Dynamic voltage restorer optimization compensation method based on grasshopper optimization algorithm

Abstract

The invention discloses a grasshopper optimization algorithm-based dynamic voltage restorer optimization compensation method, and the method comprises the steps: inputting a dynamic voltage restorer into a power grid when the voltage of a power grid side drops, employing an optimization PI controller constructed based on a grasshopper optimization algorithm, and outputting an instruction compensation voltage according to the detected actual load voltage and compensation voltage, and then the output compensation instruction is converted into a PWM wave through a PWM module, and a voltage source inverter is driven to output a corresponding voltage. By using the optimized PI controller, when the DVR is connected between the voltage source and the load through the injection transformer, the load voltage in the power distribution system can be effectively improved, meanwhile, high voltage is injected into the DVR in a short time, and the method plays a crucial role in avoiding sudden voltage drop.

Description

Technical Field

[0001] The invention relates to the technical field of power systems, and in particular to an optimization compensation method for a dynamic voltage restorer based on a grasshopper optimization algorithm. Background Art

[0002] With the increase of sustainable energy and its integration with the distribution network, power quality problems such as voltage sag and voltage expansion in the power grid have become increasingly prominent. Since power quality problems have caused huge economic losses to sensitive industrial loads, sensitive industrial customers require higher power quality, causing users and power companies to pay more attention to power quality issues. The distribution system is the weakest link in the power system, and these power quality problems have a greater impact on the distribution system. The most important and frequently occurring power quality problem in the distribution system is voltage sag. Voltage sag refers to the drop of the root mean square value of the supply voltage at the base frequency to between 10% and 90% of the rated voltage within half a cycle to one minute. Voltage sag is usually caused by short-circuit faults in the system, starting of large motors, switching operations of large-capacity electrical equipment such as transformers and capacitor banks, etc. Among them, short-circuit faults are the main cause. Dynamic Voltage Restorer (DVR) is considered to be the most effective way to reduce power quality problems. UPQC, DSTATCOM, SVC, UPS, SMEs, etc. have the same purpose as DVR, but have the disadvantages of large size, high cost and difficult maintenance compared with DVR. Therefore, DVR has become an ideal choice for mitigating voltage changes in secondary distribution systems with its advantages of small size, simplicity, effectiveness and low price. Dynamic voltage restorer is a device connected between the voltage source and the load side. It uses an injection transformer to input voltage to the distribution side to remedy problems that have a significant impact on the load voltage. The control method selected for its voltage source inverter (VSI) largely determines the performance of DVR. Therefore, a reliable and efficient control system is needed that can operate with high accuracy and stability under dynamic conditions.

[0003] At present, the control strategies used in the field of dynamic voltage restorers are mainly divided into linear and nonlinear. Linear control strategies include PI control, PR control, etc. Nonlinear control strategies include fuzzy control, emotional intelligence control (BrainEmotional Learning, BEL) and other intelligent algorithm control strategies. Domestic and foreign researchers have done a lot of research on the control strategies used in DVR devices. Although they have achieved certain results, they have not been able to effectively balance the stability, complexity, dynamic response speed and compensation ability of harmonic voltages of the system. Summary of the invention

[0004] The purpose of the present invention is to overcome the deficiencies of the prior art and provide an optimization compensation method for a dynamic voltage restorer based on a grasshopper optimization algorithm. By optimizing the PI controller using the grasshopper optimization algorithm, it is ensured that the controller has better stability when performing voltage compensation.

[0005] To achieve the above-mentioned purpose, the technical solution adopted by the present invention is: an optimization compensation method for a dynamic voltage restorer based on a grasshopper optimization algorithm. When the voltage on the grid side drops, the dynamic voltage restorer is put into the grid, and an optimized PI controller constructed based on the grasshopper optimization algorithm is used to output a compensation voltage command according to the detected actual load voltage and the compensation voltage. The output compensation command is then converted into a PWM wave through a PWM module to drive the voltage source inverter to output the corresponding voltage.

[0006] As a specific implementation, the construction of the optimized PI controller includes the following contents:

[0007] 1) Initialize PI controller parameters Kp, Ki, Kd:

[0008]

[0009] Where: e t,dq0 Represents the error signal between the reference voltage and the load voltage in the dq0 coordinate; V c,dq0 It represents the input signal of DVR PWM to PI controller in dq0 coordinate system. Kp and Ki represent the proportional coefficient and integral coefficient of PI controller respectively, and Kd represents the derivative coefficient.

[0010] 2) Initialize the number of iterations and constant parameters:

[0011] The constant parameters include: f is the attraction strength between locusts; l is the attraction range between locusts; d ij (t) is the distance between the i-th and j-th grasshoppers at the t-th iteration; C is the linear reduction parameter;

[0012] 3) Calculate the fitness value of each initial value and save the locust position with the best fitness value;

[0013] The fitness function ITAE expression is defined as follows:

[0014]

[0015] Therefore, the objective function of the optimization problem is:

[0016] min(J)=min(ITAE),

[0017] Where J is the total error of the DVR controller; e t,dq0represents the error signal between the reference voltage and the load voltage in the dq0 coordinate; t is the number of iterations;

[0018] 4) Update the linear reduction parameter C;

[0019]

[0020] Among them, C max , C min They represent the maximum and minimum values ​​of the decreasing factor respectively, and L is the maximum number of iterations;

[0021] 5) Iterative search for the best position;

[0022] Assume the search space dimension is D, x i d (t) represents the dth dimension of the tth iteration of the i-th grasshopper. The quality of the position is determined by the fitness function. The expression of the position of the next iteration is as follows:

[0023]

[0024] is the dth dimension of the initial optimal position of the locust, ub d lb d They represent the upper and lower boundaries of the locust position in d dimension, respectively, and x i (t) is the position of the i-th grasshopper at time t, x j (t) is the position of the jth grasshopper at time t, d ij (t) is the distance between the i-th and j-th grasshoppers at the t-th iteration;

[0025] 6) Determine whether the maximum number of iterations has been reached. If the condition is not met, continue to update C and update the optimal position If the termination condition is met, the optimal controller parameters are calculated and output.

[0026] As a specific implementation method, the constant parameter f is set to 0.5; l is set to 1.5; d ij (t) The value range is [1,4]; the maximum value of C is 1 and the minimum value is 0.00004.

[0027] As a specific implementation method, the specific operation steps of the dynamic voltage restorer to achieve voltage sag control are as follows:

[0028] Step 1, detecting voltage disturbance occurring in the system;

[0029] Step 2: Convert the load voltage and the reference voltage to the dq0 coordinate system for comparison to obtain an error signal;

[0030] Step 3, synchronizing the PI controller output with the power supply voltage;

[0031] Step 4: The PI controller outputs a signal to control the PWM to generate a gate pulse to drive the power source inverter for voltage compensation.

[0032] As a specific implementation method, in step 1, the voltage disturbance occurring in the detection system is specifically implemented as follows:

[0033] The three-phase load voltage V L,abc and reference voltage V ref,abc Converted into a vectorized dq0 voltage component V L,dq0 and V ref,dq0 , the three-phase reference voltage is calculated as follows:

[0034]

[0035] Use Park transformation to transform it from three-phase abc components to dq0 components. The expression is as follows:

[0036]

[0037] As a specific implementation, in step 2, the load voltage and the reference voltage are converted to the dq0 coordinate system for comparison to obtain the specific calculation formula of the error signal as follows:

[0038]

[0039] As a specific implementation method, in step three, the specific implementation of synchronizing the controller output with the power supply voltage is as follows: a phase-locked loop is used as a synchronization tool to synchronize the controller output signal with the reference input signal in frequency and phase.

[0040] As a specific implementation, in step 4, optimizing the PI controller output signal to control PWM to generate a gate pulse to drive the power source inverter to perform voltage compensation is specifically implemented as follows:

[0041] The optimized PI controller determines the output signal, V c,dq0 It is the dq0 control signal output by the PI controller to the PWM. The expression is as follows:

[0042]

[0043] Afterwards, the output control signal is converted back to the three-phase abc components to control the PWM to generate gate pulses to drive the VSI, as shown below:

[0044]

[0045] Due to the application of the above technical solution, the present invention has the following advantages compared with the prior art:

[0046] The optimized PI controller based on the grasshopper optimization algorithm is applied to the DVR, so that when the system voltage is not faulty, the controller will not send a signal to operate the DVR. When the system voltage changes beyond the acceptable range, the controller starts to work, and the DVR injects a voltage opposite to the phase of the interference, eliminating the voltage deviation and keeping the voltage level on the load close to constant. By using the optimized PI controller, when the DVR is connected between the voltage source and the load through the injection transformer, the load voltage within the distribution system can be effectively increased, and at the same time, the DVR can inject high voltage in a short time, playing a vital role in avoiding voltage sags. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a schematic diagram of the series connection between DVR and power distribution system;

[0048] Figure 2 This is the structural diagram of the proposed DVR;

[0049] Figure 3 The Thevenin equivalent circuit diagram of the proposed DVR and power distribution system in series;

[0050] Figure 4 Run vector graphics for DVR;

[0051] Figure 5 It is a PI control strategy solution. DETAILED DESCRIPTION

[0052] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and specific embodiments.

[0053] The present invention provides an optimization compensation method for a dynamic voltage restorer based on a grasshopper optimization algorithm. When the voltage on the grid side drops, the dynamic voltage restorer is put into the grid, and an optimized PI controller constructed based on the grasshopper optimization algorithm is used to output a compensation voltage command according to the detected actual load voltage and the compensation voltage. The output compensation command is then converted into a PWM wave through a PWM module to drive a voltage source inverter to output a corresponding voltage.

[0054] The schematic diagram of the DVR and power distribution system in series in this example is as follows Figure 1 As shown, the system consists of an AC voltage source connected in series with a double-winding transformer, the second and third secondary windings of the transformer are connected to two feeders respectively, the first feeder supplies power to non-sensitive loads through the double-winding transformer, and the second feeder supplies power to sensitive loads through the double-winding transformer. The dynamic voltage compensation device (DVR) is connected in series in the line to play a role in compensating voltage.

[0055] The DVR structure diagram used in this example is as follows Figure 2As shown, it consists of a series capacitor (Cs) connected to the AC side of three single-phase step-up transformers, and a series resistor (Rs) is connected in series with the capacitor bank. The DVR consists of a DC energy storage unit, a voltage source inverter (VSI), a filter, a step-up transformer, and a control system.

[0056] A. DC energy storage unit: During a sudden voltage drop, the DVR uses a DC energy storage unit to provide energy to the system. The DC energy storage unit usually relies on batteries or supercapacitors to provide the active power required to offset voltage fluctuations.

[0057] B. Voltage Source Inverter (VSI): It is a power electronic device, usually based on insulated gate bipolar transistors (IGBT) or other high-power semiconductor devices, and is a key component of DVR, used to convert the voltage of the DC battery into AC to inject a voltage of the required amplitude, phase and frequency into the transformer.

[0058] C. Filter: It consists of RLC circuit to reduce the harmonic distortion of the waveform generated by VSI.

[0059] D. Step-up transformer: It transmits the output voltage of VSI to the distribution network required for compensation. The primary winding is connected in series with the power system and the secondary winding is coupled with the VSI unit.

[0060] E. Control system: The responsibility of the control system is to monitor voltage changes and generate control signals based on the detected voltage levels.

[0061] The Thevenin equivalent circuit diagram of the DVR and power distribution system in series is as follows Figure 3 As shown, the AC voltage source is equivalent to an equivalent voltage source V S and source impedance Z S The two feed lines are defined as F1 and F2, with impedances of Z L1 and Z L2 Two loads are powered, where Z tot Represents the feeder impedance. The voltage at feeder F1 is V F1 , the voltage at feeder F2 is V F2 , sensitive load Z L2 The bus voltage is V L The DVR is connected in series between the feeder F2 bus and the load L2 bus. During the voltage sag, the injected voltage is V D , DVR is equivalent to a voltage source V c and impedance Z D .

[0062] According to Kirchhoff's voltage law, during normal operation, the voltage drop (V Pre-sag ) and line current (I s ) expression is as follows:

[0063] V per-sag =V S -I S Z S ;

[0064]

[0065] I1 and I2 represent the currents flowing through feeders F1 and F2, respectively;

[0066] When a fault F occurs on the F1 feeder, a fault current (I Sfault ) is expressed as follows. At this time, the voltage at the common bus PCC (V sag ) expression is as follows:

[0067] V sag =V S -I Sfault Z S ;

[0068]

[0069] Combined with DVR operation vector diagram, such as Figure 4 As shown, the injected voltage V during the voltage sag is calculated D The magnitude and angle expressions are as follows:

[0070]

[0071]

[0072] and Respectively represent the load voltage V L and the equivalent voltage source voltage V S The phase angle.

[0073] The design process of the proposed PI control scheme is as follows:

[0074] The specific steps of the dynamic voltage restorer to achieve voltage sag control are as follows: ① Detect the voltage disturbance occurring in the system; ② Convert the load voltage and the reference voltage to the dq0 coordinate system for comparison to obtain the error signal; ③ Synchronize the controller output with the power supply voltage; ④ The controller output signal controls the PWM to generate a gated pulse to drive the inverter output voltage, absorbing the voltage when the load voltage increases and compensating when the voltage decreases.

[0075] Specific:

[0076] 1. Detection of voltage disturbance in the system: Use Park transformation to transform the three-phase load voltage V L,abc and reference voltage V ref,abcConverted into a vectorized dq0 voltage component V L,dq0 and V ref,dq0 , the three-phase reference voltage is calculated as follows:

[0077]

[0078] Use Park transformation to transform it from three-phase abc components to dq0 components. The expression is as follows:

[0079]

[0080] 2. Convert the load voltage and the reference voltage to the dq0 coordinate system for comparison and obtain the error signal e t,dq0 :

[0081]

[0082] 3. Synchronize the controller output with the power supply voltage: Use a phase-locked loop (PLL) as a synchronization tool to synchronize the controller's output signal with the reference input signal in frequency and phase;

[0083] 4. The controller output signal controls PWM to generate gate pulses to drive the inverter output voltage, absorbs voltage when the load voltage increases, and compensates when the voltage decreases. The PI control strategy scheme is as follows Figure 5 As shown, the PI controller determines the output signal through the error signal, V c,dq0 It is the dq0 control signal of the PI controller to the PWM output, and the expression is as follows:

[0084]

[0085] Afterwards, the output control signal is converted back to the three-phase abc components to control the PWM to generate gate pulses to drive the VSI, as shown below:

[0086]

[0087] Afterwards, the VSI generates voltage and injects it into the grid through the injection transformer to achieve voltage sag compensation.

[0088] In this example, the grasshopper optimization algorithm is designed as follows: GOA is used to adjust the gain of the PI controller to control the DVR. The selected optimal gain can minimize the error signal, making it more stable and better able to respond to different disturbances, thereby ensuring that the controller has better performance under various voltage fluctuations. The modeling process of the grasshopper optimization algorithm to obtain the optimal solution is shown below.

[0089] 1. Objective function: Define the fitness function ITAE expression as follows:

[0090]

[0091] Therefore, the objective function of the optimization problem is:

[0092] min(J)=min(ITAE),

[0093] Where J is the total error of the proposed DVR controller and et,dq0 represents the error signal between the reference voltage and the load voltage in the dq0 coordinate.

[0094] 2. Set the constraints as shown below:

[0095] 0.95≤V d ≤1.05;

[0096]

[0097] THD v ≤THD v，max ;

[0098]

[0099] THD i ≤THD i，max ;

[0100] Among them, V L is the bus voltage at the sensitive load on the second feeder, THD v V L The total harmonic distortion rate should be less than the maximum value (THD v,max );THD i is the total harmonic distortion rate of the current on the second feeder, which should be less than the maximum value (THD i,max ), V h It is the voltage amplitude of the hth harmonic in the voltage signal, V1 is the amplitude of the fundamental component of the voltage, and h represents the harmonic order. h is the current amplitude of the hth harmonic in the current signal, and I1 is the amplitude of the fundamental component of the current.

[0101] 3. Run the GOA search algorithm:

[0102] The GOA optimization algorithm simulates the foraging behavior of grasshoppers. The food source is relative to the optimal solution. The search process is divided into two stages: exploration and development. The exploration process of locusts is equivalent to the adult stage of locusts, which is conducive to the global search of the algorithm, while the development process of locusts is equivalent to the larval stage of locusts. In this stage, the insect group is more inclined to move in a small range, which is conducive to the local search of the algorithm. The search process can be expressed by the following formula, in which many factors affect the search process of grasshoppers, such as the interaction between locusts, gravity, and the horizontal influence of wind.

[0103] x i (t+1)=S i (t)+G i (t)+A i (t);

[0104] Among them, x i (t+1) represents the position of the i-th locust at the t+1th iteration, S i (t) represents the interaction between the i-th locust and other locusts in the locust swarm at the t-th iteration, G i (t) is the gravity acting on the i-th locust during the t-th generation, A i (t) represents the wind force on the i-th sturgeon during the t-th generation selection.

[0105]

[0106] N is the population size of grasshoppers, d ij (t) is the distance between the i-th and j-th grasshoppers at the t-th iteration, calculated as shown in formula (25), and is the unit vector of the distance between the two grasshoppers at the tth iteration, as shown in formula (26). s represents the interaction force function between grasshoppers. f is the attraction strength between locusts, l is the attraction range between locusts, f is 0.5, l is 1.5, d ij The value range of (t) is [1,4].

[0107] d ij (t)=|x j (t)-x i (t)|;

[0108]

[0109] In addition, G i (t) and A i The calculation formula for the (t) component is as follows

[0110]

[0111] g is the gravitational constant, represents the unit vector of the grasshopper toward the center of the earth; u represents the drift constant, represents the unit vector of the wind force on the grasshopper. Therefore, x i The (t+1) formula can be expanded to:

[0112]

[0113] 4. Initialize PI parameters, calculate the fitness value of each initial value, and save the locust position with the best fitness value to That is, the initial optimal position of the locust;

[0114] 5. Iterative search for the best position: Let the dimension of the search space be D, x i d (t) represents the dth dimension of the tth iteration of the i-th grasshopper. The quality of the position is determined by the fitness function. The expression of the position of the next iteration is as follows:

[0115]

[0116] is the dth dimension of the initial optimal position of the locust, ub d lb d They represent the upper and lower boundaries of the locust position in d dimension, respectively, and x i (t) is the position of the i-th grasshopper at time t, x j (t) is the position of the jth grasshopper at time t, d ij (t) is the distance between the i-th and j-th grasshoppers at the t-th iteration, C is the linear reduction parameter, and the following formula is defined:

[0117]

[0118] Among them, C max is the maximum value of parameter C, which is 1. min is the minimum value of parameter C, which is 0.00004, t is the current number of iterations of the algorithm, and L is the maximum number of iterations of the algorithm;

[0119] 6. Determine whether the maximum number of iterations has been reached. If the condition is not met, continue to update C and update the optimal position If the termination condition is met, the algorithm ends.

[0120] GOA is used to adjust the controller gain to control the DVR. The selected gain minimizes the error signal, making it stable and responsive to different disturbances, thus ensuring better compensation performance under various voltage sag conditions.

[0121] The above embodiments are only for illustrating the technical concept and features of the present invention, and their purpose is to enable people familiar with the technology to understand the content of the present invention and implement it accordingly, and they cannot be used to limit the protection scope of the present invention. Any equivalent changes or modifications made according to the spirit of the present invention should be included in the protection scope of the present invention.

Claims

1. An optimization compensation method for a dynamic voltage restorer based on a grasshopper optimization algorithm, characterized in that: When the voltage on the grid side drops, the dynamic voltage restorer is put into the grid and an optimized PI controller built based on the grasshopper optimization algorithm is used to output a compensation voltage command according to the detected actual load voltage and the compensation voltage. The output compensation command is then converted into a PWM wave through the PWM module to drive the voltage source inverter to output the corresponding voltage.

2. The optimization compensation method of a dynamic voltage restorer based on the grasshopper optimization algorithm according to claim 1, characterized in that: The construction of the optimized PI controller includes the following contents: 1) Initialize the PI controller parameters Kp, Ki, and Kd, where Kp represents the proportional coefficient of the PI controller; Ki represents the integral coefficient of the PI controller, and Kd represents the derivative coefficient; 2) Initialize the number of iterations and constant parameters: The constant parameters include: f is the attraction strength between locusts; l is the attraction range between locusts; d ij (t) is the distance between the i-th and j-th grasshoppers at the t-th iteration; C is the linear reduction parameter; 3) Calculate the fitness value of each initial value and save the locust position with the best fitness value; The fitness function ITAE expression is defined as follows: Therefore, the objective function of the optimization problem is: min(J)=min(ITAE), Where J is the total error of the DVR controller; e t,dq0 represents the error signal between the reference voltage and the load voltage in the dq0 coordinate; t is the number of iterations; 4) Update the linear reduction parameter C; Among them, C max , C min They represent the maximum and minimum values ​​of the decreasing factor, respectively, l is the range of attraction between locusts, and L is the maximum number of iterations; 5) Iterative search for the best position; Assume the search space dimension is D, x i d (t) represents the dth dimension of the tth iteration of the i-th grasshopper. The quality of the position is determined by the fitness function. The expression of the position of the next iteration is as follows: is the dth dimension of the initial optimal position of the locust, ub d lb d They represent the upper and lower boundaries of the locust position in d dimension, respectively, and x i (t) is the position of the i-th grasshopper at time t, x j (t) is the position of the jth grasshopper at time t, d ij (t) is the distance between the i-th and j-th grasshoppers at the t-th iteration; 6) Determine whether the maximum number of iterations has been reached. If the condition is not met, continue to update C and update the optimal position If the termination condition is met, the optimal controller parameters are calculated and output.

3. The optimization compensation method of a dynamic voltage restorer based on the grasshopper optimization algorithm according to claim 2 is characterized in that: The constant parameter f is 0.5; l is 1.5; d ij (t) The value range is [1,4]; the maximum value of C is 1 and the minimum value is 0.00004.

4. The optimization compensation method of a dynamic voltage restorer based on the grasshopper optimization algorithm according to claim 1, characterized in that: The specific operation steps of the dynamic voltage restorer to achieve voltage sag control are as follows: Step 1, detecting voltage disturbances occurring in the system; Step 2: Convert the load voltage and the reference voltage to the dq0 coordinate system for comparison to obtain an error signal; Step 3, synchronizing the PI controller output with the power supply voltage; Step 4: The PI controller outputs a signal to control the PWM to generate a gate pulse to drive the power source inverter for voltage compensation.

5. The optimization compensation method of a dynamic voltage restorer based on the grasshopper optimization algorithm according to claim 4 is characterized in that: In step 1, the specific implementation of the voltage disturbance occurring in the detection system is as follows: The three-phase load voltage V L,abc and reference voltage V ref,abc Converted into a vectorized dq0 voltage component V L,dq0 and V ref,dq0 , the three-phase reference voltage is calculated as follows: Use Park transformation to transform it from three-phase abc components to dq0 components. The expression is as follows:

6. The optimization compensation method of a dynamic voltage restorer based on the grasshopper optimization algorithm according to claim 4 is characterized in that: In step 2, the load voltage and the reference voltage are converted to the dq0 coordinate system for comparison to obtain the specific calculation formula of the error signal as follows:

7. The optimization compensation method of a dynamic voltage restorer based on the grasshopper optimization algorithm according to claim 4, characterized in that: In step three, the specific implementation of synchronizing the controller output with the power supply voltage is as follows: a phase-locked loop is used as a synchronization tool to synchronize the controller output signal with the reference input signal in frequency and phase.

8. The optimization compensation method of a dynamic voltage restorer based on the grasshopper optimization algorithm according to claim 4 is characterized in that: In step 4, the specific implementation of optimizing the PI controller output signal to control PWM to generate gate pulses to drive the power source inverter to perform voltage compensation is as follows: The optimized PI controller determines the output signal, V c,dq0 It is the dq0 control signal output by the PI controller to the PWM. The expression is as follows: Afterwards, the output control signal is converted back to the three-phase abc components to control the PWM to generate gate pulses to drive the VSI, as shown below:

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