Low-power-consumption monitoring system and method for power transmission line

Abstract

The invention discloses a low-power-consumption monitoring system and method for a power transmission line, and belongs to the technical field of power transmission line monitoring. The low-power-consumption monitoring system comprises a sensor module, a data acquisition module, a data processing unit, a wireless communication module and a power management module; the sensor module comprises an optical fiber temperature sensor, a strain gauge sensor and an electromagnetic induction sensor; the data acquisition module acquires sensor data at a time interval delta t through the microcontroller; the data processing unit processes the acquired data by adopting a Kalman filtering algorithm; the wireless communication module performs data transmission by adopting a low-power-consumption Bluetooth technology BLE; the power supply management module is composed of a solar cell panel and a super capacitor, the solar cell panel supplies power to the system and charges the super capacitor during illumination, and the super capacitor supplies electric energy to the system when illumination does not exist or illumination is insufficient; according to the system and the method provided by the invention, the power consumption of the system is effectively reduced, the state of the power transmission line can be accurately monitored, and reliable guarantee is provided for stable operation of the power transmission line.

Description

Technical Field

[0001] The present invention belongs to the technical field of power transmission line monitoring, and in particular relates to a low-power consumption monitoring system and method for a power transmission line. Background Art

[0002] In the vast network of modern power systems, transmission lines are like blood vessels in the human body, carrying the key mission of transmitting electricity from the power generation end to the power consumption end. With the continuous growth of power demand and the continuous expansion of the power system, the safe and stable operation of transmission lines has become the core guarantee of power supply reliability.

[0003] While traditional transmission line monitoring systems meet the needs of monitoring various parameters of transmission lines, they are facing an increasingly prominent problem - high power consumption. This high power consumption phenomenon has brought many adverse effects. First, from the perspective of operating costs, high power consumption means a large amount of energy consumption. Power companies need to continuously provide power for these monitoring systems, which will form a considerable expense over time. For example, a large-scale transmission line network may contain many monitoring points. If the power consumption of each monitoring point is high, then the cost of energy consumption for the entire network will not be underestimated.

[0004] Secondly, in terms of power supply conditions, especially for transmission lines located in remote areas, high-power monitoring systems face severe challenges. Many remote areas have relatively weak power supply infrastructure, making it difficult to ensure stable and continuous power supply for high-power devices. These areas may lack complete grid coverage or rely on small, unstable power generation equipment, such as small wind turbines or simple diesel generators. In such a power supply environment, high-power monitoring systems are prone to power shortages, which can affect the normal operation of the monitoring system.

[0005] Furthermore, from the perspective of environmental protection and sustainable development, high power consumption is also contrary to the current concept of energy conservation and emission reduction. In the context of the global efforts to reduce energy consumption and carbon emissions, the power industry, as a major energy consumer, has the responsibility and obligation to reduce energy consumption in all aspects. The high power consumption of the transmission line monitoring system is obviously not in line with this development trend.

[0006] In addition, high power consumption may also have an indirect impact on other performance of the monitoring system. For example, in order to meet the power supply requirements of high-power devices, it may be necessary to use larger capacity batteries or more complex power supply equipment, which not only increases the size and weight of the equipment, but also may affect the deployment flexibility and maintenance costs of the equipment. Moreover, high-power devices also generate relatively more heat during operation, which may damage the electronic components inside the equipment, reduce the service life of the equipment, and further increase the overall cost of the entire monitoring system.

[0007] In summary, the development of a low-power transmission line monitoring method and system can not only meet the requirements for accurate monitoring of transmission lines, but also effectively reduce power consumption. It is of great significance for improving the operation and management efficiency of transmission lines, reducing operating costs, ensuring the monitoring of transmission lines in remote areas, and meeting the needs of environmental protection and sustainable development. Summary of the invention

[0008] The purpose of the present invention is to provide a low-power consumption monitoring system and method for a power transmission line, which effectively reduces the power consumption of the system by optimizing the design and algorithm of each module, and can accurately monitor the status of the power transmission line, thus providing a reliable guarantee for the safe and stable operation of the power transmission line.

[0009] To achieve the above-mentioned purpose, the present invention provides a low-power consumption monitoring system for a power transmission line, comprising a sensor module, a data acquisition module, a data processing unit, a wireless communication module and a power management module; the sensor module comprises an optical fiber temperature sensor, a strain gauge sensor and an electromagnetic induction sensor; the data acquisition module collects sensor data at a time interval Δt through a microcontroller; a Kalman filter algorithm is used in the data processing unit to process the collected data; the wireless communication module uses low-power consumption Bluetooth technology BLE for data transmission; the power management module is composed of a solar panel and a super capacitor, the solar panel supplies power to the system and charges the super capacitor when exposed to light, and the super capacitor provides power to the system when there is no light or insufficient light.

[0010] Preferably, the supercapacitor is in the charging process, and the solar panel is in the charging time t c Energy provided by W solar for:

[0011] W solar =P solar t c ;

[0012] Where P solar Indicates the output power of the solar panel;

[0013] During the discharge process of the supercapacitor, the energy of the supercapacitor W cap The relationship between capacitance C and voltage U is:

[0014] Preferably, the charging time of the supercapacitor is c and discharge time t d The following relations are satisfied:

[0015] P solar t c ≥P sys (t c+t d );

[0016] Where P sys Indicates the average power consumption of the system.

[0017] The present invention also provides a low power consumption monitoring method for a power transmission line, comprising the following steps:

[0018] Step 1: After the system is started, the sensor module starts working and each sensor collects the parameters of the transmission line, including temperature data T i , Tension data F i , current data I i ;

[0019] Step 2: The data acquisition module collects sensor data at a preset time interval Δt and transmits the data to the data processing unit. During the collection process, the data acquisition module calculates the average power consumption P mc The power consumption is controlled by switching between working mode and sleep mode through the microcontroller, thereby reducing the power consumption;

[0020] Step 3: The data processing unit uses the Kalman filter algorithm to filter the collected data to remove noise interference, and then calculates the comprehensive state index S of the transmission line and determines the monitoring level;

[0021] Step 4: The wireless communication module sends the processed data and comprehensive status indicator S to the monitoring center through low-power Bluetooth technology to complete the monitoring of the transmission line.

[0022] Preferably, the optical fiber temperature sensor measures temperature based on the principle of light reflection, and the relationship between the temperature T and the wavelength λ of the reflected light is as follows:

[0023] T = k1(λ-λ0);

[0024] Where k1 is the temperature-wavelength conversion coefficient and λ0 is the reference wavelength.

[0025] Preferably, the average power consumption P in step 2 is mc The calculation process is as follows:

[0026] S21, set the microcontroller in a collection cycle T c Within, the working time is Δt, and the sleeping time is T c -Δt;

[0027] S22. Calculate the energy W consumed in each working mode w and the energy consumed in sleep mode W s , the calculation expression is as follows:

[0028] W w =Pw Δt;

[0029] W s =P s (T c -Δt);

[0030] Where P w is the power consumption of the microcontroller in working mode, P s is the power consumption of the microcontroller in sleep mode;

[0031] S23. Calculate the total energy consumption W in one acquisition cycle total , the calculation expression is as follows:

[0032] W total =W w +W s =P w Δt+P s (T c -Δt);

[0033] S24, calculate the average power consumption P mc , the expression is as follows:

[0034]

[0035] Preferably, the process of filtering the collected data using the Kalman filter algorithm in step 3 is as follows:

[0036] S31, initialization; set state vector x0 = [T0, F0, I0] T ), T0, F0, I0 represent the initial estimated values ​​of temperature, tension and current respectively, and the initial covariance matrix P0 = diag(1,1,1);

[0037] S32, prediction; according to the system state equation x k =F k-1 x k-1 +w k-1 Calculate predicted status and the predicted covariance The calculation expression is as follows:

[0038]

[0039] In the formula, x k-1 is the state value at the previous moment, F k-1 is the state transfer matrix, w k-1 is the process noise, is the state estimate at the previous moment, Q k-1 is the process noise covariance matrix;

[0040] S33. Update; according to the measurement equation z k = H k x k + v k Calculate the Kalman gain K k . Update the state estimate and the covariance estimate . The specific expressions are as follows:

[0041]

[0042] In the formula, H k is the measurement matrix, v k is the measurement noise, R k is the measurement noise covariance matrix, z k is the measurement value vector, and I is the identity matrix;

[0043] S34. After multiple iterations, obtain the temperature T f , tension F f and current data I f .

[0044] Preferably, the calculation expression of the comprehensive state index S of the transmission line is as follows:

[0045] S = aT f + bF f + cI f ;

[0046] In the formula, a, b, and c are weight coefficients determined according to the characteristics of the transmission line;

[0047] The determination of the monitoring level includes the following three levels:

[0048] Level 1, indicating normal state: When S1 ≤ S ≤ S2, the transmission line operates normally, and S2 and S1 are the upper and lower limit thresholds determined according to the line design and experience;

[0049] Level 2, indicating warning state: When S < S1 or S > S2, the transmission line needs further attention;

[0050] Level 3, indicating dangerous state: When S < S3 or S > S4, the transmission line has serious potential safety hazards, and S3 and S4 are the absolute lower limit threshold and absolute upper limit threshold.

[0051] Preferably, before the wireless communication module in step 4 sends the processed data and the comprehensive state index S to the monitoring center through the low-power Bluetooth technology, adjust the transmission power P t , and the calculation expression is as follows:

[0052] P t = Pt0 +10nlog 10 (d / d0);

[0053] Where P t0 is the transmission power at the reference distance d0, and n is the path loss exponent.

[0054] Therefore, the present invention adopts the above-mentioned low power consumption monitoring system and method for power transmission lines, which has the following beneficial effects:

[0055] (1) Reduce operating costs and equipment costs: Low power consumption design reduces power consumption, reduces the operating costs of power companies on monitoring systems, and reduces the need for auxiliary equipment such as heat dissipation equipment, thereby reducing the hardware cost of the equipment;

[0056] (2) The Kalman filter algorithm is used to effectively remove noise interference and improve monitoring accuracy and reliability;

[0057] (3) Low-power Bluetooth technology is used for data transmission, and the transmission power is adjusted according to the communication distance, thereby reducing communication power consumption.

[0058] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 It is a structural schematic diagram of a low power consumption monitoring system for a power transmission line according to the present invention;

[0060] Figure 2 The figure is an overall flow chart of the low power consumption monitoring method for a power transmission line according to the present invention. DETAILED DESCRIPTION

[0061] The following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. 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.

[0062] See also Figure 1A low-power monitoring system for a power transmission line includes a sensor module, a data acquisition module, a data processing unit, a wireless communication module and a power management module; the sensor module includes an optical fiber temperature sensor, a strain gauge sensor and an electromagnetic induction sensor; the data acquisition module collects sensor data at a time interval Δt through a microcontroller; the data processing unit uses a Kalman filter algorithm to process the collected data; the wireless communication module uses low-power Bluetooth technology BLE for data transmission; the power management module consists of a solar panel and a supercapacitor, the solar panel supplies power to the system and charges the supercapacitor when there is light, and the supercapacitor provides power to the system when there is no light or insufficient light.

[0063] Among them, the supercapacitor is in the charging process, and the solar panel is in the charging time t c Energy provided by W solar for:

[0064] W solar =P solar t c ;

[0065] Where P solar Indicates the output power of the solar panel;

[0066] During the discharge process of the supercapacitor, the energy of the supercapacitor W cap The relationship between capacitance C and voltage U is:

[0067] Supercapacitor charging time t c and discharge time t d The following relations are satisfied:

[0068] P solar t c ≥P sys (t c +t d );

[0069] Where P sys Indicates the average power consumption of the system.

[0070] See also Figure 2 , a low power consumption monitoring method for a transmission line, comprising the following steps:

[0071] Step 1: After the system is started, the sensor module starts working and each sensor collects the parameters of the transmission line, including temperature data T i , Tension data F i , current data I i ; The optical fiber temperature sensor measures temperature based on the principle of light reflection. The relationship between the temperature T and the wavelength λ of the reflected light is as follows:

[0072] T = k1(λ-λ0);

[0073] Where k1 is the temperature-wavelength conversion coefficient and λ0 is the reference wavelength.

[0074] Step 2: The data acquisition module collects sensor data at a preset time interval Δt and transmits the data to the data processing unit. During the collection process, the data acquisition module calculates the average power consumption P mc The power consumption is controlled by switching between working mode and sleep mode through the microcontroller, thereby reducing the power consumption; the average power consumption P mc The calculation process is as follows:

[0075] S21, set the microcontroller in a collection cycle T c Within, the working time is Δt, and the sleeping time is T c -Δt;

[0076] S22. Calculate the energy W consumed in each working mode w and the energy consumed in sleep mode W s , the calculation expression is as follows:

[0077] W w =P w Δt;

[0078] W s =P s (T c -Δt);

[0079] Where P w is the power consumption of the microcontroller in working mode, P s is the power consumption of the microcontroller in sleep mode;

[0080] S23. Calculate the total energy consumption W in one acquisition cycle total , the calculation expression is as follows:

[0081] W total =W w +W s =P w Δt+P s (T c -Δt);

[0082] S24, calculate the average power consumption P mc , the expression is as follows:

[0083]

[0084] Step 3: The data processing unit uses the Kalman filter algorithm to filter the collected data to remove noise interference, and then calculates the comprehensive state index S of the transmission line and determines the monitoring level;

[0085] Among them, the process of filtering the collected data using the Kalman filter algorithm is as follows:

[0086] S31, initialization; set state vector x0 = [T0, F0, I0] T ), T0, F0, I0 represent the initial estimated values ​​of temperature, tension and current respectively, and the initial covariance matrix P0 = diag(1,1,1);

[0087] S32, prediction; according to the system state equation x k =F k-1 x k-1 +w k-1 Calculate predicted status and the predicted covariance The calculation expression is as follows:

[0088]

[0089] In the formula, x k-1 is the state value at the previous moment, F k-1 is the state transfer matrix, w k-1 is the process noise, is the state estimate at the previous moment, Q k-1 is the process noise covariance matrix;

[0090] S33, update; according to the measurement equation z k =H k x k +v k Calculate the Kalman gain K k , update the state estimate and covariance estimation The specific expression is as follows:

[0091]

[0092] In the formula, H k is the measurement matrix, v k To measure noise, R k is the measurement noise covariance matrix, z k is the measurement value vector, I is the identity matrix;

[0093] S34, after multiple iterations, the temperature T after Kalman filtering is obtained f , Tension F f and current data I f .

[0094] The calculation expression of the comprehensive status index S of the transmission line is as follows:

[0095] S = aT f + bF f + cI f ;

[0096] Wherein, a, b, and c are weight coefficients determined according to the characteristics of the transmission line;

[0097] The determination of the monitoring level includes the following three levels:

[0098] Level 1, indicating normal state: When S1 ≤ S ≤ S2, the transmission line operates normally, and S2 and S1 are the upper and lower limit thresholds determined according to the line design and experience;

[0099] Level 2, indicating warning state: When S < S1 or S > S2, the transmission line needs further attention;

[0100] Level 3, indicating dangerous state: When S < S3 or S > S4, there are serious safety hazards in the transmission line, and S3 and S4 are the absolute lower limit threshold and the absolute upper limit threshold.

[0101] Step 4, the wireless communication module sends the processed data and the comprehensive status index S to the monitoring center through low-power Bluetooth technology, completing the monitoring of the transmission line. Among them, before the wireless communication module sends the processed data and the comprehensive status index S to the monitoring center through low-power Bluetooth technology, the transmission power P is adjusted according to the communication distance d t , and the calculation expression is as follows:

[0102] P t = P t0 + 10nlog 10 (d / d0);

[0103] Wherein, P t0 is the transmission power under the reference distance d0, and n is the path loss exponent.

[0104] Therefore, the present invention adopts the above-mentioned low-power monitoring system and method for a transmission line. The low-power design reduces power consumption, lowers the operating cost of the power enterprise in the monitoring system, and at the same time reduces the demand for auxiliary equipment such as heat dissipation equipment, thereby reducing the hardware cost of the equipment. In addition, the Kalman filtering algorithm is adopted to effectively remove noise interference, improving the monitoring accuracy and reliability.

[0105] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

Claims

1. A low power consumption monitoring system for a power transmission line, characterized in that: It includes a sensor module, a data acquisition module, a data processing unit, a wireless communication module and a power management module; the sensor module includes an optical fiber temperature sensor, a strain gauge sensor and an electromagnetic induction sensor; the data acquisition module collects sensor data at time intervals Δt through a microcontroller; the data processing unit uses the Kalman filtering algorithm to process the acquired data; the wireless communication module uses the low-power Bluetooth technology BLE for data transmission; the power management module consists of a solar panel and a super capacitor. The solar panel powers the system and charges the super capacitor under light, and the super capacitor provides electrical energy for the system when there is no light or insufficient light.

2. A low power consumption monitoring system for a power transmission line according to claim 1, characterized in that: The supercapacitor is charging and the solar panel is charging for a period of time t c Energy provided by W solar for: W solar =P solar t c ; Where P solar Indicates the output power of the solar panel; During the discharge process of the supercapacitor, the energy of the supercapacitor W cap The relationship between capacitance C and voltage U is:

3. A low power consumption monitoring system for a power transmission line according to claim 2, characterized in that: Supercapacitor charging time t c and discharge time t d The following relations are satisfied: P solar t c ≥P sys (t c +t d ); Where P sys Indicates the average power consumption of the system.

4. A method for a low power consumption monitoring system for a power transmission line as claimed in any one of claims 1 to 3, characterized in that: It includes the following steps: Step 1: After the system is started, the sensor module starts working and each sensor collects the parameters of the transmission line, including temperature data T i , Tension data F i , current data I i ; Step 2: The data acquisition module collects sensor data at a preset time interval Δt and transmits the data to the data processing unit. During the collection process, the data acquisition module calculates the average power consumption P mc The power consumption is controlled by the method, and the switching between the working mode and the sleep mode is completed by the microcontroller; Step 3: The data processing unit uses the Kalman filtering algorithm to filter the acquired data, remove noise interference, then calculate the comprehensive state index S of the transmission line and determine the monitoring level. Step 4: The wireless communication module sends the processed data and the comprehensive state index S to the monitoring center through the low-power Bluetooth technology to complete the monitoring of the transmission line.

5. The method of a low power consumption monitoring system for a power transmission line according to claim 4, characterized in that: The optical fiber temperature sensor measures temperature based on the principle of light reflection. The relationship between its temperature T and the reflected light wavelength λ is as follows: T = k1(λ - λ0); where k1 is the temperature-wavelength conversion coefficient and λ0 is the reference wavelength.

6. The method of a low power consumption monitoring system for a power transmission line according to claim 5, characterized in that: Average power consumption P in step 2 mc The calculation process is as follows: S21, set the microcontroller in a collection cycle T c Within, the working time is Δt, and the sleeping time is T c -Δt; S22. Calculate the energy W consumed in each working mode w and the energy consumed in sleep mode W s , the calculation expression is as follows: W w =P w Δt; W s =P s (T c -Δt); Where P w is the power consumption of the microcontroller in working mode, P s is the power consumption of the microcontroller in sleep mode; S23. Calculate the total energy consumption W in one acquisition cycle total , the calculation expression is as follows: W total =W w +W s =P w Δt+P s (T c -Δt); S24, calculate the average power consumption P mc , the expression is as follows:

7. The method of a low power consumption monitoring system for a power transmission line according to claim 6, characterized in that: The process of using the Kalman filtering algorithm to filter the acquired data in Step 3 is as follows: S31, initialization; set state vector x0 = [T0, F0, I0] T ), T0, F0, I0 represent the initial estimated values ​​of temperature, tension and current respectively, and the initial covariance matrix P0 = diag(1,1,1); S32, prediction; according to the system state equation x k =F k-1 x k-1 +w k-1 Calculate predicted status and the predicted covariance The calculation expression is as follows: In the formula, x k-1 is the state value at the previous moment, F k-1 is the state transfer matrix, w k-1 is the process noise, is the state estimate at the previous moment, Q k-1 is the process noise covariance matrix; S33, update; according to the measurement equation z k =H k x k +v k Calculate the Kalman gain K k , update the state estimate and covariance estimation The specific expression is as follows: In the formula, H k is the measurement matrix, v k To measure noise, R k is the measurement noise covariance matrix, z k is the measurement value vector, I is the identity matrix; S34, after multiple iterations, the temperature T after Kalman filtering is obtained f , Tension F f and current data I f .

8. The method of a low power consumption monitoring system for a power transmission line according to claim 7, characterized in that: The calculation expression of the comprehensive state index S of the transmission line is as follows: S=aT f +bF f +cI f ; In the formula, a, b, and c are weight coefficients determined according to the characteristics of the transmission line; The determination of the monitoring level includes the following three levels: Level 1, indicating normal state: When S1 ≤ S ≤ S2, the transmission line operates normally, and S2 and S1 are the upper and lower limit thresholds determined according to the line design and experience. Level 2, indicating warning state: When S < S1 or S > S2, the transmission line needs further attention. Level 3, indicating dangerous state: When S < S3 or S > S4, the transmission line has serious potential safety hazards, and S3 and S4 are the absolute lower limit threshold and the absolute upper limit threshold.

9. The method of a low power consumption monitoring system for a power transmission line according to claim 8, characterized in that: In step 4, before the wireless communication module sends the processed data and comprehensive status indicator S to the monitoring center via low-power Bluetooth technology, the transmission power P is adjusted according to the communication distance d. t , the calculation expression is as follows: P t =P t0 +10nlog 10 (d / d0); Where P t0 is the transmission power at the reference distance d0, and n is the path loss exponent.

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