Power grid parameter adaptive detection method suitable for voltage distortion working condition of wind power generation system

Abstract

The invention discloses a power grid parameter self-adaptive detection method suitable for a voltage distortion working condition of a wind power generation system. The method comprises the steps of 1, initializing a voltage estimation value according to priori knowledge of power grid voltage; step 2, sampling through a sensor to obtain a power grid voltage containing harmonic waves and direct current components; 3, calculating an estimation error according to the power grid voltage sampling value; 4, designing a self-adaptive observer, and estimating an intermediate variable; 5, updating the voltage estimation value according to the intermediate variable obtained in the step 4; step 6, estimating the power grid voltage of the harmonic component and the direct current component of the voltage by using the intermediate variable obtained in the step 4; and step 7, repeating the step 2 to the step 6, continuously updating the parameter estimation value, and obtaining the real-time parameter of the power grid voltage. According to the invention, when the voltage of the power grid is distorted, the voltage parameter can still be accurately detected, the harmonic and direct current components are separated and extracted under the condition of no steady-state error, and the safe and stable operation of a power system is ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of measuring electrical variables, and in particular relates to a grid parameter adaptive detection method suitable for voltage distortion working conditions of a wind power generation system. Background Art

[0002] Wind power, as a distributed power source, is inherently uncertain. This characteristic leads to a continuous increase in harmonics and DC components in the power grid, causing voltage distortion and making grid voltage detection more difficult. As an important parameter in the power grid, accurate voltage parameters play a key role in the integration of new energy sources and the safe and stable operation of the power grid.

[0003] Existing voltage detection methods are typically based on ideal operating conditions. However, in wind power grids, which are subject to significant harmonics and DC components, voltage distortion is severe. Existing technologies struggle to accurately and quickly detect voltage parameters, often resulting in time domain delays or steady-state errors, ultimately impacting the safety and stability of grid operations. Therefore, a high-precision voltage parameter detection method that can effectively suppress the effects of harmonics and DC offset is urgently needed to meet the practical application needs of complex grid environments.

[0004] In summary, existing grid voltage detection technology has significant shortcomings. In complex power grids containing a large number of harmonics and DC components, voltage distortion is severe. Under such conditions, existing voltage parameter detection technologies have large errors, and cannot accurately obtain voltage parameters, ultimately posing a hidden danger to the safe and stable operation of the power grid. Summary of the Invention

[0005] In order to overcome the deficiencies of the above-mentioned prior art, the purpose of the present invention is to provide a grid parameter adaptive detection method suitable for voltage distortion conditions of wind power generation systems. Even under complex conditions where the grid voltage is distorted, that is, there are a large number of harmonics and DC component interferences in the grid, the voltage parameters can still be accurately detected, and the harmonics and DC components can be separated and extracted without steady-state errors, thereby ensuring the safe and stable operation of the power system.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is:

[0007] A grid parameter adaptive detection method applicable to a voltage distortion working condition of a wind power generation system comprises the following steps;

[0008] Step 1: Initialize the voltage estimate based on the prior knowledge of the grid voltage;

[0009] Step 2: obtaining the grid voltage including harmonics and DC components through sensor sampling;

[0010] Step 3: Calculate the estimated error based on the grid voltage sampling value obtained in step 2;

[0011] Step 4: Design an adaptive observer to estimate the intermediate variables of voltage parameters;

[0012] Step 5: updating the voltage estimate according to the intermediate variable obtained in step 4;

[0013] Step 6: Estimate the harmonic components and DC components of the grid voltage using the intermediate variables obtained in step 4 above;

[0014] Step 7: Repeat steps 2 to 6, continuously update the parameter estimation values, and obtain the real-time parameters of the grid voltage.

[0015] The prior knowledge of the grid voltage in step 1 refers to the nominal value of the grid voltage. Usually, the estimated voltage can be initialized to the nominal voltage value.

[0016] In the step 1, after the estimated value is generally initialized to the nominal voltage value, the voltage estimated value is converged to the actual value through a closed-loop algorithm. If the relevant prior knowledge is completely unknown, it is initialized to zero and then converged by relying on the closed-loop algorithm.

[0017] In the step 2, voltage signals are sampled according to voltage sensors set at key nodes of the power grid; key nodes of the power grid include access points of wind power generation systems, power grid buses, and areas near major loads.

[0018] In step 3, the formula for calculating the estimation error is:

[0019]

[0020] in: is the voltage estimation value, and v is the voltage sampling value.

[0021] In the fourth step, the adaptive algorithm theory is used to construct an adaptive observer equation based on the grid voltage distortion model and the estimation error, so that it can estimate Intermediate variables such as , thus providing a guarantee for accurate estimation of grid voltage;

[0022] Among them, the intermediate variable They represent the sine component and cosine component of the i-th harmonic of the grid voltage, Represents the DC component of the voltage. The subscripts 0 and i refer to the DC component and the i-th harmonic component, respectively.

[0023] The intermediate variables used to estimate The adaptive observer equation is:

[0024]

[0025] Where: γ αi ,γ βi ,γ0>0 and is the adjustable gain coefficient of the adaptive observer, ω is the angular frequency of the power grid, a i is an odd positive integer, t represents time, is an intermediate variable The differentials of , and the intermediate variables are obtained by integrating them

[0026] In step 5, the formula for updating the voltage estimate is:

[0027]

[0028] Where: ω is the angular frequency of the power grid, a i is an odd positive integer, and t represents time.

[0029] The subscript n refers to the nth harmonic.

[0030] The specific formula for calculating the voltage harmonic components and DC components in step 6 is:

[0031]

[0032] in: is the estimated amplitude of the i-th harmonic, when i=1 it is the fundamental amplitude, is an estimate of the DC component.

[0033] Step 7: During the operation of the power grid, the voltage parameters always change in real time. When the power grid is in operation, the method will also run synchronously to continuously calculate the real-time values of the voltage parameters.

[0034] Beneficial effects of the present invention:

[0035] This paper proposes an adaptive grid parameter detection method suitable for voltage distortion conditions in wind power generation systems. Compared to traditional methods, this method, based on adaptive algorithm theory, designs an adaptive observer for grid voltage parameters. This method uses the error between sampled and estimated voltage values to adjust voltage parameters in real time, enabling the observer to accurately estimate harmonics and DC components in the grid voltage. This method accurately estimates voltage parameters even in complex conditions with grid voltage distortion, particularly those with a large number of harmonics and DC components. It also extracts information about the fundamental wave, subharmonics, and DC signals without steady-state error, further ensuring safe and stable grid operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a flow chart of the voltage parameter estimation method implemented and provided by the present invention.

[0037] Figure 2This is a flow chart of the method for estimating power grid parameters implemented and provided by the present invention.

[0038] Figure 3 It is a structural block diagram of the method for estimating power grid parameters implemented and provided by the present invention.

[0039] Figure 4 It is a diagram of experimental results of the method for estimating power grid parameters implemented and provided by the present invention. Figure 4 (a) Grid voltage; Figure 4 (b) Estimated voltage amplitude; Figure 4 (c) the estimated fundamental voltage and its quadrature components; Figure 4 (d) Estimated fifth harmonic component; Figure 4 (e) Estimated seventh harmonic component. DETAILED DESCRIPTION

[0040] The present invention will be described in further detail below with reference to the accompanying drawings.

[0041] like Figure 1 、 Figure 2 As shown, the grid parameter adaptive detection method applicable to the voltage distortion working condition of the wind power generation system includes the following steps:

[0042] Step 1: Initialize the voltage estimate based on the prior knowledge of the grid voltage Used for initial estimation error calculation;

[0043] Step 2: The grid voltage v containing harmonics and DC components is obtained through sensor sampling and used to calculate the estimation error.

[0044] Step 3: Based on the grid voltage sampling value obtained in step 2, calculate the estimated error ε as the input of the adaptive observer. The specific formula is:

[0045]

[0046] in: is the voltage estimation value, and v is the voltage sampling value.

[0047] Step 4: Design an adaptive observer to estimate intermediate variables The final grid voltage parameters can be calculated from the intermediate variables;

[0048]

[0049] Where: γ αi ,γ βi ,γ0>0 and is the parameter introduced in this method, ω is the angular frequency of the power grid, a i is an odd positive integer, t represents time, is an intermediate variable The differentials of , and the intermediate variables can be obtained by integrating them

[0050] Step 5: Based on the intermediate variables obtained in step 4 Update voltage estimate At the same time prepare for the next cycle.

[0051]

[0052] Where: ω is the angular frequency of the power grid, a i is an odd positive integer, and t represents time.

[0053] Step 6: Use the intermediate variables obtained in step 4 to obtain the harmonic components and DC components of the voltage. The specific formula for calculating the voltage harmonic components and DC components is:

[0054]

[0055] in: is the estimated amplitude of the i-th harmonic, when i=1 it is the fundamental amplitude, is an estimate of the DC component.

[0056] Step 7: Repeat steps 2 to 6, perform cyclic optimization, and continuously update parameter estimation values to make the voltage estimation value converge quickly and obtain the real-time parameters of the grid voltage.

[0057] Attachment Figure 3 The structural diagram of the present invention is given. The voltage v is sampled by the voltage sensor, and then an adaptive observer is constructed to estimate the intermediate variable The voltage estimate, harmonics, and DC components are obtained from the intermediate variables according to the formulas in steps 5 and 6. The voltage estimate is subtracted from the sampled voltage to obtain an error value, which is used as feedback to construct an adaptive observer. The structure is a closed-loop structure with cyclic optimization, so that the estimated value converges quickly to the actual value. Figure 4 The experimental effect diagram of the present invention is given. Figure a shows that the fifth and seventh harmonic components are superimposed on the standard sinusoidal voltage, and the voltage amplitude is reduced to 60% of the original. Figure b shows the voltage amplitude estimated by the present invention. For comparison, the estimation result of the classical method based on the second-order generalized integrator phase-locked loop (SOGI-PLL) is given. It can be found that the method provided by the present invention converges faster and has higher accuracy. Figures b, c, and d respectively show the estimated fundamental voltage and its orthogonal component, the estimated fifth harmonic component, and the estimated seventh harmonic component. The experimental results prove that the method proposed by the present invention has better accuracy and can estimate harmonic components.

[0058] The above specific process is only a practical application routine of the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention and should not be limited to the contents of the present invention in the above routine.

Claims

1. A grid parameter adaptive detection method suitable for voltage distortion conditions of wind power generation systems, characterized in that: The following steps are included: Step 1: Initialize the voltage estimate based on the prior knowledge of the grid voltage; Step 2: obtaining the grid voltage including harmonics and DC components through sensor sampling; Step 3: Calculate the estimated error based on the grid voltage sampling value obtained in step 2; Step 4: Design an adaptive observer to estimate the intermediate variables of voltage parameters; Step 5: updating the voltage estimate according to the intermediate variable obtained in step 4; Step 6: Estimate the grid voltage including harmonic components and DC components using the intermediate variables obtained in step 4 above; Step 7: Repeat steps 2 to 6, continuously update the parameter estimation values, and obtain the real-time parameters of the grid voltage.

2. The grid parameter adaptive detection method applicable to voltage distortion conditions of a wind power generation system according to claim 1, characterized in that: The prior knowledge of the grid voltage in step 1 refers to the nominal value of the grid voltage.

3. The grid parameter adaptive detection method applicable to voltage distortion conditions of a wind power generation system according to claim 1, characterized in that: In the step 1, after initializing the estimated value to the nominal voltage value, the voltage estimated value is converged to the actual value through a closed-loop algorithm. If the relevant prior knowledge is completely unknown, it is initialized to zero and then converged by relying on the closed-loop algorithm.

4. The grid parameter adaptive detection method applicable to voltage distortion conditions of a wind power generation system according to claim 1, characterized in that: In the step 2, voltage signals are sampled according to voltage sensors set at key nodes of the power grid; key nodes of the power grid include access points of wind power generation systems, power grid buses, and areas near major loads.

5. The grid parameter adaptive detection method applicable to voltage distortion conditions of a wind power generation system according to claim 1, characterized in that: In step 3, the formula for calculating the estimation error is: in: is the voltage estimation value, and v is the voltage sampling value.

6. The grid parameter adaptive detection method applicable to voltage distortion conditions of a wind power generation system according to claim 1, characterized in that: In the fourth step, the adaptive algorithm theory is used to construct an adaptive observer equation based on the grid voltage distortion model and the estimation error, so that it can estimate Intermediate variables such as They represent the sine component and cosine component of the i-th harmonic of the grid voltage, Represents the DC component of the voltage. The subscripts 0 and i refer to the DC component and the i-th harmonic component, respectively.

7. The grid parameter adaptive detection method applicable to voltage distortion conditions of a wind power generation system according to claim 6, characterized in that: The intermediate variables used to estimate The adaptive observer equation is: Where: γ αi ,γ βi ,γ0>0 and is the adjustable gain coefficient of the adaptive observer, ω is the angular frequency of the power grid, a i is an odd positive integer, t represents time, is an intermediate variable The differentials of , and the intermediate variables are obtained by integrating them γ αi ,γ βi ,γ0 is the adjustable gain coefficient of the adaptive observer.

8. The grid parameter adaptive detection method applicable to voltage distortion conditions of a wind power generation system according to claim 1, characterized in that: In step 5, the formula for updating the voltage estimate is: Where: ω is the angular frequency of the power grid, a i is an odd positive integer, t represents time; the subscript n refers to the nth harmonic.

9. The grid parameter adaptive detection method applicable to voltage distortion conditions of a wind power generation system according to claim 1, characterized in that: The specific formula for calculating the voltage harmonic components and DC components in step 6 is: in: is the estimated amplitude of the i-th harmonic, when i=1 it is the fundamental amplitude, is an estimate of the DC component.

10. The grid parameter adaptive detection method applicable to voltage distortion conditions of a wind power generation system according to claim 1, characterized in that: Step 7: During the operation of the power grid, the voltage parameters always change in real time. When the power grid is in operation, the method will also run synchronously to continuously calculate the real-time values of the voltage parameters.

Images