Micro-grid reactive increment consistency control method based on feedback correction

Abstract

The invention discloses a reactive power increment consistency control method for a micro-grid based on feedback correction, and relates to a reactive power coordination and sharing control method for the micro-grid. The method comprises the following steps: step 1, aiming at a reactive voltage coordination and equalization problem of the hybrid microgrid, considering an information interaction effect between distributed power supplies, and establishing a distributed reactive increment consistency coordination control framework; 2, performing distributed secondary control on the distributed power supply based on a distributed consistency cooperative control algorithm under a consistency cooperative control framework; and 3, considering the actual operation state of the microgrid, adding a real-time feedback correction link, and carrying out dynamic feedback on the output quantity of each distributed power supply. According to the method, a hybrid micro-grid simulation model is established on a PSCAD / EMTDC platform, and a matrix laboratory (MATLAB) system is combined to program the consistency feedback correction algorithm, so that distributed optimization control of the hybrid micro-grid is realized, the proposed control method is simulated and verified, and the effectiveness of the proposed algorithm is proved.

Description

Technical Field

[0001] The present invention discloses a microgrid reactive increment consistency control method based on feedback correction, which relates to a reactive coordinated equalization control method for a microgrid. Background Art

[0002] With the rapid development of new energy, microgrids have also achieved corresponding technological development; microgrids are small power generation and distribution systems composed of distributed power sources, energy storage devices, energy conversion devices, loads, monitoring and protection devices, etc.

[0003] It aims to achieve flexible and efficient application of distributed power sources and solve the problem of connecting a large number of distributed power sources in various forms to the grid. The development and extension of microgrids can fully promote the large-scale access of distributed power sources and renewable energy, achieve highly reliable supply of various energy forms to loads, and is an effective way to realize active distribution networks, making the transition from traditional power grids to smart grids. In order to ensure high-quality regulation of microgrids, existing technicians have proposed a variety of control methods.

[0004] In the prior art, the document "Frequency and Voltage Coordination Control of Low Voltage Microgrid Inverter" (Sun Xiaofeng et al., Hebei Key Laboratory of Power Electronics Energy Saving and Transmission Control, Yanshan University) published in October 2012 adopts a secondary control method, introducing feedforward compensation into droop control to achieve secondary control of the voltage and frequency of the microgrid. The disadvantage is that if an additional virtual resistor is added to the system, the output voltage of the system will drop sharply, which cannot well reflect the voltage quality of the system.

[0005] The document "Research on Distributed Cooperative Control Strategy of Microgrid" (Wang Xinsheng, Zhang Huaqiang, School of Information and Electrical Engineering, Harbin Institute of Technology (Weihai)) published in August 2016, aimed at the voltage and frequency deviation of distributed power sources in primary droop control, and proposed a microgrid control method based on distributed control. When the microgrid is disturbed, it can effectively configure the active power of the microgrid and effectively restore the frequency and voltage of the microgrid. The disadvantage is that it fails to consider the impact of dynamic changes in the system operation process on distributed control.

[0006] The document "Research on the Regional Stability Control Method of DC Microgrid Based on Multi-agent System" (Hao Yuchen et al., State Grid Jiangsu Electric Power Company Dispatching and Control Center) published in November 2017 takes DC microgrid as the research object and realizes the regional stability control problem of microgrid under multiple working conditions. The disadvantage is that it only targets DC distribution system, and the hybrid microgrid still involves the problem of AC reactive power sharing.

[0007] The document "Research on Distributed Control Algorithm of Parallel Distributed Generation Units in Microgrids" (Fan Bo, School of Control Science and Engineering, Zhejiang University) published in November 2019 studied a distributed control strategy for parallel distributed power sources in microgrids, which ensures that the system node voltage can follow the required voltage trajectory while ensuring the accuracy of load current sharing between power sources. The disadvantage is that distributed control lacks global information and cannot achieve overall optimal scheduling.

[0008] The above literature does not coordinate and solve the contradiction between reactive power sharing in AC and DC distributed power sources and current load sharing in DC distributed power sources, and fails to consider the impact of real-time dynamic changes of hybrid microgrids on the entire operation process. Therefore, it is necessary to design a new method to meet actual application needs. Summary of the invention

[0009] The present invention proposes a reactive increment consistency control method for a microgrid based on feedback correction. Aiming at the disadvantages of traditional distributed control methods in various aspects, the present invention proposes a reactive increment consistency control method with a real-time feedback correction link. By comprehensively considering the operating status of each control variable of the microgrid, its optimal action state is judged, and real-time online feedback control of the microgrid is realized, thereby quickly realizing coordinated and equal distribution of reactive power in the microgrid, which has good use and promotion value.

[0010] The present invention provides a microgrid reactive increment consistency control method based on feedback correction, which comprises the following steps:

[0011] Step 1: Aiming at the problem of coordinated sharing of reactive power and voltage in hybrid microgrid, the information interaction between distributed power sources is considered and a distributed reactive power increment consistency collaborative control framework is established;

[0012] Step 2: Under the consistent collaborative control framework, based on the distributed consistent collaborative control algorithm, distributed secondary control is performed on the distributed power sources;

[0013] Step 3: Considering the actual operating status of the microgrid, a real-time feedback correction link is added to provide dynamic feedback on the output of each distributed power source.

[0014] Specifically, in step 1, the distributed reactive power increment consistency collaborative control framework is established as follows:

[0015] Step 1.1: Considering that the microgrid can maintain stable operation under different scenarios, the droop control strategy is adopted to control each distributed power source based on the establishment of the converter simulation model.

[0016] Step 1.2: Regarding the traditional droop control, that is, there is no information interaction in the control process, and it is difficult to achieve reactive power sharing well. Considering its communication interaction, based on the distributed reactive power increment consistency algorithm, its iterative increment can be expressed as:

[0017]

[0018] In the formula: n, i, j are consistency control coefficients, where 0 < n < 1, i > 0, j ≥ 0; Q is reactive power;

[0019] Among them, the X expression is determined by the distributed power information interaction coefficient and will be dynamically adjusted according to the consistency algorithm, as shown in formulas (2) and (3):

[0020]

[0021] In the formula: γ ab is the information interaction coefficient between adjacent distributed power sources, and satisfies γ ab ≥ 0; t is the consistency control factor, which controls the convergence speed and satisfies 0 < t < 1; a, b are the serial numbers of the distributed power sources; N a is the number of power sources adjacent to the a-th distributed power source; q a (q b ) is the number of remaining power sources when the a(b)-th distributed power source conducts information interaction;

[0022] In summary, its distributed reactive power increment consistency iteration equation is:

[0023] Q k+1 = Q k + ΔQ (4)

[0024] In the formula: Q k+1 (Q k ) is the result of the k + 1(k)-th distributed reactive power consistency iteration of reactive power.

[0025] Specifically, in step 2, during the distributed secondary control of the distributed power sources, the distributed power sources include AC distributed power sources and DC distributed power sources.

[0026] Furthermore, in step 2, the distributed secondary control of the AC distributed power source is:

[0027]

[0028] In the formula: ΔU is the voltage compensation value; ΔQ0 is the difference between the reference value and the actual value of the reactive power respectively; ΔQ is the reactive power iteration value obtained by the distributed consistency algorithm; α is the droop coefficient.

[0029] Furthermore, in step 2, the distributed secondary control of the DC distributed power source is:

[0030]

[0031] Where: U and I are the actual values ​​of voltage and current, U0 and i0 are the voltage and current under rated operating conditions; ΔU is the voltage compensation value; β is the droop coefficient; R s is the PI controller parameter; I′ is the control modulation signal; Δi is the current iteration value obtained by the distributed consensus algorithm.

[0032] Specifically, in step 3, a real-time feedback correction link is added to dynamically feedback the output of each distributed power source; the specific steps are as follows:

[0033] Step 3.1, using the output of distributed power generation as the initial value of the distributed reactive power increment consistency collaborative control algorithm, and the algorithm outputs feedback values ​​to perform real-time correction on relevant parameters, thereby achieving the purpose of controlling the microgrid;

[0034] Step 3.2, in order to solve the problem that the overall operation status of the microgrid is difficult to judge, an improved local correction function is defined to judge the specific operation status of the microgrid;

[0035] Step 3.3, in the optimal control of the AC / DC microgrid, the operating state of the grid is the environmental state characterized by the controlled electrical quantity, and each electrical quantity is normalized.

[0036] Further, in step 3.1, the real-time output variable of the AC microgrid is used as the initial value of the consistency feedback correction control algorithm. By programming the consistency feedback correction control algorithm in the MATLAB system, the algorithm calculates the output deviation of each distributed power source in real time and generates a feedback correction value. This feedback correction value will perform real-time correction on the key parameters in the droop control module, including voltage and power reference values, so as to dynamically adjust the output characteristics of the distributed power source to achieve coordination and stability within the microgrid. The corrected reference value is passed to the SVPWM module, which generates a pulse width modulation signal according to the corrected reference value, controls the switch of the inverter, and then adjusts the output AC characteristics, thereby achieving optimal control of the microgrid. Further, step 3.2 includes:

[0037] Step 3.2.1, updating the distributed control input through feedback correction and interaction with the microgrid operation status;

[0038] Step 3.2.2, under the premise of maintaining balanced current, perform reactive power regulation on the distributed power source;

[0039] In step 3.2.3, consider the problem of achieving reactive power sharing and microgrid interactive support under the premise of maintaining balanced current, and design the local feedback correction function.

[0040] Further, in step 3.2.1, the distributed control input is updated by interacting with the microgrid operation status through feedback correction, wherein the distributed reactive power increment consistency update feedback correction formula is:

[0041]

[0042] Where: Q′ is the reactive power convergence value; Q a is the reactive power consistency update feedback value; η is the feedback coefficient.

[0043] Furthermore, in step 3.2.2, reactive power regulation is performed on the distributed power source under the premise of maintaining balanced current; considering the equal-proportional current sharing of the DC microgrid, for the DC microgrid with equal-proportional current sharing, the convergence consistency value of the average current ratio is:

[0044]

[0045] Where: I a is the measured current of the ath distributed power source; I N,a is the rated current of the ath distributed power source;

[0046] For AC microgrid, the convergence consistency value of reactive power is:

[0047]

[0048] Where: Q a is the measured reactive power of the ath distributed generation.

[0049] Furthermore, in step 3.2.3, considering the problem of achieving reactive power sharing and microgrid interactive support under the premise of maintaining balanced current, the local feedback correction function is designed:

[0050]

[0051] Where: μ1, μ2, μ3 are the weights of reactive power sharing, DC current and AC / DC interactive support, and satisfy μ1+μ2+μ3=1.

[0052] Furthermore, in step 3.3, in the optimal control of the AC / DC microgrid, the operating state of the grid is the environmental state represented by the controlled electrical quantity, and the normalization process of each electrical quantity is as follows:

[0053]

[0054] The AC reactive power, DC side current and AC / DC interactive support power of reactive power measurement are selected as state variables and divided into 6 states: (-∞, -1), (-1, -0.5), (-0.5, 0), (0, 0.5), (0.5, 1), (1, +∞). The total state set can be 6 3 Each state is set to M = (m1, m2, m3,). The set of feedback correction effects is called secondary regulation control, and the feedback correction value is set to {-0.00062, -0.000546, -0.000458, -0.000382, -0.000231, -0.000004, -0.00000298, 0, 0.000346, 0.000585, 0.000728, 0.000868, 0.000927, 0.000936}MW.

[0055] The device used in the reactive increment consistency control method of a microgrid based on feedback correction of the present invention is: by building a hybrid microgrid simulation model on the PSCAD / EMTDC platform, and programming the above-mentioned consistency feedback correction algorithm in conjunction with the MATLAB system, the distributed optimization control of the hybrid microgrid is realized, and then the proposed control method is simulated and verified to prove the effectiveness of the proposed algorithm.

[0056] Compared with the prior art, the present invention has the following advantages:

[0057] 1. Optimization control algorithm: In view of complex environmental factors, an optimization control method that can interact with the actual operating environment is proposed. This control method can work effectively without an environmental model. By real-time monitoring of the operating status of the microgrid, the algorithm can dynamically adjust the control strategy. In a complex microgrid system, especially when the system topology changes or failures occur, it can still maintain a stable control effect and ensure safe and reliable operation of the system.

[0058] 2. Microgrid operating status evaluation: Considering that traditional optimization control usually relies on complex mathematical modeling and derivation, the local state function is set to evaluate whether the operating status of the microgrid is optimal, reducing the requirements for computing power.

[0059] 3. Real-time online feedback control: Through the feedback correction mechanism, the operating status of the microgrid is mastered in real time, and iterative optimization is performed based on the reward signal of performance evaluation. This real-time feedback adjustment feature allows the algorithm to flexibly adapt to changes in the operating environment, avoid inefficiencies in local areas, and ensure that the system achieves global optimality in multi-objective coordination. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] The present invention will be further described below in conjunction with the accompanying drawings.

[0061] Figure 1 The present invention is a flowchart of the steps of a microgrid reactive increment consistency control method based on feedback correction.

[0062] Figure 2 This is the consistency feedback correction control structure in the present invention.

[0063] Figure 3 It is the operating result of reactive power output under feedback correction control in the present invention.

[0064] Figure 4 It is the iterative result of reactive power consistency under feedback correction control in the present invention.

[0065] Figure 5 It is the operating result of reactive power output under the non-feedback correction control in the present invention.

[0066] Figure 6 It is the iterative result of reactive power consistency under the non-feedback correction control in the present invention. DETAILED DESCRIPTION

[0067] Combination Figure 1-6 As shown, the present invention provides a coordinated control method of a distributed drive UAV, comprising the following steps:

[0068] See attached Figure 1 The present invention provides a microgrid reactive increment consistency control method based on feedback correction, comprising the following steps:

[0069] Step 1: Aiming at the problem of coordinated sharing of reactive power and voltage in hybrid microgrid, the information interaction between distributed power sources is considered and a distributed reactive power increment consistency collaborative control framework is established;

[0070] Step 2: Under the consistency collaborative control framework, based on the distributed consistency collaborative control algorithm, distributed secondary control is performed on the distributed power sources;

[0071] Step 3: Considering the actual operating status of the microgrid, a real-time feedback correction link is added to provide dynamic feedback on the output of each distributed power source.

[0072] The specific steps of step 1 are as follows;

[0073] Step 1.1, considering that the microgrid can maintain stable operation under different scenarios, on the basis of establishing the converter simulation model, the droop control strategy is adopted to control each distributed power source.

[0074] Step 1.2 is aimed at traditional droop control, that is, the system does not exchange information during the control process, and it is difficult to achieve reactive power sharing. Considering its communication interaction, based on the distributed reactive power increment consistency algorithm, its iterative increment can be expressed as:

[0075]

[0076] Where: n, i, and j are consistency control coefficients, where 0 < n < 1, i > 0, and j ≥ 0; Q is reactive power; the expression of X is determined by the distributed power information interaction coefficient and will be dynamically adjusted according to the consistency algorithm, as shown in equations (2) and (3).

[0077]

[0078] Where: γ ab is the adjacent distributed power information interaction coefficient and satisfies γ ab ≥ 0; t is the consistency control factor that controls the convergence speed and satisfies 0 < t < 1; a and b are the serial numbers of distributed power sources; N a is the number of power sources adjacent to the a-th distributed power source; q a (q b ) is the number of remaining power sources when the a(b)-th distributed power source conducts information interaction.

[0079] In summary, the distributed reactive power increment consistency iteration equation is as follows:

[0080] Q k+1 = Q k + ΔQ (4)

[0081] Where: Q k+1 (Q k ) is the result of the k + 1(k)-th distributed reactive power consistency iteration of reactive power.

[0082] In step 2, perform distributed secondary control on the distributed power sources:

[0083] (1) AC distributed power source:

[0084]

[0085] Where: ΔU is the voltage compensation value; ΔQ0 is the difference between the reference value and the actual value of reactive power; ΔQ is the reactive power iteration value obtained from the distributed consistency algorithm; α is the droop coefficient;

[0086] (2) DC distributed power source:

[0087]

[0088] Where: U and I are the actual values of voltage and current, U0 and i0 are the voltage and current under the rated operating state; ΔU is the voltage compensation value; β is the droop coefficient; R sis the PI controller parameter; I′ is the control modulation signal; Δi is the current iteration value obtained by the distributed consensus algorithm.

[0089] In step 3, a real-time feedback correction link is added to dynamically feedback the output of each distributed power source:

[0090] Taking into account that the distributed reactive incremental consistency collaborative control algorithm takes the initial control quantity as the initial control value, which will lead to an increase in the number of iterations and thus reduce the convergence speed of the consistency collaborative control, a real-time feedback correction link is added to dynamically feedback the output of each distributed power source.

[0091] Step 3.1, the output of distributed power generation is used as the initial value of the distributed reactive power increment consistency collaborative control algorithm, and the algorithm outputs feedback value to correct the relevant parameters in real time, so as to achieve the control purpose of the microgrid, such as Figure 2 shown.

[0092] Step 3.2, in order to solve the problem that the overall operating status of the microgrid is difficult to judge, an improved local correction function is defined to further judge the specific operating status of the microgrid.

[0093] Step 3.2.1, update the distributed control input through feedback correction and interaction with the microgrid operation status, where the distributed reactive power increment consistency update feedback correction formula is:

[0094]

[0095] Where: Q′ is the reactive power convergence value; Q a is the reactive power consistency update feedback value; η is the feedback coefficient.

[0096] Step 3.2.2: Under the premise of maintaining balanced current, reactive power regulation of distributed power sources is required. Considering the equal-proportional current sharing of DC microgrid, for the DC microgrid with equal-proportional current sharing, the convergence consistency value of the average current ratio is:

[0097]

[0098] Where: I a is the measured current of the ath distributed power source; I N,a is the rated current of the ath distributed power source.

[0099] For AC microgrid, the convergence consistency value of reactive power is:

[0100]

[0101] Where: Q a is the measured reactive power of the ath distributed generation.

[0102] Step 3.2.3, considering the problem of achieving reactive power sharing and microgrid interactive support under the premise of maintaining balanced current, design the local feedback correction function:

[0103]

[0104] Where: μ1, μ2, μ3 are the weights of reactive power sharing, DC current and AC / DC interactive support, and satisfy μ1+μ2+μ3=1.

[0105] In step 3.3, in the optimal control of the AC / DC microgrid, the operating state of the grid is the environmental state represented by the controlled electrical quantity. The normalization process of each electrical quantity is as follows:

[0106]

[0107] The AC reactive power, DC side current and AC / DC interactive support power of reactive power measurement are selected as state variables and divided into 6 states: (-∞, -1), (-1, -0.5), (-0.5, 0), (0, 0.5), (0.5, 1), (1, +∞). The total state set can be 6 3 Each state is set to M = (m1, m2, m3,). The set of feedback correction effects is called secondary regulation control, and the feedback correction value is set to {-0.00062, -0.000546, -0.000458, -0.000382, -0.000231, -0.000004, -0.00000298, 0, 0.000346, 0.000585, 0.000728, 0.000868, 0.000927, 0.000936}MW.

[0108] By building a hybrid microgrid simulation model on the PSCAD / EMTDC platform and programming the above-mentioned consistency feedback correction algorithm in conjunction with the MATLAB system, the distributed optimization control of the hybrid microgrid is realized, and then the proposed control method is simulated and verified to prove the effectiveness of the proposed algorithm.

[0109] Under normal operating conditions, the microgrid maintains system stability through droop control, and the rated voltage of the AC measurement is maintained at 0.38kV and the rated frequency is 50Hz. However, due to different impedances, the reactive power generated by each distributed power source is also different. At t=3.5s, the control method is put into the system. At this time, the system frequency is in normal state, and both AC and DC microgrids can meet the load requirements. In the feedback of the microgrid operating status, if there are abnormal variables, the consistency feedback correction mechanism will be activated. According to the actual situation of the microgrid, the optimal operating value will be selected, and then the system will start secondary control to feedback and correct the electrical quantities that do not meet the standards until the variables that do not meet the standards are restored to appropriate values. Among them, Figure 3 Output results of reactive power simulation for 4 distributed power sources. Figure 4 It is the iterative result of reactive power consistency.

[0110] As can be seen from the figure, after 3.5s, the reactive power output of the four distributed power sources is different, which is caused by the difference in line impedance, so reactive power equalization cannot be achieved at this time. At this time, the operation status of the microgrid is monitored in real time. Due to the uneven reactive output of each distributed power source in the microgrid, the distributed reactive incremental consistency collaborative control strategy based on feedback correction is triggered. After the convergence iteration is completed, the system can perform the next iteration based on the result of the previous iteration. Finally, at 3.7s, the reactive output of each distributed power source reaches 18.5kvar, that is, the reactive circulation is suppressed at this time, reactive power equalization is achieved, the stability of the microgrid is improved, and the distributed real-time feedback correction control of the microgrid is completed.

[0111] Figure 5 The reactive power simulation output of distributed generation without consistent feedback correction control is shown in Figure 2. Figure 6 It is the result of the reactive power consistency iteration when there is no consistent feedback correction control. As can be seen from the figure, in the scenario without consistent feedback correction control, the AC micro-power performed 9 iterations before achieving reactive increment consistency, and the iteration process was completed at 5.2s and the reactive power sharing of the power supply was achieved.

[0112] contrast Figure 3 and Figure 4 , that is, after the consistency feedback correction link is introduced, it can be seen from the figure that the AC microgrid only performed 2 iterations before achieving reactive increment consistency, and completed the iteration process and achieved reactive power sharing of the power supply at 3.7s. Therefore, after adding feedback correction, the convergence speed of distributed consistency control of the microgrid is significantly improved.

[0113] Compared with the prior art, the present invention has the following advantages:

[0114] 1. Optimization control algorithm: In view of complex environmental factors, an optimization control method that can interact with the actual operating environment is proposed. This control method can work effectively without an environmental model. By real-time monitoring of the operating status of the microgrid, the algorithm can dynamically adjust the control strategy. In a complex microgrid system, especially when the system topology changes or failures occur, it can still maintain a stable control effect and ensure safe and reliable operation of the system.

[0115] 2. Microgrid operating status evaluation: Considering that traditional optimization control usually relies on complex mathematical modeling and derivation, the local state function is set to evaluate whether the operating status of the microgrid is optimal, reducing the requirements for computing power.

[0116] 3. Real-time online feedback control: Through the feedback correction mechanism, the operating status of the microgrid is mastered in real time, and iterative optimization is performed based on the reward signal of performance evaluation. This real-time feedback adjustment feature allows the algorithm to flexibly adapt to changes in the operating environment, avoid inefficiencies in local areas, and ensure that the system achieves global optimality in multi-objective coordination.

Claims

1. A microgrid reactive increment consistency control method based on feedback correction, characterized in that: The steps include: Step 1: Aiming at the problem of coordinated sharing of reactive power and voltage in hybrid microgrid, the information interaction between distributed power sources is considered and a distributed reactive power increment consistency collaborative control framework is established; Step 2: Under the consistent collaborative control framework, based on the distributed consistent collaborative control algorithm, distributed secondary control is performed on the distributed power sources; Step 3: Considering the actual operating status of the microgrid, a real-time feedback correction link is added to provide dynamic feedback on the output of each distributed power source.

2. According to the method of claim 1, the microgrid reactive increment consistency control method based on feedback correction is characterized in that: In step 1, the distributed reactive power increment consistency collaborative control framework is established as follows: Step 1.1: Considering that the microgrid can maintain stable operation in different scenarios, the droop control strategy is used to control each distributed power source based on the establishment of the converter simulation model. Step 1.2: For traditional droop control, that is, the system does not exchange information during the control process, it is difficult to achieve reactive power sharing. Considering its communication interaction, based on the distributed reactive power increment consistency algorithm, its iterative increment can be expressed as: Where: n, i, j are consistency control coefficients, where 0 <n<1、i> 0, j ≥ 0; Q is reactive power; The expression X is determined by the distributed power information interaction coefficient and will be dynamically adjusted according to the consistency algorithm, as shown in formula (2) (3): Where: γ ab is the information interaction coefficient between adjacent distributed power sources, and satisfies γ ab ≥0; t is the consistency control factor, which controls the convergence speed and satisfies 0 < t < 1; a and b are the serial numbers of the distributed power sources; N a is the number of power sources adjacent to the a-th distributed power source; q a (q b ) is the number of remaining power sources when the a(b)-th distributed power source conducts information interaction; In summary, the distributed reactive power increment consistency iteration equation is: Q k+1 =Q k +ΔQ (4) Where: Q k+1 (Q k ) is the reactive power at the k+1(k)th distributed reactive power consistency iteration result.

3. According to the method of claim 1, the microgrid reactive increment consistency control method based on feedback correction is characterized in that: In step 2, distributed secondary control is performed on the distributed power sources, where the distributed power sources include AC distributed power sources and DC distributed power sources.

4. According to claim 3, a microgrid reactive increment consistency control method based on feedback correction is characterized in that: In step 2, the distributed secondary control of the AC distributed power source is: Where: ΔU is the voltage compensation value; ΔQ0 is the difference between the reference value and the actual value of reactive power; ΔQ is the reactive iteration value obtained by the distributed consistency algorithm; α is the droop coefficient.

5. The method for controlling the reactive increment consistency of a microgrid based on feedback correction according to claim 3 is characterized in that: In step 2, the distributed secondary control of the DC distributed power source is: Where: U and I are the actual values ​​of voltage and current, U0 and i0 are the voltage and current under rated operating conditions; ΔU is the voltage compensation value; β is the droop coefficient; R s is the PI controller parameter; I′ is the control modulation signal; Δi is the current iteration value obtained by the distributed consensus algorithm.

6. The method for controlling the reactive increment consistency of a microgrid based on feedback correction according to claim 1 is characterized in that: In step 3, a real-time feedback correction link is added to dynamically feedback the output of each distributed power source; the specific steps are as follows: Step 3.1, using the output of distributed power generation as the initial value of the distributed reactive power increment consistency collaborative control algorithm, and the algorithm outputs feedback values ​​to perform real-time correction on relevant parameters, thereby achieving the purpose of controlling the microgrid; Step 3.2, in order to solve the problem that the overall operation status of the microgrid is difficult to judge, an improved local correction function is defined to judge the specific operation status of the microgrid; Step 3.3, in the optimal control of the AC / DC microgrid, the operating state of the grid is the environmental state characterized by the controlled electrical quantity, and each electrical quantity is normalized.

7. A microgrid reactive increment consistency control method based on feedback correction according to claim 6, characterized in that: In step 3.1, the real-time output variable of the AC microgrid is used as the initial value of the consistency feedback correction control algorithm. By programming the consistency feedback correction control algorithm in the MATLAB system, the algorithm calculates the output deviation of each distributed power source in real time and generates a feedback correction value. This feedback correction value will perform real-time correction on the key parameters in the droop control module, including voltage and power reference values, so as to dynamically adjust the output characteristics of the distributed power source to achieve coordination and stability within the microgrid. The corrected reference value is passed to the SVPWM module, which generates a pulse width modulation signal according to the corrected reference value, controls the switch of the inverter, and then adjusts the output AC characteristics, thereby achieving optimal control of the microgrid.

8. A microgrid reactive increment consistency control method based on feedback correction according to claim 6, characterized in that: Step 3.2 includes: Step 3.2.1, updating the distributed control input through feedback correction and interaction with the microgrid operation status; Step 3.2.2, under the premise of maintaining balanced current, perform reactive power regulation on the distributed power source; In step 3.2.3, consider the problem of achieving reactive power sharing and microgrid interactive support under the premise of maintaining balanced current, and design the local feedback correction function.

9. A microgrid reactive increment consistency control method based on feedback correction according to claim 8, characterized in that: Step 3.2.1, update the distributed control input through feedback correction and interaction with the microgrid operation status, where the distributed reactive power increment consistency update feedback correction formula is: Q=η(Q′-Q a k ) (7) Where: Q′ is the reactive power convergence value; Q a is the reactive power consistency update feedback value; η is the feedback coefficient.

10. A microgrid reactive increment consistency control method based on feedback correction according to claim 8, characterized in that: Step 3.2.2, under the premise of maintaining balanced current, perform reactive power regulation on distributed power sources; consider the equal-proportional current sharing of the DC microgrid. For the DC microgrid with equal-proportional current sharing, the convergence consistency value of the average current ratio is: Where: I a is the measured current of the ath distributed power source; I N,a is the rated current of the ath distributed power source; For AC microgrid, the convergence consistency value of reactive power is: Where: Q a is the measured reactive power of the ath distributed generation.

11. A microgrid reactive increment consistency control method based on feedback correction according to claim 8, characterized in that: Step 3.2.3, considering the problem of achieving reactive power sharing and microgrid interactive support under the premise of maintaining balanced current, design the local feedback correction function: Where: μ1, μ2, μ3 are the weights of reactive power sharing, DC current and AC / DC interactive support, and satisfy μ1+μ2+μ3=1.

12. A microgrid reactive increment consistency control method based on feedback correction according to claim 6, characterized in that: In step 3.3, in the optimal control of the AC / DC microgrid, the operating state of the grid is the environmental state represented by the controlled electrical quantity. The normalization process of each electrical quantity is as follows: The AC reactive power, DC side current and AC / DC interactive support power of reactive power measurement are selected as state variables and divided into 6 states: (-∞, -1), (-1, -0.5), (-0.5, 0), (0, 0.5), (0.5, 1), (1, +∞). The total state set can be 6 3 Each state is set to M = (m1, m2, m3,). The set of feedback correction effects is called secondary regulation control, and the feedback correction value is set to {-0.00062, -0.000546, -0.000458, -0.000382, -0.000231, -0.000004, -0.00000298, 0, 0.000346, 0.000585, 0.000728, 0.000868, 0.000927, 0.000936}MW.

13. The device used in the microgrid reactive increment consistency control method based on feedback correction as claimed in claim 1 is characterized in that: By building a hybrid microgrid simulation model on the PSCAD / EMTDC platform and programming the above-mentioned consistency feedback correction algorithm in conjunction with the MATLAB system, the distributed optimization control of the hybrid microgrid is realized, and then the proposed control method is simulated and verified to prove the effectiveness of the proposed algorithm.

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