Carrier communication signal demodulation method and photovoltaic power generation system

Abstract

The invention discloses a demodulation method of carrier communication signals and a photovoltaic power generation system. The demodulation method comprises the following steps: acquiring a carrier communication signal; the carrier communication signal is sampled according to a preset dynamic sampling frequency to obtain a sampling signal, the sampling signal comprises sampling data, the sampling data comprises a first frequency signal and a second frequency signal, and the first frequency signal and the second frequency signal are different in frequency; and analyzing energy in the sampling signal according to an adaptive threshold, and demodulating a logic signal according to the first frequency signal and the second frequency signal. According to the technical scheme, the application range of the demodulation chip can be effectively expanded, and the use flexibility is improved.

Description

Technical Field

[0001] The present invention relates to the field of communication technologies, and particularly to a method for demodulating carrier communication signals and a photovoltaic power generation system. Background Art

[0002] With the continuous development of technologies such as the Internet of Things and big data, the application of communication technologies in photovoltaic power generation systems has become increasingly widespread. The use of communication technologies enables photovoltaic power generation systems to transmit data in real time and monitor the operating conditions of devices, promoting the intelligent development of photovoltaic power generation systems and improving the system operation efficiency and management efficiency.

[0003] Currently, in the industry, for the demodulation of communication signals, most use dedicated demodulation chips. However, these dedicated demodulation chips have high costs and cannot modify the signal detection frequency, having certain limitations in use. These factors limit the application scope of demodulation chips and reduce the flexibility of use. Summary of the Invention

[0004] Aiming at the defects in the prior art, the present invention provides a method for demodulating carrier communication signals, which can effectively improve the application scope of demodulation chips and increase the flexibility of use.

[0005] A method for demodulating carrier communication signals provided in this application, the demodulation method includes:

[0006] Obtain a carrier communication signal;

[0007] Sample the carrier communication signal according to a preset dynamic sampling frequency to obtain a sampling signal. The sampling signal includes sampling data, and the sampling data includes a first frequency signal and a second frequency signal, and the frequencies of the first frequency signal and the second frequency signal are different;

[0008] Analyze the energy in the sampling signal according to an adaptive threshold, and demodulate a logic signal according to the first frequency signal and the second frequency signal.

[0009] In one aspect, before the step of sampling the carrier communication signal according to a preset dynamic sampling frequency, it includes:

[0010] Set a dynamic sampling frequency, and the dynamic sampling frequency is at least twice the maximum frequency of the first frequency signal and the second frequency signal.

[0011] In one aspect, the first frequency signal and the second frequency signal are maintained according to a preset time respectively. Define the sampling time of the dynamic sampling frequency as T, and the preset time is T 1 , then it satisfies: n*T≤T 1 , where n is an odd number and n≥3.

[0012] In one aspect, the sampled data includes a silent period, the sampling signal includes a plurality of the sampled data, and the silent period is used to distinguish the sampled data;

[0013] The step of demodulating a logic signal according to the first frequency signal and the second frequency signal includes:

[0014] When n is equal to 3, in the same sampled data:

[0015] If the frequency signal maintained in two consecutive preset time periods is the first frequency signal, the demodulated logic signal is the corresponding value of the first frequency signal;

[0016] If the frequency signal maintained in two consecutive preset time periods is the second frequency signal, the demodulated logic signal is the corresponding value of the second frequency signal.

[0017] In one aspect, after the step of setting a dynamic sampling frequency, it includes:

[0018] Set a bit judgment interruption frequency, and the bit judgment interruption frequency is the reciprocal of the sampling time.

[0019] In one aspect, before the step of analyzing the energy in the sampling signal according to an adaptive threshold, it includes:

[0020] Calculate the energy of the sampling signal through a single-frequency detection recursive algorithm.

[0021] In one aspect, the energy calculation formula of the sampling signal satisfies:

[0022] s[n] = x[n] + 2cos(2πK) × s[n - 1] - s[n - 2]

[0023] Sp = S[n - 1] 2 + S[n] 2 - 2cos(2πK) × S[n - 1] - S[n]

[0024] Wherein, x[n] represents the signal amplitude of the sampling signal, s[n - 1] and s[n - 2] are the results of the previous two sampling energy outputs, K is a frequency index and is an integer, s[n] is a single-frequency detection recursive intermediate variable, and Sp is the total energy value of the sampling signal.

[0025] In one aspect, the step of analyzing the energy in the sampling signal according to an adaptive threshold includes:

[0026] Obtain the maximum value and the minimum value of the sampling signal amplitude in real time;

[0027] Adjust the energy threshold according to the range mapping formed by the maximum value and the minimum value, and re - form an adaptive threshold;

[0028] Analyze the energy in the sampling signal according to the regenerated adaptive threshold.

[0029] In one aspect, the step of analyzing the energy in the sampling signal according to the adaptive threshold includes:

[0030] Obtain the actual signal of the sampling signal amplitude in real - time;

[0031] Map the actual signal to a preset standard range, and analyze the energy in the sampling signal according to a fixed adaptive threshold.

[0032] In addition, to solve the above problems, the present application also provides a photovoltaic power generation system, which includes a switching tube that receives the logic signal output by the demodulation method described above.

[0033] The beneficial effects of the present invention are as follows: Through the dynamic sampling frequency, the dynamic adjustment of the sampling frequency can be realized, making it more suitable for sampling the sampling signal and ensuring the accuracy of the sampling signal. And through the setting of the adaptive threshold, when demodulating the sampling signal, the threshold for judgment can be optimized in real - time according to the change of the sampling signal amplitude, making the demodulated logic signal more stable, reducing misjudgment caused by signal amplitude fluctuation, and improving the demodulation accuracy. Thus, the application range of the demodulation chip is improved, and the flexibility of the usage scenario is increased. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0035] Figure 1 It is a schematic flow chart of the demodulation method for the carrier communication signal of the present application;

[0036] Figure 2 It is a schematic flow chart of setting the dynamic sampling frequency in the demodulation method for the carrier communication signal of the present application;

[0037] Figure 3 It is a schematic flow chart of confirming the first frequency signal and the second frequency signal in the demodulation method for the carrier communication signal of the present application;

[0038] Figure 4 It is a schematic flow chart of setting the bit - judgment interrupt frequency in the demodulation method for the carrier communication signal of the present application;

[0039] Figure 5 It is a schematic diagram of the process steps for adjusting the adaptive threshold in the demodulation method of the carrier communication signal of this application;

[0040] Figure 6 It is another schematic diagram of the process steps for adjusting the adaptive threshold in the demodulation method of the carrier communication signal of this application;

[0041] Figure 7 It is a schematic diagram of the sampling time and the preset time in the demodulation method of the carrier communication signal of this application;

[0042] Figure 8 It is a schematic diagram of the structure of the photovoltaic power generation system of this application. Detailed implementation manners

[0043] Next, embodiments of the technical solution of the present invention will be described in detail with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, so they are only examples and cannot be used to limit the protection scope of the present invention.

[0044] It should be noted that unless otherwise specified, the technical terms or scientific terms used in this application should have the ordinary meanings understood by those skilled in the art to which the present invention belongs.

[0045] As Figure 1 shown, this application provides a demodulation method for carrier communication signals. The demodulation method of this application is mainly used to demodulate the communication signals in the photovoltaic power generation system. The demodulation method includes:

[0046] Step S10, obtaining a carrier communication signal; receiving the modulated carrier communication signal through the power line carrier communication module (such as the DC bus) of the photovoltaic power generation system. The carrier communication signal can be an FSK (Frequency Shift Keying) signal. FSK is a digital modulation technology that transmits digital information by changing the carrier frequency. For example, the FSK signal uses two or more different frequencies to represent "1" and "0" in binary data, or corresponds to logic "1" and "-1".

[0047] Step S20: Sample the carrier communication signal at a preset dynamic sampling frequency to obtain a sampled signal. The sampled signal includes sampled data, and the sampled data includes a first frequency signal and a second frequency signal, where the frequencies of the first frequency signal and the second frequency signal are different. The carrier communication signal can adopt the SunSpec protocol, which is an open communication standard widely used in the photovoltaic industry and aims to achieve interconnection and data interaction between photovoltaic devices (such as inverters, energy storage systems, rapid shutdown devices, etc.). The SunSpec protocol can improve the compatibility, scalability, and intelligence level of the photovoltaic system. Among them, the first frequency signal is the marking frequency, and the second frequency signal is the spatial frequency. The marking frequency can be 143.75 kHz, and the spatial frequency can be 131.25 kHz. Of course, the first frequency signal and the second frequency signal can also be other frequencies, and different values are represented by the magnitudes of the frequencies.

[0048] Step S30: Analyze the energy in the sampled signal according to an adaptive threshold, and demodulate the logic signal based on the first frequency signal and the second frequency signal. The determination threshold is optimized in real time according to the amplitude change of the sampled signal, that is, an adaptive threshold is formed. Under noise interference, the logic signal can still be stably demodulated through the adaptive threshold. False judgments caused by signal amplitude fluctuations are avoided, and the demodulation accuracy is improved.

[0049] In this embodiment, through the dynamic sampling frequency, the dynamic adjustment of the sampling frequency can be realized, making it more suitable for sampling the sampled signal and ensuring the accuracy of the sampled signal. And through the setting of the adaptive threshold, when demodulating the sampled signal, the determination threshold can be optimized in real time according to the amplitude change of the sampled signal, making the demodulated logic signal more stable, reducing false judgments caused by signal amplitude fluctuations, and improving the demodulation accuracy. Thus, the application range of the demodulation chip is expanded, and it can also be used under complex noise interference, increasing the flexibility of the usage scenarios.

[0050] As Figure 2 shown, in an embodiment of the present application, before the step of sampling the carrier communication signal at a preset dynamic sampling frequency, it includes:

[0051] Step S01: Set the dynamic sampling frequency, and the dynamic sampling frequency is at least twice the maximum frequency of the first frequency signal and the second frequency signal. Define the dynamic sampling frequency as Fs. According to the Nyquist sampling theorem, the dynamic sampling frequency Fs needs to satisfy: Fs ≥ 2 * Fmax, where Fmax is the maximum value of the first frequency signal and the second frequency signal. For example, if the marking frequency is the largest and the marking frequency is 143.75 kHz, then the dynamic sampling frequency Fs is 287.5 kHz. To reduce the influence of frequency fluctuation error, the dynamic sampling frequency Fs can be set to 300 kHz to ensure no aliasing in the sampling of the sampled data.

[0052] In an embodiment of the present application, the first frequency signal and the second frequency signal are maintained respectively according to a preset time. The sampling time for defining the dynamic sampling frequency is T, and the preset time is T 1 , then it satisfies: n*T≤T 1 , where n is an odd number and n≥3. Ensuring that the preset time is an odd multiple of the sampling time facilitates determining whether the frequency signal obtained by sampling is the first frequency signal or the second frequency signal. For example, among the first frequency signal and the second frequency signal obtained by sampling, if one is the most, it is determined that the signal sampled within the sampling time is that one. By setting an odd multiple, the situation of 1:1 is also avoided.

[0053] In the present application, as Figure 6 shown, for example, when n is 3, the maintenance time T1 of each frequency signal is 5.12 ms, and the sampling time T is 1.706 ms. n is usually 3. The longer the time of a single T, the more signal samples are obtained within this sampling time, and the more accurate the data.

[0054] Furthermore, the sampled data includes a silent period, and the sampling signal includes multiple sampled data. The silent period is used to distinguish the sampled data; for the time composition of a sampled data, for example, a sampled data signal is composed of a 33-bit marked frequency and a spatial frequency. The maintenance time of each frequency is 5.12 ms, and a total of 33 frequencies are emitted, and then the frequency emission is stopped and the silent period of 901.12 ms is maintained. Thus, a complete sampled data cycle is: 33*5.12 + 901.12 = 1070.08, that is, a complete sampled data cycle is 1070.08 ms. After 33 times of frequency output, a signal-free period of 901.12 ms is inserted to distinguish different instructions. It should be noted that different alternating orders of the marked frequency and the spatial frequency represent different meanings. For another example, if the marked frequency represents 1 and the spatial frequency represents -1, if the demodulated logical signal is {-1, -1, -1, +1, +1, +1, -1, +1, +1, -1, +1}, it represents on, and if the demodulated signal is {+1, +1, +1, -1, -1, -1, +1, -1, -1, +1, -1}, it represents off.

[0055] As Figure 3 shown, the steps of demodulating a logical signal based on the first frequency signal and the second frequency signal include:

[0056] Step S300, when n is equal to 3, in the same sampled data: there are three sampling times within one preset time.

[0057] Step S301, if the frequency signals maintained within two consecutive preset time periods are the first frequency signal, then the demodulated logical signal is the corresponding value of the first frequency signal; thereby determining that the sampled signal is the first frequency signal.

[0058] Step S302: If the frequency signals maintained in two consecutive preset time periods are the second frequency signal, the demodulated logic signal is the corresponding value of the second frequency signal. Then, it is determined that the sampled signal is the second frequency signal.

[0059] For example, if the marked frequency energy exceeding the adaptive threshold is detected in two consecutive 1.706 ms windows, it is determined as logic "+1"; if the spatial frequency energy exceeding the adaptive threshold is detected, it is determined as logic "-1". The instruction sequence "+1, -1, +1..." corresponds to the frequency sequence "131.25 kHz → 143.75 kHz → 131.25 kHz...".

[0060] As Figure 4 shown, in an embodiment of the present application, after the step of setting the dynamic sampling frequency, it includes:

[0061] Step S02: Set the bit judgment interrupt frequency, and the bit judgment interrupt frequency is the reciprocal of the sampling time. The bit judgment interrupt frequency represents the detection speed. For example, if the sampling time is 1.706 ms, the bit judgment interrupt frequency is 586 Hz, ensuring that 512 sampling points are processed per interrupt, and a total of 586 detections can be made within 1 s, representing the detection speed. The design of the bit judgment interrupt frequency can balance real-time performance and computational overhead. The 586 Hz interrupt frequency can not only meet the timing accuracy requirements but also avoid over-occupying CPU resources. The bit judgment interrupt frequency is a key timing parameter in photovoltaic carrier communication demodulation. Through periodic interrupts to trigger frequency detection and logic determination, it ensures the precise alignment of signal bit boundaries and the reliable demodulation of logic states.

[0062] In an embodiment of the present application, before the step of analyzing the energy in the sampling signal according to the adaptive threshold, it includes:

[0063] Calculate the energy of the sampling signal through the single-frequency detection recursive algorithm. For example, the Goertzel algorithm can be used. Goertzel is an efficient and low-resource-occupying single-frequency detection algorithm, suitable for embedded systems and real-time signal processing scenarios. It realizes the precise detection of the target frequency through recursive calculation and energy threshold determination and can be applied in the field of photovoltaic communication decoding.

[0064] In one aspect, the energy calculation formula of the sampling signal satisfies:

[0065] s[n] = x[n] + 2cos(2πK) × s[n - 1] - s[n - 2], and s[n] can be recursively updated point by point through this formula.

[0066] Sp = S[n - 1] 2 + S[n] 2×2cos(2πK)×S[n - 1] - S[n], the total value is calculated through this formula.

[0067] When using the single - frequency detection recursive algorithm, initialization is first performed: s[0] = s[1] = 0; sample point by point and recursively update s[n]. Calculate the total energy Sp of the sampling signal through s[n], and use the calculated total energy Sp to compare with the adaptive threshold. Among them, x[n] represents the signal amplitude of the sampling signal, s[n - 1] and s[n - 2] are the results of the previous two sampling energy outputs, K is the frequency index and is an integer, s[n] is the intermediate variable of single - frequency detection recursion, and Sp is the total energy value of the sampling signal.

[0068] It can be calculated through the above formula that, compared with the Fourier algorithm in the related technology which needs to calculate the entire frequency - domain spectrum, the computational complexity is significantly reduced. The Goertezl algorithm demodulates and analyzes the carrier frequency, and the algorithm is optimized so that only one multiplication floating - point operation needs to be performed for each frequency in one sampling period.

[0069] In this application, there are two cases for the analysis of the energy of the sampling signal by the adaptive threshold.

[0070] The first case is as Figure 5 shown. The steps for analyzing the energy in the sampling signal according to the adaptive threshold include:

[0071] Step S310, obtain the maximum and minimum values of the sampling signal amplitude in real - time; in this embodiment, the sampling signal amplitude is the voltage value.

[0072] Step S311, adjust the size of the energy threshold according to the range mapping formed by the maximum and minimum values to re - form the adaptive threshold; for example, the normalization method can be used to compare the signals obtained by each sampling within the same range, ensuring that the generated adaptive threshold can be effectively applied to the corresponding sampling signal. Even if the voltage fluctuates or is interfered, the signal demodulation can be effectively completed.

[0073] Step S312: Analyze the energy in the sampling signal based on the regenerated adaptive threshold. For example, the signal amplitude range is detected in real time (such as 0.8V - 2.8V), and the original range is (1.2V - 2.4V). By comparing the two and adjusting the threshold through a linear function, the real value after voltage amplitude calculation can be directly reflected in this embodiment. For example, if the original adaptive threshold is 1.2V, after the new range is expanded, the adaptive threshold is adjusted to 2V. Analyze the energy in the sampling signal based on the regenerated adaptive threshold. Detect the signal amplitude range in real time (such as 0.8V - 2.8V), then the actual amplitude value is 2.8 - 0.8V = 2V, and this amplitude is the adaptive threshold. However, this adaptive threshold is on the high side. Due to possible interference, the adaptive threshold is reduced according to the actual situation, such as reducing it by a certain proportion, so that the adaptive threshold can exclude signal interference.

[0074] Then, according to the formula calculate the actual amplitude Sv. Compare through the actual amplitude Sv, that is, compare Sv with the adaptive threshold.

[0075] The second case is as Figure 6 shown. In an embodiment of the present application, the step of analyzing the energy in the sampling signal based on the adaptive threshold includes:

[0076] Step S320: Obtain the actual signal of the sampling signal amplitude in real time;

[0077] Step S321: Map the actual signal to a preset standard range, and analyze the energy in the sampling signal based on a fixed adaptive threshold. In this way, the adaptive threshold remains unchanged, reducing the calculation amount of the adaptive threshold. Amplify and reduce the collected data, map it to the preset standard range, and then compare it with the mapped value through the adaptive threshold to determine whether it is the first frequency signal or the second frequency signal. The mapping method refers to the first case. Compared with the first case, the calculation of the adaptive threshold is reduced.

[0078] For example, by measuring the threshold value between 0 - 3.3v of the signal amplitude multiple times, and then according to the maximum and minimum values sampled, map it to between 0 - 3.3v. For example, if the actual range sampled is 0.8 - 2.2v, map 0.8 - 2.2v to between 0 - 3.3v. Using the normalization method, Y = [(X - 0.8) / (2.2 - 0.8)] * (3.3 - 0). After such an operation, substitute it into x[n] for iterative operation, so that the adaptive threshold of 0 - 3.3v can be used for calculation, and only need to calculate up to Sp. The normalization method is more targeted and simple to apply.

[0079] As Figure 8As shown, the present application also provides a photovoltaic power generation system, which includes a switching tube that receives the logic signal output by the demodulation method as described above. The carrier communication signal is obtained through a signal acquisition circuit and a band-pass filter circuit. The photovoltaic power generation system further includes a microcontroller unit, which includes a sampling module that performs signal acquisition to obtain a sampling signal. A timer controls the sampling module to perform sampling. The energy of the sampling signal is calculated through a recursive algorithm to complete the adaptive threshold calculation, perform signal time-domain analysis, demodulate the logic signal, and determine whether it is a turn-on logic control or a turn-off logic control. Then, signal amplification control is performed, and the amplified logic signal is provided to the switching tube to control the switching tube. In this embodiment, the switching tube can be used to control the connection of the photovoltaic power generation system to the power grid.

[0080] Finally, 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 them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some or all of the technical features. These modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered by the scope of the claims and the description of the present invention.

Claims

1. A method for demodulating a carrier communication signal, characterized in that: The demodulation method comprises: Acquiring a carrier communication signal; Sampling the carrier communication signal according to a preset dynamic sampling frequency to obtain a sampling signal, wherein the sampling signal includes sampling data, and the sampling data includes a first frequency signal and a second frequency signal, and the frequencies of the first frequency signal and the second frequency signal are different; The energy in the sampled signal is analyzed according to an adaptive threshold, and a logic signal is demodulated according to the first frequency signal and the second frequency signal.

2. The demodulation method according to claim 1, characterized in that: Before the step of sampling the carrier communication signal according to the preset dynamic sampling frequency, it includes: A dynamic sampling frequency is set, where the dynamic sampling frequency is at least twice the maximum frequency of the first frequency signal and the second frequency signal.

3. The demodulation method according to claim 2, characterized in that: The first frequency signal and the second frequency signal are maintained at preset times respectively, and the sampling time of the dynamic sampling frequency is defined as T, and the preset time is T1, then: n*T≤T1, n is an odd number, and n≥3.

4. The demodulation method according to claim 3, characterized in that: The sampled data includes a silent period, the sampled signal includes a plurality of the sampled data, and the silent period is used to distinguish the sampled data; The step of demodulating a logic signal according to the first frequency signal and the second frequency signal comprises: When n is equal to 3, in the same sampling data: If the frequency signal maintained for two consecutive preset time periods is the first frequency signal, the demodulated logic signal is a value corresponding to the first frequency signal; If the frequency signal maintained for two consecutive preset time periods is the second frequency signal, the demodulated logic signal is a value corresponding to the second frequency signal.

5. The demodulation method according to claim 3, characterized in that: The steps to set a dynamic sampling frequency are as follows: A bit judgment interrupt frequency is set, and the bit judgment interrupt frequency is the reciprocal of the sampling time.

6. The demodulation method according to claim 1, characterized in that: Before the step of analyzing the energy in the sampled signal according to the adaptive threshold, the method includes: The energy of the sampled signal is calculated by a single frequency detection recursive algorithm.

7. The demodulation method according to claim 6, characterized in that: The energy calculation formula of the sampling signal satisfies: s[n]=x[n]+2cos(2πK)×s[n-1]-s[n-2] Sp=S[n-1] 2 +S[n] 2 -2cos(2πK)×S[n-1]-S[n] Wherein, x[n] represents the signal amplitude of the sampling signal, s[n-1] and s[n-2] are the energy output results of the first two samplings, K is the frequency index and is an integer, s[n] is the single frequency detection recursive intermediate variable, and Sp is the energy of the sampling signal.

8. The demodulation method according to any one of claims 1 to 7, characterized in that: The step of analyzing the energy in the sampled signal according to the adaptive threshold comprises: Acquire the maximum and minimum values ​​of the amplitude of the sampling signal in real time; According to the range mapping formed by the maximum value and the minimum value, the energy threshold value is adjusted to re-form the adaptive threshold value; The energy in the sampled signal is analyzed according to the regenerated adaptive threshold.

9. The demodulation method according to any one of claims 1 to 7, characterized in that: The step of analyzing the energy in the sampled signal according to the adaptive threshold comprises: Acquire the actual signal of the sampling signal amplitude in real time; The actual signal is mapped to a preset standard range, and the energy in the sampled signal is analyzed according to a fixed adaptive threshold.

10. A photovoltaic power generation system, characterized in that: The photovoltaic power generation system comprises a switch tube, and the switch tube receives a logic signal output by the demodulation method according to any one of claims 1 to 9.

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