Method for predicting attenuation coefficient of data transmission capability of information system of photovoltaic power station

Abstract

The invention discloses a method for predicting a data transmission capability attenuation coefficient of a photovoltaic power station information system, and relates to the technical field of electrical engineering. Comprising the following steps: predicting a transmission capability attenuation coefficient when data in a photovoltaic power station information system is wirelessly transmitted; predicting a transmission capability attenuation coefficient of data transmitted through a wired transmission line in the photovoltaic power station information system; the transmission capability attenuation coefficient during wireless transmission and the transmission capability attenuation coefficient during wired transmission are utilized to obtain the comprehensive attenuation coefficient of the data transmission capability of the photovoltaic power station information system. A feasible production scheme can be made according to environmental factors such as temperature, humidity, atmospheric pressure and wind speed of a region where the photovoltaic power station is located; the data transmission is more accurate; by predicting the transmission capability attenuation coefficient of the data wired transmission line, the power loss and the voltage drop value of the wired transmission line can be obtained, the data accuracy in the transmission process is improved, and thus the production efficiency of a photovoltaic power station is improved.

Description

Technical Field

[0001] The present invention relates to the field of electrical engineering technology, and in particular to a method for predicting an attenuation coefficient of data transmission capacity of an information system of a photovoltaic power station. Background Art

[0002] With the continuous growth of global energy demand, solar energy, as a clean, renewable energy source, has gained widespread application. As the primary form of solar power generation, photovoltaic power plants face a significant impact on the operational efficiency and management of their information systems. The information systems of photovoltaic power plants are responsible for collecting, storing, and transmitting data, with data transmission being particularly crucial in photovoltaic power generation systems. However, during data transmission, the transmission capacity of information systems can be affected by various factors, leading to degradation in data transmission capabilities.

[0003] Currently, existing methods for predicting the attenuation coefficient of the data transmission capacity of photovoltaic power plant information systems mainly include substitution, impedance, and absolute methods. However, these methods have certain limitations: the substitution method is limited in the range of lines it can detect; the impedance method has high theoretical requirements, limited practical application, and low flexibility; and the absolute method suffers from low accuracy in predicting the attenuation coefficient. Therefore, a more accurate, flexible, and widely applicable prediction method is urgently needed to effectively assess the attenuation of the data transmission capacity of photovoltaic power plant information systems. Summary of the Invention

[0004] The present invention provides a method for predicting the attenuation coefficient of data transmission capacity of a photovoltaic power station information system, which effectively determines the attenuation degree of data transmission capacity during transmission, improves the accuracy of data during transmission, and solves the problems in the background technology.

[0005] To achieve the above object, the present invention provides the following technical solution: a method for predicting the attenuation coefficient of data transmission capacity of a photovoltaic power station information system, comprising the following steps:

[0006] S1: Predict the transmission capacity attenuation coefficient of data in the photovoltaic power station information system when it is transmitted wirelessly;

[0007] S2: Predict the transmission capacity attenuation coefficient of data in the photovoltaic power station information system transmitted through the wired transmission line;

[0008] S3: Using the transmission capacity attenuation coefficient during wireless transmission and the transmission capacity attenuation coefficient during wired transmission, the comprehensive attenuation coefficient of the data transmission capacity of the photovoltaic power station information system is obtained.

[0009] Furthermore, the S1 includes the following steps:

[0010] S1.1: Measure and monitor environmental parameters that affect wireless data transmission capabilities, including the average temperature T, average humidity H, atmospheric pressure P, average wind speed V in the area where the PV power station is located, the data transmission distance L in the PV power station information system, and the local PV power station's light intensity;

[0011] S1.2: Calculate the transmission capacity attenuation coefficient δ1 when the data in the photovoltaic power station information system is transmitted wirelessly. The calculation formula is as follows:

[0012]

[0013] Where P is the atmospheric pressure in the area where the photovoltaic power station is located, V is the average wind speed in the area where the photovoltaic power station is located, L is the data transmission distance in the photovoltaic power station information system, T(t) is the temperature function, H(t) is the humidity function, and L X (t) is the light intensity function; the atmospheric pressure P and average wind speed V in the area where the photovoltaic power station is located are set as constants. The data transmission distance L in the photovoltaic power station information system is determined according to the actual situation. The temperature function T(t), humidity function H(t) and light intensity function L X (t) are functions of time t obtained according to the changing curves of temperature, humidity and light intensity in the area where the photovoltaic power station is located.

[0014] Furthermore, the environmental parameters in S1.1 are monitored and collected in real time through the following modules:

[0015] Temperature monitoring module: used to collect temperature data of the area where the photovoltaic power station is located in real time and convert the temperature data into a temperature function T(t);

[0016] Humidity monitoring module: used to collect humidity data in the area where the photovoltaic power station is located in real time and convert the humidity data into humidity function H(t);

[0017] Wind speed monitoring module: used to collect wind speed data in the area where the photovoltaic power station is located in real time, and input the wind speed data as a constant V into the calculation model of the transmission capacity attenuation coefficient;

[0018] Light intensity monitoring module: used to collect light intensity data in the area where the photovoltaic power station is located in real time, and convert the light intensity data into a light intensity function L X (t);

[0019] Atmospheric pressure monitoring module: used to collect atmospheric pressure data in the area where the photovoltaic power station is located in real time, and input the atmospheric pressure data as a constant P into the calculation model of the transmission capacity attenuation coefficient.

[0020] Furthermore, the calculation model of the transmission capacity attenuation coefficient in S1.2 is based on the following algorithm:

[0021] Environmental parameter fitting algorithm: used to fit the collected temperature, humidity, and light intensity environmental parameters into a function of time t, and generate temperature function T(t), humidity function H(t), and light intensity function L X (t);

[0022] Wireless transmission attenuation model: used to calculate the transmission capacity attenuation coefficient δ1 during wireless transmission based on the fitted environmental parameter function, combined with atmospheric pressure P, wind speed V and transmission distance L.

[0023] Furthermore, in S2, a multi-physics field coupling analysis module is constructed to comprehensively consider the electric field and magnetic field distribution of the wired transmission line under different working conditions and the electromagnetic properties of the line material. Through the finite element analysis and numerical calculation method, the power loss and voltage drop parameters in the wired transmission line are accurately simulated and calculated, providing more detailed data support for the calculation of the wired transmission attenuation coefficient.

[0024] Furthermore, the S2 includes the following steps:

[0025] S2.1: Measure and monitor parameters that affect the transmission capacity of data wired transmission lines, including the apparent power at the head end of the wired transmission line The first-end voltage U1, resistance R and reactance X;

[0026] S2.2: Calculate the transmission capacity attenuation coefficient δ2 when the data in the photovoltaic power station information system is transmitted through the wired transmission line. The calculation formula is as follows:

[0027]

[0028] Where, is the apparent power input at the head end of the wired transmission line, is the loss caused by the discharge of the wired transmission line to the ground, R is the resistance of the wired transmission, X is the reactance of the wired transmission, θ is the impedance angle of the wired transmission line, and U1 is the voltage at the head end of the wired transmission line; the voltage U1 at the head end of the wired transmission line is determined according to the actual operation of the local photovoltaic power station. The resistance R and reactance X are calculated by the following formulas:

[0029]

[0030] Where j is the imaginary unit, w = 6.28f is the angular frequency of the AC power in the wired transmission line, f is the AC power frequency, and c is the capacitance per unit length of the wired transmission line.

[0031] R = r1l;

[0032] Where r1 is the resistance per unit length of the wired transmission line, and l is the length of the wired transmission line;

[0033] X = x1l;

[0034] Where x1 is the reactance per unit length of the wired transmission line.

[0035] Furthermore, the wired transmission line parameters in S2.1 are monitored and collected in real time through the following modules:

[0036] Apparent power monitoring module: used to collect the apparent power at the head end of the wired transmission line in real time

[0037] Voltage monitoring module: used to collect the voltage U1 of the head end of the wired transmission line in real time;

[0038] Resistance monitoring module: used to collect the resistance R of the wired transmission line in real time;

[0039] Reactance monitoring module: used to collect the reactance X of the wired transmission line in real time.

[0040] Furthermore, the calculation model of the transmission capacity attenuation coefficient in step 2.2 is based on the following algorithm:

[0041] Wired transmission loss model: used to calculate the apparent power Voltage U1, resistance R and reactance X, calculate the loss caused by wired transmission line discharge to ground

[0042] Wired transmission attenuation model: used to The resistance R, reactance X and impedance angle θ are used to calculate the transmission capacity attenuation coefficient δ2 during wired transmission.

[0043] Furthermore, the comprehensive attenuation coefficient δ3 in S3 is as shown in the following formula:

[0044]

[0045] Substituting the transmission capacity attenuation coefficients δ1 and δ2 obtained from S1.1 and S2.1 into the calculation formula of the comprehensive attenuation coefficient δ3, the comprehensive attenuation coefficient of the data transmission capacity of the photovoltaic power station information system in the region is calculated to be 0<δ3≤0.2%.

[0046] Furthermore, the prediction method also includes a real-time monitoring and feedback adjustment module, which collects the actual transmission error rate and packet loss rate performance indicators in real time during the data transmission process, and compares them with the expected performance range corresponding to the predicted attenuation coefficient. When the deviation exceeds the preset threshold, the model retraining and parameter update mechanism is triggered to achieve self-optimization and continuous adaptability improvement of the prediction method.

[0047] Compared with the prior art, the present invention provides a method for predicting the attenuation coefficient of data transmission capacity of a photovoltaic power station information system, which has the following beneficial effects:

[0048] The present invention provides a method for predicting the attenuation coefficient of the data transmission capacity of a photovoltaic power station information system. By predicting the attenuation coefficient of the wireless data transmission capacity, a practical production plan can be formulated based on environmental factors such as the temperature, humidity, atmospheric pressure, and wind speed of the photovoltaic power station area, thereby making data transmission more accurate. By predicting the attenuation coefficient of the transmission capacity of a wired data transmission line, the power loss and voltage drop value of the wired transmission line can be obtained. The comprehensive attenuation coefficient of the data transmission capacity of the local photovoltaic power station information system obtained by the transmission capacity attenuation coefficient during wireless transmission and the transmission capacity attenuation coefficient during wired transmission can effectively judge the degree of attenuation of the data transmission capacity during the transmission process, and then adopt a response plan to improve the accuracy of the data during the transmission process, thereby improving the production efficiency of the photovoltaic power station. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0050] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0051] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0052] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0053] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it constitute a separate or selective embodiment that is mutually exclusive with other embodiments.

[0054] See also Figure 1The present invention discloses a method for predicting the attenuation coefficient of data transmission capacity of a photovoltaic power station information system, comprising the following steps:

[0055] S1: Predict the transmission capacity attenuation coefficient of data in the photovoltaic power station information system when it is transmitted wirelessly.

[0056] Said S1 comprises the following steps:

[0057] S1.1: Measure and monitor environmental parameters that affect the wireless data transmission capability, including the average temperature T, average humidity H, atmospheric pressure P, average wind speed V in the area where the PV power station is located, the data transmission distance L in the PV power station information system, and the light intensity of the local PV power station.

[0058] S1.2: Calculate the transmission capacity attenuation coefficient δ1 when the data in the photovoltaic power station information system is transmitted wirelessly. The calculation formula is as follows:

[0059]

[0060] Where P is the atmospheric pressure in the area where the photovoltaic power station is located, V is the average wind speed in the area where the photovoltaic power station is located, L is the data transmission distance in the photovoltaic power station information system, T(t) is the temperature function, H(t) is the humidity function, and L X (t) is the light intensity function; the atmospheric pressure P and average wind speed V in the area where the photovoltaic power station is located are set as constants. The data transmission distance L in the photovoltaic power station information system is determined according to the actual situation. The temperature function T(t), humidity function H(t) and light intensity function L X (t) are functions of time t obtained according to the changing curves of temperature, humidity and light intensity in the area where the photovoltaic power station is located.

[0061] S2: Predict the transmission capacity attenuation coefficient of data in the photovoltaic power station information system transmitted through the wired transmission line.

[0062] The S2 comprises the following steps:

[0063] S2.1: Measure and monitor parameters that affect the transmission capacity of data wired transmission lines, including the apparent power at the head end of the wired transmission line The first-end voltage U1, resistance R and reactance X;

[0064] S2.2: Calculate the transmission capacity attenuation coefficient δ2 when the data in the photovoltaic power station information system is transmitted through the wired transmission line. The calculation formula is as follows:

[0065]

[0066] Where, is the apparent power input at the head end of the wired transmission line, is the loss caused by the discharge of the wired transmission line to the ground, R is the resistance of the wired transmission, X is the reactance of the wired transmission, θ is the impedance angle of the wired transmission line, and U1 is the voltage at the head end of the wired transmission line; the voltage U1 at the head end of the wired transmission line is determined according to the actual operation of the local photovoltaic power station. The resistance R and reactance X are calculated by the following formulas:

[0067]

[0068] Where j is the imaginary unit, w = 6.28f is the angular frequency of the AC power in the wired transmission line, f is the AC power frequency, and c is the capacitance per unit length of the wired transmission line.

[0069] R = r1l;

[0070] Where r1 is the resistance per unit length of the wired transmission line, and l is the length of the wired transmission line;

[0071] X = x1l;

[0072] Where x1 is the reactance per unit length of the wired transmission line.

[0073] S3: Using the transmission capacity attenuation coefficient during wireless transmission and the transmission capacity attenuation coefficient during wired transmission, the comprehensive attenuation coefficient of the data transmission capacity of the photovoltaic power station information system is obtained.

[0074] The comprehensive attenuation coefficient δ3 in S3 is as shown below:

[0075]

[0076] Substituting the transmission capacity attenuation coefficients δ1 and δ2 obtained from S1.1 and S2.1 into the calculation formula of the comprehensive attenuation coefficient δ3, the comprehensive attenuation coefficient of the data transmission capacity of the photovoltaic power station information system in the region is calculated to be 0<δ3≤0.2%.

[0077] Specifically, the environmental parameters in S1.1 are monitored and collected in real time through the following modules:

[0078] Temperature monitoring module: used to collect temperature data of the area where the photovoltaic power station is located in real time and convert the temperature data into a temperature function T(t);

[0079] Humidity monitoring module: used to collect humidity data in the area where the photovoltaic power station is located in real time and convert the humidity data into humidity function H(t);

[0080] Wind speed monitoring module: used to collect wind speed data in the area where the photovoltaic power station is located in real time, and input the wind speed data as a constant V into the calculation model of the transmission capacity attenuation coefficient;

[0081] Light intensity monitoring module: used to collect light intensity data in the area where the photovoltaic power station is located in real time, and convert the light intensity data into a light intensity function L X (t);

[0082] Atmospheric pressure monitoring module: used to collect atmospheric pressure data in the area where the photovoltaic power station is located in real time, and input the atmospheric pressure data as a constant P into the calculation model of the transmission capacity attenuation coefficient.

[0083] Specifically, the calculation model of the transmission capacity attenuation coefficient in S1.2 is based on the following algorithm:

[0084] Environmental parameter fitting algorithm: used to fit the collected temperature, humidity, and light intensity environmental parameters into a function of time t, and generate temperature function T(t), humidity function H(t), and light intensity function L X (t);

[0085] Wireless transmission attenuation model: used to calculate the transmission capacity attenuation coefficient δ1 during wireless transmission based on the fitted environmental parameter function, combined with atmospheric pressure P, wind speed V and transmission distance L.

[0086] Specifically, in S2, a multi-physics field coupling analysis module is constructed to comprehensively consider the electric field and magnetic field distribution of the wired transmission line under different working conditions and the electromagnetic properties of the line material. Through the finite element analysis and numerical calculation method, the power loss and voltage drop parameters in the wired transmission line are accurately simulated and calculated, providing more detailed data support for the calculation of the wired transmission attenuation coefficient.

[0087] Specifically, the wired transmission line parameters in S2.1 are monitored and collected in real time through the following modules:

[0088] Apparent power monitoring module: used to collect the apparent power at the head end of the wired transmission line in real time

[0089] Voltage monitoring module: used to collect the voltage U1 of the head end of the wired transmission line in real time;

[0090] Resistance monitoring module: used to collect the resistance R of the wired transmission line in real time;

[0091] Reactance monitoring module: used to collect the reactance X of the wired transmission line in real time.

[0092] Specifically, the calculation model of the transmission capacity attenuation coefficient in step 2.2 is based on the following algorithm:

[0093] Wired transmission loss model: used to calculate the apparent power Voltage U1, resistance R and reactance X, calculate the loss caused by wired transmission line discharge to ground

[0094] Wired transmission attenuation model: used to The resistance R, reactance X and impedance angle θ are used to calculate the transmission capacity attenuation coefficient δ2 during wired transmission.

[0095] Specifically, the prediction method also includes a real-time monitoring and feedback adjustment module, which collects the actual transmission error rate and packet loss rate performance indicators in real time during the data transmission process, and compares them with the expected performance range corresponding to the predicted attenuation coefficient. When the deviation exceeds the preset threshold, the model retraining and parameter update mechanism is triggered to achieve self-optimization and continuous adaptability improvement of the prediction method.

[0096] Specifically, the prediction method can be applied to photovoltaic power station information systems of different sizes and types, and can flexibly set and adjust parameters according to specific application scenarios and needs to adapt to diverse data transmission environments and requirements.

[0097] Specifically, in S3, the comprehensive attenuation coefficient can effectively determine the attenuation degree of data transmission capacity during the transmission process, and a corresponding data transmission optimization plan can be formulated based on the comprehensive attenuation coefficient to improve the data transmission accuracy and production efficiency of the photovoltaic power station information system.

[0098] The present invention provides a method for predicting the attenuation coefficient of data transmission capacity of a photovoltaic power station information system, which has the following beneficial effects:

[0099] Improve the accuracy of data transmission: By predicting the attenuation coefficient of wireless data transmission capacity, a practical production plan can be formulated based on environmental factors such as temperature, humidity, atmospheric pressure, wind speed, etc. in the area where the photovoltaic power station is located, making data transmission more accurate.

[0100] Optimize the design of wired transmission lines: By predicting the transmission capacity attenuation coefficient of data wired transmission lines, the power loss and voltage drop values of the wired transmission lines can be obtained, thereby optimizing the line design and reducing energy loss.

[0101] Comprehensive evaluation of data transmission capacity: The comprehensive attenuation coefficient of the data transmission capacity of the local photovoltaic power station information system is obtained by the transmission capacity attenuation coefficient during wireless transmission and the transmission capacity attenuation coefficient during wired transmission. This can effectively determine the degree of attenuation of data transmission capacity during the transmission process, and then take countermeasures to improve the accuracy of data during the transmission process, thereby improving the production efficiency of the photovoltaic power station. Specific embodiment:

[0103] See also Figure 1 A method for predicting the attenuation coefficient of data transmission capacity of a photovoltaic power station information system comprises the following steps:

[0104] S1: Predicting the transmission capacity attenuation coefficient of data in the photovoltaic power station information system when transmitted wirelessly; S1 includes the following steps:

[0105] S1.1: Measure and monitor environmental parameters that affect the wireless data transmission capability, including the average temperature T, average humidity H, atmospheric pressure P, average wind speed V in the area where the PV power station is located, the data transmission distance L in the PV power station information system, and the light intensity of the local PV power station.

[0106] S1.2: Calculate the transmission capacity attenuation coefficient δ1 when the data in the photovoltaic power station information system is transmitted wirelessly. The calculation formula is as follows:

[0107]

[0108] Where P is the atmospheric pressure in the area where the photovoltaic power station is located, V is the average wind speed in the area where the photovoltaic power station is located, L is the data transmission distance in the photovoltaic power station information system, T(t) is the temperature function, H(t) is the humidity function, and L X (t) is the light intensity function; the atmospheric pressure P and average wind speed V in the area where the photovoltaic power station is located are set as constants. The data transmission distance L in the photovoltaic power station information system is determined according to the actual situation. The temperature function T(t), humidity function H(t) and light intensity function L X (t) are functions of time t obtained according to the changing curves of temperature, humidity and light intensity in the area where the photovoltaic power station is located.

[0109] In this example, parameters affecting wireless data transmission capabilities in a specific region were measured and monitored. After monitoring temperature, humidity, and light intensity for a month, we obtained curves for these three variables. By analyzing these curves, we obtained the following function for the temperature variation in the region over a single day:

[0110]

[0111] Where t∈[0,24];

[0112] The humidity change function is

[0113] Among them, t∈[0,24], and the light intensity change function is L x (t) = e 2 (3t 3 -6t2 );

[0114] Among them, t∈[6,18], the average wind speed in the area is V=17km / h, the atmospheric pressure is P=101Kpa, and the wireless transmission distance of photovoltaic power station data is L=1Km.

[0115] The monitored environmental parameters are substituted into the calculation function of the transmission capacity attenuation coefficient δ1 when data is transmitted wirelessly in the photovoltaic power station information system. The calculated attenuation coefficient has a value range of 0<δ1<0.001.

[0116] It can be seen that for a wireless transmission distance of 1 km, the attenuation coefficient of data transmission capacity during the transmission process is less than one thousandth, which meets the requirements of reality and economy.

[0117] The S2 comprises the following steps:

[0118] S2.1: Measure and monitor parameters that affect the transmission capacity of data wired transmission lines, including the apparent power at the head end of the wired transmission line The first-end voltage U1, resistance R and reactance X;

[0119] S2.2: Calculate the transmission capacity attenuation coefficient δ2 when the data in the photovoltaic power station information system is transmitted through the wired transmission line. The calculation formula is as follows:

[0120]

[0121] Where, is the apparent power input at the head end of the wired transmission line, is the loss caused by the discharge of the wired transmission line to the ground, R is the resistance of the wired transmission, X is the reactance of the wired transmission, θ is the impedance angle of the wired transmission line, and U1 is the voltage at the head end of the wired transmission line; the voltage U1 at the head end of the wired transmission line is determined according to the actual operation of the local photovoltaic power station. The resistance R and reactance X are calculated by the following formulas:

[0122]

[0123] Where j is the imaginary unit, w = 6.28f is the angular frequency of the AC power in the wired transmission line, f is the AC power frequency, and c is the capacitance per unit length of the wired transmission line.

[0124] R = r1l;

[0125] Where r1 is the resistance per unit length of the wired transmission line, and l is the length of the wired transmission line;

[0126] X = x1l;

[0127] Where x1 is the reactance per unit length of the wired transmission line.

[0128] In this embodiment, the parameters affecting the data wired transmission capability of a certain section of the wired transmission line of the photovoltaic power station in the region with a transmission distance of l = 200 km are measured and monitored. After detection and calculation, the following parameters are obtained: the capacitance per unit length of the wired transmission line c = 0.012 μF / km, the resistance per unit length r1 = 0.28 Ω / km, the reactance per unit length x1 = 0.4 Ω / km, the frequency of the alternating current f = 50 Hz, the impedance angle θ = 30°, and thus the resistance R of the wired transmission line is 56 Ω, the reactance X is 80 Ω, the voltage at the head end of the wired transmission line U1 = 115 kV, the voltage at the end end U2 = 105 kV, and the power at the head end is Losses caused by discharge from wired transmission lines to the ground

[0129] The monitored parameters of the wired transmission line are substituted into the calculation function of the transmission capacity attenuation coefficient δ2 when data is transmitted through the line in the information system. The calculated attenuation coefficient satisfies δ2∈[0,0.1]. Based on the relationship between the transmission capacity attenuation coefficient and the voltage of the transmission line, it can be concluded that the voltage drop of this section of the line in this embodiment is less than or equal to 10% of the rated voltage of this section of the line, which meets the requirements of practicality and economy.

[0130] S3: Using the transmission capacity attenuation coefficient during wireless transmission and the transmission capacity attenuation coefficient during wired transmission, the comprehensive attenuation coefficient of the data transmission capacity of the photovoltaic power station information system is obtained.

[0131] The comprehensive attenuation coefficient δ3 in S3 is as shown below:

[0132]

[0133] Substituting the transmission capacity attenuation coefficients δ1 and δ2 obtained from S1.1 and S2.1 into the calculation formula of the comprehensive attenuation coefficient δ3, the comprehensive attenuation coefficient of the data transmission capacity of the photovoltaic power station information system in the region is calculated to be 0<δ3≤0.2%.

[0134] The comprehensive attenuation coefficient can be used to predict the attenuation degree of the data transmission capacity of the photovoltaic power station information system. Therefore, in the photovoltaic power station information system, the attenuation of data during transmission does not exceed 0.2% of its total input.

[0135] The present invention provides a method for predicting the attenuation coefficient of the data transmission capacity of a photovoltaic power station information system, which can effectively evaluate the attenuation of the photovoltaic power station information system during the data transmission process, thereby improving the accuracy of data transmission and the production efficiency of the photovoltaic power station. By comprehensively considering the environmental parameters and line parameters of wireless transmission and wired transmission, the method provided by the present invention has high accuracy and wide applicability, and can provide strong support for the optimization of the information system of the photovoltaic power station.

[0136] In summary, the method for predicting the attenuation coefficient of the data transmission capacity of the photovoltaic power station information system provided by the present invention can formulate a practical production plan based on environmental factors such as temperature, humidity, atmospheric pressure, wind speed, etc. in the area where the photovoltaic power station is located by predicting the attenuation coefficient of the wireless data transmission capacity; by predicting the attenuation coefficient of the data wired transmission line, the power loss and voltage drop value of the wired transmission line can be obtained; the comprehensive attenuation coefficient of the data transmission capacity of the local photovoltaic power station information system obtained by the transmission capacity attenuation coefficient during wireless transmission and the transmission capacity attenuation coefficient during wired transmission can effectively judge the attenuation degree of the data transmission capacity during the transmission process, and then take countermeasures to improve the accuracy of the data during the transmission process, thereby improving the production efficiency of the photovoltaic power station.

[0137] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0138] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for predicting the attenuation coefficient of data transmission capacity of a photovoltaic power station information system, characterized in that: The following steps are involved: S1: Predict the transmission capacity attenuation coefficient of data in the photovoltaic power station information system when it is transmitted wirelessly; S2: Predict the transmission capacity attenuation coefficient of data in the photovoltaic power station information system transmitted through the wired transmission line; S3: Using the transmission capacity attenuation coefficient during wireless transmission and the transmission capacity attenuation coefficient during wired transmission, the comprehensive attenuation coefficient of the data transmission capacity of the photovoltaic power station information system is obtained.

2. The method for predicting the attenuation coefficient of data transmission capacity of a photovoltaic power station information system according to claim 1, characterized in that: Said S1 comprises the following steps: S1.1: Measure and monitor environmental parameters that affect wireless data transmission capabilities, including the average temperature T, average humidity H, atmospheric pressure P, average wind speed V in the area where the PV power station is located, the data transmission distance L in the PV power station information system, and the local PV power station's light intensity; S1.2: Calculate the transmission capacity attenuation coefficient δ1 when the data in the photovoltaic power station information system is transmitted wirelessly. The calculation formula is as follows: Where P is the atmospheric pressure in the area where the photovoltaic power station is located, V is the average wind speed in the area where the photovoltaic power station is located, L is the data transmission distance in the photovoltaic power station information system, T(t) is the temperature function, H(t) is the humidity function, and L X (t) is the light intensity function; the atmospheric pressure P and average wind speed V in the area where the photovoltaic power station is located are set as constants. The data transmission distance L in the photovoltaic power station information system is determined according to the actual situation. The temperature function T(t), humidity function H(t) and light intensity function L X (t) are functions of time t obtained according to the changing curves of temperature, humidity and light intensity in the area where the photovoltaic power station is located.

3. The method for predicting the attenuation coefficient of data transmission capacity of a photovoltaic power station information system according to claim 2, characterized in that: The environmental parameters in S1.1 are monitored and collected in real time through the following modules: Temperature monitoring module: used to collect temperature data of the area where the photovoltaic power station is located in real time and convert the temperature data into a temperature function T(t); Humidity monitoring module: used to collect humidity data in the area where the photovoltaic power station is located in real time and convert the humidity data into humidity function H(t); Wind speed monitoring module: used to collect wind speed data in the area where the photovoltaic power station is located in real time, and input the wind speed data as a constant V into the calculation model of the transmission capacity attenuation coefficient; Light intensity monitoring module: used to collect light intensity data in the area where the photovoltaic power station is located in real time, and convert the light intensity data into a light intensity function L X (t); Atmospheric pressure monitoring module: used to collect atmospheric pressure data in the area where the photovoltaic power station is located in real time, and input the atmospheric pressure data as a constant P into the calculation model of the transmission capacity attenuation coefficient.

4. The method for predicting the attenuation coefficient of data transmission capacity of a photovoltaic power station information system according to claim 2, characterized in that: The calculation model of the transmission capacity attenuation coefficient in S1.2 is based on the following algorithm: Environmental parameter fitting algorithm: used to fit the collected temperature, humidity, and light intensity environmental parameters into a function of time t, and generate temperature function T(t), humidity function H(t), and light intensity function L X (t); Wireless transmission attenuation model: used to calculate the transmission capacity attenuation coefficient δ1 during wireless transmission based on the fitted environmental parameter function, combined with atmospheric pressure P, wind speed V and transmission distance L.

5. The method for predicting the attenuation coefficient of data transmission capacity of a photovoltaic power station information system according to claim 1, characterized in that: In S2, a multi-physics field coupling analysis module is constructed to comprehensively consider the electric field and magnetic field distribution of wired transmission lines under different working conditions and the electromagnetic characteristics of line materials. Through finite element analysis and numerical calculation methods, the power loss and voltage drop parameters in the wired transmission lines are accurately simulated and calculated, providing more detailed data support for the calculation of the wired transmission attenuation coefficient.

6. The method for predicting the attenuation coefficient of data transmission capacity of a photovoltaic power station information system according to claim 1, characterized in that: The S2 comprises the following steps: S2.1: Measure and monitor parameters that affect the transmission capacity of data wired transmission lines, including the apparent power at the head end of the wired transmission line The first-end voltage U1, resistance R and reactance X; S2.2: Calculate the transmission capacity attenuation coefficient δ2 when the data in the photovoltaic power station information system is transmitted through the wired transmission line. The calculation formula is as follows: Where, is the apparent power input at the head end of the wired transmission line, is the loss caused by the discharge of the wired transmission line to the ground, R is the resistance of the wired transmission, X is the reactance of the wired transmission, θ is the impedance angle of the wired transmission line, and U1 is the voltage at the head end of the wired transmission line; the voltage U1 at the head end of the wired transmission line is determined according to the actual operation of the local photovoltaic power station. The resistance R and reactance X are calculated by the following formulas: Where j is the imaginary unit, w = 6.28f is the angular frequency of the AC power in the wired transmission line, f is the AC power frequency, and c is the capacitance per unit length of the wired transmission line. R＝r1l； Where r1 is the resistance per unit length of the wired transmission line, and l is the length of the wired transmission line; X = x1l; Where x1 is the reactance per unit length of the wired transmission line.

7. The method for predicting the attenuation coefficient of data transmission capacity of a photovoltaic power station information system according to claim 6, characterized in that: The wired transmission line parameters in S2.1 are monitored and collected in real time through the following modules: Apparent power monitoring module: used to collect the apparent power at the head end of the wired transmission line in real time Voltage monitoring module: used to collect the voltage U1 of the head end of the wired transmission line in real time; Resistance monitoring module: used to collect the resistance R of the wired transmission line in real time; Reactance monitoring module: used to collect the reactance X of the wired transmission line in real time.

8. The method for predicting the attenuation coefficient of data transmission capacity of a photovoltaic power station information system according to claim 6, characterized in that: The calculation model of the transmission capacity attenuation coefficient in step 2.2 is based on the following algorithm: Wired transmission loss model: used to calculate the apparent power Voltage U1, resistance R and reactance X, calculate the loss caused by wired transmission line discharge to ground Wired transmission attenuation model: used to The resistance R, reactance X and impedance angle θ are used to calculate the transmission capacity attenuation coefficient δ2 during wired transmission.

9. The method for predicting the attenuation coefficient of data transmission capacity of a photovoltaic power station information system according to claim 1, characterized in that: The comprehensive attenuation coefficient δ3 in S3 is as shown below: Substituting the transmission capacity attenuation coefficients δ1 and δ2 obtained from S1.1 and S2.1 into the calculation formula of the comprehensive attenuation coefficient δ3, the comprehensive attenuation coefficient of the data transmission capacity of the photovoltaic power station information system in the region is calculated to be 0<δ3≤0.2%.

10. The method for predicting the attenuation coefficient of data transmission capacity of a photovoltaic power station information system according to claim 1, characterized in that: The prediction method also includes a real-time monitoring and feedback adjustment module, which collects the actual transmission error rate and packet loss rate performance indicators in real time during data transmission, and compares them with the expected performance range corresponding to the predicted attenuation coefficient. When the deviation exceeds the preset threshold, the model retraining and parameter update mechanism is triggered to achieve self-optimization and continuous adaptability improvement of the prediction method.

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