A new energy station wide frequency oscillation stability improvement method and system based on output topology optimization

Abstract

The present application relates to a kind of new energy field station wideband oscillation stability improvement method and system based on output topology optimization, belong to new energy grid-connected system stability analysis and operation optimization technical field.The method obtains field station topology, unit operating condition, external grid impedance, dispatch active power instruction and feeder rated parameter, establishes new energy unit multi-condition wideband impedance model;According to the candidate unit switching state and output configuration, construct node admittance matrix, calculate field station equivalent impedance and system impedance ratio matrix, and obtain the overall gain margin of field station according to generalized Nyquist stability criterion;With gain margin target deviation minimum as target, under the constraint of power balance, single machine stability and feeder current-carrying capacity, the optimal output topology is obtained by using genetic algorithm.The method can improve the wideband oscillation stability margin of new energy field station without modifying the internal control structure of unit or adding damping equipment.

Description

Technical Field

[0001] This invention relates to the field of stability analysis and operation optimization technology for new energy grid-connected systems, and in particular to a method and system for improving broadband oscillation stability of new energy power plants based on output topology optimization.

[0002] More specifically, the present invention relates to broadband impedance modeling of new energy units under multiple operating conditions, equivalent impedance calculation of new energy power stations, broadband oscillation stability assessment based on the generalized Nyquist stability criterion, and optimization of the switching status and output configuration of new energy units in a power station under a given active power dispatch command, with the overall gain margin of the new energy power station as the optimization objective. Background Technology

[0003] With the large-scale grid connection of new energy sources such as photovoltaic and wind power, the proportion of power electronic equipment in the power system is constantly increasing, and the power system is gradually showing the operating characteristics of high proportion of new energy and high proportion of power electronic equipment. Compared with traditional synchronous generators, grid-connected inverters have weaker inertia and damping characteristics, and there are multi-time-scale dynamic couplings between the control link, filtering link, collector line, step-up transformer and external power grid of the grid-connected inverter, which can easily cause subsynchronous oscillations, medium and high frequency oscillations and other broadband oscillation problems.

[0004] Existing technologies for improving the broadband oscillation stability of new energy grid-connected systems mainly include: modifying the internal control structure or control parameters of the grid-connected inverter to improve its impedance characteristics; or adding additional damping devices in new energy power plants, common coupling points, and transmission lines to suppress oscillations in specific frequency bands.

[0005] However, for large-scale renewable energy power plants already in operation, the control algorithms and key control parameters of commercial renewable energy units are usually fixed, making it difficult for plant operators to directly modify the internal control structure of the renewable energy units. Furthermore, configuring additional damping devices increases the construction, renovation, and operation and maintenance costs of renewable energy power plants. Moreover, additional damping devices are typically designed for specific oscillation modes, and their applicability may be limited when the plant topology, unit operating conditions, or external grid strength changes.

[0006] A renewable energy power station typically comprises multiple renewable energy generating units. These units are fed into a common coupling point via multiple collector feeders and then connected to a step-up transformer. Even if the total active power output of the renewable energy power station remains constant, the switching combination of different renewable energy generating units and their output configuration under different operating conditions will change the equivalent broadband impedance of the renewable energy power station, thereby altering the impedance interaction characteristics between the renewable energy power station and the external power grid.

[0007] Existing technologies typically determine the commissioning sequence of new energy generating units based on their distance from the common coupling point, line losses, or available power. They do not fully consider the impact of different power output topologies on the broadband oscillation stability margin of new energy power plants, nor do they incorporate the total active power output requirements of the power plant, the stability of individual new energy generating units, and the current carrying capacity of feeders into the power plant output topology optimization model.

[0008] Therefore, there is a need to provide a method to improve the broadband oscillation stability of new energy power plants by utilizing their existing unit switching and output regulation capabilities without altering the internal control structure of the new energy units or configuring additional damping equipment. The uploaded materials propose an overall scheme that uses a genetic algorithm to obtain the optimal output topology, with the overall gain margin of the power plant as the objective, under constraints of power balance, individual unit stability, and feeder current carrying capacity. Summary of the Invention

[0009] In view of this, the purpose of this invention is to solve the problems that existing solutions for improving the broadband oscillation stability of new energy power plants require modification of the internal control parameters of new energy units, addition of additional damping devices, and failure to consider the impact of unit switching combinations on the equivalent broadband impedance of the power plant. The invention provides a method and system for improving the broadband oscillation stability of new energy power plants based on output topology optimization.

[0010] Under the given active power dispatching command of a new energy power plant, this invention takes the switching status and output configuration of the new energy units as output topology decision variables. By calculating the equivalent impedance of the power plant and the overall gain margin of the power plant corresponding to different candidate output topologies, the optimal output topology that takes into account the overall stability of the power plant, the stability of individual units, power balance and feeder current carrying capacity is obtained.

[0011] To achieve the above objectives, the present invention provides the following technical solution: In a first aspect, the present invention provides a method for improving the broadband oscillation stability of new energy power plants based on power output topology optimization, comprising the following steps: S1 acquires the topology data of the new energy power station, the operating condition data of each new energy unit, the external grid impedance, the active power command issued by the superior dispatching authority, and the rated operating parameters of each feeder, and establishes a broadband impedance model for each new energy unit under different operating conditions.

[0012] S2. The switching status and output configuration of each new energy unit are used as output topology decision variables. For the candidate output topology formed by the output topology decision variables, the node admittance matrix of the new energy power station is established based on the broadband impedance model of each new energy unit, the power station topology data and the switching status of each new energy unit. The equivalent impedance of the new energy power station at the common coupling point is determined based on the node admittance matrix.

[0013] S3. Construct the system impedance ratio matrix based on the external grid impedance and the equivalent impedance of the power station. Use the generalized Nyquist stability criterion to determine the eigenvalue Nyquist curve of the system impedance ratio matrix. Calculate the overall gain margin of the power station corresponding to the candidate output topology based on the intersection of the eigenvalue Nyquist curve and the negative real axis.

[0014] S4. The optimization objective is to minimize the deviation of the overall gain margin of the power station from the preset gain margin target area. The constraints are to ensure that the total active power output of the new energy power station meets the active power command of the power station, that each new energy unit in operation remains stable, and that each feeder meets the current carrying capacity requirements. A new energy power station output topology optimization model is established.

[0015] S5. A genetic algorithm is used to solve the power output topology optimization model of the new energy power station to obtain the optimal power output topology scheme of the new energy power station that satisfies the constraints and has the optimal corresponding optimization objective value. The switching status and power output configuration of each new energy unit are determined according to the optimal power output topology scheme.

[0016] Furthermore, the new energy units include at least one of photovoltaic generator sets and wind turbine generator sets.

[0017] Furthermore, based on the voltage and current disturbance responses at the grid connection ports of the new energy units, a wideband impedance model of the new energy units under different operating conditions is established by adopting black-box identification, gray-box identification, or data-model fusion identification methods.

[0018] Furthermore, the different operating conditions include at least operating conditions corresponding to different active power output levels, and may also include operating conditions corresponding to different reactive power, common coupling point voltage, external power grid strength, or control mode.

[0019] Furthermore, the first i Taiwan's new energy units at frequency f The impedance matrix in the dq coordinate system at point is: (1) No. i Taiwan's new energy units at frequency f The admittance matrix in the dq coordinate system at point is: (2) in, , , and The first i Impedance matrix elements of the new energy unit, , , and The first iAdmittance matrix elements of Taiwan's new energy power units.

[0020] Furthermore, the first i The equivalent admittance of the new energy generating units after they are connected to the new energy power station is: (3) in, For the first i Taiwan's new energy units are always t The switching state variables, and: ; when When, it indicates the first i Taiwan's new energy units have been put into operation; when When, it indicates the first i The new energy unit was disconnected.

[0021] Furthermore, the nodes corresponding to the common coupling points are designated as external port nodes, and the remaining nodes in the new energy power station are designated as internal nodes. The node admittance matrix of the new energy power station is then divided into blocks according to the external port nodes and internal nodes, resulting in: (4) in, and These are the port current vector and port voltage vector at the common coupling point, respectively; and These are the injected current vector and the voltage vector of the internal node, respectively. , , and It is a block matrix of the nodal admittance matrix.

[0022] In the absence of independent external current injection into the internal nodes, let The equivalent admittance of the new energy power station at the common coupling point is obtained through network reduction: (5) The equivalent impedance of the new energy power station at the common coupling point is: (6) Furthermore, an impedance equivalent model of the new energy power plant grid connection system is established, which equates the external power grid to the external power grid impedance. And the new energy power station is equivalent to the power station's equivalent impedance. .

[0023] The system impedance ratio matrix, consisting of the external power grid impedance and the equivalent impedance of the power station, is as follows: (7) in, sFor Laplace complex variables; This is the system impedance ratio matrix.

[0024] Calculate the eigenvalues ​​of the system impedance ratio matrix: (8) in, The system impedance ratio matrix is ​​the first... k 1 eigenvalue, Represents the extraction matrix of the first... k Each feature value.

[0025] Plot the Nyquist curves for each eigenvalue according to the generalized Nyquist stability criterion. The Nyquist curves for all eigenvalues ​​do not enclose the critical point on the complex plane. When the grid-connected system of a new energy power station is deemed stable, it is determined that the system is stable; when at least one eigenvalue Nyquist curve surrounds the critical point in a manner that does not satisfy the stability condition. At that time, it was determined that the grid connection system of the new energy power station was at risk of instability.

[0026] Search for the intersection points on the eigenvalue Nyquist curves where the imaginary part is zero and lies on the negative real axis. The minimum value of the real part at each intersection point is then determined as the intersection value on the negative real axis. ,Right now: (9) in, Angular frequency; Indicates taking the real part; This indicates taking the imaginary part.

[0027] Overall gain margin of the station Calculate according to the following formula: (10) when When, it indicates that the intersection of the negative real axis is at the critical point. On the right side, the grid connection system of the new energy power station is stable; when When the intersection of the negative real axis crosses the critical point, it indicates that the grid-connected system of the new energy power station is unstable. The larger the value, the greater the broadband oscillation stability margin of the new energy power station.

[0028] Furthermore, the operating status of new energy power plants is divided into a gain margin target region, an oscillation risk warning region, and an unstable region. The gain margin target region is determined by preset lower and upper limits of gain margin; the oscillation risk warning region corresponds to an operating status where the gain margin is greater than zero but lower than the preset lower limit of gain margin; and the unstable region corresponds to an operating status where the gain margin is less than zero.

[0029] Let the target interval of the intersection of the negative real axis be: ;in, This represents the lower limit of the target interval at the intersection of the negative real axis. This represents the upper limit of the target interval for the intersection of the negative real axis. The target interval for the intersection of the negative real axis and the target region for the gain margin have the following correspondence: (11) (12) in, and These represent the lower and upper limits of the target region for gain margin, respectively.

[0030] The deviation of the candidate output topology from the target interval of the negative real axis intersection is: (13) Therefore, the objective function of the power output topology optimization model for new energy power plants is constructed as follows: (14) when When located within the target interval of the intersection of the negative real axis, ;when When the candidate output topology is located outside the target interval of the negative real axis intersection, the negative real axis intersection corresponding to the candidate output topology is moved towards the target interval by the objective function.

[0031] In other implementations, the optimization objective can be to maximize the overall gain margin of the station or minimize the deviation between the overall gain margin of the station and the preset target gain margin.

[0032] Furthermore, the power balance constraints for new energy power plants are as follows: (15) in, N This refers to the total number of new energy generating units within the new energy power station. For the first i Active power output of Taiwan's new energy generating units under candidate power output configurations; This refers to the active power command issued by the superior dispatcher for the power station.

[0033] When considering the adjustable output range of new energy units, the following conditions must also be met: (16) in, and The first i The minimum and maximum active power output allowed when the new energy generating unit is put into operation. i When the Taiwan New Energy unit was disconnected, .

[0034] Furthermore, an impedance ratio matrix is ​​established for each new energy unit put into operation, and the intersection value of its eigenvalue Nyquist curve and the negative real axis is calculated. And set single-machine stability constraints: (17) in, For the first i The eigenvalues ​​of the single-unit impedance ratio matrix of the new energy generating unit are the intersection points of the Nyquist curve and the negative real axis.

[0035] Furthermore, the first l The current-carrying capacity constraint of the feeder is: (18) in, To access the first l A collection of new energy generating units with a single feeder line; For the first i Rated apparent power of the new energy generating units; For the first l The rated line voltage of the feeder; For the first l The maximum current that a feeder is allowed to carry continuously.

[0036] When new energy generating units connected to the same feeder have the same rated apparent power S At that time, the first l The maximum number of identical new energy generating units allowed to be connected to a single feeder is: (18) The corresponding feeder current carrying capacity constraint simplifies to: (19) in, This indicates the floor function.

[0037] Based on the above objective function and constraints, the power output topology optimization model for new energy power plants can be expressed as follows:

[0038] ] (twenty one)

[0039]

[0040] Where s is the state vector composed of the switching state variables of each new energy unit; P is the output vector composed of the active power output of each new energy unit. LThis refers to the number of feeders within a new energy power station.

[0041] Furthermore, a genetic algorithm is used to solve the power output topology optimization model for renewable energy power plants. Each candidate individual corresponds to a renewable energy power plant power output topology scheme, and each candidate individual includes at least a binary gene representing the switching status of each renewable energy unit.

[0042] When the active power output of a new energy unit is determined by preset operating conditions, the chromosome can be represented as: (twenty two) When the active power output of the renewable energy units can be adjusted within a preset range, the chromosome also includes the output genes of each renewable energy unit, represented as: (twenty three) For each candidate, according to the corresponding new energy unit switching status and output configuration, the broadband impedance model of each new energy unit under the corresponding operating conditions is called to calculate the node admittance matrix, equivalent impedance of the station, system impedance ratio matrix, negative real axis intersection value and overall gain margin of the station, and the objective function value is calculated.

[0043] A penalty function is applied to candidate individuals that do not meet the power balance constraint, single-unit stability constraint, or feeder current carrying capacity constraint to obtain the fitness evaluation value of the candidate individual. For example, the evaluation function with penalty function is: (twenty four) in, It is an evaluation function with a penalty function; , and These are the penalty coefficients corresponding to power balance constraints, single-unit stability constraints, and feeder current carrying capacity constraints, respectively. , and These represent the degree of violation of the corresponding constraints.

[0044] The degree of violation of power balance constraints can be expressed as: (25) The degree of violation of single-machine stability constraints can be expressed as: (26) The degree of violation of the feeder current-carrying capacity constraint can be expressed as: (27) Genetic algorithms retain candidate individuals with high fitness through selection operations; exchange some genes of different candidate individuals through crossover operations to combine the superior characteristics of different power output topologies; and change the switching state or power output configuration of at least one new energy unit through mutation operations to increase population diversity and reduce the probability of the algorithm getting stuck in local optima.

[0045] When the maximum number of iterations is reached, the change in the optimal fitness after a preset number of generations is less than a preset threshold, or when a candidate individual that satisfies the target region of gain margin and all constraints has been obtained, the genetic algorithm is terminated, and the candidate individual with the best fitness is determined as the optimal output topology scheme for the new energy power station.

[0046] Secondly, the present invention provides a system for improving the broadband oscillation stability of new energy power stations based on power output topology optimization, including a data acquisition module, an impedance modeling module, a stability assessment module, an optimization model construction module, a topology optimization module, and a topology execution module.

[0047] The data acquisition module is used to acquire the topology data of the new energy power station, the operating condition data of each new energy unit, the external grid impedance, the active power command of the power station, and the rated operating parameters of each feeder.

[0048] The impedance modeling module is used to establish broadband impedance models for each new energy unit under different operating conditions, and to establish the node admittance matrix of the new energy power station for the candidate output topology and determine the equivalent impedance of the new energy power station at the common coupling point.

[0049] The stability assessment module is used to construct the system impedance ratio matrix of the external power grid impedance and the equivalent impedance of the station, and to calculate the overall gain margin of the station based on the Nyquist curve of the eigenvalues ​​of the system impedance ratio matrix.

[0050] The optimization model construction module is used to establish a topology optimization model for the power generation of new energy power plants with the goal of minimizing the deviation of the overall gain margin of the power plant from the preset gain margin target area, and with the total active power output of the power plant, the stability of individual units and the current carrying capacity of feeders as constraints.

[0051] The topology optimization module is used to solve the topology optimization model of the new energy power station using a genetic algorithm to obtain the optimal topology scheme for the new energy power station.

[0052] The topology execution module is used to determine the switching status and output configuration of each new energy unit according to the optimal output topology scheme of the new energy power station, and output the corresponding switching commands and output set values ​​to the power station controller or the new energy unit controller.

[0053] The beneficial effects of this invention are as follows: (1) This invention does not require modification of the control structure and control parameters inside commercial new energy units. Instead, it utilizes the existing unit switching and output regulation capabilities of new energy power stations to improve the equivalent wideband impedance of the power station, reducing the requirements for the openness of the new energy unit controller. It is suitable for improving the stability of new energy power stations that have already been put into operation.

[0054] (2) The present invention does not require additional damping devices, which can reduce the hardware modification cost, construction cost and operation and maintenance cost of new energy power stations when performing broadband oscillation control.

[0055] (3) By establishing a broadband impedance model for new energy units under multiple operating conditions and recalculating the node admittance matrix and equivalent impedance of the new energy power station for each candidate output topology, it is possible to reflect the combined effects of unit switching status, unit output level, feeder connection relationship and external grid impedance on the broadband oscillation stability of the new energy power station.

[0056] (4) The overall gain margin of the power station is used to quantify the broadband oscillation stability level of the new energy power station, and the total active power output constraint, single unit stability constraint and feeder current carrying capacity constraint are all incorporated into the power output topology optimization model to avoid local unit instability, dispatch power not meeting requirements or feeder overload caused by only improving the overall stability margin of the power station.

[0057] (5) The genetic algorithm is used to solve the discrete combination optimization problem corresponding to the switching state of new energy units. It is applicable to the output topology optimization problem of new energy power stations with nonlinear, nonconvex and nondifferentiable objective functions. It can search for output topology schemes with high stability margin in a large candidate topology space.

[0058] (6) Under the condition that the total active power output of the new energy power station remains unchanged, the overall gain margin of the new energy power station can be improved by simply changing the combination of the new energy units put into operation and the output configuration of each new energy unit, thereby improving the broadband oscillation stability of the new energy power station.

[0059] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0060] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein: Figure 1 This is a schematic diagram of the structure of a new energy power station in an embodiment of the present invention; Figure 2This is a schematic diagram of the impedance equivalent circuit model of the grid-connected system of a new energy power station in an embodiment of the present invention; Figure 3 This is a flowchart of a method for improving broadband oscillation stability of new energy power plants based on power output topology optimization in an embodiment of the present invention; Figure 4 This is a flowchart illustrating the genetic algorithm for solving the topology optimization model of new energy power plant output in an embodiment of the present invention; Figure 5 This is a schematic diagram of the basic topology of a new energy power station containing fifteen photovoltaic generator sets in an embodiment of the present invention; Figure 6 This is a schematic diagram of the optimal power output topology of the new energy power station in an embodiment of the present invention; Figure 7 The figures show the stability evaluation and simulation verification results of the traditional output topology and the optimal output topology in the embodiments of the present invention. Figure 8 This is a structural block diagram of a system for improving the broadband oscillation stability of new energy power stations based on power output topology optimization, as described in an embodiment of the present invention. Detailed Implementation

[0061] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0062] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual pictures. They should not be construed as limiting the invention. To better illustrate the embodiments of the invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0063] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "front," and "rear" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present invention. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0064] Example 1: Method for Improving the Stability of Wideband Oscillations in New Energy Power Stations like Figure 1 As shown, the renewable energy power station in this embodiment includes multiple renewable energy generating units, multiple unit step-up transformers, multiple collector lines, feeder busbars, a power station step-up transformer, and a common coupling point. The renewable energy generating units can be photovoltaic generators, wind turbine generators, or a combination of both. Each renewable energy generating unit is connected to the collector lines via its corresponding unit step-up transformer. Multiple collector lines are connected to the common coupling point via feeder busbars. The renewable energy power station is connected to the external power grid through the common coupling point.

[0065] like Figure 3 As shown, the method includes S1 to S5.

[0066] S1: Acquire data and establish a multi-condition broadband impedance model for new energy power units. Obtain the power plant topology data for the renewable energy power stations. The power plant topology data should include at least the number of renewable energy units, the connection relationship between each renewable energy unit and the feeder, the connection relationship between the feeder and the busbar, the parameters of the collector lines, the parameters of the unit step-up transformers, the parameters of the power plant step-up transformers, and the location of the common coupling point.

[0067] Obtain operating condition data for each renewable energy unit. The operating condition data should include at least the activation or deactivation status of the renewable energy unit, active power output, reactive power output, grid connection port voltage, and grid connection port current.

[0068] Within a preset wideband frequency range, a small-signal voltage disturbance is applied to the grid-connected port of the new energy unit, and the corresponding current response is obtained; or a small-signal current disturbance is applied to the grid-connected port of the new energy unit, and the corresponding voltage response is obtained. Based on the input and output response data of the grid-connected port, a wideband impedance matrix or wideband admittance matrix in dq coordinate system is established for the new energy unit under different operating conditions.

[0069] When the internal control parameters of new energy generating units are difficult to obtain, a black-box identification model is used to establish the mapping relationship between operating conditions and wideband impedance. The black-box identification model can be a neural network model, a recurrent neural network model, a support vector regression model, or other identification models that can output wideband impedance matrix elements based on the input operating conditions.

[0070] When some main circuit parameters and control parameters of the new energy unit can be obtained, a multi-condition broadband impedance model can be established by using a gray box identification model that integrates data and models. The basic structure of the broadband impedance can be determined by the physical model, and unknown parameters or model errors can be identified by using port response data.

[0071] Different operating conditions and their corresponding broadband impedance models are stored in the unit impedance model database. When evaluating candidate output topologies, the model is determined based on the first... i The active power output, reactive power output, and port voltage of the new energy generating unit are used to call up a broadband impedance model that matches the current operating condition. When there is no completely consistent operating condition in the database, the broadband impedance matrix corresponding to the current operating condition can be obtained by interpolation between adjacent operating conditions.

[0072] S2: Establish candidate power output topologies and calculate the equivalent impedance of the power station. The switching status of each new energy unit and those who have contributed As a decision variable for power output topology, a candidate power output topology is formed by the switching status and power output configuration of all new energy units.

[0073] For each new energy unit in the candidate output topology, the broadband admittance matrix under the corresponding operating condition is called according to its output configuration, and the switching state of the new energy unit is introduced into the broadband admittance model according to Equation (3).

[0074] Based on the actual electrical connection relationship of the new energy power station, the broadband admittance of the new energy unit, the admittance of the unit step-up transformer, the admittance of the collector line, the admittance of the feeder, and the admittance of the power station step-up transformer are assembled into a nodal admittance matrix.

[0075] The common coupling point is taken as the external port node, and the network is simplified for the remaining internal nodes. The equivalent admittance of the new energy power station at the common coupling point is calculated according to Equation (5), and the equivalent impedance of the power station is calculated according to Equation (6).

[0076] Since the switching status and output configuration of the new energy units corresponding to different candidate power output topologies are different, for each candidate power output topology, the broadband impedance model of the new energy units under the corresponding operating conditions is called again, and the site node admittance matrix and site equivalent impedance are recalculated.

[0077] S3: Evaluate the broadband oscillation stability of the candidate output topology. like Figure 2 As shown, the new energy power station is equivalent to the equivalent impedance of the power station. The external power grid is equivalent to the external power grid impedance. .

[0078] Calculate the system impedance ratio matrix according to equation (7), and perform eigenvalue decomposition on the system impedance ratio matrix to obtain the trajectory of each eigenvalue as a function of frequency.

[0079] Plot the Nyquist curves corresponding to each eigenvalue, and determine whether the grid-connected system of the new energy power station corresponding to the candidate power output topology is stable based on the generalized Nyquist stability criterion.

[0080] Search for the intersection point with the negative real axis in the Nyquist curves of each eigenvalue, and determine the intersection point value of the negative real axis according to equation (9). And calculate the overall gain margin of the station according to equation (10). .

[0081] When the candidate output topology corresponds to When the output is less than zero, the candidate topology is determined to be an unstable topology; when When the value is greater than zero but lower than the preset gain margin lower limit, the candidate output topology is judged as a high-risk oscillation topology; when When the candidate output topology is located within the preset gain margin target area, it is determined as the target topology.

[0082] S4: Establish a topology optimization model for the output of new energy power plants Based on the dispatchers' requirements for the safety and economy of new energy power stations, a target area for gain margin or a corresponding target interval for the intersection of the negative real axis is set.

[0083] The objective is to minimize the deviation of the negative real axis intersection value of the candidate output topology from the target interval of the negative real axis intersection. The objective function is established according to Equations (13) and (14).

[0084] Establish power balance constraints for power plants according to formula (15) so that the total active power output of the new energy power plants corresponding to the candidate power output topology is consistent with the active power command issued by the superior dispatching authority.

[0085] Establish single-unit stability constraints according to formula (17) to ensure that each new energy unit put into operation meets the single-unit stability requirements, and avoid the adverse impact of local unit instability on the overall stability of the new energy power station.

[0086] Establish the current carrying capacity constraint for each feeder according to formula (18) so that the total capacity of the new energy units put into operation on each feeder does not exceed the long-term allowable transmission capacity of the feeder. When the new energy units connected on the same feeder have the same model and rated apparent power, the feeder current carrying capacity constraint can be simplified to the number of operating units constraint according to formulas (19) and (20).

[0087] S5: Solving the optimal power output topology using a genetic algorithm. like Figure 4 As shown, first input the power plant topology data, external grid impedance, power plant active power command, multi-condition broadband impedance model of each new energy unit, and rated operating parameters of each feeder.

[0088] Set the genetic algorithm parameters, which include population size, crossover probability, mutation probability, number of elite individuals, and maximum number of iterations.

[0089] Initialize the candidate population. Each candidate individual in the population corresponds to a new energy unit switching combination and output configuration. During the initialization process, candidate individuals can be generated randomly, or the current operating topology, the traditional topology determined according to the distance of the new energy units from the common coupling point, and the historical stable topology can be used as some of the initial individuals.

[0090] The following evaluation process was performed on each candidate individual: The switching status and output configuration of each new energy unit are determined based on the candidate units; Call upon the broadband impedance model of each new energy unit under the corresponding operating conditions; Establish the nodal admittance matrix of the new energy power station and calculate the equivalent impedance of the power station; Construct the system impedance ratio matrix and calculate the overall gain margin of the station; Calculate the objective function value and determine whether the candidate individuals meet the power balance constraint, single-unit stability constraint, and feeder current carrying capacity constraint; A penalty function is applied to candidate individuals that do not meet the constraints to obtain fitness evaluation values.

[0091] Selection operations are performed based on fitness evaluation values ​​to ensure that candidate individuals with high stability margins and meeting constraints have a high genetic probability; crossover operations are used to exchange some unit switching status or output genes among different candidate individuals; and mutation operations are used to change the switching status or output configuration of at least one unit.

[0092] Determine if the algorithm's termination condition has been met. If the termination condition has not been met, use the newly generated population as the current population and continue to perform candidate individual evaluation, selection, crossover, and mutation; if the termination condition has been met, output the candidate individual with the best fitness.

[0093] Based on the output candidate units, an optimal power topology scheme for the renewable energy power station is generated, and unit switching commands and power output setpoints are output to the renewable energy power station controller. The renewable energy power station controller executes unit switching and power output adjustment according to a preset switching sequence, so that the renewable energy power station is transformed from the current power topology to the optimal power topology.

[0094] Example 2: A new energy power station containing fifteen photovoltaic generator sets like Figure 5 As shown, the new energy power station in this embodiment includes fifteen photovoltaic generator sets of the same model. The fifteen photovoltaic generator sets are numbered 1 to 15 respectively, and are connected to the busbar of the new energy power station through three feeders. The busbar is connected to the common coupling point through the power station's step-up transformer.

[0095] Due to shading in some areas, the fifteen photovoltaic generator sets were divided into two output zones. The available active power output of the first to fifth photovoltaic generator sets was 0.5 per unit, and the available active power output of the sixth to fifteenth photovoltaic generator sets was 1 per unit. The rated capacity of each photovoltaic generator set was used as the power benchmark.

[0096] The active power command received by the renewable energy power station is 8.5 per-unit value. The genetic algorithm searches for the unit switching combination that satisfies the total active power output of 8.5 per-unit value based on the available active power output of each photovoltaic generator unit.

[0097] For each candidate unit switching combination, calculate the corresponding equivalent impedance of the station, system impedance ratio matrix, eigenvalue Nyquist curve, negative real axis intersection value and overall gain margin of the station, and verify whether each photovoltaic generator unit in operation is stable and whether each feeder meets the current carrying capacity requirements.

[0098] The optimal power output topology scheme obtained by the genetic algorithm is shown in Table 1.

[0099]

[0100] Optimal output topology as follows Figure 6 As shown. Both the traditional output topology and the optimal output topology meet the dispatch requirement of 8.5 per-unit value for the total active power output of the new energy power station, but the photovoltaic generator sets put into operation are different, so the corresponding equivalent broadband impedances of the power station are different.

[0101] like Figure 7 As shown, the intersection point of the Nyquist curve of the system characteristic value corresponding to the conventional output topology and the negative real axis is:

[0102] The overall gain margin of the power station corresponding to the traditional output topology is:

[0103] Since the overall gain margin of the power station corresponding to the traditional output topology is less than zero, the grid-connected system of the new energy power station is in an unstable state.

[0104] The intersection point of the Nyquist curve of the system eigenvalues ​​corresponding to the optimal output topology and the negative real axis is:

[0105] The overall gain margin of the power station corresponding to the optimal output topology is:

[0106] Since the overall gain margin of the power station corresponding to the optimal output topology is greater than zero, the grid-connected system of the new energy power station is in a stable state.

[0107] Time-domain simulations were performed on both the conventional and optimal power output topologies. Under the conventional power output topology, the total output current of the renewable energy power plant exhibits continuous or divergent oscillating components, and its fast Fourier transform spectrum shows significant oscillation frequency components. Under the optimal power output topology, the total output current of the renewable energy power plant remains stable, and the broadband oscillation components in its fast Fourier transform spectrum are significantly reduced.

[0108] The above results indicate that, under the condition that the total active power output of the renewable energy power plants remains the same, by changing the combination of renewable energy units put into operation, the negative real axis intersection value can be changed from... Increased to 1.0784 0.7859, which increases the overall gain margin of the station from The value was increased from 0.0784 to 0.2141, thereby adjusting the new energy power station from an unstable operating state to a stable operating state.

[0109] Example 3: Wideband Oscillation Stability Improvement System for New Energy Power Stations Figure 8 As shown, this embodiment provides a broadband oscillation stability improvement system for new energy power stations based on power output topology optimization, including a data acquisition module, an impedance modeling module, a stability assessment module, an optimization model construction module, a topology optimization module, and a topology execution module.

[0110] The data acquisition module is connected to the new energy power station monitoring system, the dispatching system, and the impedance measurement device to acquire power station topology data, new energy unit operating condition data, external grid impedance, power station active power command, and feeder rated operating parameters.

[0111] The impedance modeling module is connected to the data acquisition module. It is used to establish and store multi-condition broadband impedance models of each new energy unit based on the operating condition data of the new energy unit and the input and output response data of the grid connection port. It is also used to call the broadband impedance model under the corresponding operating condition according to the candidate power output topology, establish the node admittance matrix and calculate the equivalent impedance of the station.

[0112] The stability assessment module is connected to the impedance modeling module. It is used to construct the system impedance ratio matrix based on the external power grid impedance and the equivalent impedance of the station, and to calculate the eigenvalues ​​of the system impedance ratio matrix, the Nyquist curve, the negative real axis intersection value, and the overall gain margin of the station.

[0113] The optimization model building module is connected to the stability assessment module. It is used to establish an objective function based on the overall gain margin of the power station and to establish constraints based on the active power command of the power station, the stability requirements of individual units, and the rated operating parameters of the feeders.

[0114] The topology optimization module is connected to the impedance modeling module, stability assessment module, and optimization model construction module, respectively. It is used to generate candidate power output topologies and uses a genetic algorithm to iteratively evaluate and optimize the candidate power output topologies, and output the optimal power output topology scheme.

[0115] The topology execution module is connected to the new energy power station controller and is used to convert the optimal power output topology scheme into the corresponding new energy unit switching command and active power output setting value, and send the switching command and active power output setting value to the new energy power station controller.

[0116] Before executing the optimal output topology scheme, the topology execution module can also determine the new energy units that need to be put into operation, cut off, or have their output adjusted based on the current output topology and the optimal output topology, and perform topology switching in stages according to the unit switching specifications of the new energy power station to ensure that the total active power output of the new energy power station is within the allowable deviation range during the topology switching process.

[0117] Each module in this embodiment can be implemented by one or more processors executing program instructions stored in memory, or it can be implemented by a site control server, energy management system, site monitoring system or independent broadband stability optimization control device.

[0118] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. All equivalent substitutions, simple modifications, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0119] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for improving the broadband oscillation stability of new energy power plants based on output topology optimization, characterized in that, Includes the following steps: S1: Obtain the topology data of the new energy power station, the operating condition data of each new energy unit, the external grid impedance, the active power command issued by the superior dispatching authority, and the rated operating parameters of each feeder, and establish a broadband impedance model of each new energy unit under different operating conditions. S2, taking the switching status and output configuration of each new energy unit as the output topology decision variables, for the candidate output topology formed by the output topology decision variables, based on the broadband impedance model of each new energy unit, the power station topology data and the switching status of each new energy unit, the node admittance matrix of the new energy power station is established, and the equivalent impedance of the new energy power station at the common coupling point is determined based on the node admittance matrix. S3. Construct a system impedance ratio matrix based on the external grid impedance and the equivalent impedance of the power station. Use the generalized Nyquist stability criterion to determine the eigenvalue Nyquist curve of the system impedance ratio matrix. Calculate the overall gain margin of the power station corresponding to the candidate output topology based on the intersection of the eigenvalue Nyquist curve and the negative real axis. S4. Taking the minimum deviation of the overall gain margin of the power station from the preset gain margin target area as the optimization objective, and taking the total active power output of the new energy power station meeting the active power command of the power station, the stability of each new energy unit in operation, and the current carrying capacity requirements of each feeder as constraints, a new energy power station output topology optimization model is established. S5. A genetic algorithm is used to solve the power output topology optimization model of the new energy power station to obtain the optimal power output topology scheme of the new energy power station that satisfies the constraints and has the optimal corresponding optimization objective value. The switching status and power output configuration of each new energy unit are determined according to the optimal power output topology scheme.

2. The method for improving broadband oscillation stability of new energy power stations based on power output topology optimization according to claim 1, characterized in that, The new energy units include at least one of photovoltaic generator sets and wind turbine generator sets; i Taiwan's new energy units at frequency f impedance matrix in dq coordinate system at point and the admittance matrix of the dq coordinate system They are respectively: in, , , and The first i Impedance matrix elements of the new energy unit, , , and The first i Admittance matrix elements of Taiwan's new energy power units.

3. The method for improving broadband oscillation stability of new energy power stations based on power output topology optimization according to claim 2, characterized in that, The different operating conditions include at least the operating conditions corresponding to different active power output levels. For each candidate output topology, the admittance matrix in the dq coordinate system under the corresponding operating condition is called according to the candidate output configuration of each new energy unit, and the first... i Equivalent admittance of new energy generating units after being connected to new energy power stations: in, For the first i Switching status variables of Taiwan's new energy units. ,when Time indicates the first i When the new energy units in Taiwan are put into operation, Time indicates the first i The new energy unit in Taiwan was disconnected.

4. The method for improving broadband oscillation stability of new energy power stations based on power output topology optimization according to claim 3, characterized in that, The determination of the equivalent impedance of the new energy power station at the common coupling point includes: constructing a node admittance matrix of the new energy power station based on the equivalent admittance of each new energy unit, the parameters of the step-up transformer, the parameters of the collector line, and the feeder connection relationship; establishing the station node voltage equation and the current equation of each feeder junction point based on the node admittance matrix; performing network reduction on the node admittance matrix to obtain the equivalent admittance of the new energy power station at the common coupling point, and inverting the equivalent admittance to obtain the equivalent impedance of the power station.

5. The method for improving broadband oscillation stability of new energy power stations based on output topology optimization according to claim 1, characterized in that, The system impedance ratio matrix is: in, For external power grid impedance, Given the equivalent impedance of the renewable energy power station; calculate the eigenvalues ​​of the system impedance ratio matrix. When all eigenvalues ​​are not enclosed by the Nyquist curve, the Nyquist curve will not enclose any point on the complex plane. When the corresponding candidate output topology is determined to be stable, the minimum value among the intersection points of the eigenvalue Nyquist curve and the negative real axis with the imaginary part being zero is determined as... The overall gain margin of the station is calculated according to the following formula. : Among them, when When it is determined that the new energy power station is stable, The new energy power station was determined to be unstable at that time.

6. The method for improving broadband oscillation stability of new energy power stations based on output topology optimization according to claim 5, characterized in that, The target interval of the negative real axis intersection point corresponding to the preset gain margin target region is: The objective function of the new energy power station output topology optimization model is: in, and These are the lower and upper limits of the target interval at the intersection of the negative real axes, respectively. The deviation of the negative real axis intersection value of the candidate output topology from the target interval of the negative real axis intersection.

7. The method for improving broadband oscillation stability of new energy power stations based on power output topology optimization according to claim 1, characterized in that, The constraints of the power output topology optimization model for the new energy power station include: in, N This refers to the total number of new energy generating units within the new energy power station. For the first i The active power output of Taiwan's new energy generating units under the candidate output configuration. The active power command for the power station. For the first i The eigenvalues ​​of the single-unit impedance ratio matrix of the new energy generating unit, the intersection points of the Nyquist curve and the negative real axis. To access the first l A collection of new energy generating units with feeder lines. For the first i The rated apparent power of the new energy unit in Taiwan For the first l The rated line voltage of the feeder, For the first l The maximum current that a feeder is allowed to carry continuously.

8. The method for improving broadband oscillation stability of new energy power stations based on power output topology optimization according to claim 7, characterized in that, When new energy generating units connected to the same feeder have the same rated apparent power S, the first l The current-carrying capacity constraint of the feeder is: in, For the first l The maximum number of similar new energy generating units that can be connected to a feeder within its current-carrying capacity limit. This indicates the floor function.

9. The method for improving broadband oscillation stability of new energy power stations based on output topology optimization according to claim 1, characterized in that, The genetic algorithm is used to solve the power output topology optimization model of the new energy power station, including: using binary encoding to represent the switching status of each new energy unit, with a value of 1 indicating that the new energy unit is in operation and a value of 0 indicating that the new energy unit is disconnected; setting the population size, crossover probability, mutation probability, and maximum number of iterations and initializing the population; taking different combinations of new energy unit switching statuses and power output configurations as candidate individuals; calculating the corresponding equivalent impedance of the power station, the overall gain margin of the power station, and the objective function value for each candidate individual, and imposing penalties on candidate individuals that do not meet the constraints through a penalty function; performing selection, crossover, and mutation operations based on the fitness value to generate a new generation of population; iteratively updating the population until the maximum number of iterations is reached or a preset termination condition is met, and determining the candidate individual with the best fitness as the optimal power output topology scheme of the new energy power station.

10. A system for improving the broadband oscillation stability of new energy power stations based on output topology optimization, characterized in that, include: The data acquisition module is used to acquire the topology data of the new energy power station, the operating condition data of each new energy unit, the external grid impedance, the active power command of the power station, and the rated operating parameters of each feeder. Impedance modeling module is used to establish broadband impedance models of each new energy unit under different operating conditions, and to establish the node admittance matrix of the new energy power station for the candidate output topology and determine the equivalent impedance of the new energy power station at the common coupling point. The stability assessment module is used to construct a system impedance ratio matrix between the external power grid impedance and the equivalent impedance of the station, and to calculate the overall gain margin of the station based on the Nyquist curve of the eigenvalues ​​of the system impedance ratio matrix. The optimization model construction module is used to establish a new energy power plant output topology optimization model with the goal of minimizing the deviation of the overall gain margin of the power plant from the preset gain margin target area, and with the total active power output of the power plant, the stability of individual units and the current carrying capacity of feeders as constraints. The topology optimization module is used to solve the power output topology optimization model of the new energy power station using a genetic algorithm to obtain the optimal power output topology scheme of the new energy power station. The topology execution module is used to determine the switching status and output configuration of each new energy unit according to the optimal output topology scheme of the new energy power station.

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