A new energy distributed power control method and system

Abstract

The present invention provides a new energy distributed power control method and system, which belongs to the field of networked power supply technology. The control method includes: collecting meteorological data of a preset time; outputting the predicted power of the new energy distributed power system within the preset time according to the meteorological data through the mathematical model of the new energy distributed power system; obtaining the expected output frequency and expected output voltage of the new energy distributed power system; with the goal of achieving the expected output frequency and expected output voltage, the current predicted power is proportionally distributed through a droop controller; according to the proportional distribution result, the output voltage of each distributed power source in the new energy distributed power system is adjusted through a distributed average proportional integral control algorithm; according to the adjustment result, the output voltage of each distributed power source is secondary adjusted in combination with a demand response mechanism; the secondary adjusted output voltage is output as the output voltage of the distributed power source. The present invention can improve the stability of the existing power grid.

Description

Technical Field

[0001] The present invention relates to the technical field of networked power supply, and in particular to a new energy distributed power control method and system. Background Art

[0002] New energy refers to renewable energy that has less impact on the environment than traditional energy, such as wind energy, solar energy and biomass energy. Distributed refers to a decentralized structure or method, that is, the generation, distribution and management of electricity or resources are not concentrated in a large power plant, but distributed in multiple small power generation units. Power control refers to the process of regulating, managing or controlling power output, and new energy distributed power control is to manage the power output in new energy distributed power systems through a new control method.

[0003] Controlling the distributed power of new energy can effectively optimize the operation of distributed new energy power generation systems, improve the stability of the power grid and the reliability of power supply, reduce fluctuations and overload problems, and thus achieve more efficient energy management and resource utilization. It is of great significance to promote the large-scale access of new energy to the power grid, support the development of smart grids, and promote the application and popularization of green and low-carbon energy.

[0004] Existing renewable energy distributed power control usually relies on a single prediction model and preset algorithm, lacking the ability to flexibly adapt to real-time changes and complex interferences in the system. In addition, existing methods may face coordination difficulties when connected to the grid on a large scale, and fail to fully consider the dynamic interaction between various distributed power sources, resulting in poor grid stability. In short, existing power control mostly relies on static optimization goals, ignoring the real-time and intelligent requirements of the system, resulting in less than ideal control effects in complex environments, and reduced grid stability and reliability of power supply. Summary of the invention

[0005] The main purpose of the present invention is to provide a new energy distributed power control method and system to solve the problem that the existing power control mostly relies on static optimization goals, ignores the real-time and intelligent requirements of the system, resulting in unsatisfactory control effects in complex environments, and reduces the stability of the power grid and the reliability of power supply.

[0006] In order to achieve the above object, according to one aspect of the present invention, a new energy distributed power control method is provided, comprising:

[0007] S1: Collect meteorological data for a preset period of time;

[0008] S2: Based on the meteorological data, the predicted power of the new energy distributed power system within a preset time period is output through the mathematical model of the new energy distributed power system;

[0009] S3: Obtaining the expected output frequency and expected output voltage of the new energy distributed power system;

[0010] S4: Proportional distribution of the predicted power through the droop controller with the goal of achieving the desired output frequency and the desired output voltage;

[0011] S5: According to the proportional allocation result, the output voltage of each distributed power source in the new energy distributed power system is adjusted through a distributed average proportional integral control algorithm;

[0012] S6: According to the adjustment result and in combination with the demand response mechanism, the output voltage of each distributed power source is adjusted for a second time;

[0013] S7: Output the output voltage obtained by the secondary adjustment as the output voltage of the corresponding distributed power source.

[0014] Furthermore, S2 specifically includes:

[0015] S201: Setting objective functions and constraints of the mathematical model, wherein the objective functions include a first objective function of minimizing fatigue load of the wind turbine generator set, a second objective function of minimizing the deviation between the measured voltage of the wind farm and the expected output voltage, and a third objective function of maximizing fast dynamic reactive power support capability;

[0016] S202: Under the constraints, with the goal of minimizing the first objective function, minimizing the second objective function and maximizing the third objective function, the mathematical model is solved by a genetic algorithm to output the predicted power.

[0017] Furthermore, the mathematical model is specifically:

[0018] ;

[0019] ;

[0020] ;

[0021] in, represents the time derivative of the wind turbine state vector, A wt represents the state matrix of the wind turbine, x wt represents the state vector of the wind turbine, B wt represents the input matrix of the wind turbine, represents the reference power of the wind turbine, E wt represents the state disturbance or external disturbance term of the wind turbine, Represents the pitch angle θ and torque T r The proportionality coefficient between t represents the total moment of inertia of the system, Indicates the speed ωr and torque T r The coefficient between represents the time constant of the generator, represents the proportional gain of the pitch controller, represents the integral gain of the pitch controller, represents the efficiency coefficient, represents the efficiency coefficient of the generator, represents the reference power, Indicates the base speed of the generator. Indicates the reference value of wind speed, Indicates wind speed v w With torque T r The gain factor between .

[0022] Furthermore, the first objective function is specifically:

[0023] ;

[0024] Among them, f 1 represents minimizing the fatigue load of the wind turbine, min represents minimization, n represents the total number of prediction steps, △ represents the deviation operator, T s represents the shaft torque of the motor group, and W represents the weight;

[0025] The second objective function is specifically:

[0026] ;

[0027] Among them, f 2 represents minimizing the deviation between the measured voltage and the expected output voltage, n represents the total number of prediction steps, V poc (k) represents the voltage at the grid connection point POC at step k, W poc and W Wt Both represent weighting factor matrices, V Wt (k) represents the voltage at the wind turbine at step k;

[0028] The third objective function is specifically:

[0029] ;

[0030] Among them, f 3 Indicates the maximum fast dynamic reactive power support capability, max means maximum, represents the predicted reaction power of the static VAR compensator or static VAR generator at step k, Represents the target median value of the static VAR compensator or static VAR generator reaction power, W s Represents the weighting factor of the reaction power.

[0031] Furthermore, the constraint conditions specifically include: a first constraint condition, a second constraint condition and a third constraint condition;

[0032] The first constraint is:

[0033] ;

[0034] Among them, θ(k) represents the blade angle of the generator at time k, θ min Indicates the minimum blade angle, θ max represents the maximum value of the blade angle, Δ represents the increment operator, θ lim represents the change limit of the blade angle, ω r (k) represents the rotor speed of the generator at time k, ω min represents the minimum value of the rotor speed, ω max represents the maximum value of the rotor speed, represents the reference active power of the generator at time k, represents the maximum power available from the generator at time k;

[0035] The second constraint is:

[0036] ;

[0037] in, represents the reference reactive power of the generator at time k, represents the minimum reactive power of the generator at time k, represents the maximum reactive power of the generator at time k;

[0038] The third constraint condition is as follows:

[0039] ;

[0040] in, represents the minimum reactive capacity of the static VAR compensator s, Q s represents the static VAR compensator s, Represents the reactive power reference value of the static VAR compensator, Indicates the maximum reactive capacity of the static VAR compensator, V min Indicates the minimum voltage in the system, V ref Indicates the expected output voltage value, V max Indicates the maximum voltage in the system.

[0041] Furthermore, S4 specifically includes:

[0042] S401: Calculating the frequency and voltage of the predicted power through a droop controller according to the expected output frequency, the expected output voltage and the predicted power;

[0043] S402: Determine the active power and reactive power allocated to each distributed power source according to the frequency and voltage.

[0044] Furthermore, S401 is specifically:

[0045] The frequency and voltage of the predicted power are calculated according to the following formula:

[0046] ;

[0047] ;

[0048] Among them, ω i represents the frequency of the i-th distributed generation, represents the expected output frequency, m i represents the droop coefficient of the frequency and active power of the i-th distributed generation, P i represents the active power of the i-th distributed generation, E i represents the voltage of the i-th distributed power source, represents the expected output voltage, n i represents the voltage and reactive power droop coefficient of the i-th distributed generation, Q i represents the reactive power of the i-th distributed generation, X ij represents the line reactance connecting distributed generation i and j, θ i represents the voltage phase angle of the i-th distributed generation, θ j represents the voltage phase angle of the jth distributed generation, X i represents the reactance of the ith distributed generation, E j represents the voltage of the jth distributed generation, sin( ) represents the sine function, and cos( ) represents the cosine function.

[0049] Furthermore, S5 specifically includes:

[0050] S501: Perform secondary control on the frequency through proximity communication:

[0051] ;

[0052] Among them, Ω i represents the secondary control variable of distributed generation i, k i represents the gain coefficient of distributed generation i, represents the quadratic control variable Ω i The time rate of change, a ijrepresents the communication weight between power source i and power source j. ij >0, it means that power source i and power source j communicate directly.

[0053] S502: According to the frequency after secondary control, the output voltage of each distributed power source in the new energy distributed power system is adjusted through a distributed average proportional integral control algorithm:

[0054] ;

[0055] Among them, e i represents the secondary control variable of the i-th distributed generation, represents the quadratic control variable e i The time rate of change of βi represents the gain coefficient of the i-th distributed power source, b ij represents the communication weight between the i-th distributed power source and the j-th distributed power source, represents the reactive power rating of the i-th distributed generation, represents the reactive power rating of the jth distributed generation.

[0056] According to one aspect of the present invention, there is provided a new energy distributed power control system, comprising:

[0057] processor;

[0058] A memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the above-mentioned new energy distributed power control method is implemented.

[0059] The technical solution of the present invention is applied, according to the meteorological data of the preset time length collected, the predicted power of the new energy distributed power system within the preset time length is output through the mathematical model of the new energy distributed power system, so as to avoid the instability problem of the power grid caused by power fluctuation. Then, the expected output frequency and expected output voltage of the new energy distributed power system are obtained, and the expected output frequency and expected output voltage are achieved as the goal. The current predicted power is proportionally distributed through the droop controller. Based on the proportional distribution result, the output voltage of each distributed power source in the new energy distributed power system is adjusted through the distributed average proportional integral control algorithm, so that the voltage of each part of the power grid is more balanced, and the stability and flexibility of the power grid are enhanced. Finally, combined with the demand response mechanism, the output voltage of each distributed power source is secondary adjusted, and the output voltage obtained by the secondary adjustment is output as the output voltage of the corresponding distributed power source, thereby improving the overall stability and reliability of the power grid. The overall optimization of power distribution ensures the stable operation of the power grid and the efficient use of new energy, ensures that each distributed power source can work together, reduces fluctuations and overload problems, thereby achieving more efficient energy management and resource utilization, and promoting the application and popularization of green and low-carbon energy.

[0060] In addition to the above-described purposes, features and advantages, the present invention has other purposes, features and advantages. The present invention will be further described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] The accompanying drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the accompanying drawings:

[0062] Figure 1 A schematic diagram of a process flow of a new energy distributed power control method provided by an embodiment of the present invention is shown;

[0063] Figure 2 A schematic structural diagram of a new energy distributed power control system provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0064] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0065] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0066] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention 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 terms used in this way can be interchanged where appropriate, so as to describe the embodiments of the present invention described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0067] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0068] Reference Manual Attached Figure 1 , showing a flow chart of a new energy distributed power control method provided in an embodiment of the present invention.

[0069] An embodiment of the present invention provides a new energy distributed power control method, including:

[0070] S1: Collect meteorological data for a preset period of time.

[0071] The preset duration refers to the length of the time period set for collecting meteorological data before the method is implemented. Usually a reasonable duration (such as several hours, one day or several days) is selected to provide sufficient data support for power forecasting. Meteorological data refers to data related to weather and environmental conditions, usually including wind speed, temperature, humidity, radiation, etc.

[0072] It should be noted that by collecting meteorological data, reliable basic information is provided for the entire new energy distributed power control system, which can reflect changes in environmental conditions in real time and ensure that subsequent steps can be predicted and decided based on accurate data.

[0073] S2: Based on meteorological data, the mathematical model of the new energy distributed power system is used to output the predicted power of the new energy distributed power system within a preset time period.

[0074] Among them, mathematical models are tools that describe and predict the behavior of a system through mathematical formulas, equations or algorithms. In the control of renewable energy distributed power, mathematical models are usually used to simulate the working status, power output and relationship between each distributed power source in the system and meteorological data. Predicted power refers to predicting the power output of renewable energy systems in the future based on existing meteorological data and mathematical models.

[0075] It should be noted that by using mathematical models to predict the power output of new energy distributed power systems, the system can understand in advance the power change trend in future time periods, accurately simulate the impact of various external factors, help the system optimize resource allocation, and avoid grid instability caused by sudden power fluctuations.

[0076] In a possible implementation, S2 specifically includes:

[0077] S201: Setting the objective function and constraint conditions of the mathematical model, wherein the objective function includes a first objective function of minimizing the fatigue load of the wind turbine, a second objective function of minimizing the deviation between the measured voltage of the wind farm and the expected output voltage, and a third objective function of maximizing the fast dynamic reactive power support capability.

[0078] S202: Under the constraints, with the goal of minimizing the first objective function, minimizing the second objective function and maximizing the third objective function, the mathematical model is solved by a genetic algorithm to output the predicted power.

[0079] S202 specifically includes:

[0080] S2021: Generate the initial population, set the population size, maximum number of iterations, and crossover probability.

[0081] Among them, each individual in the population represents a distributed power allocation scheme, which ensures that all distributed power sources meet the most basic constraints by randomly allocating voltage to resource nodes.

[0082] S2022: Calculate the first fitness value of all individuals in the initial population:

[0083] ;

[0084] Among them, f(i) 1 represents the first fitness value of the i-th distributed generation, X i represents the demand characteristics of the i-th distributed generation, Y q represents the characteristics of the qth load, , r represents the total load.

[0085] S2023: According to the fitness value, select individuals with higher fitness values ​​to form the optimal initial population.

[0086] S2024: Perform crossover and mutation operations on the optimal initial population to obtain a mutant population.

[0087] S2025: Calculate the second fitness value of each individual in the mutant population:

[0088] ;

[0089] Among them, f(i) 2 represents the second fitness value of the i-th distributed generation, x ik Represents the demand value of the i-th distributed generation at time k.

[0090] S2026: According to the second fitness value, retain the mutant individual with the highest fitness.

[0091] S2027: Determine whether the mutant individual with the highest fitness satisfies the constraint conditions. If so, proceed to step S2026, otherwise return to step S2022.

[0092] S2028: When the maximum number of iterations is reached, the mutant individual with the highest fitness is output as the distributed power allocation solution.

[0093] It should be noted that solving the mathematical model under constraints ensures that the various parameters in the optimization process always meet practical feasibility, can achieve a multi-dimensional balance of system goals, enhance the operating stability and flexibility of the new energy system, improve the accuracy and responsiveness of power prediction, and provide accurate data support for subsequent power regulation and allocation.

[0094] In a possible implementation, the mathematical model is specifically:

[0095] ;

[0096] ;

[0097] ;

[0098] in, represents the time derivative of the wind turbine state vector, A wt represents the state matrix of the wind turbine, x wt represents the state vector of the wind turbine, B wt represents the input matrix of the wind turbine, represents the reference power of the wind turbine, E wt represents the state disturbance or external disturbance term of the wind turbine, Represents the pitch angle θ and torque T r The proportionality coefficient between t represents the total moment of inertia of the system, Indicates the speed ωr and torque T r The coefficient between express, represents the time constant of the generator, represents the proportional gain of the pitch controller, represents the integral gain of the pitch controller, represents the efficiency coefficient, represents the efficiency coefficient of the generator, represents the reference power, Indicates the base speed of the generator. Indicates the reference value of wind speed, Indicates wind speed v w With torque T r The gain factor between .

[0099] In a possible implementation, the first objective function is specifically:

[0100] ;

[0101] Among them, f 1 represents minimizing the fatigue load of the wind turbine, min represents minimization, n represents the total number of prediction steps, △ represents the deviation operator, T s It represents the shaft torque of the motor group, and W represents the weight.

[0102] The second objective function is specifically:

[0103] ;

[0104] Among them, f 2 represents minimizing the deviation between the measured voltage and the expected output voltage, n represents the total number of prediction steps, V poc (k) represents the voltage at the grid connection point POC at step k, W poc and W Wt Both represent weighting factor matrices, V Wt (k) represents the voltage at the wind turbine at step k.

[0105] The third objective function is specifically:

[0106] ;

[0107] Among them, f 3 Indicates the maximum fast dynamic reactive power support capability, max means maximum, represents the predicted reaction power of the static VAR compensator or static VAR generator at step k, Represents the target median value of the static VAR compensator or static VAR generator reaction power, W s Represents the weighting factor of the reaction power.

[0108] In a possible implementation manner, the constraint conditions specifically include: a first constraint condition, a second constraint condition, and a third constraint condition.

[0109] The first constraint is:

[0110] ;

[0111] Among them, θ(k) represents the blade angle of the generator at time k, θ min Indicates the minimum blade angle, θ max represents the maximum value of the blade angle, Δ represents the increment operator, θ lim represents the change limit of the blade angle, ωr (k) represents the rotor speed of the generator at time k, ω min represents the minimum value of the rotor speed, ω max represents the maximum value of the rotor speed, represents the reference active power of the generator at time k, It represents the maximum power available to the generator at time k.

[0112] The second constraint is:

[0113] ;

[0114] in, represents the reference reactive power of the generator at time k, represents the minimum reactive power of the generator at time k, Represents the maximum reactive power of the generator at time k.

[0115] The third constraint condition is as follows:

[0116] ;

[0117] in, represents the minimum reactive capacity of the static VAR compensator s, Q s represents the static VAR compensator s, Represents the reactive power reference value of the static VAR compensator, Indicates the maximum reactive capacity of the static VAR compensator, V min Indicates the minimum voltage in the system, V ref Indicates the expected output voltage value, V max Indicates the maximum voltage in the system.

[0118] It should be noted that through accurate prediction, the system can better plan power distribution and improve the efficiency of energy use, while enhancing the ability to respond to emergencies and improving the overall stability and sustainability of the power grid.

[0119] S3: Obtain the expected output frequency and expected output voltage of the new energy distributed power system.

[0120] Among them, the expected output frequency refers to the target frequency value in the power grid, that is, the stable frequency that the system hopes to achieve and maintain, and the expected output voltage refers to the target voltage value in the power grid, which is the voltage level that the system hopes to achieve within a given time.

[0121] It should be noted that by setting the expected output frequency and voltage targets, a clear operating target is provided for the renewable energy distributed power control system. Setting these expected values ​​helps the system to accurately adjust and control, ensuring that the frequency and voltage of the power grid always remain within a stable and safe range, avoiding excessive fluctuations or equipment failures.

[0122] S4: With the goal of achieving the desired output frequency and the desired output voltage, the predicted power is proportionally distributed through the droop controller.

[0123] Among them, the droop controller is a control device used to adjust the relationship between output power and frequency, or power and voltage in the power system. By using the droop controller, the predicted power is proportionally allocated according to the targets of expected output frequency and expected output voltage, ensuring that the new energy distributed power sources can work together reasonably when the load changes.

[0124] In a possible implementation, S4 specifically includes:

[0125] S401: Calculate the frequency and voltage of the predicted power through a droop controller according to the expected output frequency, the expected output voltage and the predicted power.

[0126] S402: Determine the active power and reactive power allocated to each distributed power source according to the frequency and voltage.

[0127] It should be noted that the droop controller can flexibly adjust the power output of each distributed power source according to the actual operating status of the system, so as to achieve a balance between frequency and voltage. This control method avoids over-reliance on central dispatch, helps to improve the autonomy and response speed of the system, and at the same time reduces fluctuations in system operation by allocating predicted power, thereby improving the stability and reliability of the power grid.

[0128] In a possible implementation manner, S401 specifically includes:

[0129] The frequency and voltage of the predicted power are calculated according to the following formula:

[0130] ;

[0131] ;

[0132] Among them, ω i represents the frequency of the i-th distributed generation, represents the expected output frequency, m i represents the droop coefficient of the frequency and active power of the i-th distributed generation, P i represents the active power of the i-th distributed generation, E i represents the voltage of the i-th distributed power source, represents the expected output voltage, n i represents the voltage and reactive power droop coefficient of the i-th distributed generation, Q i represents the reactive power of the i-th distributed generation, X ij represents the line reactance connecting distributed generation i and j, θ i represents the voltage phase angle of the i-th distributed generation, θ j represents the voltage phase angle of the jth distributed generation, X i represents the reactance of the ith distributed generation, E j represents the voltage of the jth distributed generation, sin( ) represents the sine function, and cos( ) represents the cosine function.

[0133] S5: According to the proportional distribution result, the output voltage of each distributed power source in the new energy distributed power system is adjusted through the distributed average proportional integral control algorithm.

[0134] Among them, the distributed average proportional-integral control algorithm is a control algorithm for multivariable systems, especially suitable for distributed power supply systems. The algorithm combines proportional control and integral control. By adjusting the output voltage of the power supply, the system can maintain a stable voltage level and gradually correct any voltage deviation.

[0135] It should be noted that the output voltage of each distributed power source is adjusted by using the distributed average proportional integral control algorithm to ensure that the voltage of the entire new energy system remains within the predetermined range. The work between multiple distributed power sources is effectively coordinated, and the voltage is adjusted in real time to ensure that the power grid remains stable when facing load changes.

[0136] In a possible implementation, S5 specifically includes:

[0137] S501: Perform secondary control on the frequency through proximity communication:

[0138] ;

[0139] Among them, Ω i represents the secondary control variable of distributed generation i, k i represents the gain coefficient of distributed generation i, represents the quadratic control variable Ω i The time rate of change, a ij represents the communication weight between power source i and power source j. ij When >0, it indicates direct communication between power sources i and j.

[0140] S502: According to the frequency after secondary control, the output voltage of each distributed power source in the new energy distributed power system is adjusted through a distributed average proportional integral control algorithm:

[0141] ;

[0142] Among them, e i represents the secondary control variable of the i-th distributed generation, represents the quadratic control variable e i The time rate of change of βi represents the gain coefficient of the i-th distributed power source, b ij represents the communication weight between the i-th distributed power source and the j-th distributed power source, represents the reactive power rating of the i-th distributed generation, represents the reactive power rating of the jth distributed generation.

[0143] S6: Based on the adjustment results and combined with the demand response mechanism, the output voltage of each distributed power source is adjusted for the second time.

[0144] Among them, the demand response mechanism is a power management strategy that adjusts the load demand of consumers or various parts of the system to respond to the real-time power demand of the power grid. Secondary regulation is to optimize system performance through further adjustments after the initial adjustment. It is usually used to correct and improve problems that may not be fully resolved during the initial adjustment process to ensure more precise control effects.

[0145] S7: Output the output voltage obtained by the secondary adjustment as the output voltage of the corresponding distributed power source.

[0146] Among them, the output voltage refers to the voltage level output from the power supply to the grid. In the new energy distributed power system, the precise control of the output voltage is crucial and directly affects the power quality and stability of the grid. By using the voltage obtained by secondary regulation as the final output voltage, it is ensured that the voltage of the new energy distributed power source accurately meets the grid demand.

[0147] From the above description, it can be seen that according to the meteorological data collected for the preset time, the mathematical model of the new energy distributed power system is used to output the predicted power of the new energy distributed power system within the preset time, thereby avoiding the instability of the power grid caused by power fluctuations. Next, the expected output frequency and expected output voltage of the new energy distributed power system are obtained, and the expected output frequency and expected output voltage are taken as the goal. The current predicted power is proportionally distributed through the droop controller. Based on the proportional distribution result, the output voltage of each distributed power source in the new energy distributed power system is adjusted through the distributed average proportional integral control algorithm, so that the voltage of each part of the power grid is more balanced, and the stability and flexibility of the power grid are enhanced. Finally, combined with the demand response mechanism, the output voltage of each distributed power source is secondary adjusted, and the output voltage obtained by the secondary adjustment is output as the output voltage of the corresponding distributed power source, thereby improving the overall stability and reliability of the power grid. The overall optimization of power distribution ensures the stable operation of the power grid and the efficient use of new energy, ensures that each distributed power source can work together, reduces fluctuations and overload problems, thereby achieving more efficient energy management and resource utilization, and promoting the application and popularization of green and low-carbon energy.

[0148] Reference Manual Attached Figure 2 , showing a schematic structural diagram of a new energy distributed power control system provided by an embodiment of the present invention.

[0149] The embodiment of the present invention provides a new energy distributed power control system 20, including:

[0150] Processor 201;

[0151] The memory 202 stores computer-readable instructions, and when the computer-readable instructions are executed by the processor 201, the above-mentioned new energy distributed power control method is implemented.

[0152] From the above description, it can be seen that according to the meteorological data collected for the preset time, the mathematical model of the new energy distributed power system is used to output the predicted power of the new energy distributed power system within the preset time, thereby avoiding the instability of the power grid caused by power fluctuations. Next, the expected output frequency and expected output voltage of the new energy distributed power system are obtained, and the expected output frequency and expected output voltage are taken as the goal. The current predicted power is proportionally distributed through the droop controller. Based on the proportional distribution result, the output voltage of each distributed power source in the new energy distributed power system is adjusted through the distributed average proportional integral control algorithm, so that the voltage of each part of the power grid is more balanced, and the stability and flexibility of the power grid are enhanced. Finally, combined with the demand response mechanism, the output voltage of each distributed power source is secondary adjusted, and the output voltage obtained by the secondary adjustment is output as the output voltage of the corresponding distributed power source, thereby improving the overall stability and reliability of the power grid. The overall optimization of power distribution ensures the stable operation of the power grid and the efficient use of new energy, ensures that each distributed power source can work together, reduces fluctuations and overload problems, thereby achieving more efficient energy management and resource utilization, and promoting the application and popularization of green and low-carbon energy.

[0153] Unless otherwise specifically stated, the relative arrangement of the parts and steps described in these embodiments, numerical expressions and numerical values ​​do not limit the scope of the present invention. At the same time, it should be understood that, for ease of description, the sizes of the various parts shown in the accompanying drawings are not drawn according to the actual proportional relationship. The technology, methods and equipment known to ordinary technicians in the relevant field may not be discussed in detail, but in appropriate cases, the technology, methods and equipment should be regarded as a part of the authorization specification. In all examples shown and discussed here, any specific value should be interpreted as being merely exemplary, rather than as a limitation. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once a certain item is defined in an accompanying drawing, it does not need to be further discussed in subsequent drawings.

[0154] For ease of description, spatially relative terms such as "above", "above", "on the upper surface of", "above", etc. may be used here to describe the spatial positional relationship between a device or feature and other devices or features as shown in the figure. It should be understood that spatially relative terms are intended to include different orientations of the device in use or operation in addition to the orientation described in the figure. For example, if the device in the accompanying drawings is inverted, the device described as "above other devices or structures" or "above other devices or structures" will be positioned as "below other devices or structures" or "below other devices or structures". Thus, the exemplary term "above" can include both "above" and "below". The device can also be positioned in other different ways (rotated 90 degrees or in other orientations), and the spatially relative descriptions used here are interpreted accordingly.

[0155] In the description of the present invention, it is necessary to understand that the directions or positional relationships indicated by directional words such as "front, back, up, down, left, right", "lateral, vertical, perpendicular, horizontal" and "top, bottom" are usually based on the directions or positional relationships shown in the drawings. They are only for the convenience of describing the present invention and simplifying the description. Unless otherwise specified, these directional words do not indicate or imply that the devices or elements referred to must have a specific direction or be constructed and operated in a specific direction. Therefore, they cannot be understood as limiting the scope of protection of the present invention. The directional words "inside and outside" refer to the inside and outside relative to the contours of each component itself.

[0156] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A new energy distributed power control method, characterized in that the method include: S1: Collect meteorological data for a preset period of time; S2: outputting the predicted power of the new energy distributed power system within a preset time period according to the meteorological data and using a mathematical model of the new energy distributed power system; S3: Obtaining the expected output frequency and expected output voltage of the new energy distributed power system; S4: with the goal of achieving the desired output frequency and the desired output voltage, proportionally allocating the predicted power through a droop controller; S5: According to the proportional distribution result, the output voltage of each distributed power source in the new energy distributed power system is adjusted by a distributed average proportional integral control algorithm; S6: According to the adjustment result and in combination with the demand response mechanism, the output voltage of each distributed power source is adjusted for a second time; S7: outputting the output voltage obtained by the secondary adjustment as the output voltage of the corresponding distributed power source; The mathematical model is specifically: ； ； ； in, represents the time derivative of the wind turbine state vector, A wt represents the state matrix of the wind turbine, x wt represents the state vector of the wind turbine, B wt represents the input matrix of the wind turbine, represents the time derivative of the wind turbine state vector, A wt represents the state matrix of the wind turbine, x wt represents the state vector of the wind turbine, B wt represents the input matrix of the wind turbine, Indicates the pitch angle θ and torque T r The proportionality coefficient between J t represents the total moment of inertia of the system, Indicates speed ωr and torque T r The coefficient between represents the time constant of the generator, represents the proportional gain of the pitch controller, represents the integral gain of the pitch controller, represents the efficiency coefficient, represents the efficiency coefficient, represents the reference power, Indicates the base speed of the generator. Indicates the reference value of wind speed, Indicates wind speed v w and torque T r The gain factor between .

2. The new energy distributed power control method according to claim 1, characterized in that: The S2 specifically includes: S201: Setting the objective function and constraint conditions of the mathematical model, wherein the objective function includes a first objective function of minimizing the fatigue load of the wind turbine, a second objective function of minimizing the deviation between the measured voltage of the wind farm and the expected output voltage, and a third objective function of maximizing the fast dynamic reactive power support capability; S202: Under the constraints of the constraints, with the goal of minimizing the first objective function, minimizing the second objective function and maximizing the third objective function, the mathematical model is solved by a genetic algorithm to output the predicted power.

3. The new energy distributed power control method according to claim 2, characterized in that: The first objective function is specifically: ； in, f 1 means minimizing the fatigue load of the wind turbine, min means minimizing, n represents the total number of prediction steps, △ represents the deviation operator, T s represents the shaft torque of the motor group, W represents weight; The second objective function is specifically: ； in, f 2 means minimizing the deviation between the measured voltage and the expected output voltage, n represents the total number of prediction steps, V poc ( k ) indicates that k Step 1, Grid Connection Point POC The voltage, W poc and W Wt Both represent weighting factor matrices, V Wt ( k ) indicates that k Step 1, the voltage at the wind turbine; The third objective function is specifically: ； in, f 3 means maximizing the fast dynamic reactive power support capability, max means maximizing, Indicated in k Step 1, the predicted reactive power of the static VAR compensator or static VAR generator, represents the target median value of the static VAR compensator or static VAR generator reaction power, W s Represents the weighting factor of the reaction power.

4. The new energy distributed power control method according to claim 2, characterized in that: The constraint conditions specifically include: a first constraint condition, a second constraint condition and a third constraint condition; The first constraint condition is specifically: ensuring that the generator does not exceed its designed safe operating range under different operating conditions; The second constraint condition is specifically: ensuring that the reactive power output of the generator is kept within a reasonable range; The third constraint condition is specifically: ensuring that the working range of the static VAR compensator is within the range required by the system.

5. The new energy distributed power control method according to claim 1, characterized in that: The S4 specifically includes: S401: Calculating the frequency and voltage of the predicted power through a droop controller according to the expected output frequency, the expected output voltage and the predicted power; S402: Determine active power and reactive power allocated to each distributed power source according to the frequency and the voltage.

6. The new energy distributed power control method according to claim 5, characterized in that: The S401 is specifically as follows: The frequency and voltage of the predicted power are calculated according to the following formula: ； ； in, ω i Indicates i The frequency of the distributed power source, represents the expected output frequency, m i Indicates i The frequency and active power droop coefficient of each distributed power source, P i Indicates i The active power of distributed generation, E i Indicates i The voltage of a distributed power source, represents the expected output voltage, n i Indicates i The voltage and reactive power droop coefficient of a distributed power source, Q i Indicates i The reactive power of distributed generation, X ij Indicates the connection of distributed power supply i and j The line reactance, θ i Indicates i The voltage phase angle of a distributed power source, θ j Indicates j The voltage phase angle of a distributed power source, X i Indicates i The reactance of a distributed power source, E j Indicates j The voltage of a distributed power source, sin( ) represents the sine function, and cos( ) represents the cosine function.

7. The new energy distributed power control method according to claim 6, characterized in that: The S5 specifically includes: S501: Perform secondary control on the frequency through proximity communication: ； Among them, Ω i Distributed power supply i The secondary control variable, k i Distributed power supply i The gain factor, represents the quadratic control variable Ω i The time rate of change, a ij Indicates power supply i and power supply j The communication weight between a ij >0, indicating power i and power supply j Direct communication between S502: According to the frequency after secondary control, the output voltage of each distributed power source in the new energy distributed power system is adjusted by a distributed average proportional integral control algorithm: ； in, e i Indicates i The secondary control variables of the distributed generation are: represents the secondary control variable e i The time rate of change, βi Indicates i The gain factor of a distributed power source, b ij Indicates i The first distributed power source and the j The communication weight between distributed power sources, Indicates i The reactive power rating of each distributed generation unit, Indicates j The reactive power rating of each distributed generation unit.

8. A new energy distributed power control system, characterized in that: include: processor; A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the new energy distributed power control method according to any one of claims 1 to 7 is implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the new energy distributed power control method as described in any one of claims 1 to 7 is implemented.

Images