A smart IoT power loss monitoring and optimization system

Abstract

The present invention discloses a smart IoT power loss monitoring and optimization system, which belongs to the field of power monitoring technology, including a perception layer module, which obtains the associated parameter information generated in the key nodes of the power system; a network layer module, which is used for data transmission; a first platform layer module, which determines whether there is power loss in the power system; a second platform layer module, which determines whether there is potential power loss in the power system; and an optimization layer module, which optimizes the corresponding position of the power system according to the judgment result. The present invention can perform comprehensive analysis and processing based on the input power, output power and power factor generated in the power system to determine whether there is real-time power loss in the power system. It combines the changes in input power, output power and power factor during peak power consumption, normal power consumption and low power consumption for comprehensive analysis, which can more accurately determine whether there is power loss in the power system, thereby ensuring the stability of the power system.

Description

Technical Field

[0001] The present invention belongs to the technical field of power monitoring, and in particular relates to a smart Internet of Things power loss monitoring and optimization system. Background Art

[0002] Power loss refers to the phenomenon that electric energy is converted into other forms of energy and consumed during the transmission, distribution and consumption of electricity. This loss not only affects the efficiency and stability of the power system, but is also directly related to the effective use of energy and cost control. Therefore, it is necessary to monitor power loss to reduce it.

[0003] Existing methods for monitoring power loss mostly install measuring equipment such as energy meters at key nodes in the power system, and judge whether the power consumption is abnormal by monitoring the changes in the input and output power of the power system. Since power loss is easily affected by the power load, the power load in different periods is different, and the corresponding power loss is also different. It is not accurate enough to judge whether there is power loss only by monitoring the power changes through the energy meter, which is prone to errors. Moreover, when abnormal power loss is detected, a large power loss has already occurred. In this way, potential power loss cannot be discovered in time, thereby affecting the stability of the power system. Summary of the invention

[0004] The purpose of the present invention is to provide a smart IoT power loss monitoring and optimization system to solve the problems faced in the above-mentioned background technology.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A smart IoT power loss monitoring and optimization system, the system comprising:

[0007] A perception layer module, the perception layer module is used to obtain the associated parameter information generated in the key nodes of the power system;

[0008] A network layer module, which is used for data transmission and transmits the acquired associated parameter information to the platform layer module through the Internet of Things technology;

[0009] A first platform layer module, the first platform layer module is used to analyze the acquired associated parameter information to determine whether there is power loss in the power system;

[0010] A second platform layer module, wherein the second platform layer module performs early warning analysis based on the acquired relationship parameter information to determine whether there is potential power loss in the power system when the first platform layer module determines that there is no power loss in the power system;

[0011] The optimization layer module optimizes the corresponding position of the power system according to the judgment results of the first platform layer module and the second platform layer module.

[0012] Furthermore, the associated parameter information includes input power, output power, power factor and voltage within the key node.

[0013] Furthermore, the method for the first platform layer module to determine whether there is power loss in the power system is:

[0014] According to different electricity demand, electricity consumption time is divided into peak period Normal period And the low period , obtain the input power, output power and power factor of key nodes during peak, normal and off-peak periods;

[0015] By formula Get the peak power loss value ;

[0016] By formula The power loss value during normal period is obtained ;

[0017] By formula Obtain the power loss value during the low period ;

[0018] So through the formula Get the comprehensive value of power loss ;

[0019] when When , it is judged that there is real-time power loss in the power system;

[0020] in, The peak period starts at The peak period ends at The curve of input power obtained during the peak period over time is: The output power obtained during the peak period changes with time. The power factor variation curve obtained during the peak period is as follows: The normal period starts at The normal period ends at This is the curve of input power variation over time obtained during the normal period. The output power obtained during the normal period changes with time. This is the power factor variation curve obtained during the normal period. is the start time of the trough period, The end time of the trough period. The curve of input power obtained during the valley period over time is shown in Figure 2. The output power obtained during the valley period changes with time. This is the power factor variation curve obtained during the trough period. as well as is the preset coefficient, It is the preset power loss judgment threshold.

[0021] Furthermore, the method for the second platform layer module to determine whether there is potential power loss in the power system is:

[0022] When there is no power loss in the power system, set n collection and monitoring time points to obtain the comprehensive value of power loss at each collection and monitoring time point. , and fitted the curve of the comprehensive value of power loss changing with the acquisition and monitoring time point ;

[0023] At the same time, obtain the voltage value of each monitoring point , thereby obtaining the voltage fluctuation value And voltage deviation value ;

[0024] By formula Obtain abnormal warning value ;

[0025] when When , it is judged that there is potential power loss in the power system;

[0026] in, The first monitoring time point. The last monitoring time point. The curve of the standard power loss comprehensive value preset by the system changes with the collection and monitoring time point. It is the preset abnormal warning judgment threshold.

[0027] Furthermore, the voltage fluctuation value And voltage deviation value The acquisition method is:

[0028] Get the voltage value collected at each monitoring time point , through the formula Get the voltage fluctuation value ;

[0029] Get the voltage value collected at each monitoring time point , compare it with the standard voltage Compare and get the voltage deviation at each acquisition and monitoring time point ;

[0030] The n acquisition monitoring time points are evenly divided into two segments, recorded as the initial segment and the end segment, and the average voltage deviation of the initial segment and the end segment is obtained respectively. , , so that through the formula Get the voltage deviation value ;

[0031] in, is the maximum voltage monitored at n acquisition monitoring time points, is the minimum voltage monitored at n acquisition monitoring time points, It is the average voltage of n monitoring time points.

[0032] Furthermore, the method by which the optimization layer module optimizes the corresponding position of the power system is:

[0033] When it is determined that there is real-time power loss in the power system, an infrared thermal imager is used to check the temperature of the equipment, obtain a temperature distribution area map, find out the area with abnormal temperature and mark it as the power loss area, so as to optimize the power loss area.

[0034] Furthermore, the method for the optimization layer module to optimize the corresponding position of the power system also includes:

[0035] When it is determined that there is potential power loss in the power system, the temperature change of each device in the key node each time it works is obtained, and the temperature change curve equation of the device each time it works over time is formulated, and the slope of the curve equation each time it works is determined;

[0036] If the slope is increasing within m operations, or the average slope of m operations is higher than a preset threshold, the device is determined to be a potential power loss device, and the device is optimized accordingly.

[0037] Beneficial effects of the present invention:

[0038] The present invention can perform comprehensive analysis and processing based on the input power, output power and power factor generated in key nodes of the power system to determine whether there is real-time power loss in the power system. It combines the changes in input power, output power and power factor during peak power consumption, normal power consumption and low power consumption periods for comprehensive analysis, and can more accurately determine whether there is power loss in the power system. This can greatly improve the accuracy of monitoring and ensure the stability of the power system.

[0039] The present invention can also perform a comprehensive analysis based on the input power, output power, power factor and voltage in key nodes when judging that there is no power loss in the power system, to judge whether there is a potential power loss risk in the power system and perform early warning in time, so as to timely avoid or reduce power loss and ensure the stability of power consumption of the entire system.

[0040] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0042] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0043] 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.

[0044] In one embodiment, a smart IoT power loss monitoring and optimization system is disclosed, such as Figure 1 As shown, the system includes:

[0045] The perception layer module is used to obtain the associated parameter information generated in the key nodes of the power system, including the input power, output power, power factor and voltage in the key nodes;

[0046] The network layer module is used for data transmission, and transmits the acquired associated parameter information to the platform layer module through the Internet of Things technology;

[0047] A first platform layer module, the first platform layer module is used to analyze the acquired associated parameter information to determine whether there is power loss in the power system;

[0048] The second platform layer module, when the first platform layer module determines that there is no power loss in the power system, performs early warning analysis based on the acquired relationship parameter information to determine whether there is potential power loss in the power system;

[0049] The optimization layer module optimizes the corresponding position of the power system according to the judgment results of the first platform layer module and the second platform layer module.

[0050] Through the above technical scheme, the present application can conduct a comprehensive analysis and processing based on the input power, output power and power factor generated in the key nodes of the power system to determine whether there is real-time power loss in the power system. It combines the changes in input power, output power and power factor during peak power consumption, normal power consumption and low power consumption to conduct a comprehensive analysis, and can more accurately determine whether there is power loss in the power system, which can greatly improve the accuracy of monitoring and ensure the stability of the power system. At the same time, when it is determined that there is no power loss in the power system, a comprehensive analysis can be conducted based on the input power, output power, power factor and voltage size in the key nodes to determine whether there is a potential risk of power loss in the power system and to conduct early warning processing in a timely manner, which can timely avoid or reduce power loss and ensure the stability of power consumption in the entire system.

[0051] As an implementation mode of the present invention, the method for the first platform layer module to determine whether there is power loss in the power system is:

[0052] According to different electricity demand, electricity consumption time is divided into peak period Normal period And the low period , obtain the input power, output power, power factor and voltage of key nodes during peak, normal and valley periods;

[0053] By formula Get the peak power loss value ;

[0054] By formula The power loss value during normal period is obtained ;

[0055] By formula Obtain the power loss value during the low period ;

[0056] So through the formula Get the comprehensive value of power loss ;

[0057] when When , it is judged that there is real-time power loss in the power system;

[0058] in, The peak period starts at The peak period ends at The curve of input power obtained during the peak period over time is: The output power obtained during the peak period changes with time. The power factor variation curve obtained during the peak period is as follows: The normal period starts at The normal period ends at This is the curve of input power variation over time obtained during the normal period. The output power obtained during the normal period changes with time. This is the power factor variation curve obtained during the normal period. is the start time of the trough period, The end time of the trough period. The curve of input power obtained during the valley period over time is shown in Figure 2. The output power obtained during the valley period changes with time. This is the power factor variation curve obtained during the trough period. as well as is the preset coefficient, It is the preset power loss judgment threshold.

[0059] Through the above technical solution, this embodiment provides a method for the first platform layer module to determine whether there is power loss in the power system. Since the power load is different in different periods, the power loss is also different. Generally speaking, the more the power load, the greater the power loss. Therefore, in order to more accurately determine whether there is power loss in the power system, the power consumption time is first divided into peak period according to different power demand. Normal period And the trough period , obtain the input power, output power, and power factor of key nodes during peak, normal, and valley periods, and then use the formula Get the peak power loss value , through the formula The power loss value during normal period is obtained , through the formula Obtain the power loss value during the low period ; Then through the formula Get the comprehensive value of power loss , based on the comprehensive value of power loss, it is judged whether there is power loss in the power system, where the formula It indicates the difference between the input power and output power during the peak period. The larger the value, the greater the power loss in the power system. It indicates the change of power factor during the peak period. When the power factor is lower, it means that the ineffective current is larger, which will lead to an increase in power loss. Therefore, when its value is larger, it means that the power factor change is lower, and the power loss is greater. Therefore, when the power loss value during the peak period is The larger the value, the greater the power loss in the power system. Similarly, when the power loss value in the normal period is , power loss value during the low period The larger the value, the greater the comprehensive value of power loss. The larger the value, the greater the power loss in the power system. Therefore, the comprehensive power loss value is compared with the power loss judgment threshold preset in the system. When it exceeds the power loss judgment threshold, it means that there is real-time power loss in the power system. In this way, combined with the input and output power and power factor changes during peak, normal and low periods, it is possible to more accurately judge whether there is power loss in the power system, thereby reducing judgment errors and ensuring the stability of the power system.

[0060] Among them, the peak period Normal period And the low period The duration is set by humans, and the coefficient is preset as well as , preset power loss judgment threshold It can be determined based on empirical data, which will not be described in detail here.

[0061] As an implementation mode of the present invention, the method for the second platform layer module to determine whether there is potential power loss in the power system is:

[0062] When there is no power loss in the power system, set n collection and monitoring time points to obtain the comprehensive value of power loss at each collection and monitoring time point. , and fitted the curve of the comprehensive value of power loss changing with the acquisition and monitoring time point ;

[0063] At the same time, obtain the voltage value of each acquisition monitoring point , thereby obtaining the voltage fluctuation value And voltage deviation value ;

[0064] By formula Obtain abnormal warning value ;

[0065] when When , it is judged that there is potential power loss in the power system;

[0066] in, The first monitoring time point. The last monitoring time point. The curve of the standard power loss comprehensive value preset by the system changes with the collection and monitoring time point. It is the preset abnormal warning judgment threshold;

[0067] Voltage fluctuation value And voltage deviation value The acquisition method is: obtain the voltage value collected at each acquisition monitoring time point , through the formula Get the voltage fluctuation value ;

[0068] Get the voltage value collected at each monitoring time point , compare it with the standard voltage Compare and get the voltage deviation at each acquisition and monitoring time point ;

[0069] The n acquisition monitoring time points are evenly divided into two segments, recorded as the initial segment and the end segment, and the average voltage deviation of the initial segment and the end segment is obtained respectively. , , so that through the formula Get the voltage deviation value ;

[0070] in, is the maximum voltage monitored at n acquisition monitoring time points, is the minimum voltage monitored at n acquisition monitoring time points, It is the average voltage of n monitoring time points.

[0071] Through the above technical solution, this embodiment provides a method for the second platform layer module to determine whether there is potential power loss in the power system. First, when there is no power loss in the power system, n collection and monitoring time points are set to obtain the comprehensive value of power loss at each collection and monitoring time point. , and fitted the curve of the comprehensive value of power loss changing with the acquisition and monitoring time point , and simultaneously obtain the voltage value of each acquisition monitoring point , thereby obtaining the voltage fluctuation value And voltage deviation value , voltage fluctuation value And voltage deviation value The acquisition method is: obtain the voltage value collected at each acquisition monitoring time point , through the formula Get the voltage fluctuation value , and obtain the voltage value collected at each monitoring time point , compare it with the standard voltage Compare and get the voltage deviation at each acquisition and monitoring time point , divide the n acquisition monitoring time points into two segments, recorded as the initial segment and the end segment, and obtain the average voltage deviation of the initial segment and the end segment respectively , , so that through the formula Get the voltage deviation value , and then by the formula Obtain abnormal warning value ,formula It indicates the fluctuation of the comprehensive value of power loss within n collection and monitoring time points. The larger the value, the more unstable it is, which means the greater the possibility of potential power loss. The formula It represents the difference between the comprehensive value of power loss during n collection and monitoring time points and the comprehensive value of standard power loss. The larger the value, the greater the possibility of potential power loss. The formula It indicates the voltage fluctuation of the power system. The larger the value, the greater the possibility of potential power loss. The formula It indicates the voltage deviation of the power system. The larger the value, the greater the possibility of potential power loss in the power system. Therefore, a comprehensive analysis is conducted based on the voltage fluctuation, voltage deviation, fluctuation of the comprehensive power loss value, and change of the comprehensive power loss value. The formula Obtain abnormal warning value , and then the abnormal warning value obtained Compared with the preset abnormal warning judgment threshold, when In this way, the potential power loss risk in the power system can be discovered and warned in time, so that the potential risk can be checked and handled in time to prevent or reduce the occurrence of power loss and ensure the stability of the entire power system.

[0072] Among them, n collection and monitoring time points can be set manually, and the system preset standard power loss comprehensive value changes with the collection and monitoring time point curve The preset abnormal warning judgment threshold is determined based on the relevant data in the big data combined with historical data. This is determined based on empirical data and will not be described in detail here.

[0073] As an implementation mode of the present invention, the method for the optimization layer module to optimize the corresponding position of the power system is:

[0074] When it is determined that there is real-time power loss in the power system, an infrared thermal imager is used to check the temperature of the equipment, obtain a temperature distribution area map, find out the area with abnormal temperature and mark it as the power loss area, so as to optimize the power loss area;

[0075] When it is determined that there is potential power loss in the power system, the temperature change of each device in the key node each time it works is obtained, and the temperature change curve equation of the device each time it works over time is formulated, and the slope of the curve equation each time it works is determined;

[0076] If the slope is increasing within m operations, or the average slope of m operations is higher than a preset threshold, the device is determined to be a potential power loss device, and the device is optimized accordingly.

[0077] Through the above technical scheme, this embodiment provides a method for the optimization layer module to optimize the corresponding position of the power system. First, the location where the power loss occurs is determined. When it is determined that there is real-time power loss in the power system, an infrared thermal imager is used to check the temperature of the equipment, obtain a temperature distribution area map, find out the area with abnormal temperature and mark it as a power loss area, so as to optimize the power loss area; and when it is determined that there is potential power loss in the power system, the temperature change of each device in the key node is obtained each time it works, and the temperature change curve equation of the device each time it works is formulated, and the slope of the curve equation is determined each time it works. If the slope is increasing within m times of work, or the average slope of m times of work is higher than the preset threshold, it means that the temperature change of the equipment in the key node is abnormal, which is easy to cause power loss. Then, the equipment is determined to be a potential power loss equipment, so that the equipment is optimized accordingly. In this way, when power loss occurs, the location of power loss can be found quickly and timely and the corresponding optimization can be performed, which can narrow the optimization range and quickly restore the stability of the power system.

[0078] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the claims, they shall all fall within the protection scope of the present invention.

Claims

1. A smart IoT power loss monitoring and optimization system, characterized in that: The system comprises: A perception layer module, the perception layer module is used to obtain the associated parameter information generated in the key nodes of the power system, the associated parameter information includes the input power, output power, power factor and voltage size in the key nodes; A network layer module, which is used for data transmission and transmits the acquired associated parameter information to the platform layer module through the Internet of Things technology; A first platform layer module, the first platform layer module is used to analyze the acquired associated parameter information to determine whether there is power loss in the power system; A second platform layer module, wherein the second platform layer module performs early warning analysis based on the acquired relationship parameter information to determine whether there is potential power loss in the power system when the first platform layer module determines that there is no power loss in the power system; An optimization layer module, wherein the optimization layer module optimizes corresponding positions of the power system according to the judgment results of the first platform layer module and the second platform layer module; The method for the first platform layer module to determine whether there is power loss in the power system is: according to different power demand, the power consumption time is divided into peak period Normal period And the low period , obtain the input power, output power and power factor of key nodes during peak, normal and off-peak periods; By formula Get the peak power loss value ; By formula The power loss value during normal period is obtained ; By formula Obtain the power loss value during the valley period ; So through the formula Get the comprehensive value of power loss ; when When , it is judged that there is real-time power loss in the power system; in, The peak period starts at The peak period ends at The curve of input power obtained during the peak period over time is: The output power obtained during the peak period changes with time. The power factor variation curve obtained during the peak period is as follows: The normal period starts at The normal period ends at This is the curve of input power variation over time obtained during the normal period. The output power obtained during the normal period changes with time. This is the power factor variation curve obtained during the normal period. is the start time of the trough period, The end time of the trough period. The curve of input power obtained during the valley period over time is shown in Figure 2. The output power obtained during the valley period changes with time. This is the power factor variation curve obtained during the trough period. as well as is the preset coefficient, is the preset power loss judgment threshold; The method for the second platform layer module to determine whether there is potential power loss in the power system is: when there is no power loss in the power system, n collection and monitoring time points are set to obtain the comprehensive value of power loss at each collection and monitoring time point. , and fitted the curve of the comprehensive value of power loss changing with the acquisition and monitoring time point ; At the same time, obtain the voltage value of each monitoring point , thereby obtaining the voltage fluctuation value And voltage deviation value ; By formula Obtain abnormal warning value ; when When , it is judged that there is potential power loss in the power system; in, The first monitoring time point. The last monitoring time point. The curve of the standard power loss comprehensive value preset by the system changes with the collection and monitoring time point. It is the preset abnormal warning judgment threshold; The voltage fluctuation value And voltage deviation value The acquisition method is: obtain the voltage value collected at each acquisition monitoring time point , through the formula Get the voltage fluctuation value ; Get the voltage value collected at each monitoring time point , compare it with the standard voltage Compare and get the voltage deviation at each acquisition and monitoring time point ; The n acquisition monitoring time points are evenly divided into two segments, recorded as the initial segment and the end segment, and the average voltage deviation of the initial segment and the end segment is obtained respectively. , , so that through the formula Get the voltage deviation value ; in, is the maximum voltage monitored at n acquisition monitoring time points, is the minimum voltage monitored at n acquisition monitoring time points, It is the average voltage of n monitoring time points.

2. According to claim 1, a smart IoT power loss monitoring and optimization system is characterized in that: The method by which the optimization layer module optimizes the corresponding position of the power system is: When it is determined that there is real-time power loss in the power system, an infrared thermal imager is used to check the temperature of the equipment, obtain a temperature distribution area map, find out the area with abnormal temperature and mark it as the power loss area, so as to optimize the power loss area.

3. The smart IoT power loss monitoring and optimization system according to claim 2 is characterized in that: The method for the optimization layer module to optimize the corresponding position of the power system also includes: When it is determined that there is potential power loss in the power system, the temperature change of each device in the key node each time it works is obtained, and the temperature change curve equation of the device each time it works over time is formulated, and the slope of the curve equation each time it works is determined; If the slope is increasing within m operations, or the average slope of m operations is higher than a preset threshold, the device is determined to be a potential power loss device, and the device is optimized accordingly.

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