Multi-energy integrated real-time monitoring system based on big data

Abstract

The invention relates to the technical field of big data monitoring, in particular to a multi-energy integrated real-time monitoring system based on big data, which monitors temperatures of different production line areas of an energy-saving motor and obtains electric energy parameters of the energy-saving motor through a monitor, and stores historical sample data monitored by the monitor through an analyzer. An energy consumption significant influence period and an energy consumption gentle influence period can be determined through a controller based on energy consumption influence tendency characterization values corresponding to different temperature influence periods, and the running state of the energy-saving motor is monitored, so that whether the energy consumption effect of the energy-saving motor predicted by energy influence characterization parameters meets a predetermined standard or not is determined; to determine whether to activate the thermal compensation device. The influence of the temperature difference of each production line area on the energy consumption effect of the energy-saving motor in the operation process of the multi-energy integrated real-time monitoring system is considered, and the thermal compensation device is adaptively involved, so that the efficiency of the real-time monitoring system is improved.

Description

Technical Field

[0001] The present invention relates to the field of big data monitoring, and in particular to a multi-energy integrated real-time monitoring system based on big data. Background Art

[0002] Driven by the global energy transition, integrated energy systems are becoming increasingly complex, integrating multiple energy sources such as electricity, heat, and steam. Traditional monitoring methods suffer from data fragmentation, low processing efficiency, and a lack of dynamic analysis, making them incapable of meeting the demands of coordinated multi-energy operations. The rapid development of the Internet of Things, cloud computing, and big data technologies has made it possible to collect, transmit, and analyze massive amounts of energy data in real time. With its powerful data mining and analysis capabilities, big data technology can effectively integrate heterogeneous data from multiple sources, enabling real-time monitoring and intelligent decision-making for energy systems. This provides crucial technical support for improving energy efficiency, optimizing resource allocation, and promoting sustainable energy development.

[0003] Chinese patent publication number: CN107450431B, discloses an integrated energy management system, including: an energy information management system, a data collection server, and energy consumption collection terminals, energy data exchange terminals, and enterprise energy consumption switches located in each energy consumption area of an enterprise; the energy information management system is in communication with the data collection server, which is in communication with the enterprise energy consumption switches in each energy consumption area of the enterprise, the enterprise energy consumption switches in each energy consumption area are in communication with the energy data exchange terminals in that energy consumption area, and the energy data exchange terminals in that energy consumption area are in communication with the energy consumption collection terminals in that energy consumption area; the data collection server is used to collect energy consumption reported by the energy collection terminals in each energy consumption area; the energy information management system is used to visualize the energy consumption collected by the data collection server, thereby realizing real-time visualization management of energy consumption.

[0004] Chinese patent publication number: CN118071168B, discloses an integrated energy management system, including a prediction model monitor, a central processing module, an analyzer, and a comparison module. The modules are connected by signals. By monitoring the prediction process of the energy prediction model and extracting multiple feature data related to the prediction process of the energy prediction model from the monitoring data, a prediction hidden danger assessment index is generated, the prediction process of this energy prediction model is evaluated, the prediction process with greater hidden dangers is marked, and a data analysis set is established based on the marking results. The data analysis set is analyzed to determine a repair plan for the prediction model. When there is an obvious abnormal risk in the stability of the energy prediction model, an early warning signal is issued, which helps to improve the stability and accuracy of the prediction, avoid energy waste and decision-making errors caused by model instability, and help identify energy-saving potential, thereby improving energy utilization efficiency.

[0005] However, the prior art still has the following problems: In the existing technology, the difference in energy loss characteristics of energy-saving motors caused by the influence of different ambient temperatures in different production line areas in different historical periods is not taken into account, which causes the increase in energy consumption and the impact of energy consumption effects when the thermal compensation device is uniformly turned on, resulting in low energy efficiency. Summary of the Invention

[0006] In order to solve the above problems, the present invention provides a multi-energy integrated real-time monitoring system based on big data, which overcomes the problem in the prior art that energy-saving motors do not take into account the influence of environmental temperature differences in different production line areas in different historical periods, resulting in differences in energy loss characteristics of energy-saving motors, thereby affecting energy consumption effects and resulting in low energy consumption efficiency.

[0007] To achieve the above objectives, the present invention provides a multi-energy integrated real-time monitoring system based on big data, comprising: A collection component for collecting energy consumption characteristic parameters of different production line areas over a historical period, including a power analyzer for collecting energy-saving motor electrical energy parameters in different production line areas, and a thermal compensation device for changing the temperature of the energy-saving motor; A monitor including a plurality of temperature sensors for monitoring the temperature of the energy-saving motors in each production line area during different historical periods and an electric energy monitoring unit for obtaining electric energy parameters of the energy-saving motors; an analyzer, connected to the acquisition component and the monitor, respectively, for storing historical sample data within a historical period, identifying temperature impact periods based on temperature differences in various production line areas of the energy-saving motor during different historical periods, and analyzing energy consumption impact tendency characterization values of the energy-saving motor during different temperature impact periods based on changes in energy consumption characteristic parameters of different production line areas; A controller is connected to the acquisition component, the monitor, and the analyzer, respectively, and is used to determine the energy consumption significant impact period and the energy consumption moderate impact period based on the energy consumption impact tendency characterization value in different temperature impact periods; and monitor the energy-saving motor operation status based on the determination result, including: determining an energy impact characterization parameter based on a change in the temperature of the energy-saving motor and a change ratio in the energy conversion efficiency within a predetermined period to predict whether the energy consumption effect of the energy-saving motor meets a predetermined standard, and determining whether to enable the thermal compensation device based on the power consumption of the thermal compensation device and the current power loss; The energy consumption characteristic parameters include electrical energy parameters, water consumption and steam consumption.

[0008] Preferably, the analyzer is used to identify the temperature impact period based on the temperature difference of each production line area of the energy-saving motor in different historical periods, wherein: To calculate the variance of the temperature of each production line area of energy-saving motors in each historical period; If the variance of the temperature in each historical period is greater than a predetermined variance threshold, the historical period is determined to be a temperature-affected period.

[0009] Preferably, the energy consumption impact tendency characterization value is determined based on the sum of the first historical sample data feature, the second historical sample data feature, and the third historical sample data feature, wherein: The first historical sample data feature is determined based on the sum of the ratio of the rate of change of the electric energy conversion power in a single production line area to the rate of change threshold and the ratio of the current change rate of the energy-saving motor to the current change threshold; The second historical sample data feature is determined based on a difference between water usage in a single production line area and a predetermined water usage threshold, and is determined based on a ratio of the water usage difference to the water usage difference threshold; The third historical sample data feature is determined based on the difference between the steam usage in a single production line area and a predetermined steam usage threshold, and is determined based on the ratio of the steam usage difference to the steam usage difference threshold.

[0010] Preferably, the controller is configured to determine a period of significant energy consumption impact and a period of moderate energy consumption impact based on energy consumption impact tendency characterization values within different temperature impact periods, including: If the energy consumption impact tendency representation value is greater than or equal to the preset impact tendency representation value, the energy consumption cycle category of the actual period is determined to be a period with significant energy consumption impact; If the energy consumption impact tendency representation value is less than the preset impact tendency representation value, the energy consumption cycle category of the actual cycle is determined to be an energy consumption flat impact cycle.

[0011] Preferably, the controller monitors the running state of the energy-saving motor based on the determination result, including: If the result of the determination is that the energy consumption significantly affects the period, then determining whether the energy consumption effect of the energy-saving motor predicted by the energy impact characterization parameter meets the predetermined standard based on the amount of change in the temperature of the energy-saving motor and the change ratio of the energy conversion efficiency within the predetermined period, and determining whether to enable the thermal compensation device based on the power consumption of the thermal compensation device and the current power loss; If the result is determined to be a period of gentle energy consumption impact, the thermal compensation device is not enabled.

[0012] Preferably, the controller is used to determine the energy impact characterization parameter based on the change in the temperature of the energy-saving motor and the change ratio of the energy conversion efficiency within a predetermined period, including: The ratio of the change amount of the energy-saving motor temperature to the energy-saving motor temperature change threshold is used to calculate and determine the first energy influencing parameter feature; The ratio of the change in energy conversion efficiency of the energy-saving motor to the energy loss efficiency change threshold is used to calculate the second energy influencing parameter feature; The sum of the first energy impact parameter characteristic and the second energy impact parameter characteristic is calculated and determined as the energy impact characterization parameter.

[0013] Preferably, the controller is used to predict whether the energy consumption effect of the energy-saving motor meets the predetermined standard based on the energy impact characterization parameter, including: If the energy impact characterization parameter is less than or equal to the preset energy impact characterization parameter, it is predicted that the energy consumption effect of the energy-saving motor meets the predetermined standard; If the energy impact characterization parameter is greater than the preset energy impact characterization parameter, it is predicted that the energy consumption effect of the energy-saving motor does not meet the predetermined standard.

[0014] Preferably, the controller is used to determine whether to enable the thermal compensation device based on the power consumption of the thermal compensation device and the current power loss when it is predicted that the energy consumption effect of the energy-saving motor does not meet the predetermined standard.

[0015] Preferably, the controller is configured to determine whether to enable the thermal compensation device based on the power consumption of the thermal compensation device and the current power loss, including: If the power consumption of the thermal compensation device is less than or equal to the current power loss, determining to activate the thermal compensation device; If the power consumption of the thermal compensation device is greater than the current power loss, it is determined not to enable the thermal compensation device.

[0016] Preferably, the present invention further comprises a display unit, which is connected to the monitor, the analyzer and the controller respectively, and is used to display the data monitored by the monitor.

[0017] Compared with the prior art, the present invention provides a multi-energy integrated real-time monitoring system based on big data, including an acquisition component, a monitor, an analyzer, and a controller. The acquisition component collects energy consumption characteristic parameters of different production line areas in a historical period, including converting electrical energy into mechanical energy and changing the thermal compensation status of the temperature of each production line area of the energy-saving motor according to actual conditions. The monitor monitors the temperature of different production line areas of the energy-saving motor and obtains the electrical energy parameters of the energy-saving motor. The analyzer can store the historical sample data monitored by the monitor. Moreover, the controller determines the energy consumption significant impact period and the energy consumption gentle impact period based on the energy consumption impact tendency characterization value corresponding to different temperature impact periods, monitors the operating status of the energy-saving motor, and determines the energy impact characterization parameter to predict whether the energy consumption effect of the energy-saving motor meets the predetermined standard, so as to determine whether to enable the thermal compensation device, consider the impact of the temperature difference of the energy-saving motor on the energy loss efficiency during the operation of the energy monitoring system, and adaptively intervene in the thermal compensation device to ensure the energy loss efficiency of the energy monitoring system.

[0018] In particular, the present invention can accurately obtain the rules of how energy-saving motors are affected by temperature in different time periods by identifying the temperature influence cycle, and can accurately determine the temperature influence cycle of the historical period by calculating the variance of the temperature of each production line area of the energy-saving motor in each historical period. Moreover, the energy consumption influence tendency characterization value of the energy-saving motor in different temperature influence cycles can be accurately analyzed through the changes in the energy consumption characteristic parameters, thereby improving the efficiency of the energy-saving motor.

[0019] In particular, the present invention can determine the energy impact characterization parameters through the change in the energy-saving motor temperature and the change ratio of the energy conversion efficiency, thereby improving the accuracy of the energy consumption effect of the energy-saving motor. The energy consumption effect of the energy-saving motor can be predicted through the energy impact characterization parameters, and whether the performance of the energy-saving motor will decline can be predicted in advance, reducing the occurrence of the energy-saving motor's conversion efficiency decline caused by the influence of the temperature influence cycle, and improving the stability and energy loss efficiency of the energy-saving motor.

[0020] In particular, the present invention can determine the energy consumption significant impact period and the energy consumption moderate impact period through the energy consumption impact tendency characterization values corresponding to different temperature impact periods, thereby improving energy utilization efficiency. Moreover, by determining whether the thermal compensation device is enabled for the energy-saving motor, the energy utilization efficiency is further improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a structural block diagram of a multi-energy integrated real-time monitoring system based on big data according to an embodiment of the present invention; Figure 2 A logic decision diagram for identifying a temperature influence period according to an embodiment of the present invention; Figure 3A logic decision diagram for analyzing energy consumption impact tendency characterization values of energy-saving motors according to an embodiment of the present invention; Figure 4 This is a logic decision diagram for determining a period with significant energy consumption impact and a period with moderate energy consumption impact according to an embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention.

[0023] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0024] It should be noted that, in the description of the present invention, unless otherwise expressly specified or limited, the term "connection" should be understood in a broad sense. For example, it can mean a fixed connection, a detachable connection, or an integral connection; it can mean a mechanical connection or an electrical connection; it can mean a direct connection or an indirect connection through an intermediate medium; it can mean internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0025] See also Figure 1 As shown in FIG, which is a structural block diagram of a multi-energy integrated real-time monitoring system based on big data according to an embodiment of the present invention, the present invention provides a multi-energy integrated real-time monitoring system based on big data, comprising: A collection component for collecting energy consumption characteristic parameters of different production line areas over a historical period, including a power analyzer for collecting energy-saving motor electrical energy parameters in different production line areas, and a thermal compensation device for changing the temperature of the energy-saving motor; A monitor including a plurality of temperature sensors for monitoring the temperature of the energy-saving motors in each production line area during different historical periods and an electric energy monitoring unit for obtaining electric energy parameters of the energy-saving motors; an analyzer, connected to the acquisition component and the monitor, respectively, for storing historical sample data within a historical period, identifying temperature impact periods based on temperature differences in various production line areas of the energy-saving motor during different historical periods, and analyzing energy consumption impact tendency characterization values of the energy-saving motor during different temperature impact periods based on changes in energy consumption characteristic parameters of different production line areas; A controller is connected to the acquisition component, the monitor, and the analyzer, respectively, and is used to determine the energy consumption significant impact period and the energy consumption moderate impact period based on the energy consumption impact tendency characterization value in different temperature impact periods; and monitor the energy-saving motor operation status based on the determination result, including: determining an energy impact characterization parameter based on a change in the temperature of the energy-saving motor and a change ratio in the energy conversion efficiency within a predetermined period to predict whether the energy consumption effect of the energy-saving motor meets a predetermined standard, and determining whether to enable the thermal compensation device based on the power consumption of the thermal compensation device and the current power loss; The energy consumption characteristic parameters include electrical energy parameters, water consumption and steam consumption.

[0026] In practice, the multi-energy integrated real-time monitoring method based on big data includes: Step S1: collecting energy consumption characteristic parameters of different production line areas and different time periods in a historical period, and using a power analyzer to collect energy-saving motor power parameters; the energy consumption characteristic parameters include power parameters, water usage, and steam usage; Step S2, identifying a temperature impact period based on the temperature difference of each production line area of the energy-saving motor in different historical periods; Step S3: monitoring the temperature of the energy-saving motor in each production line area during different historical periods and monitoring the electric energy parameters of the energy-saving motor; identifying the temperature impact period based on the temperature difference of the energy-saving motor in each production line area during different historical periods; and analyzing the energy consumption impact tendency representation value of the energy-saving motor in different temperature impact periods based on the change of the energy consumption characteristic parameters of the different production line areas; Step S4: determining a period of significant energy consumption impact and a period of moderate energy consumption impact based on the energy consumption impact tendency characterization values within different temperature impact periods; and monitoring the operating state of the energy-saving motor based on the determination result, including: An energy impact characterization parameter is determined based on the amount of change in the temperature of the energy-saving motor within a predetermined period and the proportion of change in the energy conversion efficiency to predict whether the energy consumption effect of the energy-saving motor meets the predetermined standard, and whether to enable the thermal compensation device is determined based on the power consumption of the thermal compensation device and the current power loss.

[0027] Specifically, the system includes an acquisition component, a monitor, an analyzer, and a controller. The energy-saving motor converts electrical energy into mechanical energy and changes the thermal compensation status of the temperature of each production line area of the energy-saving motor according to actual conditions. The monitor monitors the temperature of different production line areas of the energy-saving motor and obtains the electrical energy parameters of the energy-saving motor. The analyzer stores the historical sample data monitored by the monitor. Moreover, the controller determines the energy consumption significant impact period and the energy consumption moderate impact period based on the energy consumption impact tendency characterization value corresponding to different temperature impact periods, monitors the operating status of the energy-saving motor, and determines the energy impact characterization parameters to predict whether the energy consumption effect of the energy-saving motor meets the predetermined standards, so as to determine whether to enable the thermal compensation device, consider the impact of the temperature difference of the energy-saving motor on the energy loss efficiency during the operation of the energy monitoring system, and adaptively intervene in the thermal compensation device to ensure the energy loss efficiency of the energy monitoring system.

[0028] Specifically, the present invention is applied to various energy-consuming factory areas. Commonly, the factory areas include energy-saving motors and integrated energy management platforms. Energy-saving motors are usually installed in various production lines. Due to differences in ambient temperature, the energy loss temperature of energy-saving motors varies. In addition, there may also be certain temperature differences in different production line areas.

[0029] Specifically, there is no specific limitation on the structure of the monitor, analyzer, controller itself and each unit therein, and they can be composed of logical components, which include field programmable processors, computers or microprocessors in computers.

[0030] Specifically, the form of the thermal compensation device is not limited. It can be liquid-cooled or air-cooled. For example, a small cooling fan is set on the energy-saving motor to dissipate heat for the energy-saving motor. Other forms can also be used, which will not be repeated here.

[0031] Specifically, there is no specific limitation on the location of the temperature sensor. The temperature sensor can be set in the energy-saving motor area, which will not be described in detail here.

[0032] Specifically, the power monitoring unit may be a logical component for acquiring information, for example, it may be connected to an energy-saving motor management system to acquire relevant parameters, which will not be described in detail here.

[0033] See also Figure 2 The above is a logic decision diagram for identifying the temperature impact period of an embodiment of the present invention. The analyzer of the present invention is used to identify the temperature impact period based on the temperature difference of each production line area of the energy-saving motor in different historical periods, wherein: To calculate the variance of the temperature of each production line area of energy-saving motors in each historical period; If the variance of the temperature in each historical period is greater than a predetermined variance threshold, the historical period is determined to be a temperature-affected period.

[0034] Specifically, the variance threshold is determined based on the average variance of the temperatures obtained in several historical periods and is set between 1.15 and 1.3 times the average variance.

[0035] Specifically, in order to reflect the monitorability of temperature changes and their impact on energy-saving motors, the historical period is selected in the interval [2h, 4h].

[0036] See also Figure 3 As shown, it is a logical decision diagram for analyzing the energy consumption impact tendency characterization value of an energy-saving motor according to an embodiment of the present invention. The energy consumption impact tendency characterization value according to the embodiment of the present invention is determined based on the sum of the first historical sample data feature, the second historical sample data feature, and the third historical sample data feature, wherein: The first historical sample data feature is determined based on the sum of the ratio of the rate of change of the electric energy conversion power in a single production line area to the rate of change threshold and the ratio of the current change rate of the energy-saving motor to the current change threshold; The second historical sample data feature is determined based on a difference between water usage in a single production line area and a predetermined water usage threshold, and is determined based on a ratio of the water usage difference to the water usage difference threshold; The third historical sample data feature is determined based on the difference between the steam usage in a single production line area and a predetermined steam usage threshold, and is determined based on the ratio of the steam usage difference to the steam usage difference threshold.

[0037] In an embodiment, the analyzer is used to analyze the energy consumption impact tendency characterization value of the energy-saving motor in different temperature impact cycles based on the change of energy consumption characteristic parameters of different production line areas, including: Calculating the sum of the ratio of the rate of change of the electric energy conversion power in a single production line area to the rate of change threshold and the ratio of the current change rate of the energy-saving motor to the current change threshold to determine as the first historical sample data feature; Calculating the difference between the water usage in a single production line area and a predetermined water usage threshold, and determining the ratio of the water usage difference to the water usage difference threshold as a second historical sample data feature; Calculating the difference between the steam usage in a single production line area and a predetermined steam usage threshold, and determining a ratio of the steam usage difference to the steam usage difference threshold as a third historical sample data feature; The sum of the first historical sample data feature, the second historical sample data feature, and the third historical sample data feature is determined as the energy consumption impact tendency representation value.

[0038] Specifically, the rate of change of electric energy conversion power reflects the change in the efficiency of energy-saving motors in converting electric energy under different temperature influence cycles. The rate of change threshold is a reference value used to measure whether the degree of such change is significant. In implementation, it is set as the average rate of change of electric energy within several historical cycles. By calculating the ratio, the rate of change can be standardized, which is convenient for comparison and comprehensive analysis with other characteristics.

[0039] Specifically, the ratio of the current change rate to the current change threshold is similar to the ratio of the current change rate. The change of current will also be affected by temperature. This ratio can reflect the degree of influence of temperature on the current change. The current change threshold is set to the average value of the current change rate in several historical cycles in implementation. The sum of these two ratios is used as the first historical sample data feature, comprehensively considering the changes of the two important electrical energy parameters of conversion power and current under different temperature influence cycles.

[0040] Specifically, the difference between water usage and a predetermined water usage threshold reflects the fluctuation in water usage under different temperature cycles. The predetermined water usage threshold is pre-determined and determined based on the average water usage during system operation over the first three months of a historical cycle. The water usage difference threshold serves as a reference for determining whether energy consumption fluctuations are significant. In practice, the water usage difference threshold is set as the average of water usage differences over several historical cycles.

[0041] Similarly, the difference between steam usage and the predetermined steam usage threshold reflects the magnitude of steam usage fluctuations under different temperature-affected cycles. The steam usage threshold and the steam usage difference threshold serve as reference values for determining whether energy consumption fluctuations are significant. In practice, the steam usage difference threshold is set to the average of steam usage changes over several historical cycles. The calculated ratio normalizes water usage changes and steam usage changes, yielding a characteristic value that reflects the extent of temperature's impact on energy consumption fluctuations.

[0042] Specifically, the energy consumption impact tendency value is derived by summing the first, second, and third historical sample data features. This value integrates the temperature impact of multiple characteristic parameters, such as the change in electric energy conversion power, the current change rate, and the change in water and steam usage, under different temperature impact cycles. It can more comprehensively reflect the temperature impact tendency of energy-saving motors under specific temperature impact cycles.

[0043] Specifically, by analyzing multiple parameters, we can more accurately assess the impact of temperature on energy-saving motors. Different electrical parameters reflect the performance changes of energy-saving motors from different perspectives. Comprehensively considering these parameters can reduce the limitations of single-parameter evaluation and provide a more comprehensive and accurate assessment of temperature impacts.

[0044] See also Figure 4 As shown, it is a logical decision diagram for determining the energy consumption significant impact period and the energy consumption moderate impact period according to an embodiment of the present invention. The controller of the present invention is used to determine the energy consumption significant impact period and the energy consumption moderate impact period based on the energy consumption impact tendency characterization value within different temperature impact periods, including: If the energy consumption impact tendency representation value is greater than or equal to the preset impact tendency representation value, the energy consumption cycle category of the actual period is determined to be a period with significant energy consumption impact; If the energy consumption impact tendency representation value is less than the preset impact tendency representation value, the energy consumption cycle category of the actual cycle is determined to be an energy consumption flat impact cycle.

[0045] Specifically, the preset impact tendency representation value serves as a key judgment criterion, playing the role of determining the period of significant impact on energy consumption and the period of moderate impact on energy consumption. In implementation, the preset impact tendency representation value is selected within the range of [4.25,4.50].

[0046] Specifically, when the energy consumption impact tendency characterization value is greater than or equal to the preset impact tendency characterization value, it is determined to be a period with significant energy consumption impact. This indicates that during this period, the impact of temperature on the energy-saving motor is more significant, which may cause significant changes in the performance of the energy-saving motor. Preferably, there are differences in the energy loss properties of each production line area. The difference in energy loss in each production line area leads to reduced energy conversion efficiency, or excessive temperature changes may cause stress changes within the energy-saving motor, affecting the life and safety of the energy-saving motor.

[0047] Specifically, if the energy consumption impact tendency representation value is less than a preset impact tendency representation value, it is determined to be a period of moderate energy consumption impact. During this period, the impact of temperature on the energy-saving motor is relatively small, and the performance of the energy-saving motor changes more gradually. During this period, the energy-saving motor can operate in a relatively stable state, and performance indicators such as lifespan are relatively stable.

[0048] Specifically, the controller monitors the operating state of the energy-saving motor based on the determination result, including: If the result of the determination is that the energy consumption significantly affects the period, then determining whether the energy consumption effect of the energy-saving motor predicted by the energy impact characterization parameter meets the predetermined standard based on the amount of change in the temperature of the energy-saving motor and the change ratio of the energy conversion efficiency within the predetermined period, and determining whether to enable the thermal compensation device based on the power consumption of the thermal compensation device and the current power loss; If the result is determined to be a period of gentle energy consumption impact, the thermal compensation device is not enabled.

[0049] Specifically, temperature significantly impacts energy-saving motors during periods of significant energy consumption impact. By monitoring changes in energy-saving motor temperature, we can understand the extent to which ambient temperature fluctuations affect the energy monitoring system. Furthermore, the percentage change in energy conversion efficiency reflects the performance of energy-saving motors under varying temperature conditions. Combining these two parameters to determine the energy impact parameter allows for a more comprehensive assessment of the impact of temperature on the entire plant's energy loss system.

[0050] Specifically, a sharp rise in the temperature of an energy-saving motor can cause changes in its output voltage and current, impacting its conversion efficiency. By analyzing the ratio of temperature change to energy conversion efficiency, we can predict whether the motor's energy efficiency under these drastic temperature fluctuations meets predetermined standards.

[0051] Specifically, during periods of significant energy consumption, the costs and benefits of using thermal compensation devices need to be considered. The power consumption of thermal compensation devices is a key consideration; if excessive power consumption is introduced, it can reduce overall system efficiency. Current energy losses also need to be considered; if these are significant, enabling thermal compensation devices may be necessary to mitigate temperature-related energy losses.

[0052] Specifically, if the thermal compensation device's power consumption is high but the current energy loss is relatively small, the thermal compensation device might not be activated. Instead, other measures might be taken, such as adjusting the angle of the energy-saving motor or reducing the charge and discharge power of the energy-saving motor, to reduce the impact of temperature on the system. Conversely, if the energy loss is large but the thermal compensation device's power consumption is within an acceptable range, the thermal compensation device might be activated to improve system stability and reliability.

[0053] Specifically, the controller is used to determine the energy impact characterization parameter based on the change in the temperature of the energy-saving motor and the change ratio of the energy conversion efficiency within a predetermined period, including: The ratio of the change amount of the energy-saving motor temperature to the energy-saving motor temperature change threshold is used to calculate and determine the first energy influencing parameter feature; The ratio of the change in energy conversion efficiency of the energy-saving motor to the energy loss efficiency change threshold is used to calculate the second energy influencing parameter feature; The sum of the first energy impact parameter characteristic and the second energy impact parameter characteristic is calculated and determined as the energy impact characterization parameter.

[0054] To reflect temperature differences, the temperature change threshold of the energy-saving motor is set based on the average temperature value of the energy-saving motor in the historical period, and is set between 0.25 times and 0.35 times the average temperature value.

[0055] The change in energy conversion efficiency is set based on the average energy conversion efficiency of energy-saving motors in a historical period, and is set between 0.15 times and 0.5 times the average energy conversion efficiency.

[0056] Specifically, the change in the energy conversion efficiency of the energy-saving motor reflects the performance changes of the energy-saving motor under different temperature conditions. Preferably, when the temperature difference is large, the energy conversion efficiency decreases. The larger the change, the more significant the impact on the performance of the energy-saving motor.

[0057] Specifically, the energy impact characterization parameter is obtained by adding the first energy impact parameter characteristic and the second energy impact parameter characteristic. This parameter comprehensively considers the impact of the energy-saving motor temperature change and the energy-saving motor energy conversion efficiency change on the energy conversion of the entire system. Preferably, if both characteristic values are large, it means that the energy-saving motor temperature change and the energy-saving motor performance change have a significant impact on energy conversion, and the energy impact characterization parameter will also be large. If both characteristic values are small, it means that the temperature change and performance change have a small impact on energy conversion, and the energy impact characterization parameter will also be small.

[0058] Specifically, the controller is used to predict whether the energy consumption effect of the energy-saving motor meets the predetermined standard based on the energy impact characterization parameter, including: If the energy impact characterization parameter is less than or equal to the preset energy impact characterization parameter, it is predicted that the energy consumption effect of the energy-saving motor meets the predetermined standard; If the energy impact characterization parameter is greater than the preset energy impact characterization parameter, it is predicted that the energy consumption effect of the energy-saving motor does not meet the predetermined standard.

[0059] Specifically, the preset energy impact characterization parameter is a pre-determined key reference value used to determine whether the energy efficiency of an energy-saving motor meets predetermined standards. It is determined based on a combination of factors, including the energy-saving motor's design performance, historical operating data, and the system's energy efficiency requirements. Preferably, the energy impact characterization parameter is averaged over a historical period to determine a value sufficient to determine the energy efficiency by conducting extensive analysis of the energy conversion performance of similar energy-saving motors under different operating conditions.

[0060] Specifically, when the energy impact characterization parameter is less than or equal to the preset energy impact characterization parameter, the predicted energy consumption effect of the energy-saving motor meets the predetermined standard. This indicates that under the current operating conditions, the energy conversion situation reflected by the temperature change of the energy-saving motor and the change in the energy conversion efficiency of the energy-saving motor is within an acceptable range, and the energy-saving motor can consume energy according to the expected performance requirements. Preferably, the temperature change of the energy-saving motor is relatively small, and the impact on the energy-saving motor is not significant. At the same time, the energy conversion efficiency of the energy-saving motor is also maintained at a high level, which can meet the system's requirements for energy loss capacity and efficiency.

[0061] Specifically, if the energy impact parameter is greater than the preset energy impact parameter, the energy efficiency of the energy-saving motor is predicted to fail to meet the predetermined standard. This indicates that the current energy conversion situation is outside the acceptable range. This may be due to excessively high or drastically fluctuating motor temperatures, which significantly affects the motor's performance and reduces energy conversion efficiency, thus failing to meet the predetermined energy efficiency requirements. This increases energy losses during charging and discharging, and reduces energy loss capacity and efficiency.

[0062] Specifically, the controller is used to determine whether to enable the thermal compensation device based on the power consumption of the thermal compensation device and the current power loss when predicting that the energy consumption effect of the energy-saving motor does not meet the predetermined standard.

[0063] Specifically, in a plant's energy loss system, when the predicted energy consumption of energy-saving motors falls short of predetermined standards, measures are considered to improve the situation. A thermal compensation device is a possible solution, but it also consumes power. Therefore, a comprehensive assessment of the thermal compensation device's power consumption and current power losses is necessary to determine whether enabling it will improve overall system performance.

[0064] Specifically, the controller is used to determine whether to enable the thermal compensation device based on the power consumption of the thermal compensation device and the current power loss, including: If the power consumption of the thermal compensation device is less than or equal to the current power loss, determining to activate the thermal compensation device; If the power consumption of the thermal compensation device is greater than the current power loss, it is determined not to enable the thermal compensation device.

[0065] Specifically, the thermal compensation device's power consumption is the difference between the kilowatt-hours consumed by the motor with the thermal compensation device enabled and the kilowatt-hours consumed without it. Activating the thermal compensation device also consumes energy, but it also reduces the motor's energy losses. By comparing the thermal compensation device's power consumption with the current energy loss, the optimal energy-saving strategy for the motor can be identified, thereby improving the efficiency of the monitoring system by reducing energy loss.

[0066] Specifically, it also includes a display unit, which is connected to the monitor, the analyzer and the controller respectively, and is used to display the data monitored by the monitor.

[0067] Specifically, the display unit is connected to each monitor and can display the data monitored by the monitor in real time. This is crucial for the operation and management of the plant's power generation system. Ideally, the display unit allows users to keep track of key parameters such as the output power and energy consumption of energy-saving motors, as well as temperature. In practical applications, operators can intuitively see the current system status, detect abnormalities promptly, and take appropriate measures.

[0068] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

Claims

1. A multi-energy integrated real-time monitoring system based on big data, characterized in that: include: A collection component for collecting energy consumption characteristic parameters of different production line areas over a historical period, including a power analyzer for collecting energy-saving motor electrical energy parameters in different production line areas, and a thermal compensation device for changing the temperature of the energy-saving motor; A monitor including a plurality of temperature sensors for monitoring the temperature of the energy-saving motors in each production line area during different historical periods and an electric energy monitoring unit for obtaining electric energy parameters of the energy-saving motors; an analyzer, connected to the acquisition component and the monitor, respectively, for storing historical sample data within a historical period, identifying temperature impact periods based on temperature differences in various production line areas of the energy-saving motor during different historical periods, and analyzing energy consumption impact tendency characterization values of the energy-saving motor during different temperature impact periods based on changes in energy consumption characteristic parameters of different production line areas; a controller connected to the acquisition component, the monitor, and the analyzer, respectively, for determining a period of significant energy consumption impact based on energy consumption impact tendency characterization values within different temperature impact periods; Based on the determination results, the operating status of the energy-saving motor is monitored, including: determining an energy impact characterization parameter based on a change in the temperature of the energy-saving motor and a change ratio in the energy conversion efficiency within a predetermined period to predict whether the energy consumption effect of the energy-saving motor meets a predetermined standard, and determining whether to enable the thermal compensation device based on the power consumption of the thermal compensation device and the current power loss; The energy consumption characteristic parameters include electrical energy parameters, water consumption and steam consumption.

2. The multi-energy integrated real-time monitoring system based on big data according to claim 1 is characterized in that: The analyzer is used to identify the temperature impact period based on the temperature difference of each production line area of the energy-saving motor in different historical periods, wherein, To calculate the variance of the temperature of each production line area of energy-saving motors in each historical period; If the variance of the temperature in each historical period is greater than a predetermined variance threshold, the historical period is determined to be a temperature-affected period.

3. The multi-energy integrated real-time monitoring system based on big data according to claim 2 is characterized in that: The energy consumption impact tendency characterization value is determined based on the sum of the first historical sample data feature, the second historical sample data feature, and the third historical sample data feature, wherein: The first historical sample data feature is determined based on the sum of the ratio of the rate of change of the electric energy conversion power in a single production line area to the rate of change threshold and the ratio of the current change rate of the energy-saving motor to the current change threshold; The second historical sample data feature is determined based on a difference between water usage in a single production line area and a predetermined water usage threshold, and is determined based on a ratio of the water usage difference to the water usage difference threshold; The third historical sample data feature is determined based on the difference between the steam usage in a single production line area and a predetermined steam usage threshold, and is determined based on the ratio of the steam usage difference to the steam usage difference threshold.

4. The multi-energy integrated real-time monitoring system based on big data according to claim 3 is characterized in that: The controller is configured to determine a period of significant energy consumption impact and a period of moderate energy consumption impact based on energy consumption impact tendency characterization values within different temperature impact periods, including: If the energy consumption impact tendency representation value is greater than or equal to the preset impact tendency representation value, the energy consumption cycle category of the actual period is determined to be a period with significant energy consumption impact; If the energy consumption impact tendency representation value is less than the preset impact tendency representation value, the energy consumption cycle category of the actual cycle is determined to be an energy consumption flat impact cycle.

5. The multi-energy integrated real-time monitoring system based on big data according to claim 1 is characterized in that: The controller monitors the operating state of the energy-saving motor based on the determination result, including: If the result of the determination is that the energy consumption significantly affects the period, then determining whether the energy consumption effect of the energy-saving motor predicted by the energy impact characterization parameter meets the predetermined standard based on the amount of change in the temperature of the energy-saving motor and the change ratio of the energy conversion efficiency within the predetermined period, and determining whether to enable the thermal compensation device based on the power consumption of the thermal compensation device and the current power loss; If the result is determined to be a period of gentle energy consumption impact, the thermal compensation device is not enabled.

6. The multi-energy integrated real-time monitoring system based on big data according to claim 1 is characterized in that: The controller is used to determine the energy impact characterization parameter based on the change amount of the energy-saving motor temperature and the change ratio of the energy conversion efficiency within a predetermined period, including: The ratio of the change amount of the energy-saving motor temperature to the energy-saving motor temperature change threshold is used to calculate and determine the first energy influencing parameter feature; The ratio of the change in energy conversion efficiency of the energy-saving motor to the energy loss efficiency change threshold is used to calculate the second energy influencing parameter feature; The sum of the first energy impact parameter characteristic and the second energy impact parameter characteristic is calculated and determined as the energy impact characterization parameter.

7. The multi-energy integrated real-time monitoring system based on big data according to claim 6 is characterized in that: The controller is used to predict whether the energy consumption effect of the energy-saving motor meets the predetermined standard based on the energy impact characterization parameter, including: If the energy impact characterization parameter is less than or equal to the preset energy impact characterization parameter, it is predicted that the energy consumption effect of the energy-saving motor meets the predetermined standard; If the energy impact characterization parameter is greater than the preset energy impact characterization parameter, it is predicted that the energy consumption effect of the energy-saving motor does not meet the predetermined standard.

8. The multi-energy integrated real-time monitoring system based on big data according to claim 7 is characterized in that: The controller is used to determine whether to enable the thermal compensation device based on the power consumption of the thermal compensation device and the current power loss when predicting that the energy consumption effect of the energy-saving motor does not meet the predetermined standard.

9. The multi-energy integrated real-time monitoring system based on big data according to claim 1 is characterized in that: The controller is used to determine whether to enable the thermal compensation device based on the power consumption of the thermal compensation device and the current power loss. include, If the power consumption of the thermal compensation device is less than or equal to the current power loss, determining to activate the thermal compensation device; If the power consumption of the thermal compensation device is greater than the current power loss, it is determined not to enable the thermal compensation device.

10. The multi-energy integrated real-time monitoring system based on big data according to claim 1 is characterized in that: The system further comprises a display unit, which is connected to the monitor, the analyzer and the controller respectively and is used to display the data monitored by the monitor.

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