Voltage control strategy determination method and device and electronic equipment

Abstract

The invention discloses a voltage control strategy determination method and device and electronic equipment. The method comprises the following steps: controlling reactive compensation equipment of power generation equipment according to an initial control strategy, and determining a voltage measurement value of the power generation equipment at a grid-connected point; determining an electrical parameter prediction value of the power generation equipment based on the voltage measurement value; and determining a target control strategy for the reactive compensation equipment based on the electric parameter predicted value. The technical problem that the grid-connected point voltage stability of the new energy power generation equipment is not ideal in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the field of power system control, and in particular to a method, device and electronic equipment for determining a voltage control strategy. Background Art

[0002] In order to promote the optimization and upgrading of the energy industry and achieve clean and low-carbon development, the new energy industry has achieved leapfrog development, and the proportion of new energy installed capacity has increased. Wind power generation is one of the most promising forms of power generation in the development of renewable energy. However, wind power generation has significant randomness and volatility. The uncertainty of wind speed makes the wind power output change greatly in a short period of time, which in turn causes the voltage at the wind farm grid connection point to fluctuate greatly, posing a threat to the stability of the grid voltage and bringing huge challenges to the optimization and control of the power system.

[0003] To meet the above challenges, wind farms are usually equipped with a variety of voltage regulating equipment. By controlling various equipment, the reactive output of multiple voltage regulating equipment in wind farms can be finely controlled to solve the problem that the voltage at the wind farm outlet is easily affected by the uncertainty of wind power and fluctuates rapidly. In the prior art, the voltage control method at the wind farm grid connection point mostly adopts a control strategy based on the maximum reactive margin. This control strategy has problems such as low control accuracy, poor robustness and real-time adaptability. It does not effectively utilize the reactive compensation equipment resources in the wind farm, nor does it coordinate the optimal configuration of the reactive compensation equipment resources in the wind farm, resulting in poor stability of the voltage at the wind farm grid connection point.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present application provide a method, device and electronic device for determining a voltage control strategy to at least solve the technical problem of unsatisfactory voltage stability at the grid connection point of new energy power generation equipment existing in the related art.

[0006] According to one aspect of an embodiment of the present application, a method for determining a voltage control strategy is provided, including: controlling a reactive compensation device of a power generation device according to an initial control strategy to determine a voltage measurement value of the power generation device at a grid connection point; determining an electrical parameter prediction value of the power generation device based on the voltage measurement value; and determining a target control strategy for the reactive compensation device based on the electrical parameter prediction value.

[0007] Optionally, the reactive compensation equipment includes multiple types of compensation equipment, which correspond to different reactive compensation methods respectively. The electrical parameter prediction values ​​include voltage prediction values ​​and prediction adjustment amounts corresponding to the multiple types of compensation equipment respectively. Based on the voltage measurement values, the electrical parameter prediction values ​​of the power generation equipment are determined, including: determining a voltage sensitivity matrix, wherein the voltage sensitivity matrix represents the degree of influence of active power changes and reactive power changes on the power generation equipment respectively; based on the voltage sensitivity matrix and the voltage measurement values, determining the voltage prediction values ​​and the prediction adjustment amounts corresponding to the multiple types of compensation equipment respectively.

[0008] Optionally, the electrical parameter prediction value includes a voltage prediction value, and based on the electrical parameter prediction value, a target control strategy for the reactive compensation device is determined, including: based on the electrical parameter prediction value, determining a scheduling objective function that balances a first objective function and a second objective function, wherein the first objective function is used to represent the deviation between the voltage prediction value and a reference voltage, and the second objective function is used to represent the ability of the power generation equipment to maintain a reactive margin; and using the scheduling objective function to obtain a target control strategy.

[0009] Optionally, the reactive compensation equipment includes multiple types of compensation equipment, and the multiple types of compensation equipment correspond to different reactive compensation methods respectively. The electrical parameter prediction value also includes the reactive prediction adjustment amount of the power generation equipment, and the prediction adjustment amount corresponding to the multiple types of compensation equipment respectively. Based on the electrical parameter prediction value, a scheduling objective function that balances the first objective function and the second objective function is determined, including: determining constraints based on the voltage prediction value, the reactive prediction adjustment amount, and the prediction adjustment amount corresponding to the multiple types of compensation equipment respectively; determining the scheduling objective function based on the constraints, the first objective function, and the second objective function.

[0010] Optionally, the multiple types of compensation equipment include static VAR compensators and reactive power supply equipment. Based on the voltage prediction value, the reactive power prediction adjustment amount, and the prediction adjustment amounts corresponding to the multiple types of compensation equipment, constraints are determined, including: based on the active power injection amount and the reactive power injection amount of the predetermined node in the power generation equipment, a first constraint condition is obtained so that the power of the predetermined node is balanced; based on the voltage prediction value, a second constraint condition representing the voltage range of the grid connection point is determined; based on the prediction adjustment amount corresponding to the reactive power supply equipment, a third constraint condition representing the limit on the number of switching times of the reactive power supply equipment is determined; based on the prediction adjustment amount corresponding to the static VAR compensator, a fourth constraint condition representing the reactive output limit of the static VAR compensator is determined; based on the reactive power prediction adjustment amount, a fifth constraint condition representing the reactive processing limit of the power generation equipment is determined.

[0011] Optionally, the multiple types of reactive power compensation equipment also include a static VAR compensator, and the method further includes: determining a reactive power margin deviation of the static VAR compensator based on a predicted adjustment amount and a predetermined optimal output corresponding to the static VAR compensator; and determining a second objective function based on the margin deviation.

[0012] Optionally, determining a scheduling objective function that balances the first objective function and the second objective function includes: when the electrical parameter prediction value includes prediction values ​​corresponding to multiple prediction moments respectively, determining the weight values ​​corresponding to the multiple prediction moments respectively based on the time sequence of the multiple prediction moments; determining the first target value and the second target value corresponding to the multiple prediction moments respectively, wherein the first target value is the optimal value of the first objective function at the corresponding prediction moment, and the second target value is the optimal value of the second objective function at the corresponding prediction moment; processing the first objective function and the second objective function according to the first target values, the second target values, and the weight values ​​respectively corresponding to the multiple prediction moments to determine the scheduling objective function.

[0013] According to another aspect of an embodiment of the present application, a voltage control strategy determination device is provided, including: a voltage measurement value determination module, which is used to control the reactive compensation equipment of the power generation equipment according to the initial control strategy, and determine the voltage measurement value of the power generation equipment at the grid connection point; an electrical parameter prediction value determination module, which determines the electrical parameter prediction value of the power generation equipment based on the voltage measurement value; and a target control strategy determination module, which is used to determine the target control strategy for the reactive compensation equipment based on the electrical parameter prediction value.

[0014] According to another aspect of an embodiment of the present application, a non-volatile storage medium is provided, wherein the non-volatile storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing any one of the voltage control strategy determination methods.

[0015] According to another aspect of an embodiment of the present application, an electronic device is provided, comprising: one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by one or more processors, the one or more processors implement any one of the voltage control strategy determination methods.

[0016] In the embodiment of the present application, the reactive power compensation equipment of the power generation equipment is controlled according to the initial control strategy to determine the voltage measurement value of the power generation equipment at the grid connection point; based on the voltage measurement value, the predicted value of the electrical parameter of the power generation equipment is determined; based on the predicted value of the electrical parameter, the target control strategy for the reactive power compensation equipment is determined. The purpose of reducing the voltage fluctuation of the grid connection point by predicting the grid connection point voltage and controlling the various reactive power compensation equipment of the power generation equipment is achieved, and the technical effect of improving the voltage stability of the grid connection point of the new energy power generation equipment is achieved, thereby solving the technical problem of unsatisfactory voltage stability of the grid connection point of the new energy power generation equipment existing in the related art. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0018] Figure 1 is a flow chart of an optional voltage control strategy determination method provided according to an embodiment of the present application;

[0019] Figure 2 It is a flowchart of an optional method for determining a voltage control strategy provided in an embodiment of the present application;

[0020] Figure 3 is an active power output diagram of an optional voltage control strategy determination method provided in an embodiment of the present application;

[0021] Figure 4 is a first result diagram of an optional voltage control strategy determination method provided according to an embodiment of the present application;

[0022] Figure 5 is a second result diagram of an optional voltage control strategy determination method provided according to an embodiment of the present application;

[0023] Figure 6 is a third result diagram of an optional voltage control strategy determination method provided according to an embodiment of the present application;

[0024] Figure 7 is a fourth result diagram of an optional voltage control strategy determination method provided according to an embodiment of the present application;

[0025] Figure 8 is a first schematic diagram of an optional voltage control strategy determination method provided according to an embodiment of the present application;

[0026] Fig. 9 is a second schematic diagram of an optional voltage control strategy determination method provided according to an embodiment of the present application;

[0027] Fig.10 It is a schematic diagram of an optional voltage control strategy determination device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0029] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0030] For the convenience of description, some nouns or terms involved in the embodiments of the present application are explained below:

[0031] The grid connection point voltage refers to the voltage at the connection point between renewable energy power generation facilities such as wind farms and photovoltaic power stations and the grid in the power system. It is the key point for interaction between wind farms or photovoltaic power stations and the main power grid.

[0032] A weak sending-end system (WSS) refers to an area in a power system where the power source is far away from the load center and electric energy is transmitted to the load center through long-distance, low-impedance transmission lines or transformers. It has problems such as poor voltage stability, insufficient reactive power support, and weak dynamic response capability.

[0033] SVC (Static Var Compensator) is a fast-response reactive power compensation device that can suppress rapid changes in voltage and reduce the impact of voltage drops by adjusting the output reactive power in real time, so that the power grid can quickly recover stability and has a strong dynamic support capability for the power grid voltage.

[0034] According to an embodiment of the present application, a method embodiment for determining a voltage control strategy is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0035] Figure 1 is a flow chart of an optional voltage control strategy determination method provided according to an embodiment of the present application, such as Figure 1 As shown, the method comprises the following steps:

[0036] Step S102, controlling the reactive power compensation device of the power generation equipment according to the initial control strategy to determine the voltage measurement value of the power generation equipment at the grid connection point;

[0037] It can be understood that according to the initial control strategy, the reactive compensation equipment of the power generation equipment is controlled, and after the control strategy of the reactive compensation equipment is executed, the grid connection point voltage of the power generation equipment is measured to obtain the voltage measurement value of the grid connection point. Executing the control strategy of the reactive compensation equipment according to the grid connection point voltage of the power generation equipment can effectively control the volatility of the grid connection point voltage. Measuring the grid connection point voltage after executing the control strategy can ensure the accuracy of the measurement results and provide data support for the subsequent formulation of the reactive compensation equipment control strategy.

[0038] Optionally, the above-mentioned power generation equipment is a new energy power generation equipment, such as wind power generation, photovoltaic power generation, etc. Due to the intermittent and uncertain nature of natural resources, such as wind speed and light intensity, the frequency and voltage fluctuations of the power grid are large, affecting the stability and power quality of the power system. Therefore, it is necessary to control the voltage fluctuation of the power grid by reasonably controlling the reactive power compensation equipment of the power generation equipment to ensure the safety and reliability of the power system and maximize the utilization efficiency of new energy.

[0039] Step S104, determining the predicted value of the electrical parameter of the power generation equipment based on the voltage measurement value;

[0040] It can be understood that the predicted values ​​of the electrical parameters of the power generation equipment can be obtained by using the voltage prediction model according to the voltage measurement value of the grid connection point. By combining the actual voltage measurement value and the voltage prediction model, the accuracy of the predicted values ​​of the electrical parameters of the power generation equipment can be improved, the control effect of the subsequent reactive compensation equipment control strategy can be improved, and the stability of the voltage at the grid connection point can be ensured.

[0041] In an optional embodiment, the reactive compensation equipment includes multiple types of compensation equipment, and the multiple types of compensation equipment correspond to different reactive compensation methods respectively. The electrical parameter prediction values ​​include voltage prediction values ​​and prediction adjustment amounts corresponding to the multiple types of compensation equipment respectively. Based on the voltage measurement values, the electrical parameter prediction values ​​of the power generation equipment are determined, including: determining a voltage sensitivity matrix, wherein the voltage sensitivity matrix represents the degree of influence of active power changes and reactive power changes on the power generation equipment respectively; based on the voltage sensitivity matrix and the voltage measurement values, determining the voltage prediction values ​​and the prediction adjustment amounts corresponding to the multiple types of compensation equipment respectively.

[0042] It can be understood that the reactive power compensation equipment of the power generation equipment includes multiple types of compensation equipment, such as capacitor / reactor groups, SVC (i.e., static VAR compensator), doubly-fed induction generators and permanent magnet synchronous generators, etc. Each compensation equipment has a different reactive power compensation method. When controlling the grid connection point voltage, the voltage sensitivity matrix is ​​first determined, and a voltage prediction model based on voltage sensitivity is constructed. Based on the above-mentioned grid connection point voltage measurement value and the voltage prediction model based on voltage sensitivity, the voltage prediction value and the reactive power prediction adjustment amount corresponding to the multiple types of compensation equipment are obtained. The above-mentioned voltage sensitivity matrix can be used to represent the degree of influence of active power changes and reactive power changes on the voltage of the power generation equipment. By constructing a voltage prediction model based on voltage sensitivity, the changing trend of the voltage at the grid connection point of the power generation equipment can be more accurately predicted, and then the reactive compensation equipment can be controlled to perform reactive output and reduce the volatility of the grid connection point voltage.

[0043] Optionally, the reactive power compensation equipment includes multiple types of compensation equipment, such as capacitor / reactor group, SVC, doubly fed induction generator and permanent magnet synchronous generator (i.e. reactive power compensation of the power generation equipment itself), etc. Each compensation equipment has different reactive power compensation methods. The capacitor group in the capacitor / reactor group can provide capacitive reactive power, the reactor group can absorb inductive reactive power, the capacitor / reactor group (i.e. reactive power supply equipment) has a large adjustment capacity and a response time of minutes, and is a discrete reactive power compensation device. SVC is a fast-response reactive power compensation device based on power electronics technology, which can quickly adjust the output of reactive power. The SVC has a small adjustment capacity and a response time of milliseconds. It is a continuous reactive power compensation device and is a valuable dynamic reactive resource in the event of a fault. The doubly fed induction generator and the permanent magnet synchronous generator belong to the reactive power compensation of the power generation equipment itself, and their reactive power compensation is related to the converter capacity, and the response time is in seconds. Among them, the doubly fed induction generator performs reactive power compensation by controlling the inverter on the rotor side, and the permanent magnet synchronous generator performs reactive power compensation by a full-power inverter. By coordinating and controlling multiple types of reactive power compensation equipment, the adjustment capability of each device can be fully utilized, the frequent operation of the equipment can be reduced, and the equipment life and system economy can be improved.

[0044] Optionally, the bus voltage of the power generation equipment can be obtained by the power flow calculation method. Assuming that the structure of the power generation equipment remains unchanged, the sensitivity matrix obtained by linearizing the power flow equation can be used to predict the system voltage, which effectively simplifies the calculation while ensuring the prediction accuracy. The Newton method is used to calculate the power flow of the power generation equipment at time t, and the formula is obtained:

[0045]

[0046] Among them, ΔP represents the error vector of active power; ΔQ represents the error vector of reactive power; Δθ represents the change matrix of voltage phase angle; ΔU represents the change matrix of voltage effective value; U(t) -1 The inverse matrix of the matrix representing the change in voltage effective value.

[0047] The Jacobian matrix J in the above formula is:

[0048]

[0049] Among them, H, R, K, and L are block matrices in the Jacobian matrix respectively.

[0050] Multiply both sides of the power flow calculation formula by the inverse of the Jacobian matrix J -1 , we get the formula:

[0051]

[0052] Among them, A, B, C, and D are block matrices in the inverse matrix of the Jacobian matrix.

[0053] According to the above formula, the sensitivity matrix S of voltage with respect to active power and reactive power can be obtained. The formula of S is:

[0054]

[0055] in, represents the sensitivity matrix of voltage with respect to active power; Represents the sensitivity matrix of voltage with respect to reactive power.

[0056] Based on the above formula, the voltage prediction model of the power generation equipment at time t is obtained:

[0057]

[0058] in, U represents the voltage prediction value matrix of the power generation equipment grid connection point at time t+iΔt predicted at time t; PCC (t|t) represents the voltage matrix of the grid-connected point of the power generation equipment at time t, that is, the voltage measurement value of the above-mentioned power generation equipment at the grid-connected point, which is actually measured by the power generation equipment measurement system; S represents the sensitivity matrix, that is, the sensitivity matrix of the power generation equipment to active power, SVC (static VAR compensator) reactive compensation, and reactive compensation of the power generation equipment itself, which is a known quantity; ΔP pre (t+jΔt|t) represents the change in active power of the power generation equipment at time t, which is the input quantity; and n(t+jΔt|t), are the control variables to be predicted, where They represent the reactive power forecast adjustment of SVC reactive power compensation and reactive power compensation of the power generation equipment at time t+jΔt, respectively. n(t+jΔt|t) represents the number of switched capacitor / reactor groups (i.e., reactive power equipment). A positive number indicates switching on and a negative number indicates switching off. ΔQ C Represents the capacity of a single capacitor / reactor group; N represents the prediction step of the power generation equipment, and i (i=1, 2, 3, ..., N) and j represent the i-th and j-th moments in N moments.

[0059] Step S106: determining a target control strategy for the reactive power compensation device based on the predicted value of the electrical parameter.

[0060] It can be understood that according to the predicted values ​​of the electrical parameters obtained by the above voltage prediction model, the target control strategy for multiple types of reactive compensation equipment is determined. By executing the above target control strategy, the grid connection point voltage of the power generation equipment can be accurately controlled, the stability of the grid connection point voltage of the power generation equipment can be maintained, and the safe and stable operation of the power system can be ensured.

[0061] In an optional embodiment, the electrical parameter prediction value includes a voltage prediction value, and based on the electrical parameter prediction value, a target control strategy for the reactive compensation device is determined, including: based on the electrical parameter prediction value, determining a scheduling objective function that balances a first objective function and a second objective function, wherein the first objective function is used to represent the deviation between the voltage prediction value and a reference voltage, and the second objective function is used to represent the ability of the power generation equipment to maintain a reactive margin; and using the scheduling objective function to obtain a target control strategy.

[0062] It can be understood that, using the above voltage prediction model, the predicted values ​​of electrical parameters can be obtained, including the predicted voltage value of the grid connection point, the reactive power prediction adjustment of the power generation equipment, the predicted adjustment corresponding to multiple types of compensation equipment, and the number of switching groups of capacitors / reactors (i.e., reactive power supply equipment). The first objective function is determined using the predicted voltage value of the grid connection point in the predicted electrical parameter value, wherein the first objective function represents the offset of the predicted voltage value of the grid connection point, i.e., the deviation between the predicted voltage value and the reference voltage, and the second objective function represents the deviation between the reactive compensation predicted value of the SVC reactive compensation equipment and the optimal reactive margin of the SVC reactive compensation equipment (i.e., the predetermined optimal output), i.e., the ability of the power generation equipment to maintain the reactive margin. Based on the first objective function and the second objective function, a scheduling objective function that balances the first objective function and the second objective function is obtained, and a scheduling model for reactive compensation equipment is constructed, such as MPC (i.e., model predictive control). Using the reactive compensation equipment scheduling model, the target control strategy of the reactive compensation equipment is obtained. By introducing a scheduling objective function that balances the above-mentioned first objective function and the second objective function as the optimization objective, the obtained target control strategy not only takes into account the stability of the grid-connected point voltage, but also enables the power generation equipment to maintain sufficient reactive power margin when dealing with uncertainties, thereby improving the rapid response capability of the power generation equipment in disturbance conditions and enhancing the anti-interference capability of the power generation equipment.

[0063] Optionally, for the first objective function The formula is:

[0064]

[0065] in, represents the grid connection point reference voltage at time t+iΔt, and i (i=1, 2, 3, ..., N) represents the i-th moment among N moments.

[0066] In an optional embodiment, the reactive compensation equipment includes multiple types of compensation equipment, and the multiple types of compensation equipment correspond to different reactive compensation methods respectively. The electrical parameter prediction value also includes the reactive prediction adjustment amount of the power generation equipment, and the prediction adjustment amount corresponding to the multiple types of compensation equipment respectively. Based on the electrical parameter prediction value, a scheduling objective function that balances the first objective function and the second objective function is determined, including: determining constraints based on the voltage prediction value, the reactive prediction adjustment amount, and the prediction adjustment amount corresponding to the multiple types of compensation equipment respectively; determining the scheduling objective function based on the constraints, the first objective function, and the second objective function.

[0067] It can be understood that the reactive power compensation equipment of the power generation equipment includes multiple types of compensation equipment, such as capacitor / reactor groups, SVC, doubly fed induction generators and permanent magnet synchronous generators, etc. Each compensation equipment has a different reactive power compensation method. The predicted value of the electrical parameter includes the predicted value of the voltage at the grid connection point, the reactive power prediction adjustment of the power generation equipment, the predicted adjustment corresponding to multiple types of compensation equipment, and the number of switching groups of the capacitor / reactor group (i.e., reactive power supply equipment). Based on the predicted value of the voltage at the grid connection point, the reactive power prediction adjustment of the power generation equipment, the predicted adjustment corresponding to multiple types of compensation equipment, and the number of switching groups of the capacitor / reactor group (i.e., reactive power supply equipment), the constraints of the reactive power compensation equipment scheduling model are determined. Based on the constraints of the reactive power compensation equipment scheduling model, the first objective function and the second objective function, the scheduling objective function of the reactive power compensation equipment scheduling model is determined. Through the constraints and objective functions determined based on the predicted values ​​of the electrical parameters, the effective coordination and refined control of the reactive power compensation equipment of the power generation equipment are guaranteed, which not only improves the stability of the voltage of the power generation equipment, but also enhances the anti-interference ability, creating favorable conditions for the consumption of new energy such as wind power.

[0068] In an optional embodiment, the multiple types of compensation equipment include a static VAR compensator and a reactive power supply device. Based on the voltage prediction value, the reactive power prediction adjustment amount, and the prediction adjustment amounts corresponding to the multiple types of compensation equipment, constraints are determined, including: based on the active power injection amount and the reactive power injection amount of the predetermined node in the power generation equipment, a first constraint condition is obtained so that the power of the predetermined node is balanced; based on the voltage prediction value, a second constraint condition representing the voltage range of the grid connection point is determined; based on the prediction adjustment amount corresponding to the reactive power supply device, a third constraint condition representing the limit on the number of switching times of the reactive power supply device is determined; based on the prediction adjustment amount corresponding to the static VAR compensator, a fourth constraint condition representing the reactive output limit of the static VAR compensator is determined; based on the reactive power prediction adjustment amount, a fifth constraint condition representing the reactive processing limit of the power generation equipment is determined.

[0069] It can be understood that the reactive compensation equipment of the power generation equipment includes multiple types of compensation equipment including static VAR compensators (i.e. SVC equipment), reactive power supply equipment (i.e. capacitor / reactor group) and reactive compensation equipment of the power generation equipment itself. Based on the predicted value of the voltage at the grid connection point, the reactive prediction adjustment amount of the power generation equipment, the predicted adjustment amounts corresponding to the multiple types of compensation equipment respectively and the number of switching groups of the capacitor / reactor group (i.e. reactive power supply equipment), the constraints of the reactive compensation equipment scheduling model are determined. The above constraints include: according to the active injection amount and reactive injection amount of the predetermined node (e.g., grid connection point) of the power generation equipment, a first constraint condition is obtained to keep the power of the predetermined node balanced; based on the voltage prediction value, a second constraint condition representing the voltage range of the grid connection point is determined; based on the predicted adjustment amount corresponding to the reactive power supply equipment, a third constraint condition representing the switching times limit of the reactive power supply equipment is determined; based on the predicted adjustment amount corresponding to the SVC equipment, a fourth constraint condition representing the reactive output limit of the SVC equipment is determined; based on the reactive prediction adjustment amount, a fifth constraint condition representing the reactive processing limit of the power generation equipment is determined. The first constraint condition is used to ensure that the active and reactive injection power of the predetermined node and the active and reactive load demand power and active and reactive outflow power of the predetermined node are balanced; the second constraint condition is used to ensure that the voltage prediction value of the predetermined node at the prediction time does not exceed the upper and lower limits of the node voltage; the third constraint condition is used to ensure that the predicted value of the number of switching groups at the prediction time of the predetermined node does not exceed the upper and lower limits of the number of switching groups of the predetermined node, and the predicted value of the number of switching groups of the capacitor / reactor group of the predetermined node within the predetermined time does not exceed the upper limit of the number of switching groups of the node; the fourth constraint condition is used to ensure that the reactive compensation prediction value of the SVC reactive compensation device at the prediction time does not exceed the reactive compensation upper and lower limits of the SVC reactive compensation device; the fifth constraint condition is used to ensure that the reactive compensation prediction value of the power generation device itself at the prediction time does not exceed the reactive compensation upper and lower limits of the power generation device itself. By establishing multi-modal constraints, the target control strategy output by the reactive compensation device scheduling model can be effectively ensured, which not only meets the purpose of accurately and effectively controlling the reactive compensation device and maintaining the stability of the grid connection point voltage, but also takes into account the physical limitations and feasibility of the reactive compensation device, and improves the safety and reliability of the power system.

[0070] Optionally, the above constraint condition can be divided into an equality constraint condition (i.e., a first constraint condition and an inequality constraint condition, wherein the first constraint condition is an equality constraint condition, and the first constraint condition is used to ensure that the active and reactive injection power of the predetermined node and the active and reactive load demand power and the active and reactive outflow power of the predetermined node are balanced. The formula of the first constraint condition is:

[0071]

[0072] in, represents the active power injection amount of node k at time t; represents the reactive power injection amount of node k at time t, specifically the capacitor / reactor group switching plan to be optimized for the next day; G represents the phase difference between the voltages at nodes k and h at time t; kh represents the conductance of the circuit kh; B kh Indicates the susceptance of the line kh; N s Represents a collection of nodes; and They represent the voltages of node k and node h at time t respectively.

[0073] The second constraint is an inequality constraint, which is used to ensure that the voltage prediction value of the predetermined node at the prediction time does not exceed the upper and lower limits of the node voltage. The formula of the second constraint is:

[0074]

[0075] Among them, U max , U min Respectively represent the upper and lower limits of the predetermined node voltage.

[0076] The third constraint is an inequality constraint, which is used to ensure that the predicted value of the number of switching groups at the predicted time of the predetermined node does not exceed the upper and lower limits of the number of switching groups of the predetermined node, and the predicted value of the number of switching groups of the capacitor / reactor group at the predetermined node within the predetermined time does not exceed the upper limit of the number of switching groups of the node. The formula of the third constraint is:

[0077]

[0078] in, Respectively represent the lower limit and upper limit of the number of capacitor / reactor groups switched at the predetermined node k; N kC,max Indicates the upper limit of the number of capacitor / reactor groups switched on and off at a predetermined node.

[0079] The fourth constraint is an inequality constraint, which is used to ensure that the reactive compensation prediction value of the SVC reactive compensation device at the prediction time does not exceed the reactive compensation upper and lower limits of the SVC reactive compensation device. The formula of the fourth constraint is:

[0080]

[0081] in, They represent the lower and upper limits of reactive power compensation of SVC reactive power compensation equipment respectively; Q SVC (t|t) represents the initial reactive power compensation state of SVC.

[0082] The fifth constraint is an inequality constraint, which is used to ensure that the reactive power compensation prediction value of the power generation equipment itself at the prediction time does not exceed the reactive power compensation upper and lower limits of the power generation equipment itself. The formula of the fifth constraint is:

[0083]

[0084] in, They represent the lower and upper limits of reactive power compensation of the power generation equipment itself; Q W (t|t) represents the initial reactive power compensation state of the power generation equipment itself.

[0085] In summary, the inequality constraints of the reactive compensation equipment scheduling model include the upper and lower limit constraints of the voltage amplitude of each node, the compensation constraints of the reactive compensation equipment, and the constraints on the number of switching groups of capacitors / reactors. The formula of the inequality constraints is:

[0086]

[0087] In an optional embodiment, the multiple types of reactive power compensation equipment also include a static VAR compensator, and the method also includes: determining a reactive power margin deviation of the static VAR compensator based on a predicted adjustment amount and a predetermined optimal output corresponding to the static VAR compensator; and determining a second objective function based on the margin deviation.

[0088] It can be understood that the multiple types of reactive compensation equipment of the power generation equipment include static VAR compensators (i.e., SVC equipment), and the predicted adjustment amount of the SVC is obtained by using the voltage prediction model. The reactive compensation prediction value of the SVC is obtained based on the predicted adjustment amount of the above-mentioned SVC, and the reactive compensation prediction value of the SVC reactive compensation equipment is subtracted from the optimal reactive margin of the SVC reactive compensation equipment (i.e., the predetermined optimal output) to obtain the reactive margin deviation of the SVC equipment. Based on the reactive margin deviation of the SVC equipment, the second objective function of the reactive compensation equipment scheduling model is obtained. By introducing the reactive margin of the SVC equipment, the refined control of the reactive compensation of the SVC equipment can be improved, the voltage stability and dynamic reactive adjustment capability of the power generation equipment can be enhanced, and the efficient and stable operation of the power system can be promoted.

[0089] Optionally, for the second objective function The formula is:

[0090]

[0091] Among them, Q SVC (t) represents the initial reactive power compensation state of SVC; Q S,Best Indicates the optimal reactive power compensation state of SVC (i.e., the predetermined optimal output); It represents the predicted reactive power compensation value of SVC at time t+jΔt.

[0092] Optionally, SVC is used as a fast dynamic reactive power compensation device. Its main function is to respond quickly when disturbance occurs in the power generation equipment and provide reactive power compensation support. Therefore, in a steady state, reactive power compensation of the power generation equipment itself is given priority, and sufficient dynamic reactive power margin is reserved for transient faults. The dynamic reactive power margin index is the second objective function. The second objective function Indicates the degree to which the SVC reactive power compensation state deviates from its optimal reactive power compensation state. The larger it is, the lower the reactive power margin of the power generation equipment is. When the SVC operates in the optimal reactive power compensation state, 0 means the reactive power margin of the power generation equipment is the largest. Due to the influence of the operating characteristics of different power generation equipment, the optimal reactive power compensation state of SVC is different. When the power generation equipment is prone to low voltage failure, SVC should retain sufficient upward adjustment margin, so it should be as far away from the upper limit of compensation as possible. Conversely, when the power generation equipment is prone to high voltage failure, SVC should retain sufficient downward adjustment margin, so it should be as far away from the lower limit of compensation as possible. In general, the optimal compensation state of SVC is the average of the upper and lower limits, that is, to ensure the maximum margin of bidirectional regulation.

[0093] In an optional embodiment, determining a scheduling objective function that balances the first objective function and the second objective function includes: in a case where the electrical parameter prediction value includes prediction values ​​corresponding to multiple prediction moments respectively, determining the weight values ​​corresponding to the multiple prediction moments respectively based on the time sequence of the multiple prediction moments; determining the first target value and the second target value corresponding to the multiple prediction moments respectively, wherein the first target value is the optimal value of the first objective function at the corresponding prediction moment, and the second target value is the optimal value of the second objective function at the corresponding prediction moment; processing the first objective function and the second objective function according to the first target values, the second target values, and the weight values ​​corresponding to the multiple prediction moments respectively, to determine the scheduling objective function.

[0094] It can be understood that based on the grid connection point voltage measurement value at the current moment, the voltage prediction model is used to obtain the electrical parameter prediction values ​​corresponding to multiple moments after the current moment. Based on the time sequence of multiple prediction moments, the weight values ​​of the first objective function and the weight values ​​of the second objective function corresponding to the multiple prediction moments are determined, and the first objective value of the first objective function and the second objective value of the second objective function corresponding to the multiple prediction moments are determined. The above-mentioned first objective value is the optimal value corresponding to the prediction moment when only the first objective function is optimal, and the above-mentioned second objective value is the optimal value corresponding to the prediction moment when only the second objective function is optimal. Based on the weight values ​​of the first objective function and the weight values ​​of the second objective function corresponding to the above-mentioned multiple prediction moments, as well as the first objective values ​​corresponding to multiple prediction moments and the first objective values ​​corresponding to multiple prediction moments, a scheduling objective function that balances the first objective function and the second objective function is obtained. By balancing the first objective function and the second objective function, it is ensured that the target control strategy can not only maintain voltage stability, but also retain sufficient reactive power margin to enhance the anti-interference ability of the power generation equipment.

[0095] Optionally, the first objective function may reflect the voltage stability of the power generation equipment, and the second objective function may reflect the anti-interference ability of the power generation equipment. By balancing the first objective function and the second objective function, a scheduling objective function that comprehensively considers the voltage stability and anti-interference ability of the power generation equipment may be obtained. The formula of the scheduling objective function is:

[0096]

[0097] in, and Represent the weight coefficients of the first objective function and the second objective function respectively, satisfying Since the prediction accuracy of power generation equipment decreases with time, it is necessary to reduce the weight value of the function with time, that is, and is a decreasing sequence; and They represent the first objective value and the second objective value of the first objective function and the second objective function respectively when considering the optimal situation separately. and It means that the first objective function and the second objective function are normalized respectively.

[0098] Optionally, due to the existence of prediction errors, the reactive compensation prediction values ​​corresponding to the multiple types of compensation devices obtained based on the prediction adjustment amounts corresponding to the multiple types of compensation devices have certain errors with the actual reactive compensation. Therefore, a feedback correction link is required. After the reactive compensation device of the power generation equipment executes according to the control strategy instructions, the voltage measurement value actually read by the power generation equipment is used as the initial value of a new round of rolling optimization to form a closed-loop control of the system. The formula for the initial value of a new round of rolling optimization is:

[0099]

[0100] in, Indicates the voltage measurement value actually read by the power generation equipment at time t+1; U PCC (t+1|t+1) represents the initial voltage value at time t+1 obtained based on rolling optimization, that is, the voltage matrix of the grid-connected point of the power generation equipment at time t+1 input by the voltage prediction model.

[0101] Optionally, rolling optimization is a dynamic optimization strategy that is often used to solve complex system control problems with uncertainties and constraints. Rolling optimization is based on the concepts of a finite prediction window (or rolling window) and a control window. The prediction window contains the predicted state and disturbance of the system for a period of time in the future, while the control window specifies the time period in which the control strategy will be actually applied. Usually, the control window is shorter than the prediction window. In the process of determining the target control strategy of the reactive compensation device of the power generation equipment, first, based on the current voltage measurement value, the predicted value of the electrical parameters of the power generation equipment for a period of time in the future (that is, the voltage prediction value and the predicted adjustment amount corresponding to multiple types of compensation equipment) is determined. Secondly, based on the above-mentioned electrical parameter prediction values, the target control strategy of the reactive compensation device that meets the constraints and optimizes the scheduling objective function is determined. Then, according to the rolling optimization principle, the power generation equipment will only execute the first item (or the first few items) of the target control strategy for a period of time in the future, and re-measure the grid connection point voltage and reactive compensation device state of the power generation equipment after the execution is completed. Finally, the re-measured grid-connected point voltage of the power generation equipment is fed back to the power generation equipment as the updated voltage measurement value, and the target control strategy is re-determined based on the updated voltage measurement value to ensure that the target control strategy is always determined based on the latest voltage measurement value. In the process of determining the target control strategy of the reactive power compensation equipment of the power generation equipment, the application of rolling optimization enables the control strategy to better adapt to the randomness and volatility of wind power output, which can not only maintain the real-time nature of the control strategy, but also use future forecast information for advance planning, thereby improving the stability and controllability of the grid-connected point voltage of the power generation equipment, reducing the risk of system voltage collapse, and increasing the operating efficiency and power consumption capacity of the power generation equipment.

[0102] Through the above step S102, the reactive power compensation equipment of the power generation equipment is controlled according to the initial control strategy to determine the voltage measurement value of the power generation equipment at the grid connection point; step S104, based on the voltage measurement value, the predicted value of the electrical parameter of the power generation equipment is determined; step S106, based on the predicted value of the electrical parameter, the target control strategy for the reactive power compensation equipment is determined. The purpose of reducing the voltage fluctuation of the grid connection point by predicting the grid connection point voltage and controlling the various reactive power compensation equipment of the power generation equipment can be achieved, and the technical effect of improving the voltage stability of the grid connection point of the new energy power generation equipment is achieved, thereby solving the technical problem of unsatisfactory voltage stability of the grid connection point of the new energy power generation equipment existing in the related art.

[0103] Based on the above embodiments and optional embodiments, the present application proposes an optional implementation method to control various reactive power compensation devices of power generation equipment to maintain the stability of the voltage at the grid connection point. Figure 2 is a flow chart of an optional method for determining a voltage control strategy provided in an embodiment of the present application, such as Figure 2 As shown in FIG. 1 , the voltage control strategy determination method is divided into five steps, namely: S1, reading wind power (i.e., power generation equipment) power forecast and grid component parameter information; S2, establishing a voltage prediction model based on sensitivity; S3, establishing a reactive power optimization model (i.e., reactive power compensation equipment optimization scheduling model) with the goal of minimizing the voltage offset at the grid connection point (i.e., the first objective function) and maximizing the dynamic reactive power margin (i.e., the second objective function); S4, establishing a feedback correction optimization rolling scheduling model; S5, proposing a voltage interval control method for the grid connection point of a wind farm based on model predictive control (i.e., determining the target control strategy for reactive power compensation equipment). The above steps will be explained below.

[0104] Step S1, reading wind power forecast and grid component parameter information;

[0105] S101: Obtain the day-ahead predicted active output (i.e., active power) curve of the wind farm, obtain the grid-connected point voltage matrix of the wind farm at time t, and obtain the equipment parameters of the wind farm grid-connected transformer, wind turbine, capacitor / reactor group, and SVC (i.e., static VAR compensator);

[0106] S102: Obtain the sensitivity matrix of the system's active power, SVC reactive output (i.e., SVC reactive power), and wind turbine reactive output (i.e., reactive power of the power generation equipment itself), and obtain grid component parameter information;

[0107] S103: Obtain the upper and lower limits of the voltage amplitude of each node, and obtain the reactive compensation equipment adjustment information, including the upper and lower limits of reactive output and the number of switching times of capacitor / reactor groups.

[0108] Step S2, establishing a voltage prediction model based on sensitivity;

[0109] The bus voltage of the system (i.e., power generation equipment) can generally be obtained by flow calculation, but the calculation will increase significantly. Assuming that the system grid structure remains unchanged, the sensitivity matrix obtained by linearizing the flow equation can be used to predict the system voltage, which effectively simplifies the calculation while ensuring the prediction accuracy. The specific calculation process is as follows: the Newton method is used to calculate the flow of the power grid at time t, and the formula is obtained:

[0110]

[0111] Among them, ΔP represents the error vector of active power; ΔQ represents the error vector of reactive power; Δθ represents the change matrix of voltage phase angle; ΔU represents the change matrix of voltage effective value; U(t) -1 The inverse matrix of the matrix representing the change in voltage effective value.

[0112] The Jacobian matrix J in the above formula is:

[0113]

[0114] Among them, H, R, K, and L are block matrices in the Jacobian matrix respectively.

[0115] Multiply both sides of the equation by the inverse of the Jacobian matrix J -1 ,have to:

[0116]

[0117] Among them, A, B, C, and D are block matrices in the inverse matrix of the Jacobian matrix.

[0118] According to the above formula, the sensitivity matrix S of voltage with respect to active power and reactive power can be obtained. The formula of S is:

[0119]

[0120] in, represents the sensitivity matrix of voltage with respect to active power; Represents the sensitivity matrix of voltage with respect to reactive power.

[0121] Based on the above formula, the voltage prediction model of the wind farm at time t is obtained:

[0122]

[0123] in, U represents the voltage prediction value matrix of the power generation equipment grid connection point at time t+iΔt predicted at time t; PCC(t|t) represents the voltage matrix of the grid-connected point of the power generation equipment at time t, that is, the voltage measurement value of the above-mentioned power generation equipment at the grid-connected point, which is actually measured by the power generation equipment measurement system; S represents the sensitivity matrix, that is, the sensitivity matrix of the power generation equipment to active power, SVC (static VAR compensator) reactive compensation, and reactive compensation of the power generation equipment itself, which is a known quantity; ΔP pre (t+jΔt|t) represents the change in active power of the power generation equipment at time t, which is the input quantity; and n(t+jΔt|t), are the control variables to be predicted, where They represent the reactive power forecast adjustment of SVC reactive power compensation and reactive power compensation of the power generation equipment at time t+jΔt, respectively. n(t+jΔt|t) represents the number of switched capacitor / reactor groups (i.e., reactive power equipment). A positive number indicates switching on and a negative number indicates switching off. ΔQ C Represents the capacity of a single capacitor / reactor group; N represents the prediction step of the power generation equipment, and i (i=1, 2, 3, ..., N) and j represent the i-th and j-th moments in N moments.

[0124] Step S3, establishing a reactive power optimization model with the goal of minimizing the voltage deviation at the grid connection point and maximizing the dynamic reactive power margin;

[0125] S301: Establishing a wind farm reactive power optimization dispatching model with minimum grid connection point voltage deviation;

[0126] The goal is to minimize the deviation between the grid connection point voltage and the reference voltage in the future N moments predicted by the voltage prediction model (i.e. the first objective function ), the formula is:

[0127]

[0128] in, represents the grid connection point reference voltage at time t+iΔt, and i (i=1, 2, 3, ..., N) represents the i-th moment among N moments.

[0129] S302: Considering the time constant and capacity characteristics of the reactive power compensation device, a reactive power optimization dispatching model of a wind farm with the maximum dynamic reactive power margin is established;

[0130] As a fast dynamic reactive power compensation device, SVC is mainly used to respond quickly to disturbances in wind farms and provide reactive power support. Therefore, in steady state, wind turbine reactive power output is given priority, and sufficient dynamic reactive power margin is reserved for transient faults. The dynamic reactive power margin index (i.e., the first objective function) is introduced into the objective function. ), the formula is:

[0131]

[0132] Among them, Q SVC (t) represents the initial reactive power compensation state of SVC; Q S,Best Indicates the optimal reactive power compensation state of SVC (i.e., the predetermined optimal output); It represents the predicted reactive power compensation value of SVC at time t+jΔt.

[0133] Optionally, the dynamic reactive margin index represents the degree to which the reactive output of the SVC deviates from its optimal reactive output. The larger the value, the lower the reactive margin. When the SVC operates at the optimal reactive output state, the value is 0, and the reactive margin of the system reaches the maximum. Due to the influence of operating characteristics between different wind farms, the optimal reactive output of the SVC is not the same. When the wind farm is prone to low voltage failure, the SVC must retain sufficient upward regulation margin, so it should be kept as far away from the output upper limit as possible. In general, the optimal output of the SVC is the average of the upper and lower limits, that is, to ensure that the margin for bidirectional regulation is maximized.

[0134] S303: Establish a two-dimensional multi-objective optimization scheduling model;

[0135] The rolling optimization model of model prediction comprehensively considers the stability and anti-interference ability of wind farm voltage, and obtains a two-dimensional multi-objective optimization function (i.e., scheduling objective function), which is:

[0136]

[0137] in, and Represent the weight coefficients of the first objective function and the second objective function respectively, satisfying Since the prediction accuracy of power generation equipment decreases with time, it is necessary to reduce the weight value of the function with time, that is, and is a decreasing sequence; and They represent the first objective value and the second objective value of the first objective function and the second objective function respectively when considering the optimal situation separately. and It means that the first objective function and the second objective function are normalized respectively.

[0138] S304: Establishing system model equality and inequality constraints;

[0139] The formula for the equality constraint is:

[0140]

[0141] in, represents the active power injection amount of node k at time t; represents the reactive power injection amount of node k at time t, specifically the capacitor / reactor group switching plan to be optimized for the next day; G represents the phase difference between the voltages at nodes k and h at time t; kh represents the conductance of the circuit kh; B kh Indicates the susceptance of the line kh; N s Represents a collection of nodes; and They represent the voltages of node k and node h at time t respectively.

[0142] The formula for the inequality constraint is:

[0143]

[0144] Among them, U max , U min Respectively represent the upper and lower limits of the predetermined node voltage; Respectively represent the lower limit and upper limit of the number of capacitor / reactor groups switched at the predetermined node k; N kC,max Indicates the upper limit of the number of switching groups of capacitors / reactors at the predetermined node; They represent the lower and upper limits of reactive power compensation of SVC reactive power compensation equipment respectively; Q SVC (t|t) represents the initial reactive power compensation state of SVC; They represent the lower and upper limits of the wind turbine's own reactive power output respectively; Q W (t|t) represents the initial reactive power compensation state of the power generation equipment itself.

[0145] Step S4, establishing a feedback correction optimization rolling scheduling model;

[0146] In actual operation, due to the existence of wind power prediction errors, there is a certain error between the wind power output in the prediction model and the actual output, and a feedback correction link is required. After the system reactive power compensation equipment acts according to the control instruction (i.e., the target control strategy), the voltage vector actually read by the measurement system is used as the initial value of a new round of rolling optimization to form a closed-loop control of the system. The formula for the initial value of a new round of rolling optimization is:

[0147]

[0148] in, Represents the voltage vector at time t+1 collected by the actual measurement system; U PCC (t+1|t+1) represents the initial value vector at time t+1 obtained based on the rolling optimization, that is, the voltage matrix of the grid-connected point of the power generation equipment at time t+1 input by the voltage prediction model.

[0149] Optionally, rolling optimization is a dynamic optimization strategy that is often used to solve complex system control problems with uncertainties and constraints. Rolling optimization is based on the concepts of a finite prediction window (or rolling window) and a control window. The prediction window contains the predicted state and disturbance of the system for a period of time in the future, while the control window specifies the time period in which the control strategy will be actually applied. Usually, the control window is shorter than the prediction window. In the process of determining the target control strategy of the reactive compensation device of the power generation equipment, first, based on the current voltage measurement value, the predicted value of the electrical parameters of the power generation equipment for a period of time in the future (that is, the voltage prediction value and the predicted adjustment amount corresponding to multiple types of compensation equipment) is determined. Secondly, based on the above-mentioned electrical parameter prediction values, the target control strategy of the reactive compensation device that meets the constraints and optimizes the scheduling objective function is determined. Then, according to the rolling optimization principle, the power generation equipment will only execute the first item (or the first few items) of the target control strategy for a period of time in the future, and re-measure the grid connection point voltage and reactive compensation device state of the power generation equipment after the execution is completed. Finally, the re-measured grid-connected point voltage of the power generation equipment is fed back to the power generation equipment as the updated voltage measurement value, and the target control strategy is re-determined based on the updated voltage measurement value to ensure that the target control strategy is always determined based on the latest voltage measurement value. In the process of determining the target control strategy of the reactive power compensation equipment of the power generation equipment, the application of rolling optimization enables the control strategy to better adapt to the randomness and volatility of wind power output, which can not only maintain the real-time nature of the control strategy, but also use future forecast information for advance planning, thereby improving the stability and controllability of the grid-connected point voltage of the power generation equipment, reducing the risk of system voltage collapse, and increasing the operating efficiency and power consumption capacity of the power generation equipment.

[0150] Step S5, proposing a voltage range control method for a wind farm grid connection point based on model predictive control.

[0151] The above reactive power optimization control model can be simplified to a quadratic programming problem, and the model can be solved by calling the quadratic programming function provided by the predetermined optimization toolbox. The action instruction sequence of each reactive compensation device is obtained by solving, and only the first control instruction of the sequence is issued to each reactive compensation device to enter the next round of optimization.

[0152] The voltage control strategy determination method can be applied to a software application, and the software application can be used as follows Figure 2 The strategy shown.

[0153] Step S1: Read wind power forecast and grid component parameter information;

[0154] Take a real wind farm as an example. The wind farm capacity is 120MW, with 6 feeders, each of which is connected to 10 2MW double-fed wind turbines. The wind turbines are stepped up to 35KV through a box transformer with a ratio of 36.75±2×2.5% / 0.69KV (kilovolts), and connected to the 35KV busbar of the wind farm booster station through the feeder. The capacity of the booster transformer is 100MVA (megavolt-ampere), the ratio is 110KV / 35KV, and it is connected to the external power grid through a 40km (kilometer) transmission line. The low-voltage side busbar of the wind farm booster station is equipped with a set of SVC with a capacity of -28~20Mvar (megafarad), three groups of capacitors, and two groups of reactors, each with a capacity of 20Mvar. The control cycle of the model predictive control is 15min, the optimization cycle is 4h (hours), the prediction step N=16, and the control step M=1.

[0155] Figure 3 is an active output diagram of an optional voltage control strategy determination method provided in an embodiment of the present application, and the wind farm predicted active output curve is as follows: Figure 3 shown. Figure 3 The horizontal axis is time, the unit is min (minutes); the vertical axis is wind power, the unit is MV.

[0156] S2: Establish a voltage prediction model based on sensitivity;

[0157] S3: Establish a reactive power optimization model with the goal of minimizing the voltage deviation at the grid connection point and maximizing the dynamic reactive power margin;

[0158] S4: Establish a feedback correction optimization rolling scheduling model;

[0159] S5: Calculate the reactive power output plan of capacitor / reactor group, SVC, wind turbine, and the voltage at the wind farm connection point.

[0160] In order to verify the effect of the voltage interval control method of the wind farm grid connection point based on model predictive control, the voltage control method based on centralized control is taken as a control, and the number of capacitor / reactor group switching groups, SVC, wind turbine reactive power output plan, and wind farm grid connection point voltage of the above two methods are calculated respectively.

[0161] Figure 4 is a first result diagram of an optional voltage control strategy determination method provided in an embodiment of the present application, Figure 4 The horizontal axis is time, and the vertical axis is the number of capacitor / reactor groups switched on and off. Figure 4 As shown, compared with the centralized voltage control method, the target control strategy obtained by MPC (i.e., model predictive control method) makes the change range of the number of capacitor / reactor group switching groups smaller, reduces the switching frequency of capacitor / reactor groups, extends the life of capacitor / reactor group equipment, reduces equipment maintenance costs, and improves system stability.

[0162] Figure 5 is a second result diagram of an optional voltage control strategy determination method provided in an embodiment of the present application, Figure 5 The horizontal axis is time, and the vertical axis is the reactive power output of SVC. Figure 5 As shown in the figure, the deviation of the optimal reactive output of SVC by MPC method is only 1 / 4 of that by centralized voltage control method, and its reactive output can basically be maintained near the optimal reactive output -4 Mvar.

[0163] Figure 6 is a third result diagram of an optional voltage control strategy determination method provided in an embodiment of the present application, Figure 6 The horizontal axis is time, and the vertical axis is the reactive power output of the fan. Figure 6 As shown in the figure, compared with the centralized voltage control method, the wind turbine reactive output of the MPC method is relatively high and reaches its peak at around 12:00. At this time, the reactive output of the SVC is significantly lower than that of the SVC of the centralized voltage control method, and it still remains near the optimal reactive output, indicating that the MPC method can ensure the priority arrangement of wind turbine reactive output through coordinated control and ensure that the SVC is near the optimal reactive output point.

[0164] Figure 7 is a fourth result diagram of an optional voltage control strategy determination method provided according to an embodiment of the present application, Figure 7 The horizontal axis is time, and the vertical axis is the grid connection point voltage. Figure 7 As shown in the figure, the standard deviation of the voltage at the wind farm grid connection point of the MPC method is reduced by 45.83% compared with the centralized control voltage control method, and the peak-to-valley difference is reduced by 56.04%. Because the model predictive control predicts the system state in the future, performs multi-step rolling optimization on the scheduling plan of the reactive compensation equipment in the wind farm, and arranges its output reasonably, it can effectively reduce the fluctuation of the wind farm outlet voltage, and at the same time reserve a certain dynamic reactive power margin for the system to cope with potential disturbances in the future, and achieve excellent voltage control effect at the wind farm grid connection point.

[0165] Table 1 is a comparison table of the effects of the MPC method and the centralized voltage control method in terms of the SVC optimal reactive output deviation and the grid connection point voltage. As can be seen from Table 1, for the SVC optimal reactive output deviation, the SVC optimal reactive output deviation of the MPC method is only 1 / 4 of that of the centralized voltage control method; for the grid connection point voltage, the standard deviation of the wind farm grid connection point voltage of the MPC method is reduced by 45.83% compared with the centralized voltage control method, and the peak-to-valley difference is reduced by 56.04%.

[0166] Table 1 Comparison of SVC optimal reactive output deviation and grid connection point voltage effect

[0167]

[0168] Figure 8 is a first schematic diagram of an optional voltage control strategy determination method provided according to an embodiment of the present application, the structural topology diagram of a wind farm is as follows Figure 8 As shown in the figure, inside the wind farm, the low-voltage busbar of the wind farm booster station is connected to several feeders, each of which is connected to multiple wind turbines through a trunk line, and reactive compensation equipment such as SVC, capacitor / reactor groups are connected to the low-voltage busbar. Figure 8 The wind farm shown uses the MPC method to finely control the reactive power voltage of the wind farm. Fig. 9 is a second schematic diagram of an optional voltage control strategy determination method provided according to an embodiment of the present application, that is, for example Figure 8 The schematic diagram of the wind farm using the MPC method is shown in the figure. The MPC method takes the minimum voltage deviation at the grid connection point and the maximum dynamic reactive margin of the SVC as the objective function to solve the dispatching instructions of each reactive compensation device in the wind farm. The control method mainly consists of three parts: voltage prediction model, rolling optimization model, and feedback correction. Fig. 9 The horizontal axis is the time series, and the vertical axis is the voltage at the wind farm grid connection point. Fig. 9 As shown, first at the current time t, read the initial grid-connected point voltage U of the system PCC (t|t), based on a certain voltage prediction model, predict the voltage at the wind farm grid connection point within N steps in the future Secondly, a rolling optimization model is constructed with the minimum cumulative voltage deviation and the maximum dynamic reactive power margin within the prediction step as the objective function, and the scheduling plan sequence of wind farm reactive compensation equipment within N steps is solved (Δu(t|t), Δu(t+1|t),…,Δu(t+M-1|t)). The first M scheduling plan sequences in the control sequence are sent to the reactive compensation equipment. In order to ensure the accuracy of the system, M is generally 1, that is, only the scheduling plan sequence Δu(t|t) at time t is taken. Finally, after the dispatch instruction is executed, the time window is moved back and the voltage vector of the system grid connection point is re-read as the initial value U for the new round of optimization PCC (t+1|t+1), achieving the purpose of feedback correction and forming a closed-loop optimization.

[0169] The above optional implementation methods achieve at least the following effects: by introducing rolling optimization and feedback correction links, a closed-loop optimization is formed, the control accuracy of the grid-connected point voltage is improved, and the voltage stability of the power generation equipment is effectively maintained; by introducing a variety of optimization objectives and constraints, the target control strategy can not only give full play to the reactive regulation capabilities of various reactive compensation equipment, but also enhance the anti-interference ability of the power generation equipment.

[0170] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0171] In this embodiment, a voltage control strategy determination device is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the terms "module" and "device" can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0172] According to an embodiment of the present application, there is also provided an embodiment of a device for implementing a method for determining a voltage control strategy. Fig.10 is a schematic diagram of a voltage control strategy determination device according to an embodiment of the present application, such as Fig.10 As shown, the above-mentioned voltage control strategy determination device includes a voltage measurement value determination module 1002, an electrical parameter prediction value determination module 1004, and a target control strategy determination module 1006. The device is described below.

[0173] The voltage measurement value determination module 1002 is used to control the reactive power compensation device of the power generation device according to the initial control strategy to determine the voltage measurement value of the power generation device at the grid connection point;

[0174] The electric parameter prediction value determination module 1004 is connected to the voltage measurement value determination module 1002, and determines the electric parameter prediction value of the power generation equipment based on the voltage measurement value;

[0175] The target control strategy determination module 1006 is connected to the electrical parameter prediction value determination module 1004 and is used to determine the target control strategy for the reactive power compensation device based on the electrical parameter prediction value.

[0176] In a voltage control strategy determination device provided in an embodiment of the present application, a voltage measurement value determination module 1002 is set to control the reactive compensation device of the power generation equipment according to the initial control strategy to determine the voltage measurement value of the power generation equipment at the grid connection point; an electric parameter prediction value determination module 1004 is connected to the voltage measurement value determination module 1002 to determine the predicted value of the electric parameter of the power generation equipment based on the voltage measurement value; a target control strategy determination module 1006 is connected to the electric parameter prediction value determination module 1004 to determine the target control strategy for the reactive compensation device based on the predicted value of the electric parameter. The purpose of reducing the voltage fluctuation of the grid connection point by predicting the grid connection point voltage and controlling the various reactive compensation devices of the power generation equipment is achieved, and the technical effect of improving the voltage stability of the grid connection point of the new energy power generation equipment is achieved, thereby solving the technical problem of unsatisfactory voltage stability of the grid connection point of the new energy power generation equipment existing in the related art.

[0177] It should be noted that the above modules can be implemented by software or hardware. For example, for the latter, it can be implemented in the following ways: the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0178] It should be noted that the voltage measurement value determination module 1002, the electrical parameter prediction value determination module 1004, and the target control strategy determination module 1006 correspond to steps S102 to S106 in the embodiment, and the examples and application scenarios implemented by the above modules and the corresponding steps are the same, but are not limited to the contents disclosed in the above embodiments. It should be noted that the above modules can be run in a computer terminal as part of the device.

[0179] It should be noted that the optional or preferred implementation of this embodiment can refer to the relevant description in the embodiment, which will not be repeated here.

[0180] The above-mentioned voltage control strategy determination device may also include a processor and a memory. The voltage measurement value determination module 1002, the electrical parameter prediction value determination module 1004, the target control strategy determination module 1006, etc. are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize the corresponding functions.

[0181] The processor includes a kernel, which retrieves the corresponding program unit from the memory. There can be one or more kernels. The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one storage chip.

[0182] An embodiment of the present application provides a non-volatile storage medium on which a program is stored. When the program is executed by a processor, a method for determining a voltage control strategy is implemented.

[0183] The embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program stored in the memory and can be run on the processor. When the processor executes the program, the following steps are implemented: according to the initial control strategy, the reactive power compensation device of the power generation device is controlled to determine the voltage measurement value of the power generation device at the grid connection point; based on the voltage measurement value, the predicted value of the electrical parameter of the power generation device is determined; based on the predicted value of the electrical parameter, the target control strategy for the reactive power compensation device is determined. The device in this article can be a server, a PC, etc.

[0184] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing an initialization program having the following method steps: controlling the reactive compensation device of the power generation device according to the initial control strategy, and determining the voltage measurement value of the power generation device at the grid connection point; determining the predicted value of the electrical parameter of the power generation device based on the voltage measurement value; and determining the target control strategy for the reactive compensation device based on the predicted value of the electrical parameter.

[0185] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0186] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0187] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0188] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0189] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0190] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0191] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0192] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0193] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0194] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for determining a voltage control strategy, characterized in that: include: According to the initial control strategy, the reactive power compensation device of the power generation device is controlled to determine the voltage measurement value of the power generation device at the grid connection point; Determining a predicted value of an electrical parameter of the power generation device based on the voltage measurement value; Based on the predicted value of the electrical parameter, a target control strategy for the reactive power compensation device is determined.

2. The method according to claim 1, characterized in that The reactive power compensation device includes multiple types of compensation devices, each of which corresponds to a different reactive power compensation mode. The electrical parameter prediction value includes a voltage prediction value and prediction adjustment amounts corresponding to each of the multiple types of compensation devices. The step of determining the electrical parameter prediction value of the power generation device based on the voltage measurement value includes: Determine a voltage sensitivity matrix, wherein the voltage sensitivity matrix represents the influence of active power change and reactive power change on the power generation equipment respectively; Based on the voltage sensitivity matrix and the voltage measurement value, the voltage prediction value and the prediction adjustment amounts corresponding to the multiple types of compensation devices are determined.

3. The method according to claim 1, characterized in that The electrical parameter prediction value includes a voltage prediction value, and determining a target control strategy for the reactive power compensation device based on the electrical parameter prediction value includes: Based on the predicted value of the electrical parameter, determining a scheduling objective function that balances a first objective function and a second objective function, wherein the first objective function is used to represent the deviation between the predicted voltage value and a reference voltage, and the second objective function is used to represent the ability of the power generation equipment to maintain a reactive power margin; The target control strategy is obtained by adopting the scheduling objective function.

4. The method according to claim 3, characterized in that: The reactive power compensation device includes multiple types of compensation devices, each of which corresponds to a different reactive power compensation mode. The electrical parameter prediction value also includes a reactive power prediction adjustment amount of the power generation device and the prediction adjustment amounts corresponding to the multiple types of compensation devices. The determining of the scheduling objective function that balances the first objective function and the second objective function based on the electrical parameter prediction value includes: Determine a constraint condition based on the voltage prediction value, the reactive power prediction adjustment amount, and the prediction adjustment amounts respectively corresponding to the multiple types of compensation equipment; The scheduling objective function is determined based on the constraint conditions, the first objective function, and the second objective function.

5. The method according to claim 4, characterized in that The multiple types of compensation devices include static VAR compensators and reactive power supply devices. The constraint conditions are determined based on the voltage prediction value, the reactive power prediction adjustment amount, and the prediction adjustment amounts corresponding to the multiple types of compensation devices, including: Based on the active power injection amount and reactive power injection amount of the predetermined node in the power generation equipment, a first constraint condition is obtained so that the power of the predetermined node is kept balanced; Based on the voltage prediction value, determining a second constraint condition representing a voltage range of the grid connection point; Based on the predicted adjustment amount corresponding to the reactive power supply device, determining a third constraint condition representing a limit on the number of switching times of the reactive power supply device; Determining a fourth constraint condition representing reactive power output limitation of the static VAR compensator based on the predicted adjustment amount corresponding to the static VAR compensator; Based on the reactive power prediction adjustment amount, a fifth constraint condition representing a reactive power handling limitation of the power generation equipment is determined.

6. The method according to claim 4, characterized in that The multiple types of compensation devices also include a static VAR compensator, and the method further includes: Determining a reactive margin deviation of the static VAR compensator based on a predicted adjustment amount and a predetermined optimal output corresponding to the static VAR compensator; Based on the margin deviation amount, the second objective function is determined.

7. The method according to claim 3, characterized in that The determining of the scheduling objective function that balances the first objective function and the second objective function comprises: In a case where the electrical parameter prediction value includes prediction values ​​corresponding to a plurality of prediction moments respectively, determining weight values ​​corresponding to the plurality of prediction moments respectively based on the time sequence of the plurality of prediction moments; Determine a first target value and a second target value respectively corresponding to the multiple prediction moments, wherein the first target value is an optimal value of the first target function at the corresponding prediction moment, and the second target value is an optimal value of the second target function at the corresponding prediction moment; The first objective function and the second objective function are processed according to the first objective values, the second objective values, and the weight values ​​respectively corresponding to the multiple prediction moments to determine the scheduling objective function.

8. A voltage control strategy determination device, characterized in that: include: A voltage measurement value determination module, used to control the reactive power compensation device of the power generation equipment according to the initial control strategy, and determine the voltage measurement value of the power generation equipment at the grid connection point; An electrical parameter prediction value determination module, which determines the electrical parameter prediction value of the power generation equipment based on the voltage measurement value; The target control strategy determination module is used to determine the target control strategy for the reactive power compensation device based on the predicted value of the electrical parameter.

9. A non-volatile storage medium, characterized in that: The non-volatile storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the voltage control strategy determination method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: include: One or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the voltage control strategy determination method described in any one of claims 1 to 7.

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