A wind power generation system power accurate detection method based on DC offset estimation compensation

Abstract

A kind of wind power generation system power accurate detection method based on DC offset estimation compensation, comprising the following steps;Step one, grid voltage, current is carried out ADC sampling, obtains sample value;Step two, four successive sampling points are extracted in turn, and every four sampling points are grouped as a group;Step three, take a group of data, remove DC by difference, calculate the intermediate variable related to frequency, provide input for frequency estimation;Step four, the frequency is iteratively updated using the normalized gradient method, and the estimated value of the intermediate variable of the sample data and the frequency is obtained;Step five, estimate the DC offset, amplitude and phase;Step six, based on the estimated DC offset, amplitude and phase, calculate power, eliminate DC interference;Step seven, steps four to six are executed in a loop until the output is stable.The present application can still achieve high-precision measurement of power parameters under complex working conditions of grid voltage subjected to DC offset interference, and enhance the operation reliability of power system.

Description

Technical Field

[0001] This invention belongs to the field of electrical variable measurement technology, specifically relating to a method for accurate power detection of wind power generation systems based on DC offset estimation compensation. Background Technology

[0002] As wind power becomes a distributed power source, its increasing integration has led to a growing phenomenon of DC offset in grid voltage and current signals, making grid power measurement more complex and difficult. Power, as a crucial parameter reflecting power transmission efficiency and system operating status, is essential for accurate measurement in energy management, electricity billing, and system scheduling and control. Existing power detection methods are often designed based on ideal operating conditions, neglecting the impact of DC offset, which may introduce significant errors under complex operating conditions, affecting the accuracy of power detection. Therefore, there is an urgent need for a high-precision power detection method that can effectively suppress the influence of DC offset to meet the practical application requirements in complex grid environments.

[0003] Existing power detection methods typically employ bandpass filters to eliminate DC components or construct quadrature signals to decouple the signal in order to reduce the impact of DC offset. However, the application of filters usually introduces problems such as phase delay and amplitude attenuation, making it difficult to achieve timely and accurate tracking, especially when power changes rapidly or when high dynamic response is required. On the other hand, calculation methods based on quadrature signals are prone to introducing steady-state errors when the signal contains DC components, affecting the accuracy of active and reactive power calculations.

[0004] In summary, existing methods have the following shortcomings in scenarios involving DC offset:

[0005] First, when the frequency fluctuates or the load changes abruptly, the power calculation results are lagging or overshooting, resulting in poor dynamic tracking capability. Second, the coupling effect of DC offset with noise and harmonics leads to insufficient steady-state accuracy. Third, some methods have high algorithm complexity and are difficult to optimize parameters. Summary of the Invention

[0006] In order to overcome the shortcomings of the existing technology, the purpose of this invention is to provide a method for accurate power detection of wind power generation system based on DC offset estimation compensation. Under the complex operating conditions where the grid voltage is affected by DC offset interference, it can still achieve high-precision measurement of power parameters and enhance the operational reliability of the power system.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0008] A method for accurate power detection of a wind power generation system based on DC offset estimation compensation includes the following steps;

[0009] Step 1: Sample the grid voltage and current using an ADC to obtain the sampled values;

[0010] Step two: Group the samples into sets of four consecutive sampling points.

[0011] Step 3: Take any set of sampled values, eliminate DC through differential calculation, and calculate intermediate quantities related to frequency to provide input for frequency estimation;

[0012] Step 4: Construct a frequency estimator. Based on the intermediate value, iteratively update the frequency using the normalized gradient method to obtain the estimated values ​​of the intermediate variable and frequency of the sampled value.

[0013] Step 5: Based on the estimated values ​​of intermediate variables and frequency, estimate the DC offset, amplitude, and phase;

[0014] Step 6: Calculate the power based on the estimated DC offset, amplitude, and phase to eliminate DC interference;

[0015] Step 7: Repeat steps 4 through 6 until the output stabilizes.

[0016] In step two: Current: [I k,0 ,I k,1 ,I k,2 ,I k,3 Voltage: [U] k,0 U k,1 U k,2 U k,3 ];

[0017] Wherein, the subscripts (k,0), (k,1), (k,2), and (k,3) are the first, second, third, and fourth sampling points of the k-th group of sampled data, and k = 1, 2, 3...

[0018] In step three:

[0019] Using the basic formulas of trigonometric functions, calculate intermediate quantities in algebraic expressions and construct specific algebraic expressions between four consecutive samples;

[0020] The data in group k is:

[0021] [I k,0 ,I k,1 ,I k,2 ,I k,3 ],[U k,0 U k,1 U k,2 U k,3 ]

[0022] [I k,0 ,I k,1 ,I k,2 ,Ik,3 The expressions for ] are as follows:

[0023]

[0024] [U k,0 U k,1 U k,2 U k,3 The expressions for ] are as follows:

[0025]

[0026] Where I and U represent the amplitudes of the current and voltage signals, respectively, ω is the signal angular frequency, and f is the signal frequency. These are the current signals I. k,0 Voltage signal U k,0 The phase angle, T s f is the sampling time interval. s I is the sampling frequency. dc U dc These are the DC offsets contained in the current and voltage, respectively.

[0027] The DC offset is then explicitly eliminated using differential operations on four consecutive sampling points.

[0028] Calculate the intermediate quantities related to the current signal (the voltage signal processing method is the same as the current signal; simply replace I in steps three to five with U):

[0029] Step 3-1: Define intermediate variables for

[0030]

[0031] Step 3-2: Define intermediate variables for

[0032]

[0033] Step 3-3: According to Calculate intermediate variables Construct a specific algebraic expression between four consecutive samples

[0034]

[0035] Therefore, there is

[0036]

[0037] Therefore, there are intermediate variables. This allows us to directly obtain the frequency estimate by iterating through each set of sampled data.

[0038] Step four specifically involves:

[0039] A frequency estimator is constructed using the normalized gradient method to achieve adaptive frequency estimation;

[0040] Step 4-1: Calculate the normalization coefficient m(k) for the k-th data set.

[0041]

[0042] Intermediate variables obtained based on the kth group of sampled data;

[0043] Step 4-2: Calculate the estimation error e(k) for the k-th data set.

[0044]

[0045] This is an intermediate variable obtained based on the k-th group of sampled data; To obtain an estimate of the current intermediate variable γ when sampling the kth group of data, initial value The default value is 0;

[0046] Step 4-3: Calculate the estimated value of the intermediate variable γ when the (k+1)th set of data is obtained.

[0047]

[0048] To obtain an estimate of the current intermediate variable γ when sampling data for the (k+1)th group;

[0049] Step 4-4: Calculate the estimated frequency of the (k+1)th sampled data.

[0050]

[0051] Step five specifically involves:

[0052] The frequency estimate obtained from step four and intermediate variables Calculate the DC offset, amplitude, and phase;

[0053] Step 5-1: Calculate the estimated value of the DC offset contained in the current when obtaining the (k+1)th set of sampled data. (k+1):

[0054]

[0055] [I k+1,0 ,I k+1,1 ,I k+1,2 ,I k+1,3[ ] represents the (k+1)th data group;

[0056] Step 5-2: Calculate the estimated value of the orthogonal signal of the current when the (k+1)th set of sampled data is obtained.

[0057] Step 5-3: Calculate the estimated value of the current amplitude when the (k+1)th set of sampled data is obtained.

[0058]

[0059] Step 5-4: Calculate the estimated phase of the current when obtaining the (k+1)th set of sampled data.

[0060]

[0061] Step six specifically involves:

[0062] Based on steps three to five above, the amplitude and phase estimates of the current and voltage when obtaining the (k+1)th set of sampled data are obtained.

[0063] remember This is the phase difference between the voltage and the current at this time;

[0064] The active power is calculated as follows:

[0065]

[0066] The reactive power calculation method is as follows:

[0067]

[0068] Step seven specifically involves:

[0069] The frequency and DC offset parameters are updated using the latest data until the power estimation error is less than a certain threshold for several consecutive times. At this point, the estimated value is considered to be the true value.

[0070] The beneficial effects of this invention are:

[0071] (1) This invention proposes a power detection method for power grids with DC offset. By introducing information based on the estimated frequency, the amplitude, phase and DC offset of the signal can be effectively extracted, thereby subtracting the DC offset from the original signal and ensuring that the power is determined only by the fundamental AC component, thus improving the accuracy and stability of power detection.

[0072] (2) After obtaining the frequency, amplitude and phase estimation results, this method can restore the power parameters well by combining them with the conventional power calculation model. Even when the power grid frequency fluctuates or the load changes significantly, the designed adaptive method can maintain a relatively stable and reliable detection effect. Attached Figure Description

[0073] Figure 1 This is a flowchart of the power grid power estimation method implemented and provided by the present invention.

[0074] Figure 2 This is a flowchart illustrating the implementation of the power grid power estimation method provided by this invention. Detailed Implementation

[0075] The present invention will now be described in further detail with reference to the accompanying drawings.

[0076] like Figure 1 , Figure 2 As shown, a method for accurate power detection of a wind power generation system based on DC offset estimation compensation includes the following steps;

[0077] Step 1: Sample the grid voltage and current using an ADC to provide a data foundation for subsequent processing;

[0078] Step 2: Based on the sampled values ​​obtained in Step 1, extract four consecutive sample points in sequence, and group them into groups of four:

[0079] Current: [I] k,0 ,I k,1 ,I k,2 ,I k,3 Voltage: [U] k,0 U k,1 U k,2 U k,3 ],

[0080] Where the subscripts (k,0), (k,1), (k,2), and (k,3) represent the first, second, third, and fourth sampling points of the k-th group of sampled data. (k = 1, 2, 3...)

[0081] Step 3: Take any set of data, use the basic formulas of trigonometric functions to calculate the intermediate quantity of the algebraic expression, and construct a specific algebraic expression between four consecutive samples;

[0082] To simplify the expression, let's take the k-th data set as an example:

[0083] [I k,0 ,I k,1 ,I k,2 ,I k,3 ],[U k,0 Uk,1 U k,2 U k,3 ]

[0084] To illustrate the implementation process in detail, let ω be the angular frequency of the current and voltage. I ω U (The two are normally equal), with a frequency of f. I f U .

[0085] [I k,0 ,I k,1 ,I k,2 ,I k,3 The expressions for ] are as follows:

[0086]

[0087] ω I =2πf I

[0088] [U k,0 U k,1 U k,2 U k,3 The expressions for ] are as follows:

[0089]

[0090] Where I and U represent the amplitudes of the current and voltage signals, respectively. These are the current signals I. k,0 Voltage signal U k,0 The phase angle, T s f is the sampling time interval. s I is the sampling frequency. dc U dc These represent the DC offset in the current and voltage, respectively.

[0091] The DC offset is explicitly eliminated by differential operation of four consecutive sampling points.

[0092] The calculation of intermediate quantities related to the current signal is performed in the same way as the voltage signal:

[0093] Step 3-1: Define intermediate variables for

[0094]

[0095] Step 3-2: Define intermediate variables for

[0096]

[0097] The DC component is directly canceled by differential operation, while the trigonometric function relationship related to frequency ω is preserved, providing the necessary conditions for subsequent frequency estimation and parameter calculation.

[0098] Step 3-3: According to and Calculate intermediate variables Construct a specific algebraic expression between four consecutive samples

[0099]

[0100]

[0101] Therefore, there is

[0102]

[0103] Similarly,

[0104]

[0105] Therefore, there is an intermediate variable in the current. and voltage intermediate variables Therefore, by iterating through each set of sampled data, the estimated frequency value can be obtained directly. and

[0106] However, due to the presence of harmonics and DC offset interference in actual operating conditions, the estimated frequency may fluctuate and deviate from the true value.

[0107] Therefore, this invention utilizes the normalized gradient method to achieve adaptive estimation, making the observed γ I γ U Gradually approaching the true value.

[0108] Step 4: Construct a frequency estimator using the normalized gradient method to achieve adaptive frequency estimation.

[0109] Step 4-1: Calculate the normalization coefficient m of the k-th data set. I (k), m U (k)

[0110]

[0111] This is an intermediate variable obtained based on the kth group of sampled data.

[0112] Step 4-2: Calculate the estimation error e of the k-th data set. I (k), e U (k)

[0113]

[0114] This is an intermediate variable obtained based on the k-th group of sampled data; To obtain an estimate of the current intermediate variable γ when sampling the kth group of data, initial value The default value is 0.

[0115] Step 4-3: Calculate the estimated value of the intermediate variable γ when the (k+1)th set of data is obtained.

[0116]

[0117] To obtain the current intermediate variable γ when obtaining the (k+1)th group of sampled data I γ U The estimated value.

[0118] Step 4-4: Calculate the estimated frequency of the (k+1)th sampled data.

[0119]

[0120] Step 5: Estimate the DC offset, and then estimate the amplitude and phase by subtracting the DC component from the original signal;

[0121] The frequency estimate obtained from step four and intermediate variables The DC offset, amplitude, and phase are calculated.

[0122] Step 5-1: Calculate the estimated values ​​of the DC offset in the current and voltage for the (k+1)th set of sampled data.

[0123]

[0124] [I k+1,0 ,I k+1,1 ,I k+1,2 ,I k+1,3 ]、[U k+1,0 U k+1,1 U k+1,2 U k+1,3 [ ] represents the (k+1)th data group;

[0125] Step 5-2: Calculate the estimated values ​​of the orthogonal signals of current and voltage for the (k+1)th set of sampled data.

[0126]

[0127] Step 5-3: Calculate the estimated values ​​of current and voltage amplitudes for the (k+1)th set of sampled data.

[0128]

[0129] Step 5-4: Calculate the estimated phase values ​​of current and voltage for the (k+1)th set of sampled data.

[0130]

[0131] Step Six: Perform power calculations based on the obtained parameters.

[0132] Based on steps three to five above, the amplitude and phase estimates of the current and voltage when obtaining the (k+1)th set of sampled data are obtained.

[0133] remember This is the phase difference between voltage and current at this time.

[0134] The active power is calculated as follows:

[0135]

[0136] The reactive power calculation method is as follows:

[0137]

[0138] Step 7: Repeat steps 4 to 6, updating parameters such as frequency and DC offset with the latest data, until the power estimation error is less than a certain threshold for several consecutive times. Then, the estimated value at this time is considered to be the true value.

[0139] The above-described specific process is merely a practical application example of the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention, and should not be limited to the content involved in the present invention in the above example.

[0140] Application Examples:

[0141] Taking a grid-connected wind power generation simulation system as an example, the system operates under complex conditions where the power grid has ±2% DC offset and frequency fluctuation (49Hz-51Hz).

[0142] To verify the actual effectiveness of the method of this invention, it is compared with the traditional bandpass filter method and the orthogonal signal decoupling method. Traditional methods rely on whole-cycle data buffering (e.g., 200 points / cycle for 50Hz power frequency) and complex floating-point operations, resulting in a single power analysis taking up to 20ms and limited dynamic tracking capability. In contrast, this invention uses a four-sampling-point grouping strategy combined with linear combination of intermediate variables. Directly deriving the frequency and DC offset reduces the single calculation cycle to within 8ms, and memory usage is only 5% of that of traditional methods.

[0143] In scenarios involving sudden frequency changes (e.g., 50Hz → 49.5Hz), traditional bandpass filters require over 30ms to stabilize due to phase delay, resulting in an overshoot error of 0.15Hz. This invention, however, achieves adaptive frequency estimation via a normalized gradient method, completing tracking within 12ms with a steady-state error below 0.02Hz. For DC offset compensation, traditional orthogonal decoupling methods require iterative calculations and matrix operations, taking over 20ms and producing an amplitude error of 1.2%. This invention, however, directly estimates the offset using a three-step integer addition / subtraction method and a single division, reducing the compensation time to 5ms and improving the fundamental amplitude accuracy to 0.05%. Actual testing shows that this invention optimizes power detection error by an order of magnitude compared to traditional methods in scenarios involving DC offset and frequency fluctuations. Furthermore, by eliminating the need for an external high-precision filter, hardware costs are significantly reduced. This method is applicable to scenarios dominated by power frequency fluctuations and DC offset. If there is non-power frequency interference in the power grid, it needs to be combined with a pre-filter module to expand its applicability. However, it has the advantages of high real-time performance, low resource consumption and cost in new energy grid-connected systems, providing an innovative solution for accurate power detection in complex power grid environments.

Claims

1. A method for accurate power detection of a wind power generation system based on DC offset estimation compensation, characterized in that, Includes the following steps; Step 1: Sample the grid voltage and current using an ADC to obtain the sampled values; Step two: Group the samples into sets of four consecutive sampling points. Step 3: Take any set of sampled values, eliminate DC through differential calculation, and calculate the intermediate variables related to frequency to provide input for frequency estimation; Step 4: Based on the intermediate variables, the frequency is iteratively updated using the normalized gradient method to obtain the estimated values ​​of the intermediate variables and frequencies of the sampled values; Step 5: Based on the estimated values ​​of intermediate variables and frequency, estimate the DC offset, amplitude, and phase; Step 6: Calculate the power based on the estimated DC offset, amplitude, and phase to eliminate DC interference; Step 7: Repeat steps 4 through 6 until the output stabilizes; In step two: Current: ,Voltage: ; Where the subscripts (k,0), (k,1), (k,2), and (k,3) represent the first, second, third, and fourth sampling points of the k-th group of sampled data. DC offset is explicitly eliminated by differential operation of four consecutive sampling points; Calculate relevant intermediate quantities for the current signal; the voltage signal processing method is the same as that for the current signal. Step 3-1: Define intermediate variables for Step 3-2: Define intermediate variables for Step 3-3: According to Calculate intermediate variables Construct the algebraic expression between four consecutive samples. Therefore, there is Therefore, there are intermediate variables. This allows us to directly obtain the frequency estimate by iterating through each set of sampled data. ; Step four specifically involves: A frequency estimator is constructed using the normalized gradient method to achieve adaptive frequency estimation; Step 4-1: Calculate the first... Normalization coefficients of group data Based on the Intermediate variables obtained from group sampling data; Step 4-2: Calculate the first... estimation error of the set of data For the first Intermediate variables obtained from group sampling data; To obtain the first The current intermediate variable when sampling group data The estimated value, initial value The default value is 0; Step 4-3: Calculate the first... Intermediate variables when using grouped data The estimated value To obtain the first Current intermediate variable when sampling group data The estimated value; Step 4-4: Calculate the first... Estimated frequency when sampling data in groups ； Step five specifically involves: The frequency estimate obtained from step four and intermediate variables The DC offset, amplitude, and phase are calculated. Step 5-1: Calculate the first... Estimate of DC offset in current when sampling data. : For the first Group data; Step 5-2: Calculate the first... Estimate of the orthogonal signal of the current when sampling data in groups : Step 5-3: Calculate the first... Estimated value of current amplitude when sampling data. : Step 5-4: Calculate the first... Estimated phase of current when sampling data. : ； in, These represent the amplitudes of the current and voltage signals, respectively. The signal angular frequency, For signal frequency, Current signal voltage signal phase angle, The sampling time interval, Sampling frequency, , These are the DC offsets contained in the current and voltage, respectively.

2. The method for accurate power detection of a wind power generation system based on DC offset estimation compensation according to claim 1, characterized in that, In step three: No. The data set is as follows: , The expressions are as follows: The expressions are as follows: in, These represent the amplitudes of the current and voltage signals, respectively. The signal angular frequency, For signal frequency, Current signal voltage signal phase angle, The sampling time interval, Sampling frequency, , These are the DC offsets contained in the current and voltage, respectively.

3. The method for accurate power detection of a wind power generation system based on DC offset estimation compensation according to claim 1, characterized in that, Step six specifically involves: Based on steps three to five above, we obtain the... Current and voltage amplitude and phase estimation during group sampling data. , ; remember , which is the phase difference between the voltage and the current at this moment; The active power is calculated as follows: The reactive power calculation method is as follows: 。 4. The method for accurate power detection of a wind power generation system based on DC offset estimation compensation according to claim 3, characterized in that, Step seven specifically involves: The frequency and DC offset parameters are updated using the latest data until the power estimation error is less than a certain threshold for several consecutive times. At this point, the estimated value is considered to be the true value.

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