Novel control method for suppressing noise

Abstract

The invention discloses a novel control method for suppressing noise, which is used for suppressing system noise based on first-order extended PID (Proportion Integration Differentiation) control. By upgrading or replacing the original control link in the controlled system with the achievement of the invention, the interference of external noise to the to-be-controlled system can be resisted to a certain extent under reasonable control parameters. According to the specific implementation mode of the noise suppression controller, the controller is formed by connecting a proportional control link, an integral control link, a differential control link and a time delay link in parallel, most PID control applied to the current industrial field can be achieved through simple transformation, an original control structure does not need to be dismantled, and the cost is low. The realizability and the utilization value are high; and for periodic noise and random noise, the method has relatively strong anti-interference performance, and shows relatively strong adaptability and robustness for abnormal data conditions such as data loss and data asynchronization.

Description

Technical Field

[0001] This invention belongs to the field of power technology, and relates to noise suppression technology, and in particular to a novel control method for suppressing noise. Background Technology

[0002] With the power system exhibiting increasingly prominent characteristics of high proportions of new energy and high proportions of power electronics, improving the stability of the power system has become a top priority. Among these challenges, noise suppression is a common problem in the control field. Noise can be introduced into the power system from various control aspects, such as signal introduction, system operation, and even inappropriate control elements, thus affecting its normal and stable operation.

[0003] Currently, PID control technology is still used in approximately 95% of industrial control loops. In many components of power systems, such as grid-connected inverters, PI control is still widely used to form dual closed-loop control. However, PI control has drawbacks such as steady-state error, weak anti-interference capability, and slow response speed, and its noise suppression capability is relatively limited. Furthermore, the derivative control (D control), another control element in PID control technology, may even amplify electronic component noise, thus it is not considered for noise control. Therefore, traditional PID control does not perform satisfactorily in noise suppression. In recent years, mainstream research has gradually shifted towards adopting other types of control strategies to reduce noise, but their universality and cost are often criticized.

[0004] In 2023, the extended PID control algorithm was proposed, which improved the structure of the PID controller and enhanced the control potential of PID-type controllers. Researching the effect of extended PID control on improving damping in power systems has significant engineering value. Based on this, it is believed that the potential of PID control in noise suppression has been greatly underestimated. With proper setting of control parameters and matching of control loops, it is possible to significantly improve the noise suppression capability of PID control, and even potentially eliminate the negative effects of D control.

[0005] In summary, this invention proposes a novel control algorithm that can suppress noise, which has significant engineering value for improving controller structure, enhancing control potential, and improving system robustness and accuracy.

[0006] Purpose of the invention

[0007] To address the shortcomings of existing technologies, this invention proposes a control method that can be used to suppress oscillations. It can be implemented through simple modifications for most PID controls currently used in the industrial field without dismantling the original control structure, thus exhibiting high feasibility and utilization value. It also demonstrates strong anti-interference capabilities against periodic and random noise, and strong adaptability and robustness to abnormal data conditions such as data loss and data asynchrony. Summary of the Invention

[0008] According to a first aspect of this application, a novel control algorithm for oscillation noise is provided, which may include the following steps:

[0009] Step 1: Write out the standardized format for PID control;

[0010] The continuous and discrete expressions for PID control are as follows:

[0011]

[0012] Where: proportional gain k p Integral gain k i Integration time constant t i Differential gain k d Differential time constant t d Here are the PID control parameters; T0 is the sampling period; u(t), y(t), e(t), and t are continuous control signals, output signals, error signals, and variables, respectively; u(k), y(k), e(k), and k are discrete control signals, output signals, error signals, and variables, respectively. When k... d When the value is 0, Equation (1) means PI control.

[0013] Step 2: Introduce the k-3 historical time signal to obtain the initial-order extended PID control;

[0014] When a PID controller generates a control signal at time k, it needs to use historical signals from times k, k-1, and k-2. Based on this, the historical signal from time k-3 is introduced, resulting in a basic type of primary extended PID control. To maintain consistency with PI control, primary extended PID control can be written as:

[0015]

[0016] In the formula, the real number k5 is the proportionality coefficient of the k-3 term. By determining different coefficients for the error signals at different historical moments, noise can be suppressed. The coefficient determination method aims to minimize the noise level of the observed signal and uses an adaptive method for iterative optimization.

[0017] According to a second aspect of this application, a novel controller implementation method for oscillating noise is provided, which may include the following steps:

[0018] Step 1: The general structure of a conventional PID control system in a conventional power system;

[0019] Taking continuous expression as an example, in a general PID controller of a power system, the input signal of the controller, namely the error signal e(t), is the difference between the given value y* and the actual value y(t) of the system output signal. The PID controller is composed of a proportional control element, an integral control element, and a derivative control element connected in parallel. After the error signal passes through the PID controller, it becomes the controller control signal u(t), which is input into the controlled system to obtain the output signal y(t).

[0020] Step 2: Determine the implementation form of the initial-order extended PID control;

[0021] Compared with conventional PID control, the initial-order PID control of this invention for noise suppression adds a k-3 historical time signal. Therefore, only a time delay element needs to be connected in parallel with the PID control element. The time delay is usually the sampling period T0. Attached Figure Description

[0022] Figure 1 The block diagram of a primary PID controller for noise suppression.

[0023] Figure 2 This describes the topology of a photovoltaic grid-connected system and its inverter control structure.

[0024] Figure 3 This describes the control effect under data noise conditions.

[0025] Figure 4 This describes the control effect in the event of data loss.

[0026] Figure 5 To assess the control effect under asynchronous conditions. Detailed Implementation

[0027] The embodiments will now be described in detail with reference to the accompanying drawings.

[0028] Figure 1 The diagram shows the principle block diagram of the initial-order extended PID control based on equation (2), which can be used to suppress noise.

[0029] A photovoltaic power generation system mainly consists of a photovoltaic array and a grid-connected inverter, and its typical topology is as follows: Figure 2 As shown, the direct current generated by the photovoltaic array is converted into alternating current by a grid-connected inverter and then fed into the power grid. Figure 2 In the middle, C dc For photovoltaic output voltage regulator capacitors, L and C f For the filter inductor and capacitor, u PV and i PV The output voltage and current of the photovoltaic system are i0 and u are u, respectively. k i1 represents the inverter output voltage and current, u c and i gFor grid-connected voltage and current. In grid-connected inverter control, the photovoltaic output voltage reference value u is obtained through maximum power point tracking (MPPT) technology. PVref The inverter voltage outer loop control controls the DC voltage, while the current inner loop controls the active and reactive current components of the inverter, ultimately resulting in a three-phase modulation signal that is applied to the inverter.

[0030] In a photovoltaic grid-connected inverter, the transfer function of the voltage outer loop control is H. v (s), the d-axis of the inner current loop is H id (s), the q-axis of the inner current loop is H iq (s). In conventional photovoltaic grid-connected systems, the voltage outer loop control, the current inner loop d-axis, and the current inner loop q-axis all employ ordinary PI control. To demonstrate the function of this invention, the photovoltaic outer loop control H... v (s) It still uses the common PI control, while the d-axis and q-axis of the inner current loop are both adopted. Figure 1 The initial extended PID control shown only requires connecting a derivative element and a time delay element in parallel with the original PI control element.

[0031] Table 1 Control parameters in photovoltaic inverters

[0032] <![CDATA[k1]]> <![CDATA[t1 / s]]> <![CDATA[k2]]> <![CDATA[t2 / s]]> <![CDATA[k3]]> <![CDATA[t3 / s]]> <![CDATA[k d2 ]]> <![CDATA[k a2 ]]> <![CDATA[k d3 ]]> <![CDATA[k a3 ]]> 10 <![CDATA[1×10 -6 ]]> 1 0.05 0.001 1 <![CDATA[6.0312×10 -6 ]]> 3.1379 0.0823 0.1095

[0033] In the example, the solar radiation intensity is 1000 W / m 2 Under the reference condition of 25 ℃ for photovoltaic cells, the maximum output power of the photovoltaic array is 0.1 MW, and the voltage and current at the maximum power point are 630 V and 158 A, respectively. The photovoltaic power station is connected to the 380 V grid via a transformer; the photovoltaic output voltage stabilizing capacitor C... dc The filter current is 25 mF, the filter inductance L is 0.1061 mH, and the filter capacitor C is... f The value is 1 mF; the simulation interval is 20 ms. The control parameters for the photovoltaic inverter can be found in Table 1. Where k... i For the proportional gain of each control element, t i k represents the integral time of each control element. di k represents the differential gain of each control element. ai Let i = 1, 2, 3, where i = 1 represents the parameters of the outer loop control loop for photovoltaic voltage, i = 2 represents the parameters of the inner loop d-axis control loop for photovoltaic current, and i = 3 represents the parameters of the inner loop q-axis control loop for photovoltaic current.

[0034] Depend on Figure 2 It can be seen that the initial sampling data input to the photovoltaic inverter control circuit is the photovoltaic output voltage u. PV Its outer loop control also has a certain impact on the subsequent inner loop control. Therefore, taking the photovoltaic output voltage u as an example...PV Taking an abnormal signal sampling situation as an example, this paper discusses the noise resistance capability of the present invention and its adaptability to abnormal sampling data.

[0035] (1) Noise interference during data measurement or transmission can negatively impact the controller. Generally, this is because the derivative term may amplify the measurement noise.

[36] In the electromagnetic transient process of power system and the control of power electronic converter, PI control is usually used instead of PID control.

[0036] To explore whether extended PID control can maintain a certain level of anti-interference capability against noise, similar to PI control, this section discusses two cases: periodic noise and random noise.

[0037] Periodic noise is taken as:

[0038]

[0039] The upper limit of the random noise amplitude is taken as approximately 20% of the photovoltaic output voltage reference value of 0.63 kV:

[0040]

[0041] like Figure 3 As shown, when the measurement signal u PV In the presence of noise interference, whether it is periodic noise or random noise, despite the addition of a derivative element, the control effect of this invention is still better than the original PI control, and it has a certain degree of anti-interference against different noises.

[0042] (2) When there are problems with the network transmission mechanism or when sensors or actuators malfunction, there is a probability that sampling data will be lost. Figure 2 Based on the example, set u PV The sampled data may be lost with varying probabilities. When data is lost, the sampled data at that time is set to 0.

[0043] Figure 4 The data loss scenarios with a 5% and 10% probability were demonstrated. Under different data loss probabilities, this invention stabilized the system faster than PI control, and the output power ripple was relatively smaller. It also exhibited a certain degree of adaptability to data loss, thus ensuring the power quality of photovoltaic power generation to some extent.

[0044] (3) Due to data transmission, data acquisition, network anomalies, etc., there may be a certain time delay between the input controller signal and the actual signal. Figure 2 Based on the example, consider u PV The signal is input to the photovoltaic inverter after different time delays.

[0045] Figure 5 The scenarios with 10 ms and 40 ms delays were considered. With only a 10 ms delay, both the present invention and the original PI control provided effective control of the system, but the control speed was slower than in the previous no-delay scenario. With a 40 ms delay, the PI control could no longer control the system, and the photovoltaic output power began to exhibit significant oscillations, leading to system instability. The present invention, however, still effectively accelerated the convergence of system oscillations. In both the 10 ms and 40 ms delay scenarios, the present invention demonstrated better control performance and stronger damping capability than PI control.

[0046] This invention demonstrates strong resistance to noise interference, excellent adaptability, and a strong ability to handle various data anomalies. It exhibits a very strong control effect in enhancing system damping and improving noise interference resistance, thus possessing significant potential engineering value for upgrading existing PID control systems in industry.

[0047] The method of the present invention is applicable not only to the photovoltaic grid-connected system in the embodiments, but also to any physical system that can use a controller, including but not limited to electrical, petrochemical, manufacturing, metallurgical and other fields.

[0048] The method of the present invention is applicable not only to the periodic noise and the random noise in the embodiments, but also to noise interference problems of other forms.

[0049] Those skilled in the art should understand that the embodiments of the present invention are merely illustrative of preferred implementations, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A novel noise suppression control method, characterized in that: The method includes the following steps: Step 1: Determine the location of the controller component that needs improvement (i.e., the specific application location of this invention); Step 2: According to the project requirements, list the extended PID, primary extended PID, or PID control algorithms used in this invention and determine the control parameters to be determined; Step 3: Apply the novel noise suppression controller obtained in Step 2 to the specific implementation location determined in Step 1; the control parameter determination method aims to minimize the noise level of the observed signal and uses an adaptive method for iterative optimization to achieve noise suppression.

2. The method according to claim 1, characterized in that: The location of the controller component that needs improvement may or may not have a control unit in place.

3. The method according to claim 2, characterized in that: The controller component that needs improvement may already have a control unit, which could be a PID controller or another type of controller.

4. The method according to claim 1, characterized in that: The primary extended PID control algorithm used in this invention is as follows:

5. Where: proportional gain k p Integral gain k i Integration time constant t i Differential gain k d Differential time constant t d For PID control parameters, the real number k5 is the proportional coefficient of the k-3 term; T0 is the sampling period; u(t), y(t), e(t), t are continuous control signals, output signals, error signals, and variables, and u(k), y(k), e(k), k are discrete control signals, output signals, error signals, and variables.

6. The method according to claim 4, characterized in that: The primary extended PID control algorithm used in this invention requires the determination of control parameters including the proportional gain k. p Integral gain k i Integration time constant t i Differential gain k d Differential time constant t d , real number k5.

7. The method according to claim 5, characterized in that: Control parameters can be set in certain ways, including theoretical calculation methods, engineering experience methods, adaptive iterative methods, parameter optimization methods, and artificial intelligence methods.

8. The method according to claims 5 and 6, characterized in that: The purpose of determining the control parameters is to suppress noise by setting different coefficients for the error signals at different historical times.

9. The method according to claim 1, characterized in that: The novel noise suppression controller obtained in step 2 is applied to the specific implementation location determined in step 1. A noise suppression controller is set up in the control loop of the specific implementation, which is composed of a proportional control loop, an integral control loop, a derivative control loop, and a time delay loop connected in parallel.

10. The method according to claims 1 and 8, characterized in that: The input signal of the controller, namely the error signal e(t), is the difference between the given value y* and the actual value y(t) of the system output signal. The error signal is processed by the noise suppression controller described in claim 8 to obtain the controller control signal u(t), which is then input into the controlled system to obtain the output signal y(t).

11. The method according to claim 7, characterized in that: When there is an existing control loop in the specific implementation location, and the existing control loop is a PI control, it is only necessary to connect a derivative element and a time delay element in parallel with the existing control loop; when the existing control loop is a PID control, it is only necessary to connect a time delay element in parallel with the existing control loop; there is no need to remove the existing control structure.

12. The method according to claim 8, characterized in that: The time delay of the time delay element can be taken as the sampling period of the controller.

13. The method according to claim 1, characterized in that: This novel noise-suppressing controller is applicable not only to the photovoltaic grid-connected system in the embodiment, but also to any physical system that can use a controller, including but not limited to electrical, petrochemical, manufacturing, and metallurgical fields.

14. The method according to claim 1, characterized in that: This novel noise suppression controller is applicable not only to the periodic noise and random noise in the embodiments, but also to other forms of noise interference problems.

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