Bidirectional charging pile reactive power and voltage distributed cooperative control method and system based on consistency algorithm

Abstract

The invention relates to the field of bidirectional charging pile control optimization, in particular to a bidirectional charging pile reactive power and voltage distributed cooperative control method and system based on a consistency algorithm, and the method comprises the steps: taking each bidirectional charging pile as a node, broadcasting the total reactive power vacancy of the node to a neighbor node, and receiving the total reactive power vacancy of the neighbor node; obtaining reactive power correction based on the total reactive power vacancy of the current node and the neighbor node, and adjusting the virtual impedance by adopting the reactive power correction; iteratively calculating the estimation of each node on the average voltage of the whole network under the virtual impedance by adopting an integral consistency algorithm to obtain a target value of the average voltage of the whole network; obtaining a voltage correction term of each node based on the target value, and correcting a voltage reference value of each node by adopting the voltage correction term to obtain a target voltage reference value of each node; the method can eliminate the fault risk of the central node, reduces the communication load, and achieves the flexible expansion of the system scale.

Description

Technical Field

[0001] This invention relates to the field of bidirectional charging pile control optimization, specifically to a distributed collaborative control method for reactive power and voltage of bidirectional charging piles based on a consensus algorithm. Background Technology

[0002] With global environmental and energy shortages becoming increasingly severe, promoting a revolution in green energy production and consumption, and building a clean, low-carbon, safe, and efficient energy system has become an inevitable trend. Against this backdrop, electric vehicles (EVs), with their characteristics as mobile energy storage devices, are increasingly demonstrating their value in the energy sector. Therefore, rationally scheduling the charging and discharging behavior of EVs can effectively smooth grid load fluctuations, achieving peak shaving and valley filling, while simultaneously enabling bidirectional flow between the energy subgrid and vehicles (i.e., V2G, Vehicle-to-Grid). This has significant practical implications for improving energy efficiency and ensuring stable grid operation.

[0003] The core idea of ​​V2G technology is to transform the energy storage of idle electric vehicles into a "buffer resource" for the power grid, facilitating the reliable and efficient operation of microgrids through flexible charging and discharging control. However, with the large-scale integration of new energy sources such as wind and solar power, as well as electric vehicles with V2G characteristics, into the power grid, the grid structure is gradually shifting from a traditional centralized model to a distributed, multi-source collaborative model, significantly increasing its complexity. This shift directly leads to an increasingly severe situation for power grid peak regulation: on the one hand, the output of new energy sources is intermittent and fluctuating, easily causing power imbalances in the grid; on the other hand, when a large number of V2G charging piles are operating in parallel, without effective coordinated control, not only will their energy storage regulation role be difficult to realize, but they may also impact the frequency and voltage stability of the power grid due to uneven power distribution and transient oscillations.

[0004] Against the backdrop of the global energy transition, the large-scale integration of new energy power generation (wind power and solar power) and electric vehicles (EVs) into the power grid is driving the evolution of microgrids from a "centralized" to a "distributed, multi-source coordinated" model. However, this structural evolution also brings new challenges to power quality: In this context, how to utilize advanced energy information management technology to achieve synergistic optimization among multiple energy systems (new energy, V2G energy storage, and loads), improve the overall energy utilization rate, and alleviate the pressure on grid peak regulation; the superposition, reflection, and resonance of harmonic currents after multiple units are connected in parallel, causing voltage distortion, equipment overheating, and protection malfunctions; V2G piles themselves have the potential for reactive power and harmonic suppression, but due to the lack of a coordination mechanism, they operate independently, resulting in dispersed and inefficient harmonic control effects. These are all key issues that the current power grid system urgently needs to address.

[0005] To address the aforementioned issues, existing static power distribution control schemes based on fixed droop characteristics employ a local controller for charging piles with preset static parameters, eliminating the need for node interaction. They allocate active power based on the charging pile's rated capacity and reactive power based on fixed capacitive reactance, focusing only on the microgrid's basic frequency and voltage indicators, ignoring fluctuations in renewable energy sources, battery SOC / SOH, and user charging / discharging demands. However, this technology suffers from: 1) poor dynamic adaptability, struggling to cope with sudden changes in renewable energy / load, easily leading to frequency and voltage deviations exceeding permissible limits; 2) high equipment risk, ignoring battery SOC, potentially causing allergies and shortening battery life; 3) insufficient accuracy, failing to consider line impedance / equipment parameter differences, easily causing power distribution to deviate from preset ratios; 4) failure to consider the distribution characteristics of harmonic currents, resulting in unbalanced harmonic reactive power distribution, easily causing local node voltage distortion; and 5) inability to respond to random harmonic disturbances introduced by nonlinear loads or renewable energy inverters, with delayed or even ineffective mitigation. Another approach uses a centralized control method for parallel V2G charging piles with secondary control. This approach employs a three-tier architecture: a central control layer, a communication network, and an execution layer. The central controller collects global data (frequency, voltage, power, and SOC), calculates the total power adjustment, and distributes it accordingly. Local controllers then track and adjust the power. However, this technology has several drawbacks: 1) It is highly dependent on communication, and delays / interruptions can lead to control lag; as the scale increases, bandwidth becomes insufficient. 2) If the central controller fails, the harmonic mitigation function is completely paralyzed, and the system loses its ability to respond to harmonic disturbances. 3) It has poor scalability; adding new charging piles requires reconfiguration of parameters, resulting in high costs. 4) The central node needs to collect and process harmonic data across the entire frequency band, leading to a significant increase in communication bandwidth and computational load, resulting in poor real-time performance.

[0006] Therefore, there is an urgent need to design a V2G charging pile control method that can eliminate the risk of central node failure, reduce communication load, and enable flexible expansion of system scale. Summary of the Invention

[0007] To address the aforementioned problems in existing technologies, this invention proposes a distributed collaborative control method for reactive power and voltage in bidirectional charging piles based on a consensus algorithm, comprising: Each bidirectional charging pile is a node, broadcasting the total reactive power deficit of the node to neighboring nodes and receiving the total reactive power deficit of neighboring nodes; The reactive power correction amount is obtained based on the total reactive power deficit of this node and neighboring nodes, and the virtual impedance is adjusted using the reactive power correction amount; Under the virtual impedance, the integral consensus algorithm is used to iteratively calculate the estimate of the average voltage of the entire network by each node to obtain the target value of the average voltage of the entire network. Based on the target value, the voltage correction term for each node is obtained, and the voltage reference value of each node is corrected using the voltage correction term to obtain the target voltage reference value for each node.

[0008] Optionally, the total reactive power deficit includes reactive power deficit and basic reactive power deficit, wherein the reactive power deficit is related to the filter capacitor, harmonic order, and amplitude of harmonic current of the corresponding node.

[0009] Optionally, the formula for calculating the total reactive power deficit is: ,

[0010] in, For the first Total reactive power deficit of each node This represents a basic shortfall in reactive power. This is a shortfall due to lack of effective response. The total harmonic order is... For harmonic order, For the first The node of the first The amplitude of the second harmonic current. The angular frequency of the power grid. For the first The filter capacitors at each node.

[0011] Optionally, the step of obtaining the reactive power correction amount based on the total reactive power deficit of the current node and neighboring nodes includes: The consistency error is obtained based on the difference between the total reactive power deficit of this node and its neighboring nodes; The reactive power correction amount is obtained by calculating the consistency error using PI control.

[0012] Optionally, the formula for calculating the consistency error is:

[0013] in, For nodes Consistency error, For consistency gain, For capacity weights, For nodes Total reactive power deficit For nodes Adjacent nodes Total reactive power deficit.

[0014] Optionally, the formula for calculating the capacity weight is:

[0015] in, For nodes Rated apparent power capacity, For nodes Adjacent nodes The rated apparent power capacity.

[0016] Optionally, the calculation formula for adjusting the virtual impedance using the reactive power correction amount is as follows:

[0017] in, For adaptive inductors, For adaptive resistance value, For nodes The static inductance at that location, For nodes The static resistance value at that location, To correct the gain for the inductor, To correct the gain for the resistor, For nodes The reactive power correction at the location.

[0018] Optionally, the step of iteratively calculating the estimate of the network average voltage by each node using an integral consensus algorithm under the virtual impedance to obtain the target value of the network average voltage includes: Based on the virtual impedance, the virtual impedance caused by... shaft and Voltage drop across the shaft; Using the voltage drop to each node shaft and The voltage components of the axis are corrected to obtain the axis and the sum of the axes at each node. The accurate voltage components of the shaft; Based on each node shaft and The accurate voltage component of the axis is obtained by iteratively calculating the estimate of the average voltage of the entire network by each node using an integral consensus algorithm, thus obtaining the target value of the average voltage of the entire network.

[0019] Optional, each node shaft and The formula for calculating the accurate voltage component of the shaft is:

[0020] in, For virtual nodes exist The accurate voltage components of the shaft, For virtual nodes exist The accurate voltage components of the shaft, For the inverter output current at Components on the axis, For the inverter output current at Components on the axis, The angular frequency of the power grid. For nodes The virtual resistance at that location, For nodes Virtual inductance at the location.

[0021] Optionally, the integral consensus algorithm uses the following formula to iteratively calculate each node's estimate of the average voltage of the entire network:

[0022] in, For nodes In time The local estimate of the average output voltage of the entire network. For nodes In time Actual measured output voltage Axial components, For integral consistency gain, In time From neighboring nodes The received estimate of its own average voltage across the entire network. In time Its current average voltage estimate, For nodes The set of adjacent nodes.

[0023] Optionally, the step of obtaining the voltage correction term for each node based on the target value includes: Based on the target value, the local voltage mismatch at each node is obtained; The voltage mismatch is calculated using PI control to obtain the voltage correction term.

[0024] Optionally, the formula for calculating the voltage correction term is:

[0025] in, For nodes Voltage correction term, For nodes of Controller transfer function This represents the local voltage mismatch. , For nodes Rated voltage, This is the target value for the average voltage across the entire network.

[0026] Optionally, the formula for calculating the target voltage reference value is:

[0027] in, The target voltage reference value, For nodes Rated voltage, For nodes The reactive power droop factor, For nodes Current reactive power output For virtual nodes exist The accurate voltage components of the shaft, For nodes Voltage correction term.

[0028] Optionally, the node reactive power droop coefficient The following formula is used for control:

[0029] in, The initial reactive power droop coefficient is a constant. The gain is dynamically adjusted to accommodate the reactive power droop factor. This is the consistency error.

[0030] A second aspect of this invention provides a bidirectional charging pile reactive power and voltage distributed collaborative control system based on a consensus algorithm, comprising: The first calculation module is used to broadcast the total reactive power deficit of this node to neighboring nodes and receive the total reactive power deficit of neighboring nodes, with each bidirectional charging pile as a node. The acquisition module is used to obtain the reactive power correction amount based on the total reactive power deficit of the current node and neighboring nodes, and to adjust the virtual impedance using the reactive power correction amount; The second calculation module is used to iteratively calculate the estimate of the average voltage of the entire network by each node under the virtual impedance using an integral consensus algorithm to obtain the target value of the average voltage of the entire network. The correction module is used to obtain the voltage correction term for each node based on the target value, and to correct the voltage reference value of each node using the voltage correction term to obtain the target voltage reference value for each node.

[0031] Optionally, the total reactive power deficit in the first calculation module includes reactive power deficit and basic reactive power deficit, wherein the reactive power deficit is related to the filter capacitor, harmonic order, and amplitude of harmonic current of the corresponding node.

[0032] Optionally, the formula for calculating the total reactive power deficit in the first calculation module is as follows: ,

[0033] in, For the first Total reactive power deficit of each node This represents a basic shortfall in reactive power. This is a shortfall due to lack of effective response. The total harmonic order is... For harmonic order, For the first The node of the first The amplitude of the second harmonic current. The angular frequency of the power grid. For the first The filter capacitors at each node.

[0034] Optionally, the acquisition module obtains the reactive power correction amount based on the total reactive power deficit of the current node and its neighboring nodes, and the steps include: The consistency error is obtained based on the difference between the total reactive power deficit of this node and its neighboring nodes; The reactive power correction amount is obtained by calculating the consistency error using PI control.

[0035] Optionally, the formula for calculating the consistency error in the acquisition module is:

[0036] in, For nodes Consistency error, For consistency gain, For capacity weights, For nodes Total reactive power deficit For nodes Adjacent nodes Total reactive power deficit.

[0037] Optionally, the formula for calculating the capacity weight in the acquisition module is:

[0038] in, For nodes Rated apparent power capacity, For nodes Adjacent nodes The rated apparent power capacity.

[0039] Optionally, the calculation formula for adjusting the virtual impedance using the reactive power correction amount in the acquisition module is as follows:

[0040] in, For adaptive inductors, For adaptive resistance value, For nodes The static inductance at that location, For nodes The static resistance value at that location, To correct the gain for the inductor, To correct the gain for the resistor, For nodes The reactive power correction at the location.

[0041] Optionally, the second calculation module uses an integral consensus algorithm to iteratively calculate the estimate of the network average voltage for each node under the virtual impedance to obtain the target value of the network average voltage. The steps include: Based on the virtual impedance, the virtual impedance caused by... shaft and Voltage drop across the shaft; Using the voltage drop to each node shaft and The voltage components of the axis are corrected to obtain the axis and the sum of the axes at each node. The accurate voltage components of the shaft; Based on each node shaft and The accurate voltage component of the axis is obtained by iteratively calculating the estimate of the average voltage of the entire network by each node using an integral consensus algorithm, thus obtaining the target value of the average voltage of the entire network.

[0042] Optionally, each node in the second computing module shaft and The formula for calculating the accurate voltage component of the shaft is:

[0043] in, For virtual nodes exist The accurate voltage components of the shaft, For virtual nodes exist The accurate voltage components of the shaft, For the inverter output current at Components on the axis, For the inverter output current at Components on the axis, The angular frequency of the power grid. For nodes The virtual resistance at that location, For nodes Virtual inductance at the location.

[0044] Optionally, the integral consensus algorithm in the second calculation module uses the following formula to iteratively calculate the estimate of the average voltage of the entire network by each node:

[0045] in, For nodes In time The local estimate of the average output voltage of the entire network. For nodes In time Actual measured output voltage Axial components, For integral consistency gain, In time From neighboring nodes The received estimate of its own average voltage across the entire network. In time Its current average voltage estimate, For nodes The set of adjacent nodes.

[0046] Optionally, the correction module obtains the voltage correction term for each node based on the target value, and the steps include: Based on the target value, the local voltage mismatch at each node is obtained; The voltage mismatch is calculated using PI control to obtain the voltage correction term.

[0047] Optionally, the calculation formula for the voltage correction term in the correction module is as follows:

[0048] in, For nodes Voltage correction term, For nodes of Controller transfer function This represents the local voltage mismatch. , For nodes Rated voltage, This is the target value for the average voltage across the entire network.

[0049] Optionally, the formula for calculating the target voltage reference value in the correction module is as follows:

[0050] in, The target voltage reference value, For nodes Rated voltage, For nodes The reactive power droop factor, For nodes Current reactive power output For virtual nodes exist The accurate voltage components of the shaft, For nodes Voltage correction term.

[0051] Optionally, the nodes in the correction module reactive power droop coefficient The following formula is used for control:

[0052] in, The initial reactive power droop coefficient is a constant. The gain is dynamically adjusted to accommodate the reactive power droop factor. This is the consistency error.

[0053] In another aspect, the present invention also provides a computing device, comprising: at least one processor and a memory; The memory is used to store one or more programs; When the one or more programs are executed by the one or more processors, a distributed collaborative control method for reactive power and voltage of bidirectional charging piles based on a consensus algorithm, as described above, is implemented.

[0054] In another aspect, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed, it implements the above-described method for distributed collaborative control of reactive power and voltage of bidirectional charging piles based on a consensus algorithm.

[0055] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention provides a distributed collaborative control method and system for reactive power and voltage of bidirectional charging piles based on a consensus algorithm. The method includes: using each bidirectional charging pile as a node, broadcasting the total reactive power deficit of the current node to neighboring nodes and receiving the total reactive power deficit from neighboring nodes; obtaining a reactive power correction amount based on the total reactive power deficit of the current node and neighboring nodes, and adjusting the virtual impedance using the reactive power correction amount; using an integral consensus algorithm to iteratively calculate the estimate of the average voltage of the entire network by each node under the virtual impedance to obtain the target value of the average voltage of the entire network; obtaining the voltage correction term for each node based on the target value, and using the voltage correction term to correct the voltage reference value of each node to obtain the target voltage reference value of each node. This invention, by employing neighbor node communication and a consensus algorithm, constructs an innovative distributed collaborative control mechanism, significantly improving the efficiency and reliability of reactive power optimization allocation and secondary voltage / frequency recovery of V2G charging piles in microgrids. Specifically, it has the following advantages: 1) Significantly improves system reliability and anti-interference capability Through a decentralized distributed architecture, each V2G charging station relies solely on local information exchange with neighboring nodes to achieve coordination, completely eliminating the single point of failure risk of "central controller failure leading to overall instability" inherent in centralized control. The sparse communication topology reduces dependence on global communication links; even if some communication links are interrupted, the remaining nodes can still maintain basic control functions through local consensus, significantly improving the system's resilience under complex operating conditions.

[0056] 2) Optimize control accuracy and dynamic performance to achieve multi-objective coordination. Leveraging the asymptotic convergence characteristics of consensus algorithms, each charging station can accurately correct frequency / voltage deviations based on local information consensus, resolving the steady-state value deviation problem caused by VSG droop control and stabilizing the frequency and voltage at the point of common coupling (PCC) near their rated values. By dynamically adjusting the reactive power droop coefficient, it is possible to achieve precise distribution of reactive power according to preset targets while suppressing transient power oscillations when multiple units are connected in parallel. This approach balances the advantages of VSG voltage support with coordinated accuracy and dynamic response speed.

[0057] 3) Reduce system costs and expansion barriers to support large-scale applications. Compared to centralized control, which requires significant investment in building a global communication network and a high-performance central controller, this solution significantly reduces investment in communication infrastructure through a local communication mode. Furthermore, the balanced computing power requirements of each node lower hardware costs. When adding a new charging station, only the communication links of adjacent nodes need to be connected and local coordination parameters configured; there is no need to reconstruct the global control logic, significantly improving the system's scalability.

[0058] 4) Enhance adaptability to distributed energy environments and improve energy utilization efficiency. Addressing the typical characteristics of distributed microgrids, such as fluctuating power output from renewable energy sources and random load changes, this solution shortens control response time through real-time local decision-making at each node, enabling rapid smoothing of power fluctuations. Precise power allocation and V2G charging / discharging scheduling promote local consumption of renewable energy sources like wind and solar power, reducing wind and solar curtailment, achieving synergistic optimization of the "source-load-storage" system, and improving the overall energy efficiency and economy of the microgrid.

[0059] Based on the aforementioned advantages, this technical solution offers comprehensive advantages in reliability, control precision, economy, and scalability, providing key technical support for the efficient participation of V2G charging piles in microgrid regulation, supporting the consumption of new energy sources, and enabling the large-scale grid connection of electric vehicles. In particular, the introduction of neighbor node communication and consensus algorithms significantly reduces the system's dependence on the central node while maintaining efficient collaboration, thereby improving the system's flexibility and robustness. Attached Figure Description

[0060] Figure 1 A schematic diagram of a microgrid architecture with multiple charging piles; Figure 2 A schematic diagram of a bidirectional charging pile and its control system; Figure 3 This is a schematic diagram of the current controller model structure; Figure 4 This is a schematic diagram of the voltage controller model structure; Figure 5 This is a schematic diagram of the primary controller model structure; Figure 6 This is a schematic diagram illustrating the principle of active power distribution curves under active power-frequency control. Figure 7 This is a flowchart illustrating the distributed collaborative control method for reactive power and voltage of bidirectional charging piles based on a consensus algorithm proposed in this invention. Figure 8 This is a detailed schematic diagram illustrating the steps of obtaining reactive power correction based on the total reactive power deficit of the local node and neighboring nodes as proposed in this invention. Figure 9 The present invention proposes Figure 7 A detailed step diagram of step S3; Figure 10 This is a detailed schematic diagram illustrating the steps of obtaining the voltage correction term for each node based on the target value proposed in this invention. Figure 11 This is a schematic diagram of the distributed collaborative control system for reactive power and voltage of bidirectional charging piles based on consensus algorithm proposed in this invention. Figure 12 This is a schematic diagram of the electronic device proposed in this invention. Detailed Implementation

[0061] This invention proposes a distributed collaborative control method for reactive power and voltage of bidirectional charging piles based on a consensus algorithm. Focusing on the core requirement of reactive power optimization allocation for V2G charging piles in microgrids, this invention constructs a complete technical solution encompassing "model building, hierarchical control, collaborative optimization, and implementation verification." The core relies on a distributed architecture and consensus algorithm to address the problems of strong dependence, low accuracy, and poor scalability inherent in traditional control methods. The system's layers work collaboratively, effectively addressing issues such as single-point failures in centralized control, steady-state deviations in reactive power allocation, and dynamic topology changes. This improves the accuracy of reactive power regulation and the stability of grid operation in the context of high penetration of new energy sources and large-scale integration of electric vehicles.

[0062] Example 1: A distributed collaborative control method for reactive power and voltage of bidirectional charging piles based on a consensus algorithm is proposed for secondary control in a microgrid with multiple charging piles connected in parallel. The microgrid architecture is as follows. Figure 1As shown, each bidirectional charging pile includes a primary control system, which can make timely and accurate adjustments to the output characteristics of the bidirectional charging pile. Communication between multiple bidirectional charging piles enables information exchange between nodes. Through secondary control, the frequency deviation of the primary frequency regulation can be compensated, while suppressing power oscillation between parallel charging piles and achieving reasonable power distribution.

[0063] The schematic diagram of the bidirectional charging pile and its control system is as follows: Figure 2 As shown, the control system mainly consists of a current controller, a voltage controller, a primary controller, and a secondary controller.

[0064] In practical applications, bidirectional charging piles are equipped with corresponding filters at their output terminals to reduce the switching frequency ripple of the output voltage. LC filters are typically used to eliminate harmonics. Additionally, there is the coupling inductance of the inverter. Figure 2 middle, For filtering inductors, For filtering resistors, For filtering capacitors, For coupled inductors, For coupling resistors, for The inverter output filter inductor current of the shaft is... for The inverter output filter inductor current of the shaft is... for The inverter output port voltage of the shaft. for The inverter output port voltage of the shaft. for The output capacitor voltage of the shaft, for The output capacitor voltage of the shaft, To output inductor current, Output inductor voltage, This is the grid-connected bus voltage. The output voltage frequency of the bidirectional charging pile, subscript Indicates the first One bidirectional charging station To correct the frequency, To correct the voltage, This refers to the AC output port voltage of the inverter. This refers to the AC side current of the inverter.

[0065] 1) Current controller model (e.g.) Figure 3 (As shown) Classic current controllers and voltage controllers mainly include PI control and proportional resonant control. The model of the current controller can be described by equations (1) to (2).

[0066] (1) (2) in, for Reference value for the inverter output port voltage of the shaft. for Reference value for the inverter output port voltage of the shaft. The system's rated angular frequency, The filter inductor, ignoring the inverter modulation process, can make , , for Reference value for the inverter output filter inductor current of the shaft. for Reference value for the inverter output filter inductor current of the shaft. for Actual measured value of the inverter output filter inductor current on the shaft. for Actual measured value of the inverter output filter inductor current on the shaft. The proportional gain of the current PI controller. is the integral coefficient of the current PI controller.

[0067] 2) Voltage controller model (e.g.) Figure 4 (As shown) The classic PI-based voltage controller model can be described by equations (3) to (4).

[0068] (3) (4) in, for Reference value for the inverter output filter inductor current of the shaft. for Reference value for the inverter output filter inductor current of the shaft. For current feedforward gain, for The output inductor current of the shaft, for The output inductor current of the shaft, The system's rated angular frequency, For nodes The filter capacitor, This is the reference value for the output capacitor voltage along the d-axis. This is the reference value for the output capacitor voltage on the q-axis. This represents the actual measured value of the output capacitor voltage along the d-axis. This is the actual measured value of the output capacitor voltage on the q-axis. For nodes The proportional gain of the voltage PI controller, For nodes The integral coefficient of the voltage PI controller.

[0069] 3) Primary controller model (e.g.) Figure 5 (As shown) The primary controller employs a virtual synchronous generator (VSG) for control. By simulating the operating characteristics of a synchronous generator (SG), VSG control, which enables the charging pile's output characteristics to have inertial support capabilities, has been extensively studied by scholars both domestically and internationally. The mathematical model of the SG mainly consists of two parts: the rotor and the stator. The rotor's motion equation can be given by Newton's second law, reflecting the inertia and damping characteristics of the SG rotor. Its expression is: (5) in, For rotational inertia, The damping coefficient is... The rated rotor angular frequency, This is the actual rotor angular frequency. For mechanical power, Electromagnetic power (i.e., output active power). For the angle of attack.

[0070] The prime mover adjustment equation is: (6) in, For a given amount of work, The difference coefficient, Rated rotor angular frequency, This is the actual rotor angular frequency.

[0071] Combining equations (5) and (6), we can obtain equations (7) and (8): (7) (8) in, The first-order inertial time constant, This is the active power-frequency droop factor.

[0072] 4) Secondary controller model Since the steady-state performance of the system is being analyzed, the dynamic performance of the charging pile controlled by VSG is not considered at this time. The active power-frequency relationship under steady state is as follows:

[0073] The active power distribution curve under active power-frequency control is as follows: Figure 6As shown, the reactive power-voltage droop characteristic curve is similar. When the load in the microgrid suddenly increases or decreases, in order to maintain the balance of active and reactive power, each charging pile needs to readjust its output power, and the system moves from the equilibrium point o to b or a. At this time, the active and reactive power in the system are balanced, but under the influence of the droop mechanism, the frequency / voltage deviates from the rated value, and secondary control is needed to restore the frequency / voltage. Secondary control can restore the frequency and voltage by readjusting the power reference value output by each charging pile to match the load power. To achieve frequency / voltage restoration while maintaining the active / reactive power distribution capability, the widely adopted distributed secondary control strategy is as follows:

[0074] in, For nodes rate of change of angular frequency The rate of change of the rated angular frequency. For nodes The rate of change of active power, For nodes The inertial constant, For nodes The rate of change of external control input.

[0075]

[0076] in, The control gain related to frequency deviation, For nodes and nodes Connection weights between them For nodes angular frequency, For nodes angular frequency, For nodes The frequency adjustment coefficient, The rated rotor angular frequency, The control gain related to power deviation, For nodes The inertial constant, For nodes The inertial constant, For nodes active power, For nodes The active power.

[0077] This application employs a bidirectional charging pile reactive power and voltage distributed collaborative control method based on a consensus algorithm for secondary control. Figure 7 As shown, it includes the following steps S1 to S4.

[0078] S1, with each bidirectional charging pile as a node, broadcasts the total reactive power deficit of this node to neighboring nodes and receives the total reactive power deficit of neighboring nodes.

[0079] Each bidirectional charging pile is regarded as a node in a distributed communication network, and the communication connection relationship between charging piles is defined through "adjacency topology".

[0080] The total reactive power deficit of each pile is calculated in real time based on the topology. : ,

[0081] in, For the first Total reactive power deficit of each node This represents a basic shortfall in reactive power. This is a shortfall due to lack of effective response. The total harmonic order is... For harmonic order, For the first The node of the first The amplitude of the second harmonic current. The angular frequency of the power grid. For the first The filter capacitors at each node.

[0082] S2, obtain the reactive power correction amount based on the total reactive power deficit of this node and neighboring nodes, and use the reactive power correction amount to adjust the virtual impedance.

[0083] In a further preferred embodiment, the reactive power correction amount is obtained based on the total reactive power deficit of the current node and its neighboring nodes, such as... Figure 8 As shown, the steps include: Step 1: Obtain the consistency error based on the difference between the total reactive power deficit of this node and its neighboring nodes; Step 2: PI control is used to calculate the reactive power correction amount for the consistency error.

[0084] In a further preferred embodiment, the formula for calculating the consistency error in step 1 is:

[0085] in, For nodes Consistency error, For consistency gain, For capacity weights, For nodes Total reactive power deficit For nodes Adjacent nodes Total reactive power deficit.

[0086] In a further preferred embodiment, the formula for calculating the capacity weight is:

[0087] in, For nodes Rated apparent power capacity, For nodes Adjacent nodes The rated apparent power capacity.

[0088] In a further optimized scheme, the formula for calculating the reactive power correction in step 2 is:

[0089] in, For nodes The reactive power correction at the location, The proportional gain of the PI controller. This represents the integral coefficient of the PI controller.

[0090] In a further preferred embodiment, the calculation formula for adjusting the virtual impedance using the reactive power correction amount is as follows:

[0091] in, For adaptive inductors, For adaptive resistance value, For nodes The static inductance at that location, For nodes The static resistance value at that location, To correct the gain for the inductor, To correct the gain for the resistor, For nodes The reactive power correction at the location.

[0092] S3, under the virtual impedance, the integral consensus algorithm is used to iteratively calculate the estimate of the average voltage of the whole network by each node to obtain the target value of the average voltage of the whole network.

[0093] In further optimized solutions, such as Figure 9 As shown, step S3 includes: S31, Based on the virtual impedance, obtain the virtual impedance caused by... shaft and Voltage drop across the shaft; S32, using the voltage drop to adjust each node shaft and The voltage components of the axis are corrected to obtain the axis and the sum of the axes at each node. The accurate voltage components of the shaft; S33, based on each node shaft and The accurate voltage component of the axis is obtained by iteratively calculating the estimate of the average voltage of the entire network by each node using an integral consensus algorithm, thus obtaining the target value of the average voltage of the entire network.

[0094] In a further optimized scheme, each node's shaft and The formula for calculating the accurate voltage component of the shaft is:

[0095] in, For virtual nodes exist The accurate voltage components of the shaft, For virtual nodes exist The accurate voltage components of the shaft, For the inverter output current at Components on the axis, For the inverter output current at Components on the axis, The angular frequency of the power grid. For nodes The virtual resistance at that location, For nodes Virtual inductance at the location.

[0096] Ideally, the average voltage across the entire network would be:

[0097] in, The voltage is the average voltage across the entire network under ideal conditions, and N is the total number of nodes in the network. For nodes The voltage at that point.

[0098] In a further preferred embodiment, the integral consensus algorithm performs iterative calculations to make the estimated voltage value of each node infinitely close to the true average voltage value of the entire network. The following formula is used to iteratively calculate the estimate of the average voltage of the entire network by each node:

[0099] in, For nodes In time The local estimate of the average output voltage of the entire network. For nodes In time Actual measured output voltage Axial components, For integral consistency gain, In time From neighboring nodes The received estimate of its own average voltage across the entire network. In time Its current average voltage estimate, For nodes The set of adjacent nodes.

[0100] S4. Based on the target value, obtain the voltage correction term for each node, and use the voltage correction term to correct the voltage reference value of each node to obtain the target voltage reference value for each node.

[0101] In a further preferred embodiment, the voltage correction term for each node is obtained based on the target value, such as... Figure 10 As shown, the steps include: Step 1: Obtain the local voltage mismatch at each node based on the target value; Step 2: Calculate the voltage mismatch using PI control to obtain the voltage correction term.

[0102] In a further preferred embodiment, the formula for calculating the voltage correction term is:

[0103] in, For nodes Voltage correction term, For nodes of Controller transfer function This represents the local voltage mismatch. , For nodes Rated voltage, This is the target value for the average voltage across the entire network.

[0104] In a further preferred embodiment, the formula for calculating the target voltage reference value is:

[0105] in, The target voltage reference value, For nodes Rated voltage, For nodes The reactive power droop factor, For nodes Current reactive power output For virtual nodes exist The accurate voltage components of the shaft, For nodes Voltage correction term.

[0106] In a further optimized scheme, to further improve the reactive power distribution effect and enable the droop coefficient to be corrected in real time according to the reactive power distribution deviation in the neighborhood, thereby improving the consistency and convergence speed of reactive power sharing, a dynamic adjustment mechanism for the reactive power droop coefficient is introduced. reactive power droop coefficient The following formula is used for control:

[0107] in, The initial reactive power droop coefficient is a constant. To dynamically adjust the gain for reactive power droop coefficient, the sensitivity of the droop coefficient to consistency error is adjusted. This is the consistency error.

[0108] Example 2: Based on the same inventive concept, this invention also provides a bidirectional charging pile reactive power and voltage distributed collaborative control system based on a consensus algorithm, such as... Figure 11 As shown, it includes: The first calculation module is used to broadcast the total reactive power deficit of this node to neighboring nodes and receive the total reactive power deficit of neighboring nodes, with each bidirectional charging pile as a node. The acquisition module is used to obtain the reactive power correction amount based on the total reactive power deficit of the current node and neighboring nodes, and to adjust the virtual impedance using the reactive power correction amount; The second calculation module is used to iteratively calculate the estimate of the average voltage of the entire network by each node under the virtual impedance using an integral consensus algorithm to obtain the target value of the average voltage of the entire network. The correction module is used to obtain the voltage correction term for each node based on the target value, and to correct the voltage reference value of each node using the voltage correction term to obtain the target voltage reference value for each node.

[0109] In a further preferred embodiment, the total reactive power deficit in the first calculation module includes reactive power deficit and basic reactive power deficit, wherein the reactive power deficit is related to the filter capacitor, harmonic order, and amplitude of harmonic current of the corresponding node.

[0110] In a further preferred embodiment, the formula for calculating the total reactive power deficit in the first calculation module is as follows: ,

[0111] in, For the first Total reactive power deficit of each node This represents a basic shortfall in reactive power. This is a shortfall due to lack of effective response. The total harmonic order is... For harmonic order, For the first The node of the first The amplitude of the second harmonic current. The angular frequency of the power grid. For the first The filter capacitors at each node.

[0112] In a further preferred embodiment, the acquisition module obtains the reactive power correction amount based on the total reactive power deficit of the current node and its neighboring nodes, and the steps include: The consistency error is obtained based on the difference between the total reactive power deficit of this node and its neighboring nodes; The reactive power correction amount is obtained by calculating the consistency error using PI control.

[0113] In a further preferred embodiment, the formula for calculating the consistency error in the acquisition module is:

[0114] in, For nodes Consistency error, For consistency gain, For capacity weights, For nodes Total reactive power deficit For nodes Adjacent nodes Total reactive power deficit.

[0115] In a further preferred embodiment, the formula for calculating the capacity weight in the acquisition module is:

[0116] in, For nodes Rated apparent power capacity, For nodes Adjacent nodes The rated apparent power capacity.

[0117] In a further preferred embodiment, the calculation formula for adjusting the virtual impedance using the reactive power correction amount is as follows:

[0118] in, For adaptive inductors, For adaptive resistance value, For nodes The static inductance at that location, For nodes The static resistance value at that location, To correct the gain for the inductor, To correct the gain for the resistor, For nodes The reactive power correction at the location.

[0119] In a further preferred embodiment, the second calculation module uses an integral consensus algorithm to iteratively calculate the estimate of the average voltage of the entire network by each node under the virtual impedance to obtain the target value of the average voltage of the entire network. The steps include: Based on the virtual impedance, the virtual impedance caused by... shaft and Voltage drop across the shaft; Using the voltage drop to each node shaft and The voltage components of the axis are corrected to obtain the axis and the sum of the axes at each node. The accurate voltage components of the shaft; Based on each node shaft and The accurate voltage component of the axis is obtained by iteratively calculating the estimate of the average voltage of the entire network by each node using an integral consensus algorithm, thus obtaining the target value of the average voltage of the entire network.

[0120] In a further preferred embodiment, the nodes in the second computing module shaft and The formula for calculating the accurate voltage component of the shaft is:

[0121] in, For virtual nodes exist The accurate voltage components of the shaft, For virtual nodes exist The accurate voltage components of the shaft, For the inverter output current at Components on the axis, For the inverter output current at Components on the axis, The angular frequency of the power grid. For nodes The virtual resistance at that location, For nodes Virtual inductance at the location.

[0122] In a further preferred embodiment, the integral consensus algorithm in the second calculation module uses the following formula to iteratively calculate the estimate of the average voltage of the entire network by each node:

[0123] in, For nodes In time The local estimate of the average output voltage of the entire network. For nodes In time Actual measured output voltage Axial components, For integral consistency gain, In time From neighboring nodes The received estimate of its own average voltage across the entire network. In time Its current average voltage estimate, For nodes The set of adjacent nodes.

[0124] In a further preferred embodiment, the correction module obtains the voltage correction term for each node based on the target value, and the steps include: Based on the target value, the local voltage mismatch at each node is obtained; The voltage mismatch is calculated using PI control to obtain the voltage correction term.

[0125] In a further preferred embodiment, the calculation formula for the voltage correction term in the correction module is as follows:

[0126] in, For nodes Voltage correction term, For nodes of Controller transfer function This represents the local voltage mismatch. , For nodes Rated voltage, This is the target value for the average voltage across the entire network.

[0127] In a further preferred embodiment, the formula for calculating the target voltage reference value in the correction module is as follows:

[0128] in, The target voltage reference value, For nodes Rated voltage, For nodes The reactive power droop factor, For nodes Current reactive power output For virtual nodes exist The accurate voltage components of the shaft, For nodes Voltage correction term.

[0129] In a further preferred embodiment, the nodes in the correction module reactive power droop coefficient The following formula is used for control:

[0130] in, The initial reactive power droop coefficient is a constant. The gain is dynamically adjusted to accommodate the reactive power droop factor. This is the consistency error.

[0131] Example 3 like Figure 12 As shown, the present invention also provides an electronic device, which may be a computer device, a microcontroller device, a smart mobile device, etc. The electronic device in this embodiment may include a processor, a memory, a transceiver component, etc. The memory, processor, and transceiver component are connected via a bus; the memory can be used to store executable programs, and an exemplary executable program may include instructions; the processor is used to execute the instructions stored in the memory. The memory can also be used to store data, which can be accessed and / or modified when instructions are executed.

[0132] The processor may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, and it is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions in the storage medium to realize the corresponding method flow or corresponding function, so as to realize the steps of the bidirectional charging pile reactive power and voltage distributed collaborative control method based on consensus algorithm in the above embodiment.

[0133] Example 4 Based on the same inventive concept, this invention also provides a readable storage medium, specifically an electronic device readable storage medium (Memory). This readable storage medium is a memory device within an electronic device used to store programs and data. It is understood that the storage medium here can include both built-in storage media within the electronic device and extended storage media supported by the electronic device. The storage medium provides storage space, which stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more executable programs (including program code). It should be noted that the storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. Loading and executing one or more instructions stored in the storage medium by the processor can implement the steps of the bidirectional charging pile reactive power and voltage distributed collaborative control method based on a consensus algorithm in the above embodiments.

[0134] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0135] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0136] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1The function specified in one or more boxes.

[0137] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0138] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of the claims of the present invention pending approval.

Claims

1. A distributed collaborative control method for reactive power and voltage of bidirectional charging piles based on a consensus algorithm, characterized in that, include: Each bidirectional charging pile is a node, broadcasting the total reactive power deficit of the node to neighboring nodes and receiving the total reactive power deficit of neighboring nodes; The reactive power correction amount is obtained based on the total reactive power deficit of this node and neighboring nodes, and the virtual impedance is adjusted using the reactive power correction amount; Under the virtual impedance, the integral consensus algorithm is used to iteratively calculate the estimate of the average voltage of the entire network by each node to obtain the target value of the average voltage of the entire network. Based on the target value, the voltage correction term for each node is obtained, and the voltage reference value of each node is corrected using the voltage correction term to obtain the target voltage reference value for each node.

2. The distributed collaborative control method for reactive power and voltage of bidirectional charging piles based on consensus algorithm as described in claim 1, characterized in that, The total reactive power deficit includes reactive power deficit and basic reactive power deficit. The reactive power deficit is related to the filter capacitor, harmonic order, and amplitude of harmonic current at the corresponding node.

3. The distributed collaborative control method for reactive power and voltage of bidirectional charging piles based on consensus algorithm according to claim 2, characterized in that, The formula for calculating the total reactive power deficit is as follows: in, For the first Total reactive power deficit of each node This represents a basic shortfall in reactive power. This is a shortfall due to lack of effective work. The total harmonic order is... For harmonic order, For the first The node of the first The amplitude of the second harmonic current. The angular frequency of the power grid. For the first The filter capacitors at each node.

4. The distributed collaborative control method for reactive power and voltage of bidirectional charging piles based on consensus algorithm according to claim 1, characterized in that, The steps for obtaining the reactive power correction amount based on the total reactive power deficit of this node and its neighboring nodes include: The consistency error is obtained based on the difference between the total reactive power deficit of this node and its neighboring nodes; The reactive power correction amount is obtained by calculating the consistency error using PI control.

5. The distributed collaborative control method for reactive power and voltage of bidirectional charging piles based on consensus algorithm according to claim 4, characterized in that, The formula for calculating the consistency error is: in, For nodes Consistency error, For consistency gain, For capacity weights, For nodes Total reactive power deficit For nodes Adjacent nodes Total reactive power deficit.

6. The distributed collaborative control method for reactive power and voltage of bidirectional charging piles based on consensus algorithm as described in claim 5, characterized in that, The formula for calculating the capacity weight is: in, For nodes Rated apparent power capacity, For nodes Adjacent nodes The rated apparent power capacity.

7. The distributed collaborative control method for reactive power and voltage of bidirectional charging piles based on consensus algorithm according to claim 1, characterized in that, The calculation formula for adjusting the virtual impedance using the reactive power correction amount is as follows: in, For adaptive inductors, For adaptive resistance value, For nodes The static inductance at that location, For nodes The static resistance value at that location, To correct the gain for the inductor, To correct the gain for the resistor, For nodes The reactive power correction at the location.

8. The distributed collaborative control method for reactive power and voltage of bidirectional charging piles based on consensus algorithm as described in claim 1 or 7, characterized in that, The step of iteratively calculating the estimate of the network average voltage by each node using an integral consensus algorithm under the virtual impedance to obtain the target value of the network average voltage includes: Based on the virtual impedance, the virtual impedance caused by... shaft and Voltage drop across the shaft; Using the voltage drop to each node shaft and The voltage components of the axis are corrected to obtain the axis and the sum of the axes at each node. The accurate voltage component of the shaft; Based on each node shaft and The accurate voltage component of the axis is obtained by iteratively calculating the estimate of the average voltage of the entire network by each node using an integral consensus algorithm, thus obtaining the target value of the average voltage of the entire network.

9. The distributed collaborative control method for reactive power and voltage of bidirectional charging piles based on consensus algorithm as described in claim 8, characterized in that, The formulas for calculating the axis and the accurate voltage components of each axis are as follows: in, For virtual nodes exist The accurate voltage components of the shaft, For virtual nodes exist The accurate voltage components of the shaft, For the inverter output current at Components on the axis, For the inverter output current at Components on the axis, The angular frequency of the power grid. For nodes The virtual resistance at that location, For nodes Virtual inductance at the location.

10. The distributed collaborative control method for reactive power and voltage of bidirectional charging piles based on consensus algorithm according to claim 8, characterized in that, The integral consensus algorithm uses the following formula to iteratively calculate each node's estimate of the average voltage of the entire network: in, For nodes In time The local estimate of the average output voltage of the entire network. For nodes In time Actual measured output voltage Axial components, For integral consistency gain, In time From neighboring nodes The received estimate of its own average voltage across the entire network. In time Its current average voltage estimate, For nodes The set of adjacent nodes.

11. The distributed collaborative control method for reactive power and voltage of bidirectional charging piles based on consensus algorithm according to claim 1, characterized in that, The step of obtaining the voltage correction term for each node based on the target value includes: Based on the target value, the local voltage mismatch at each node is obtained; The voltage mismatch is calculated using PI control to obtain the voltage correction term.

12. The distributed collaborative control method for reactive power and voltage of bidirectional charging piles based on consensus algorithm as described in claim 11, characterized in that, The formula for calculating the voltage correction term is: in, For nodes Voltage correction term, For nodes of Controller transfer function This represents the local voltage mismatch. , For nodes Rated voltage, This is the target value for the average voltage across the entire network.

13. The distributed collaborative control method for reactive power and voltage of bidirectional charging piles based on consensus algorithm according to claim 1 or 4, characterized in that, The formula for calculating the target voltage reference value is as follows: Among them, is the target voltage reference value, is the rated voltage of node , is the reactive power droop coefficient of node , is the reactive power currently output by node , is the accurate voltage component of the virtual node on the axis, is the voltage correction term of node .

14. The distributed collaborative control method for reactive power and voltage of bidirectional charging piles based on consensus algorithm according to claim 13, characterized in that, The reactive power droop coefficient of the node is controlled by the following formula: in, The initial reactive power droop coefficient is a constant. The gain is dynamically adjusted to accommodate the reactive power droop factor. This is the consistency error.

15. A bidirectional charging pile reactive power and voltage distributed collaborative control system based on a consensus algorithm, characterized in that, include: The first calculation module is used to broadcast the total reactive power deficit of this node to neighboring nodes and receive the total reactive power deficit of neighboring nodes, with each bidirectional charging pile as a node. The acquisition module is used to obtain the reactive power correction amount based on the total reactive power deficit of the current node and neighboring nodes, and to adjust the virtual impedance using the reactive power correction amount; The second calculation module is used to iteratively calculate the estimate of the average voltage of the entire network by each node under the virtual impedance using an integral consensus algorithm to obtain the target value of the average voltage of the entire network. The correction module is used to obtain the voltage correction term for each node based on the target value, and to correct the voltage reference value of each node using the voltage correction term to obtain the target voltage reference value for each node.

16. The bidirectional charging pile reactive power and voltage distributed collaborative control system based on consensus algorithm according to claim 15, characterized in that, The total reactive power deficit in the first calculation module includes reactive power deficit and basic reactive power deficit. The reactive power deficit is related to the filter capacitor, harmonic order, and amplitude of harmonic current of the corresponding node.

17. The bidirectional charging pile reactive power and voltage distributed collaborative control system based on consensus algorithm according to claim 16, characterized in that, The formula for calculating the total reactive power deficit in the first calculation module is as follows: in, For the first Total reactive power deficit of each node This represents a basic shortfall in reactive power. This is a shortfall due to lack of effective response. The total harmonic order is... For harmonic order, For the first The node of the first The amplitude of the second harmonic current. The angular frequency of the power grid. For the first The filter capacitors at each node.

18. The bidirectional charging pile reactive power and voltage distributed collaborative control system based on consensus algorithm according to claim 15, characterized in that, The acquisition module obtains the reactive power correction amount based on the total reactive power deficit of the current node and its neighboring nodes, and the steps include: The consistency error is obtained based on the difference between the total reactive power deficit of this node and its neighboring nodes; The reactive power correction amount is obtained by calculating the consistency error using PI control.

19. The bidirectional charging pile reactive power and voltage distributed collaborative control system based on consensus algorithm according to claim 18, characterized in that, The formula for calculating the consistency error in the acquisition module is as follows: in, For nodes Consistency error, For consistency gain, For capacity weights, For nodes Total reactive power deficit For nodes Adjacent nodes Total reactive power deficit.

20. The bidirectional charging pile reactive power and voltage distributed collaborative control system based on consensus algorithm according to claim 19, characterized in that, The formula for calculating the capacity weight in the acquisition module is as follows: in, For nodes Rated apparent power capacity, For nodes Adjacent nodes The rated apparent power capacity.

21. The bidirectional charging pile reactive power and voltage distributed collaborative control system based on consensus algorithm according to claim 15, characterized in that, The calculation formula for adjusting the virtual impedance using the reactive power correction amount in the acquisition module is as follows: in, For adaptive inductors, For adaptive resistance value, For nodes The static inductance at that location, For nodes The static resistance value at that location, To correct the gain for the inductor, To correct the gain for the resistor, For nodes The reactive power correction at the location.

22. The bidirectional charging pile reactive power and voltage distributed collaborative control system based on consensus algorithm according to claim 15 or 21, characterized in that, The second calculation module uses an integral consensus algorithm to iteratively calculate the estimate of the average voltage of the entire network by each node under the virtual impedance to obtain the target value of the average voltage of the entire network. The steps include: Based on the virtual impedance, the virtual impedance caused by... shaft and Voltage drop across the shaft; Using the voltage drop to each node shaft and The voltage components of the axis are corrected to obtain the axis and the sum of the axes at each node. The accurate voltage component of the shaft; Based on each node shaft and The accurate voltage component of the axis is obtained by iteratively calculating the estimate of the average voltage of the entire network by each node using an integral consensus algorithm, thus obtaining the target value of the average voltage of the entire network.

23. The bidirectional charging pile reactive power and voltage distributed collaborative control system based on consensus algorithm according to claim 22, characterized in that, The calculation formulas for the axes and accurate voltage components of each node in the second calculation module are as follows: in, For virtual nodes exist The accurate voltage components of the shaft, For virtual nodes exist The accurate voltage components of the shaft, For the inverter output current at Components on the axis, For the inverter output current at Components on the axis, The angular frequency of the power grid. For nodes The virtual resistance at that location, For nodes Virtual inductance at the location.

24. The bidirectional charging pile reactive power and voltage distributed collaborative control system based on consensus algorithm according to claim 22, characterized in that, The integral consensus algorithm in the second calculation module uses the following formula to iteratively calculate the estimate of the average voltage of the entire network by each node: in, For nodes In time The local estimate of the average output voltage of the entire network. For nodes In time Actual measured output voltage Axial components, For integral consistency gain, In time From neighboring nodes The received estimate of its own average voltage across the entire network. In time Its current average voltage estimate, For nodes The set of adjacent nodes.

25. The bidirectional charging pile reactive power and voltage distributed collaborative control system based on consensus algorithm according to claim 15, characterized in that, The correction module obtains the voltage correction term for each node based on the target value, and the steps include: Based on the target value, the local voltage mismatch at each node is obtained; The voltage mismatch is calculated using PI control to obtain the voltage correction term.

26. The bidirectional charging pile reactive power and voltage distributed collaborative control system based on consensus algorithm according to claim 25, characterized in that, The calculation formula for the voltage correction term in the correction module is as follows: in, For nodes Voltage correction term, For nodes of Controller transfer function This represents the local voltage mismatch. , For nodes Rated voltage, This is the target value for the average voltage across the entire network.

27. The distributed collaborative control method for reactive power and voltage of bidirectional charging piles based on consensus algorithm as described in claim 15 or 18, characterized in that, The formula for calculating the target voltage reference value in the correction module is as follows: in, The target voltage reference value, For nodes Rated voltage, For nodes The reactive power droop factor, For nodes Current reactive power output For virtual nodes exist The accurate voltage components of the shaft, For nodes Voltage correction term.

28. The distributed collaborative control method for reactive power and voltage of bidirectional charging piles based on consensus algorithm according to claim 27, characterized in that, The reactive power droop coefficient of the nodes in the correction module is controlled by the following formula: in, The initial reactive power droop coefficient is a constant. The gain is dynamically adjusted to accommodate the reactive power droop factor. This is the consistency error.

29. A computer device, characterized in that, include: At least one processor and memory; The memory and processor are connected via a bus; The memory is used to store one or more programs; When the one or more programs are executed by the at least one processor, the distributed collaborative control method for reactive power and voltage of bidirectional charging piles based on the consensus algorithm as described in any one of claims 1 to 14 is implemented.

30. A computer-readable storage medium, characterized in that, It contains an execution program, which, when executed, implements the bidirectional charging pile reactive power and voltage distributed collaborative control method based on the consensus algorithm as described in any one of claims 1 to 14.

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