Distributed power supply power optimization output control method and system

Abstract

The invention discloses a distributed power supply power optimization output control method and system, and the method comprises the steps: obtaining the active power transmission capacity of a distributed power supply in a power distribution network system and the capacity of power generation equipment, simplifying the power distribution network system through a Thevenin equivalent circuit, and creating a control strategy simplification model; on the basis of a control strategy simplified model, parameters of the Thevenin equivalent circuit are identified in real time through a least square method, and dynamic characteristics of the power grid are obtained; based on the obtained dynamic characteristics of the power grid, obtaining an active power prediction value of the distributed power supply in real time, and judging whether power output needs to be adjusted; on the basis of judgment on adjustment power output, reactive power output is increased, and active power transmission capacity of a power distribution network system and capacity constraints of power generation equipment are combined, so that active power maximum output of the distributed power supply is realized. The method ensures that the new energy equipment can safely and stably transmit active power to the system in different network states, and shows good adaptability and flexibility.

Description

Technical Field

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

[0002] With the transformation of the global energy structure and the advancement of sustainable development strategies, distributed new energy equipment, such as solar photovoltaics and wind power generation, are being integrated into the distribution network at an unprecedented rate. These new energy devices, with their advantages of wide distribution, cleanness and environmental protection, provide a new source of electricity for the power grid, help reduce dependence on fossil energy, and promote the green upgrade of energy consumption. With the diversification of load types and user behaviors, the power supply security and stability of the distribution network face new challenges. The power demand at the user end has become more unpredictable, which puts higher requirements on the regulation capacity of the power grid. If the output power of the distributed power source exceeds the transmission capacity of the system, it will cause equipment oscillation or instability, and may even cause the paralysis of the local power grid, affecting the reliability and safety of power supply.

[0003] At present, in order to improve the transmission capacity of the distribution network, a common method is to enhance the carrying capacity of the system through reactive power compensation equipment. Reactive power compensation equipment can improve the power factor of the power grid, reduce line losses, and improve the transmission efficiency of the power grid. However, this method also has certain limitations. First, the construction and maintenance of a large number of reactive power compensation equipment will inevitably increase the construction cost of power grid operators. Secondly, how to achieve orderly coordination among these devices and avoid mutual interference is also a technical challenge. Therefore, exploring a more economical, efficient and easy-to-coordinate distributed power supply power optimization output control method is of great significance to improving the transmission capacity and power supply stability of the power grid. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In view of the above existing problems, the present invention is proposed.

[0006] Therefore, the present invention provides a distributed power supply power optimization output control method and system to solve the problems of high cost and complex equipment coordination in the existing distributed power supply power optimization output control method.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In a first aspect, the present invention provides a distributed power supply power optimization output control method, comprising:

[0009] Obtain the active power transmission capacity and the capacity of the power generation equipment of the distributed power generation in the distribution network system, simplify the distribution network system through the Thevenin equivalent circuit, and create a simplified control strategy model;

[0010] Based on the simplified model of the control strategy, the parameters of the Thevenin equivalent circuit are identified in real time by the least square method to obtain the dynamic characteristics of the power grid;

[0011] Based on the dynamic characteristics of the power grid, the active power forecast value of the distributed power source is obtained in real time to determine whether the power output needs to be adjusted;

[0012] Based on the judgment of adjusting power output, the reactive power output is increased, and the maximum active power output of distributed power sources is achieved by combining the active power transmission capacity of the distribution network system and the capacity constraints of the power generation equipment.

[0013] As a preferred solution of the distributed power supply power optimization output control method described in the present invention, wherein:

[0014] The method of obtaining the active power transmission capacity of the distributed power source in the power distribution network system comprises the following steps:

[0015] Collect line parameters and node characteristic data of the distribution network;

[0016] Use power system analysis software to perform topological analysis on distribution networks;

[0017] Calculate the active power transfer capacity of the distribution network through power flow analysis based on line parameters and grid topology;

[0018] Taking into account the operating status of the power grid, including load changes and power supply fluctuations, and adjusting the calculation results of transmission capacity;

[0019] A genetic algorithm is applied to find the optimal active power transfer capacity.

[0020] As a preferred solution of the distributed power supply power optimization output control method described in the present invention, wherein:

[0021] The simplification of the distribution network system by using the Thevenin equivalent circuit includes determining an equivalent impedance and an equivalent voltage source.

[0022] As a preferred solution of the distributed power supply power optimization output control method described in the present invention, wherein:

[0023] The parameters of the Thevenin equivalent circuit are identified in real time by the least square method, including: the equivalent potential E eq , equivalent resistance Req and equivalent reactance X eq ;

[0024] The least squares method real-time identification includes constructing an objective function and solving a linear equation group.

[0025] As a preferred solution of the distributed power supply power optimization output control method described in the present invention, wherein:

[0026] The determining whether the power output needs to be adjusted includes:

[0027] When the distributed generation power generation active power forecast value P pred Exceeding the transmission capacity limit P lim When the power factor is reduced, the output reactive power Q of the distributed power source is increased. ref , the maximum output active power P out .

[0028] As a preferred solution of the distributed power supply power optimization output control method described in the present invention, wherein:

[0029] The output reactive power Q of the distributed power source ref and the maximum active power P out , from the following system of equations, construct a fixed point iteration format to solve it:

[0030]

[0031] Where: ε is the system stability margin, S lim The capacity of the power generation equipment.

[0032] As a preferred solution of the distributed power supply power optimization output control method described in the present invention, wherein:

[0033] The real-time obtained distributed power source active power forecast value is the distributed power source active power value after 30 seconds.

[0034] In a second aspect, the present invention provides a distributed power supply power optimization output control system, comprising:

[0035] Create a module to obtain the active power transmission capacity and the capacity of the power generation equipment of the distributed power generation in the distribution network system, simplify the distribution network system through the Thevenin equivalent circuit, and create a simplified model of the control strategy;

[0036] An identification module, used to identify the parameters of the Thevenin equivalent circuit in real time by a least square method based on a simplified model of a control strategy, so as to obtain the dynamic characteristics of the power grid;

[0037] A judgment module is used to obtain the active power prediction value of the distributed power source in real time based on the dynamic characteristics of the power grid, and to judge whether the power output needs to be adjusted;

[0038] The constraint module is used to achieve the maximum active power output of the distributed power source based on the judgment of the adjusted power output, combined with the active power transmission capacity of the distribution network system and the capacity constraints of the power generation equipment.

[0039] In a third aspect, the present invention provides a computing device, comprising:

[0040] Memory, used to store programs;

[0041] A processor is used to execute the computer executable instructions, which, when executed by the processor, implement the steps of the distributed power supply power optimization output control method.

[0042] In a fourth aspect, the present invention provides a computer-readable storage medium, comprising: when the program is executed by a processor, the steps of implementing the distributed power supply power optimization output control method are implemented.

[0043] Beneficial effects of the present invention:

[0044] 1) Improve system transmission capacity: The transmission capacity of the distribution network can be effectively improved by optimizing the control method. By optimizing the power factor and reactive power output of the equipment, the critical short-circuit ratio of the system can be reduced, allowing more active power to flow to the grid.

[0045] 2) Enhance equipment stability: The proposed active support control strategy can quickly respond to changes in the state of the distribution network, identify the Thevenin equivalent circuit parameters in real time through the least squares method, and adjust the active and reactive output of new energy equipment in time to ensure the safe and stable operation of the equipment under various operating conditions, and avoid equipment oscillation or instability caused by output power exceeding the system transmission capacity.

[0046] 3) Strong adaptability and flexibility: The proposed control strategy is not only applicable to the current state of the distribution network, but also can adapt to changes in the distribution network structure, such as changes in the Thevenin equivalent parameters caused by the withdrawal or access of equipment. It can optimize the control parameters in real time to ensure that under different network conditions, new energy equipment can safely and stably deliver active power to the system, showing good adaptability and flexibility. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0048] Figure 1 A basic flow chart of a distributed power supply power optimization output control method provided by an embodiment of the present invention;

[0049] Figure 2 A schematic diagram of an IEEE33-node distribution network of a distributed power supply power optimization output control method provided by an embodiment of the present invention;

[0050] Figure 3 A voltage and power angle curve diagram at 3.5MW of a distributed power supply power optimization output control method provided by an embodiment of the present invention;

[0051] Figure 4 A voltage and power angle curve diagram at 4.5MW of a distributed power supply power optimization output control method provided by an embodiment of the present invention;

[0052] Figure 5 A voltage and power angle curve diagram under the control of a distributed power supply power optimization output control method provided by an embodiment of the present invention;

[0053] Figure 6 A power curve diagram under control of a distributed power supply power optimization output control method provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0054] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0055] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0056] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0057] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0058] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0059] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0060] Example 1

[0061] Reference Figure 1 , is an embodiment of the present invention, which provides a distributed power supply power optimization output control method, such as Figure 1 As shown, the following steps are included:

[0062] S1: Obtain the active power transmission capacity and the capacity of the power generation equipment of the distributed power generation in the distribution network system, simplify the distribution network system through the Thevenin equivalent circuit, and create a simplified control strategy model;

[0063] In the embodiment of the present application, the active power transmission capacity P of the distributed power source in the distribution network system is obtained. lim The method is determined by analyzing the line parameters and node characteristic data and topological structure of the distribution network, including the following steps:

[0064] a) Collect line parameters and node characteristic data of distribution network;

[0065] b) Use power system analysis software to perform topological analysis on the distribution network;

[0066] c) Calculate the active power transmission capacity of the distribution network through power flow analysis based on line parameters and grid topology;

[0067] d) Taking into account the operating status of the power grid, including load changes and power supply fluctuations, and adjusting the calculation results of the transmission capacity;

[0068] e) Apply optimization algorithms to find the optimal active power transfer capacity;

[0069] In the embodiment of the present application, a genetic algorithm (GA) can be used to optimize the active power transmission capacity P lim , specifically including the following steps:

[0070] Objective function:

[0071] The goal is to maximize the transmission capacity, and we can define a fitness function f(x) to measure the quality of the solution, where x is a vector containing line parameters and node characteristics.

[0072] Iteration process:

[0073] 1. Initialize the population: Randomly generate an initial population of N individuals.

[0074] 2. Evaluate fitness: calculate f(x) for each individual.

[0075] 3. Selection operation: Select individuals with high fitness as parents. Common selection strategies include roulette selection, tournament selection, etc.

[0076] 4. Crossover operation: Randomly select two of the selected parents for crossover to generate new offspring.

[0077] 5. Mutation operation: mutate the offspring and change certain genes to explore new solution space.

[0078] 6. Replacement: Replace some individuals in the population with new offspring.

[0079] 7. Termination condition: Repeat the above steps until the termination condition is met, such as reaching the maximum number of iterations or the fitness no longer improves.

[0080] In another possible implementation, the optimization algorithm may also be a particle swarm optimization algorithm (PSO); specifically comprising the following steps:

[0081] Particle swarm optimization algorithm is an optimization algorithm that simulates the flight behavior of a flock of birds. Particles fly in the solution space and find the optimal solution by updating their own position and speed.

[0082] vi (t+1)=wv i (t)+c 1 r 1 (pbest i -x i (t))+c 2 r 2 (gbest-x i (t))

[0083] x i (t+1)=x i (t)+v i (t+1)

[0084] Among them, x i (t) represents the position of the ith particle at time t (i.e., a set of line parameters and node characteristics); v i (t) represents the velocity of the ith particle at time t; pbest i represents the best historical position of particle i; gbest represents the best of all the best historical positions of particles; w is the inertia weight, which controls the degree to which the particle maintains the current direction; c 1 and c 2 is the acceleration constant; r 1 and r 2 is a random number in the interval [0, 1].

[0085] The particle's position x i will be updated to the position at the next moment, and the fitness function f(x i ).

[0086] In the above two algorithms, the fitness function f(x) should be designed to reflect P lim Optimization goals, such as:

[0087]

[0088] in, is the active power transfer capacity calculated based on parameter x, is the target transmission capacity.

[0089] Through continuous iteration and optimization, these algorithms can find the parameter x that maximizes f(x), thereby determining the optimal active power transfer capacity P. lim .

[0090] In the embodiment of the present application, the capacity S of the distributed power generation equipment is obtained. lim This is achieved by measuring and recording the rated output power of the power generation equipment.

[0091] It should be noted that obtaining the active power transmission capacity of distributed power sources and the capacity of power generation equipment is the starting point of the control strategy. These data provide the operating range and physical limitations of the system and set the basic boundary conditions for subsequent control actions.

[0092] S2: Based on the simplified model of the control strategy, the parameters of the Thevenin equivalent circuit are identified in real time by the least square method to obtain the dynamic characteristics of the power grid;

[0093] In the embodiment of the present application, the Thévenin equivalent circuit simplification includes determining an equivalent impedance and an equivalent voltage source. The least squares identification includes constructing an objective function and solving a linear equation system.

[0094] In the embodiment of the present application, the parameters of the Thevenin equivalent circuit are identified in real time by the least square method, including: E eq is the equivalent potential, R eq is the equivalent resistance, X eq is the equivalent reactance.

[0095] In an embodiment of the present application, the distribution network parameters are collected in real time, and when the Thevenin equivalent parameters change due to the exit or entry of equipment, the parameters of the Thevenin equivalent circuit are calculated and identified in a timely manner.

[0096] It should be noted that by simplifying the distribution network using the Thevenin equivalent circuit model, it can be abstracted into an equivalent voltage source and a series resistor. This step is based on the physical parameters provided by S1. The circuit parameters are identified in real time through the least squares method to obtain the current dynamic characteristics of the power grid and provide real-time power grid status information for subsequent power prediction and control.

[0097] S3: Based on the dynamic characteristics of the power grid, the active power prediction value of the distributed power source is obtained in real time to determine whether the power output needs to be adjusted;

[0098] In the embodiment of the present application, the active power prediction value P pred It is obtained through historical data analysis and prediction model. Get the predicted value of distributed power source active power P pred It is the active power value of the distributed generation after 30 seconds.

[0099] It should be noted that the real-time active power forecast value reflects the expected output of distributed power sources in the future. Based on this information, the system can determine whether the current power output is close to or exceeds the system transmission capacity, and whether power output needs to be adjusted to avoid overload or instability.

[0100] S4: Based on the judgment of adjusting power output, combined with the active power transmission capacity of the distribution network system and the capacity constraints of the power generation equipment, the maximum active power output of the distributed power generation is achieved.

[0101] In the embodiment of the present application, when P pred >P lim When the power factor is reduced, the output reactive power Q of the distributed power source is increased. ref , in the distribution network system transmission capacity P lim and equipment power generation capacity S lim Under the constraint, the maximum active power P of distributed generation can be achieved. out Output.

[0102] In the embodiment of the present application, the reduction of the power factor is achieved by adjusting the control parameters of the distributed power source.

[0103] In the embodiment of the present application, when the distributed power generation active power prediction value P pred Exceeding the transmission capacity limit P lim When the output reactive power of distributed generation is Q ref and the maximum active power P out From the following set of equations, construct a fixed point iteration format to solve them.

[0104]

[0105] Among them, ε is the system stability margin.

[0106] It should be noted that when the system determines that the active power output needs to be adjusted, the control strategy will adjust the power factor and reactive power output of the distributed power source in combination with the transmission capacity of the power grid system and the capacity constraints of the power generation equipment obtained in S1 and S2, so as to maximize the active power output of the distributed power source without violating the system safety and physical limitations of the equipment.

[0107] This embodiment also provides a distributed power supply power optimization output control system, including:

[0108] Create a module to obtain the active power transmission capacity and the capacity of the power generation equipment of the distributed power generation in the distribution network system, simplify the distribution network system through the Thevenin equivalent circuit, and create a simplified model of the control strategy;

[0109] An identification module, used to identify the parameters of the Thevenin equivalent circuit in real time by a least square method based on a simplified model of a control strategy, so as to obtain the dynamic characteristics of the power grid;

[0110] A judgment module is used to obtain the active power prediction value of the distributed power source in real time based on the dynamic characteristics of the power grid, and to judge whether the power output needs to be adjusted;

[0111] The constraint module is used to achieve the maximum output of the active power of the distributed power source based on the judgment of the adjusted power output and the constraints of the transmission capacity of the distribution network system and the power generation capacity of the equipment.

[0112] Furthermore, it also includes:

[0113] Memory, used to store programs;

[0114] A processor is used to load the program to execute the distributed power supply power optimization output control method.

[0115] This embodiment also provides a computer-readable storage medium storing a program, which, when executed by a processor, implements the distributed power supply power optimization output control method.

[0116] The storage medium proposed in this embodiment and the distributed power supply power optimization output control method proposed in the above embodiment belong to the same inventive concept. The technical details not described in detail in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0117] Through the above description of the implementation methods, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ReadOnly, Memory, ROM), random access memory (RandomAccess Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform the methods of various embodiments of the present invention.

[0118] Example 2

[0119] Refer to Table 1 and Figure 2-6 , which is an embodiment of the present invention, provides a distributed power supply power optimization output control method. In order to verify its beneficial effects, scientific demonstration is carried out through specific implementation methods and implementation effects.

[0120] The specific embodiments are as follows:

[0121] Adopt IEEE-33 node active distribution network including new energy equipment, energy storage and multi-type loads, such as Figure 2 As shown, an example is constructed, Matlab is used to solve the Thevenin equivalent circuit, and Simulink is used to simulate the system state variable adjustment process;

[0122] Thevenin equivalent circuit parameters, critical short circuit ratio CSCR, active power transfer capacity P under different network conditions lim , as shown in Table 1.

[0123] Table 1 Parameters

[0124] <![CDATA[R eq ]]> <![CDATA[R eq ]]> <![CDATA[X eq ]]> CSCR <![CDATA[P lim ]]> 1 0.9534 0.1117 0.2062 1.0474 3.7007 2 0.9395 0.1180 0.2078 1.0124 3.6484 3 1.0140 0.0961 0.2005 1.1356 4.0724 4 1.0811 0.0801 0.1885 1.221 4.6549 5 1.0680 0.0835 0.1890 1.1918 4.632

[0125] The capacity of the new energy equipment is 4.5MW, the current output power is 2.5MW, and the power factor is 1. The node voltage information is calculated by combining the Thevenin equivalent circuit, and the initial values ​​of each state variable in the equipment control link are derived. Then, the output power of the equipment is increased by 1MW and 2MW respectively, and the equipment phase-locking angle and node voltage amplitude are obtained as follows: Figure 3 and Figure 4 shown.

[0126] from Figure 5 It was found that the output power of the equipment was less than the system transmission power capacity of 3.7MW. After a period of adjustment, the phase-locking angle and node voltage amplitude of the equipment entered a new stable operating state.

[0127] Figure 6 It shows that when the device output power exceeds the system transmission capacity, it will cause the phase-locked loop and port voltage oscillation.

[0128] The system Thevenin equivalent circuit parameter values ​​and system safety margin ε are introduced, and the active and reactive control reference values ​​are obtained by fixed point iteration method, which are 4.46MW and 0.63MW respectively. After being introduced into the simulation model, it is observed that the equipment phase-locking angle and node voltage amplitude are as follows Figure 5 As shown, the power changes as Figure 6 shown. Figure 5 The state variable reaches a steady-state value after 0.5s, and at this time the device output active power increases by 20% compared with the maximum stable output power of the device when the unit factor is 1, indicating the effectiveness of this method.

[0129] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A distributed power supply power optimization output control method, characterized in that: include: Obtain the active power transmission capacity and the capacity of the power generation equipment of the distributed power generation in the distribution network system, simplify the distribution network system through the Thevenin equivalent circuit, and create a simplified control strategy model; Based on the simplified model of the control strategy, the parameters of the Thevenin equivalent circuit are identified in real time by the least square method to obtain the dynamic characteristics of the power grid; Based on the dynamic characteristics of the power grid, the active power forecast value of the distributed power source is obtained in real time to determine whether the power output needs to be adjusted; Based on the judgment of adjusting power output, the reactive power output is increased, and the maximum active power output of distributed power sources is achieved by combining the active power transmission capacity of the distribution network system and the capacity constraints of the power generation equipment.

2. The distributed power supply power optimization output control method according to claim 1, characterized in that: The method of obtaining the active power transmission capacity of the distributed power source in the power distribution network system comprises the following steps: Collect line parameters and node characteristic data of the distribution network; Use power system analysis software to perform topological analysis on distribution networks; Calculate the active power transfer capacity of the distribution network through power flow analysis based on line parameters and grid topology; Taking into account the operating status of the power grid, including load changes and power supply fluctuations, and adjusting the calculation results of transmission capacity; An optimization algorithm is applied to find the optimal active power transfer capacity.

3. The distributed power supply power optimization output control method according to claim 1 or 2, characterized in that: The simplification of the distribution network system by using the Thevenin equivalent circuit includes determining an equivalent impedance and an equivalent voltage source.

4. The distributed power supply power optimization output control method according to claim 3, characterized in that: The parameters of the Thevenin equivalent circuit are identified in real time by the least square method, including: the equivalent potential E eq , equivalent resistance R eq and equivalent reactance X eq ; The least squares method real-time identification includes constructing an objective function and solving a linear equation group.

5. The distributed power supply power optimization output control method according to claim 4, characterized in that: The determining whether the power output needs to be adjusted includes: When the distributed generation power generation active power forecast value P pred Exceeding the active power transfer capacity P lim When the power factor is reduced, the output reactive power Q of the distributed power source is increased. ref , the maximum output active power P out .

6. The distributed power supply power optimization output control method according to claim 5, characterized in that: The output reactive power Q of the distributed power source ref and the maximum active power P out , from the following system of equations, construct a fixed point iteration format to solve it: Among them, ε is the system stability margin, S lim The capacity of the power generation equipment.

7. The distributed power supply power optimization output control method according to claim 6, characterized in that: The real-time obtained distributed power source active power forecast value is the distributed power source active power value after 30 seconds.

8. A system based on the distributed power supply power optimization output control method according to claim 1, characterized in that: Create a module to obtain the active power transmission capacity and the capacity of the power generation equipment of the distributed power generation in the distribution network system, simplify the distribution network system through the Thevenin equivalent circuit, and create a simplified model of the control strategy; An identification module, used to identify the parameters of the Thevenin equivalent circuit in real time by a least square method based on a simplified model of a control strategy, so as to obtain the dynamic characteristics of the power grid; A judgment module is used to obtain the active power prediction value of the distributed power source in real time based on the dynamic characteristics of the power grid, and to judge whether the power output needs to be adjusted; The constraint module is used to achieve the maximum active power output of the distributed power source based on the judgment of the adjusted power output, combined with the active power transmission capacity of the distribution network system and the capacity constraints of the power generation equipment.

9. An electronic device, characterized in that: include: Memory, used to store programs; A processor is used to load the program to execute the steps of the distributed power supply power optimization output control method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a program, characterized in that: When the program is executed by the processor, the steps of the distributed power supply power optimization output control method as described in any one of claims 1 to 7 are implemented.

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