Park-based intelligent power utilization data analysis and management system

Abstract

The invention relates to the technical field of park power consumption management, and discloses an intelligent power consumption data analysis and management system based on a park, and the system comprises a park information collection module which is used for collecting the functional layout information of the park; the region division module is used for dividing the park into a plurality of target regions according to the functional layout information of the park; the power utilization data acquisition module is used for regularly acquiring power utilization information data of each target area in the park; and the data analysis module is used for performing data analysis on the power utilization information data and generating an equipment supervision strategy according to the data analysis. The method can overcome the unified influence of the power consumption environment, the production efficiency and other factors on the power consumption of each target area, can timely discover the target area with the power consumption abnormally changed through analysis, carries out the targeted power consumption monitoring of the target area, and improves the robustness of the power consumption data analysis of the park.

Description

Technical Field

[0001] The present invention relates to the technical field of park electricity management, and in particular to an intelligent electricity data analysis and management system based on a park. Background Art

[0002] Power consumption analysis and management is a comprehensive process that aims to achieve real-time monitoring, analysis, optimization and safety management of power consumption through technical means and management measures. As a region where a large number of enterprises and personnel are concentrated, the power consumption analysis and management of the park plays an important role in improving operational efficiency, ensuring power safety, promoting energy conservation and emission reduction, and optimizing resource allocation.

[0003] Existing park management technology can quickly understand the park's electricity usage by real-time monitoring of electricity usage data within the park, including key indicators such as voltage, current, and power factor.

[0004] The park can usually be divided into multiple areas according to functional distribution, such as industrial areas, commercial areas, office areas, etc. Decentralized management of electricity consumption in each area can improve the efficiency and accuracy of electricity data collection and management. However, the peaks and troughs of electricity consumption in various areas of the park are often synchronized. This is mainly because the production and operation activities of various enterprises in the park usually have certain regularities. For example, when new projects in the park are put into use or the scale of production and operation of enterprises is expanded, the overall electricity consumption will increase, and the electricity consumption in each area will also increase accordingly. Similarly, in seasonal changes, such as increased electricity consumption for air conditioning in summer and increased electricity consumption for heating in winter, these seasonal changes will also be reflected in the electricity consumption of each area. The electricity consumption environment in the above example has a uniform impact on the electricity consumption of each area. Therefore, the existing technology only analyzes the amplitude of changes in electricity consumption in each area separately, and it is difficult to promptly discover areas with abnormal changes in electricity consumption.

[0005] However, existing technologies usually ignore the fact that failure of electrical equipment can also cause changes in electricity consumption. When a large change in the electricity consumption data of a park is detected, it is difficult to determine whether it is caused by a failure of electrical equipment in the park. Therefore, timely response measures cannot be arranged based on the electricity monitoring results. Summary of the invention

[0006] The purpose of the present invention is to provide an intelligent power consumption data analysis and management system based on the park to solve the above technical problems: The purpose of the present invention can be achieved through the following technical solutions: An intelligent power consumption data analysis and management system based on a park, the system comprising: Park information collection module, used to collect functional layout information of the park; The area division module is used to divide the park into several target areas according to the functional layout information of the park; The electricity consumption data collection module is used to regularly collect electricity consumption information data of each target area in the park; A data analysis module is used to perform data analysis on the power consumption information data and generate an equipment supervision strategy based on the data analysis; the process of performing data analysis on the power consumption information data includes: calculating the difference between the current power consumption data of the target area and the historical average power consumption data of the corresponding target area, and marking the difference as the power consumption variation coefficient, analyzing and obtaining the discreteness of the distribution of the power consumption variation coefficient of each target area, and if the discreteness exceeds a preset standard, screening the target area to be monitored according to the power consumption variation coefficient and the number of power-consuming equipment in the target area.

[0007] As a further technical solution, the system further includes: An electric equipment management module, which is used to execute the equipment supervision strategy and monitor the electric equipment in the target area to be monitored, and includes a collection terminal and an edge computing unit. The collection terminal is used to collect status information parameters of each electric equipment in the target area, and the edge computing unit is used to perform fault risk assessment on the relevant electric equipment according to the status information parameters of the electric equipment; A communication module, used to establish a communication connection between the power consumption equipment management module and the cloud, and upload the fault risk assessment result data of the power consumption equipment to the cloud; The cloud is used to store the fault risk assessment result data of electrical equipment and the basic information parameters of the corresponding equipment; The early warning module includes an early warning generation unit and a human-computer interaction unit. The early warning generation unit is used to generate an early warning prompt strategy according to the failure risk assessment result of the electrical equipment; and the human-computer interaction unit is used to execute the early warning prompt strategy.

[0008] As a further technical solution, the process of collecting electricity consumption information data of each target area in the park includes: Installing electric energy meters electrically connected to the electric devices in the corresponding target areas in each target area, and obtaining the electric energy consumption data of the target area through the electric energy meters; A unified communication protocol is used to transmit the electricity consumption data of each target area to the electricity consumption data analysis module.

[0009] As a further technical solution, the process of analyzing and obtaining the discreteness of the distribution of the coefficient of variation of electricity consumption in each target area includes: Through the following formula ~ Calculate the power consumption difference evaluation coefficient of the park ; ; ; ; in, is the power consumption of the i-th target area; is the historical average electricity consumption of the i-th target area; is the number of target areas; is the preset proportional coefficient corresponding to the i-th target area; is the power consumption variation coefficient of the i-th target area; The electricity consumption difference evaluation coefficient Difference from preset threshold To compare: like , then no device supervision policy is generated; like , the target area to be monitored is selected according to the power consumption change coefficient of the target area.

[0010] As a further technical solution, the process of screening the target area to be monitored includes: By formula Calculate the power consumption abnormality risk factor of the target area ; in, , is a preset first weight coefficient; is the coefficient of change of electricity consumption in the target area; is the number of electrical equipment in the corresponding target area; The abnormal risk value of electricity consumption With preset threshold Make a comparison: like , then the status information of the electrical equipment in the target area will not be collected; like , the status information of the electrical equipment in the target area is collected, and the failure risk of the relevant electrical equipment is evaluated according to the status information parameters of the electrical equipment through the edge computing unit.

[0011] As a further technical solution, the process of collecting status information parameters of electrical equipment includes: when the electrical equipment is under preset working conditions, collecting change data of the output power, operating noise volume and average component temperature of the electrical equipment within a preset unit time period, and at the same time, obtaining the corresponding standard change curves of the output power, operating noise volume and average component temperature of the electrical equipment.

[0012] As a further technical solution, the process of fault risk assessment of relevant electrical equipment includes: By formula Calculate the failure risk factor of electrical equipment ; in, is a preset second weight coefficient; The output power, operating noise volume and average component temperature of the electrical equipment change over time; It is the standard variation curve of the output power, operating noise volume and average temperature of components of electrical equipment; , They are the left and right endpoints of the preset unit time period respectively; The failure risk factor of the electrical equipment With preset risk threshold To compare: like , it is judged that the electrical equipment is operating normally; like , it is judged that the electrical equipment is operating abnormally, and a fault warning prompt signal for the electrical equipment is generated through the early warning module and an early warning is issued.

[0013] As a further technical solution, the system further includes: The historical data update module is used to update the historical average power consumption data of the target area. The process of updating the historical average power consumption data of the target area is as follows: if it is determined that there are abnormal power consumption devices in the target area, the historical average power consumption data of the target area will not be updated; otherwise, the historical average power consumption data of the target area will be updated through the formula Calculate and obtain the updated historical average power consumption value ,in, The total number of times the electricity consumption data of the target area is collected.

[0014] Beneficial effects of the present invention: (1) The present invention calculates the electricity consumption variation coefficient between the current electricity consumption data of the target area and the historical average electricity consumption data of the corresponding target area, and then analyzes and obtains the discreteness of the distribution of the electricity consumption variation coefficient of each target area. This analysis can overcome the uniform influence of factors such as the electricity consumption environment and production efficiency on the electricity consumption of each target area. Through analysis, the target area with abnormal electricity consumption changes can be discovered in time, and targeted electricity consumption monitoring can be performed on the target area, thereby improving the robustness of the park electricity consumption data analysis.

[0015] (2) The present invention provides an intelligent power consumption data analysis and management system based on the park. First, the park is divided into multiple target areas according to the functional layout of the park, so as to facilitate the separate monitoring and management of each target area to improve management efficiency. By monitoring and analyzing the power consumption information of each target area, the target area with abnormal power consumption is screened out, and the fault risk of the power equipment in the area is evaluated and checked. Therefore, by analyzing the power consumption data of the park, not only the power consumption trend of the park can be revealed, but also abnormal power equipment can be identified, so that maintenance measures for the power equipment can be arranged in a timely manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The present invention will be further described below in conjunction with the accompanying drawings.

[0017] Figure 1 This is a block diagram of the contents of the park-based intelligent electricity consumption data analysis and management system in the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] See also Figure 1 As shown, a park-based intelligent electricity consumption data analysis and management system, the system includes: The park information collection module is used to collect the functional layout information of the park. The area division module is used to divide the park into several target areas according to the functional layout information of the park. Specifically, according to the functional layout of the park, areas with similar power consumption characteristics are divided into the same power consumption area. For example, the production area, office area, dormitory area, etc. are divided into different power consumption target areas. In addition, the load density and power supply reliability of each area are also considered. The load density is the power load per unit area. Areas with high load density may require more power supply and a more complex power grid structure. Power supply reliability is to determine the power supply reliability level of each area according to the operational requirements of the park.

[0020] The electricity consumption data collection module is used to regularly collect electricity consumption information data of each target area in the park. Specifically, independent electricity meters can be installed in each area, and the electricity consumption change data on the electricity meters can be regularly obtained.

[0021] The data analysis module is used to perform data analysis on the power consumption information data and generate equipment supervision strategies based on the data analysis. Specifically, the process of performing data analysis on the power consumption information data includes: calculating the difference between the current power consumption data of the target area and the historical average power consumption data of the corresponding target area, and marking the difference as the power consumption change coefficient, analyzing and obtaining the discreteness of the distribution of the power consumption change coefficient of each target area, and if the discreteness exceeds the preset standard, screening the target area to be monitored according to the power consumption change coefficient and the number of power-consuming equipment in the target area. Through the above analysis, the unified influence of factors such as the power consumption environment and production efficiency on the power consumption of each target area can be overcome, the target area with abnormal power consumption can be discovered in time, and targeted power consumption monitoring can be performed on the area. The robustness and efficiency of the power consumption data analysis in the park are improved. That is, a sudden change in power consumption in a certain target area does not mean that the area has abnormal power consumption, but only when the change in power consumption in the target area is significantly different from that in other areas does it reflect the possibility of abnormal power consumption in the area.

[0022] Through the above technical solution, this embodiment provides an intelligent electricity consumption data analysis and management system based on the park. First, the park is divided into multiple target areas according to the functional layout of the park, which facilitates separate monitoring and management of each target area to improve management efficiency.

[0023] The system further comprises: The power equipment management module is used to execute the equipment supervision strategy, including a collection terminal and an edge computing unit. The collection terminal is used to collect status information parameters of each power equipment in the target area, and the edge computing unit is used to perform fault risk assessment on the relevant power equipment based on the status information parameters of the power equipment.

[0024] A communication module is used to establish a communication connection between the power consumption equipment management module and the cloud, and upload the fault risk assessment result data of the power consumption equipment to the cloud, so that the maintenance personnel can call the data in time when repairing the faulty power consumption equipment; The cloud is used to store the fault risk assessment result data of electrical equipment and the basic information parameters of the corresponding equipment. The basic information parameters specifically include the spare capacity of the electrical equipment, the equipment year, etc., providing useful data for the maintenance and analysis process of the faulty equipment.

[0025] The early warning module includes an early warning generation unit and a human-computer interaction unit. The early warning generation unit is used to generate an early warning prompt strategy according to the failure risk assessment result of the electrical equipment; the human-computer interaction unit is used to execute the early warning prompt strategy. The human-computer interaction unit specifically includes a handheld terminal (such as a mobile phone) of relevant staff or a uniformly set display terminal (such as a display set up in the park management department).

[0026] Through the above technical solution, this embodiment provides other contents of the system, including: communication module, cloud and early warning module. It realizes the storage and call of power consumption data analysis result information, and provides early warning prompts and data support for the management decision of park managers.

[0027] The process of collecting electricity consumption information data for each target area in the park includes: Installing electric energy meters electrically connected to the electric devices in the corresponding target areas in each target area, and obtaining the electric energy consumption data of the target area through the electric energy meters; A unified communication protocol is used to transmit the power consumption data of each target area to the power consumption data analysis module. Through the unified protocol, the power consumption data can be transmitted to the power consumption data analysis module in real time and accurately, ensuring the timeliness of power grid monitoring, dispatching and other work.

[0028] Through the above technical solution, a process for collecting electricity consumption information data of each target area in the park is provided, the electricity consumption data of each target area is obtained through independently set electric energy meters, and then the electricity consumption data of each target area is transmitted to the electricity consumption data analysis module using a unified communication protocol.

[0029] The process of analyzing and obtaining the discreteness of the distribution of the coefficient of variation of electricity consumption in each target area includes: Through the following formula ~ Calculate the power consumption difference evaluation coefficient of the park ; ; ; ; in, is the power consumption of the i-th target area; is the historical average electricity consumption of the i-th target area; is the number of target areas; is the preset proportional coefficient corresponding to the i-th target area; is the power consumption variation coefficient of the i-th target area; The electricity consumption difference evaluation coefficient Difference from preset threshold To compare: like , then no device supervision policy is generated; like , the target area to be monitored is selected according to the power consumption change coefficient of the target area.

[0030] Through the above technical solution, this embodiment provides a process for analyzing the power consumption information data. Specifically, firstly, the formula , , Calculate the power consumption difference evaluation coefficient of the park , it can be seen from the formula that this coefficient not only reflects the difference between the target area's electricity consumption information and its historical electricity consumption information, but also reflects the changes in the electricity consumption relationship between different regions. Difference from preset threshold Comparison: Considering the uniform impact of environmental factors, production efficiency and other factors on the electricity consumption of each target area, the changes in electricity consumption in each area have a certain correlation. , indicating that the difference in power consumption in each area is small, no equipment supervision strategy is generated; when , it means that the power consumption changes in various areas are quite different, so the target area to be monitored is selected according to the power consumption change coefficient of the target area, and then the fault risk analysis of the power equipment in the target area to be monitored is performed. It should be noted that in the above formula, is the power consumption of the i-th target area; is the historical average electricity consumption of the i-th target area, which is obtained by accumulating the historical electricity consumption and dividing it by the number of electricity consumption collection times. is the number of target areas; is a preset proportional coefficient corresponding to the i-th target area, which is related to the characteristics of the device itself and can be obtained based on empirical data. is the power consumption variation coefficient of the i-th target area.

[0031] The process of selecting target areas for monitoring includes: By formula Calculate the power consumption abnormality risk factor of the target area ; in, , is a preset first weight coefficient; is the coefficient of change of electricity consumption in the target area; is the number of electrical equipment in the corresponding target area; The abnormal risk value of electricity consumption With preset threshold Make a comparison: like , then the status information of the electrical equipment in the target area will not be collected; like , the status information of the electrical equipment in the target area is collected, and the failure risk of the relevant electrical equipment is evaluated according to the status information parameters of the electrical equipment through the edge computing unit.

[0032] Through the above technical solution, this embodiment provides a process for screening the target area to be monitored. Specifically, firstly, Calculate the power consumption abnormality risk factor of the target area ,From the formula, we can see that the abnormal risk coefficient is related to the number of power-consuming devices in the target area. The larger the number, the more uncontrollable factors there are, and the greater the probability that the power consumption change is caused by equipment failure. Then the power consumption abnormal risk value With preset threshold Make a comparison: If , indicating that the risk of abnormal power consumption in the target area is relatively small, and the status information of the power equipment in the target area is not collected; if , indicating that the abnormal risk of power consumption in the target area is relatively high. Therefore, the status information of the power-consuming equipment in the target area is collected, and the failure risk of the relevant power-consuming equipment is evaluated according to the status information parameters of the power-consuming equipment through the edge computing unit.

[0033] The process of collecting status information parameters of electrical equipment includes: when the electrical equipment is under preset working conditions, collecting change data of the output power, operating noise volume and average component temperature of the electrical equipment within a preset unit time period, and at the same time, obtaining the corresponding standard change curves of the output power, operating noise volume and average component temperature of the electrical equipment.

[0034] Through the above technical solution, this embodiment provides a process for collecting state information parameters of electrical equipment. Specifically, when the electrical equipment is under preset working conditions, the change data of the output power, operating noise volume and component average temperature of the electrical equipment within a preset unit time period are collected, and at the same time, the standard change curves of the output power, operating noise volume and component average temperature of the electrical equipment are obtained accordingly. It should be noted that each standard change curve is obtained based on normal equipment under the same preset working conditions as above.

[0035] The process of conducting failure risk assessment on relevant electrical equipment includes: By formula Calculate the failure risk factor of electrical equipment ; in, is a preset second weight coefficient; The output power, operating noise volume and average component temperature of the electrical equipment over time, specifically, such as: is the output power variation of the electrical equipment over time, is the value of the operating noise volume of the electrical equipment changing over time, It is the average temperature change of the components of the electrical equipment over time. It is the standard variation curve of the output power, operating noise volume and average temperature of components of electrical equipment. ~ The corresponding relationship with output power, operating noise volume and average component temperature is the same as above. The explanation is the same, so I won’t repeat it here. , They are the left and right endpoints of the preset unit time period respectively; The failure risk factor of the electrical equipment With preset risk threshold To compare: like , it is judged that the electrical equipment is operating normally; like , it is judged that the electrical equipment is operating abnormally, and a fault warning prompt signal for the electrical equipment is generated through the early warning module and an early warning is issued.

[0036] Through the above technical solution, this embodiment provides a process for evaluating the failure risk of relevant electrical equipment, that is, firstly through the formula Calculate the failure risk factor of electrical equipment , and then the failure risk factor of the electrical equipment With preset risk threshold Compare: If , indicating that the failure risk of the electrical equipment is small, so it is judged that the electrical equipment is operating normally; if , indicating that the failure risk of the electrical equipment is relatively high. Therefore, it is judged that the electrical equipment is operating abnormally, and a fault warning prompt signal for the electrical equipment is generated through the early warning module and an early warning is issued. The early warning content specifically includes the equipment name and the location information of the equipment in the park.

[0037] The system further comprises: The historical data update module is used to update the historical average power consumption data of the target area. The process of updating the historical average power consumption data of the target area is as follows: if it is determined that there are abnormal power consumption devices in the target area, the historical average power consumption data of the target area will not be updated; otherwise, the historical average power consumption data of the target area will be updated through the formula Calculate and obtain the updated historical average power consumption value ,in, is the total number of times the target area power consumption data is collected. Through the above technical solution, this embodiment provides a specific method for updating the historical average power consumption data of the target area.

[0038] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. An intelligent power consumption data analysis and management system based on a park, characterized in that: The system comprises: Park information collection module, used to collect functional layout information of the park; The area division module is used to divide the park into several target areas according to the functional layout information of the park; The electricity consumption data collection module is used to regularly collect electricity consumption information data of each target area in the park; A data analysis module is used to perform data analysis on the power consumption information data and generate an equipment supervision strategy based on the data analysis; the process of performing data analysis on the power consumption information data includes: calculating the difference between the current power consumption data of the target area and the historical average power consumption data of the corresponding target area, and marking the difference as the power consumption variation coefficient, analyzing and obtaining the discreteness of the distribution of the power consumption variation coefficient of each target area, and if the discreteness exceeds a preset standard, screening the target area to be monitored according to the power consumption variation coefficient and the number of power-consuming equipment in the target area.

2. According to claim 1, the intelligent power consumption data analysis and management system based on the park is characterized in that: The system further comprises: An electric equipment management module, which is used to execute the equipment supervision strategy and monitor the electric equipment in the target area to be monitored, and includes a collection terminal and an edge computing unit. The collection terminal is used to collect status information parameters of each electric equipment in the target area, and the edge computing unit is used to perform fault risk assessment on the relevant electric equipment according to the status information parameters of the electric equipment; A communication module, used to establish a communication connection between the power consumption equipment management module and the cloud, and upload the fault risk assessment result data of the power consumption equipment to the cloud; The cloud is used to store the fault risk assessment result data of electrical equipment and the basic information parameters of the corresponding equipment; The early warning module includes an early warning generation unit and a human-computer interaction unit. The early warning generation unit is used to generate an early warning prompt strategy according to the failure risk assessment result of the electrical equipment; and the human-computer interaction unit is used to execute the early warning prompt strategy.

3. According to claim 2, the intelligent power consumption data analysis and management system based on the park is characterized in that: The process of collecting electricity consumption information data for each target area in the park includes: Installing electric energy meters electrically connected to the electric devices in the corresponding target areas in each target area, and obtaining the electric energy consumption data of the target area through the electric energy meters; A unified communication protocol is used to transmit the electricity consumption data of each target area to the electricity consumption data analysis module.

4. The intelligent power consumption data analysis and management system based on a park according to claim 3 is characterized in that: The process of analyzing and obtaining the discreteness of the distribution of the coefficient of variation of electricity consumption in each target area includes: Through the following formula ~ Calculate the power consumption difference evaluation coefficient of the park ; ； ； ； in, is the power consumption of the i-th target area; is the historical average electricity consumption of the i-th target area; is the number of target areas; is the preset proportional coefficient corresponding to the i-th target area; is the power consumption variation coefficient of the i-th target area; The electricity consumption difference evaluation coefficient Difference from preset threshold To compare: like , then no device supervision policy is generated; like , the target area to be monitored is selected according to the power consumption change coefficient of the target area.

5. The intelligent power consumption data analysis and management system based on the park according to claim 4 is characterized in that: The process of selecting target areas for monitoring includes: By formula Calculate the power consumption abnormality risk factor of the target area ; in, , is a preset first weight coefficient; is the coefficient of change of electricity consumption in the target area; is the number of electrical equipment in the corresponding target area; The abnormal risk value of electricity consumption With preset threshold Make a comparison: like , then the status information of the electrical equipment in the target area will not be collected; like , the status information of the electrical equipment in the target area is collected, and the failure risk of the relevant electrical equipment is evaluated according to the status information parameters of the electrical equipment through the edge computing unit.

6. The intelligent power consumption data analysis and management system based on the park according to claim 5 is characterized in that: The process of collecting status information parameters of electrical equipment includes: when the electrical equipment is under preset working conditions, collecting change data of the output power, operating noise volume and average component temperature of the electrical equipment within a preset unit time period, and at the same time, obtaining the corresponding standard change curves of the output power, operating noise volume and average component temperature of the electrical equipment.

7. The intelligent power consumption data analysis and management system based on a park according to claim 6 is characterized in that: The process of conducting failure risk assessment on relevant electrical equipment includes: By formula Calculate the failure risk factor of electrical equipment ; in, is a preset second weight coefficient; The output power, operating noise volume and average component temperature of the electrical equipment change over time; It is the standard variation curve of the output power, operating noise volume and average temperature of components of electrical equipment; , They are the left and right endpoints of the preset unit time period respectively; The failure risk factor of the electrical equipment With preset risk threshold To compare: like , it is judged that the electrical equipment is operating normally; like , it is judged that the electrical equipment is operating abnormally, and a fault warning prompt signal for the electrical equipment is generated through the early warning module and an early warning is issued.

8. The intelligent power consumption data analysis and management system based on a park according to claim 7 is characterized in that: The system further comprises: The historical data update module is used to update the historical average power consumption data of the target area. The process of updating the historical average power consumption data of the target area is as follows: if it is determined that there are abnormal power consumption devices in the target area, the historical average power consumption data of the target area will not be updated; otherwise, the historical average power consumption data of the target area will be updated through the formula Calculate and obtain the updated historical average power consumption value ,in, The total number of times the electricity consumption data of the target area is collected.

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