation and is respectively connected to the power distribution power supply and the edge gateway, the intelligent collector 3 is arranged on the line between the energy storage station and the end user and is connected to the edge gateway, the intelligent collector 2 is arranged on the pipeline between the natural gas main supply and the gas distribution unit and is connected to the edge gateway, and the intelligent collector 4 is arranged on the pipeline between the gas storage station and the end user and is connected to the edge gateway.

[0022] Thermal power, solar power, wind power, and geothermal power generation are respectively equipped with subsidiary substations. Multiple substations are connected to the power distribution unit, and the power distribution power supply is connected to the edge data acquisition layer. The shunt lines of the power distribution unit are respectively connected to multiple energy storage stations and regional users, and the lines between the power distribution unit and the energy storage station are interconnected to reduce the delay of power regulation. The intelligent collector 3 collects the total input power of the power distribution unit, the power consumption of users in each region, and the power status of each energy storage station in real time, including the remaining power, charging power, and discharging power, etc. It monitors the power consumption mode and peak power consumption period of regional users in order to better predict demand, and simultaneously uploads the data to the upper edge computing layer for data collection and data processing. The power distribution unit first gives priority to the supply of electricity to users in multiple regions, and The surplus power is stored in the energy storage station near each regional user, and during the peak power consumption period, the power of the energy storage station is preferentially called to meet the needs of regional users to reduce the pressure on the power distribution unit. The power of the energy storage station is allocated in sequence according to the priority of regional users to ensure that key users are given priority. When the power of the regional energy storage station is insufficient, the input power of the power distribution unit is reasonably allocated. When the power consumption of users in a certain area suddenly increases, power is allocated from nearby energy storage stations first. If the power of the energy storage station is insufficient, more power is obtained from the power distribution unit to reduce the power control delay between regional users with high and low power demand. If a certain energy storage station fails or runs out of power, the allocation strategy is adjusted in time to allocate the regional users originally served by it to other energy storage stations or directly supply power to the power distribution unit.

[0023] During periods of low electricity consumption, energy storage stations are given priority for charging to reserve energy. For regional users with lower electricity consumption, the power supply can be appropriately reduced and the excess electricity can be allocated to charging energy storage stations. If there is excess power generation from solar, wind, and geothermal energy, it will be used first to charge energy storage stations and meet regional user needs.

[0024] Collect the total gas intake of the gas distribution unit, the gas consumption of users in each region, and the gas status of each gas storage station in real time, including the remaining gas volume, filling rate, deflation rate, etc., monitor the gas consumption patterns and peak gas consumption periods of regional users, and collect external environmental information, such as temperature changes, gas supply stability, etc. During peak gas consumption periods, prioritize the gas volume of the gas storage station to meet the needs of regional users to reduce the pressure on the gas distribution unit. According to the priority of regional users, allocate the gas volume of the gas storage station in turn to ensure stable supply for high-priority important public facilities and key industrial users, and prioritize during low gas consumption periods. The gas storage station is inflated to reserve energy. For regional users with smaller gas consumption, the gas supply pressure can be appropriately reduced, and the excess gas can be allocated to the gas storage station for charging. The allocation strategy is dynamically adjusted based on the real-time monitored changes in regional user gas consumption and the gas status of the gas storage station. When the gas consumption of users in a certain area suddenly increases, gas is allocated from nearby gas storage stations first. If the gas storage station is insufficient, more gas is obtained from the gas distribution unit. When a gas storage station fails or runs out of gas, the allocation strategy is adjusted in time to allocate users in the area it originally served to other gas storage stations or directly supply gas from the gas distribution unit.

[0025] The edge server analyzes the supply data of electricity and gas, and uses the energy monitoring and evaluation module to evaluate the electricity and gas demand of end users, analyzes the electricity and gas consumption patterns of regional users, identifies peak and trough periods, and predicts the demand change trend in the future. At the same time, it evaluates the capacity utilization, charging and discharging efficiency, and health status of energy storage stations and gas storage stations. Among regional users, the energy consumption patterns of users in different regions are compared to draw time series curves of electricity and gas consumption, and peak and trough periods are found. According to historical data and industry standards, a reasonable energy consumption benchmark value is determined. For different types of regional users and equipment, a reference range of average electricity and gas consumption is set, and the actual energy consumption is compared with the benchmark value to find regional users that exceed the benchmark range. The energy scheduling decision module issues instructions to the centralized scheduling module, and adjusts the power distribution unit and the gas distribution unit through the centralized scheduling module. The energy storage station and gas storage station are adaptively and uniformly managed and scheduled to realize cross-time storage and allocation of energy, improve the stability and reliability of the entire energy system, and continuously optimize the algorithms and models of the energy monitoring and evaluation module and the energy scheduling decision module to improve prediction accuracy and decision efficiency.

[0026] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A comprehensive energy dispatching system based on distributed edge intelligence, characterized by: It includes a lower automatic control management layer and an upper edge calculation management layer. The lower automatic control management layer includes a power distribution unit and a gas distribution unit. The upper edge calculation management layer also includes an edge data collection layer, a fault warning / diagnosis module, an energy monitoring and evaluation module, an energy scheduling management layer, an energy scheduling decision module, and a centralized scheduling module. The edge energy data collection layer includes intelligent collectors 1-4. The intelligent collector 1 is arranged on the line between thermal power, solar energy, wind energy, geothermal energy and each substation and is respectively connected to the power distribution power supply and the edge gateway. The intelligent collector 3 is arranged on the line between the energy storage station and the end user and is connected to the edge gateway. The intelligent collector 2 is arranged on the pipeline between the natural gas main supply and the gas distribution unit and is connected to the edge gateway. The intelligent collector 4 is arranged on the pipeline between the gas storage station and the end user and is connected to the edge gateway.

2. According to claim 1, a comprehensive energy dispatching system based on distributed edge intelligence is characterized in that: The thermal power, solar power, wind power and geothermal power generation are respectively equipped with subsidiary substations, a plurality of the substations are connected to a power distribution unit, and the power distribution power source is connected to an edge data collection layer.

3. The integrated energy dispatching system based on distributed edge intelligence according to claim 1 is characterized in that: The shunt lines of the power distribution unit are respectively connected to multiple energy storage stations and regional users, and the lines between the power distribution unit and the energy storage stations are interconnected to reduce the delay of power regulation. The intelligent collector 3 collects the total input power of the power distribution unit, the power consumption of users in each region, and the power status of each energy storage station (including remaining power, charging power, discharging power, etc.) in real time, monitors the power consumption patterns and peak power consumption periods of regional users in order to better predict demand, and simultaneously uploads the data to the upper edge computing layer for data collection and data processing.

4. The integrated energy dispatching system based on distributed edge intelligence according to claim 1 is characterized in that: The power distribution unit firstly supplies electricity to users in multiple regions, and stores excess electricity in energy storage stations near users in each region. During peak hours of electricity consumption, the power of energy storage stations is preferentially called to meet the needs of regional users to reduce the pressure on the power distribution unit. The power of energy storage stations is allocated in sequence according to the priorities of regional users to ensure that key users are given priority. When the power of regional energy storage stations is insufficient, the input power of the power distribution unit is reasonably allocated. When the power consumption of users in a certain region suddenly increases, power is allocated from nearby energy storage stations in priority. If the power of energy storage stations is insufficient, more power is obtained from the power distribution unit to reduce the power control delay between regional users with high and low power demand. If a certain energy storage station fails or runs out of power, the distribution strategy is adjusted in time to allocate the regional users originally served by it to other energy storage stations or directly supply power to the power distribution unit. During periods of low electricity consumption, energy storage stations are given priority for charging to reserve energy. For regional users with lower electricity consumption, the power supply can be appropriately reduced and the excess electricity can be allocated to charging energy storage stations. If there is excess power generation from solar, wind, and geothermal energy, it will be used first to charge energy storage stations and meet regional user needs.

5. The integrated energy dispatching system based on distributed edge intelligence according to claim 1 is characterized in that: Collect the total gas intake of the gas distribution unit, the gas consumption of users in each area, and the gas status of each gas storage station (including remaining gas volume, inflation rate, deflation rate, etc.) in real time, monitor the gas consumption patterns and peak gas consumption periods of regional users, and collect external environmental information, such as temperature changes, gas supply stability, etc.

6. The integrated energy dispatching system based on distributed edge intelligence according to claim 1 is characterized in that: During peak gas consumption periods, priority is given to calling on the gas storage station's gas volume to meet the needs of regional users to reduce the pressure on the gas distribution unit. The gas volume of the gas storage station is allocated in turn according to the priority of regional users to ensure stable supply to high-priority important public facilities and key industrial users. During low gas consumption periods, priority is given to filling the gas storage station to reserve energy. For regional users with smaller gas consumption, the gas supply pressure can be appropriately reduced and the excess gas can be allocated to the gas storage station for filling.

7. The integrated energy dispatching system based on distributed edge intelligence according to claim 1 is characterized in that: The distribution strategy is dynamically adjusted based on the real-time monitored changes in gas consumption of regional users and the gas status of gas storage stations. When the gas consumption of users in a certain area suddenly increases, gas is allocated from nearby gas storage stations first. If the gas station is short of gas, more gas is obtained from the gas distribution unit. When a gas storage station fails or runs out of gas, the distribution strategy is adjusted in time to allocate users in the area it originally served to other gas storage stations or directly supply gas from the gas distribution unit.

8. The integrated energy dispatching system based on distributed edge intelligence according to claim 1 is characterized in that: The edge server analyzes the supply data of electricity and gas, and evaluates the electricity and gas demands of terminal users with the help of the energy monitoring and evaluation module, analyzes the electricity and gas consumption patterns of regional users, identifies peak and trough periods, and predicts the demand change trend in the future. At the same time, it evaluates the capacity utilization, charging and discharging and charging and discharging efficiency, and the health status of the equipment of the energy storage station and the gas storage station. Among regional users, the energy consumption patterns of users in different regions are compared to draw time series curves of electricity and gas consumption, and the peak and trough periods are found. According to historical data and industry standards, a reasonable energy consumption benchmark value is determined. For different types of regional users and equipment, a reference range of average electricity and gas consumption is set, and the actual energy consumption is compared with the benchmark value to find regional users that exceed the benchmark range.

9. The integrated energy dispatching system based on distributed edge intelligence according to claim 1, characterized in that: The energy dispatch decision module issues instructions to the centralized dispatch module, and adjusts the power distribution unit and the gas distribution unit through the centralized dispatch module, performs adaptive unified management and dispatch of energy storage stations and gas storage stations, realizes cross-time storage and allocation of energy, improves the stability and reliability of the entire energy system, continuously optimizes the algorithms and models of the energy monitoring and evaluation module and the energy dispatch decision module, and improves prediction accuracy and decision-making efficiency.

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