Frequency inertia cooperative control method and device for distributed new energy cluster

Abstract

The invention provides a frequency inertia cooperative control method and device for a distributed new energy cluster, and relates to the technical field of power grids. According to the method, the frequency deviation and the frequency change rate of each monitoring point are obtained by analyzing the power grid operation data, then the active power adjustment amount of each monitoring point is determined, and power distribution is performed on the active power adjustment amount in combination with each function group in the distributed new energy cluster. And a cooperative control scheme of the quick response group, the continuous support group and the standby group is determined, active power adjustment is performed on the distributed new energy cluster, and frequency inertia support is realized. Through cooperative control of the active power of the distributed new energy cluster, active output of the photovoltaic unit, the wind power unit and the energy storage unit is cooperatively changed, frequency inertia support of the power grid is realized, and the frequency stability of the power grid is improved.

Description

Technical Field

[0001] The present invention relates to the field of electric power grid technology, and in particular to a frequency-inertia coordinated control method and device for a distributed new energy cluster. Background Art

[0002] With the transformation of the global energy structure, the proportion of distributed renewable energy (such as solar photovoltaic and wind power generation) in the power system continues to increase. Distributed renewable energy is intermittent and uncertain, which brings new challenges to the stable operation of traditional power grids. In particular, the maintenance of grid frequency has become increasingly complex. Frequency is one of the key indicators for measuring the stability of power systems and the quality of power supply. Changes in grid frequency not only affect the safe operation of the power system, but may also have adverse effects on end users, such as damage to electrical equipment or shortened service life.

[0003] Traditional power systems mainly rely on the spinning reserve capacity provided by large thermal power plants to maintain frequency stability. These power plants adjust the output power by adjusting the speed of the steam turbine to quickly respond to changes in the grid frequency. However, with the large-scale access of distributed renewable energy, the frequency regulation of new power grids with a high proportion of renewable energy has become more difficult. On the one hand, the volatility and unpredictability of renewable energy generation increase the fluctuation of grid frequency; on the other hand, since distributed power sources lack the inertia support of traditional synchronous generators, it is difficult for the grid to quickly recover to the nominal frequency when faced with sudden load changes or power generation interruptions.

[0004] As the proportion of renewable energy continues to increase, the inertia level of the power system gradually decreases, which slows down the grid's response to disturbances and prolongs the recovery time, affecting the overall stability of the power system. Summary of the invention

[0005] The present invention provides a frequency-inertia coordinated control method and device for a distributed new energy cluster, which can realize frequency inertia support for a power grid and improve the frequency stability of the power grid through the coordinated control of the active power of the distributed new energy cluster.

[0006] In a first aspect, the present invention provides a frequency-inertia collaborative control method for a distributed new energy cluster, the method comprising: acquiring grid operation data of each monitoring point in the grid, and real-time operation data of a distributed new energy cluster; the distributed new energy cluster comprises a photovoltaic unit, a wind power unit and an energy storage unit; based on the grid operation data of each monitoring point, determining the frequency deviation and the frequency change rate of each monitoring point; based on the frequency deviation and the frequency change rate of each monitoring point, determining the active power adjustment amount; based on the real-time operation data of the distributed new energy cluster, grouping the distributed new energy, determining each functional group, the functional group comprising a quick response group, a continuous support group and a standby group; based on the active power adjustment amount and each functional group, determining a collaborative control scheme for each functional group; based on the collaborative control scheme, performing active power adjustment on the distributed new energy cluster to achieve frequency inertia support.

[0007] In one possible implementation, the frequency deviation and frequency change rate of each monitoring point are determined based on the grid operation data of each monitoring point, including: for any monitoring point, based on the grid frequency at the current moment and the grid standard frequency, calculating the frequency deviation of the monitoring point; based on the grid frequency at the current moment and the grid frequency at the moment before the current moment, calculating the frequency change rate of the monitoring point.

[0008] In one possible implementation, the active power adjustment amount is determined based on the frequency deviation and frequency change rate of each monitoring point, including: determining the PID control parameters of each monitoring point based on the grid capacity of each monitoring point; and calculating the active power adjustment amount of each monitoring point based on the PID control parameters of each monitoring point, as well as the frequency deviation and frequency change rate of each monitoring point.

[0009] In one possible implementation, the real-time operating data of the distributed new energy cluster includes the output active power and real-time power generation of each photovoltaic unit and each wind power unit, and the charge state of each energy storage unit; based on the real-time operating data of the distributed new energy cluster, the distributed new energy is grouped to determine each functional group, including: based on the output active power and real-time power generation of each photovoltaic unit and each wind power unit, the power generation output ratio of each photovoltaic unit and each wind power unit is determined; based on the power generation output ratio of each photovoltaic unit and each wind power unit, the functional group of each photovoltaic unit and each wind power unit is determined; based on the charge state of each energy storage unit and the installed capacity of each energy storage unit, the functional group of each energy storage unit is determined; based on the functional group of each photovoltaic unit and each wind power unit, the functional group of each energy storage unit is determined.

[0010] In a possible implementation, based on the active power adjustment amount and each functional group, a coordinated control scheme of each functional group is determined, including: based on the location information of each functional group, each functional group is divided to determine multiple regional functional clusters, each regional functional cluster includes a rapid response group, a continuous support group and a standby group; based on the location information of multiple regional functional clusters and the location information of each monitoring point, the relative position relationship between each regional functional cluster and each monitoring point is determined; based on the active power adjustment amount of each monitoring point and the relative position relationship between each regional functional cluster and each monitoring point, the active power adjustment amount of each regional functional cluster is determined; based on the active power adjustment amount of each regional functional cluster and the adjustment capacity of the photovoltaic unit, wind power unit and energy storage unit in each regional functional cluster, the active power adjustment amount of each unit in each regional functional cluster is determined; based on the group of each unit in each functional group, the adjustment time of each unit is determined; based on the active power adjustment amount and adjustment time of each unit in each regional functional cluster, the coordinated control scheme of each functional group is determined.

[0011] In one possible implementation, based on a collaborative control scheme, power regulation is performed on a distributed new energy cluster to achieve frequency inertia support, including: calculating the reactive power adjustment of each unit based on the active power adjustment of each unit in the collaborative control scheme and the real-time power factor of each unit; generating collaborative control instructions for each unit based on the active power adjustment, reactive power adjustment and adjustment time of each unit; and sending collaborative control instructions to each unit in the distributed new energy cluster.

[0012] In one possible implementation, based on a collaborative control scheme, power regulation is performed on a distributed new energy cluster to achieve frequency inertia support, including: monitoring the power output ratio of each photovoltaic unit and each wind power unit in the distributed new energy cluster and the charge state of each energy storage unit; determining the regulation capability of each unit in the distributed new energy cluster based on the power output ratio of each photovoltaic unit and each wind power unit and the charge state of each energy storage unit; performing verification based on the collaborative control instructions of each unit and the regulation capability of each unit to determine the real-time regulation status of each unit; the real-time regulation status is used to characterize whether the current unit has the ability to execute collaborative control instructions; and updating the collaborative control scheme of each functional group based on the real-time regulation status of each unit.

[0013] In a possible implementation, after power regulation of a distributed new energy cluster is performed based on a collaborative control scheme to achieve frequency inertia support, the method further includes: obtaining the grid operation data at the current moment and the real-time operation data of the distributed new energy cluster, the grid operation data and the real-time operation data of the distributed new energy cluster in a set period before the current moment, and the weather data and date type in a future period after the current moment; extracting features based on the grid operation data at the current moment and the real-time operation data of the distributed new energy cluster, the grid operation data and the real-time operation data of the distributed new energy cluster in a set period before the current moment, and the weather data and date type in a future period after the current moment, and determining frequency prediction features; determining the grid prediction frequency at each moment in the future period based on the frequency prediction features and a preset frequency prediction model; determining the active power adjustment amount at each moment in the future period based on the grid prediction frequency at each moment in the future period; determining the collaborative energy storage scheme of the distributed new energy cluster based on the active power adjustment amount at each moment in the future period; the collaborative energy storage scheme includes the active output power of each photovoltaic unit and each wind power unit and the charging and discharging power of each energy storage unit; based on the collaborative energy storage scheme, collaboratively controlling each unit of the distributed new energy cluster to achieve collaborative energy storage.

[0014] In a possible implementation, before determining the predicted power grid frequency at each moment in the future time period based on the frequency prediction characteristics and the preset frequency prediction model, it also includes: obtaining the power grid operation data and the operation data of the distributed new energy cluster in the historical period, as well as the weather data and date type in the historical period; dividing the power grid operation data and the operation data of the distributed new energy cluster in the historical period, as well as the weather data and date type in the historical period, into time windows to determine multiple sample data; wherein each sample data includes the power grid operation data and the operation data of the distributed new energy cluster at the first moment, the power grid operation data and the operation data of the distributed new energy cluster in the set time period before the first moment, and the weather data and date type in the future time period after the first moment; the first moment is any moment in the historical period; feature extraction is performed on multiple sample data to obtain the real-time feature of the first moment, the historical feature before the first moment, and the future feature after the first moment; multiple training samples are generated with the real-time feature of the first moment and the historical feature before the first moment as input and the future feature after the first moment as output; neural network training is performed based on the multiple training samples to obtain the preset frequency prediction model.

[0015] In the second aspect, an embodiment of the present invention provides a frequency-inertia collaborative control device for a distributed new energy cluster, the device comprising: a communication module, used to obtain power grid operation data of each monitoring point in the power grid, and real-time operation data of the distributed new energy cluster; the distributed new energy cluster comprises a photovoltaic unit, a wind power unit and an energy storage unit; a processing module, used to determine the frequency deviation and frequency change rate of each monitoring point based on the power grid operation data of each monitoring point; determine the active power adjustment amount based on the frequency deviation and frequency change rate of each monitoring point; based on the real-time operation data of the distributed new energy cluster, group the distributed new energy and determine each functional group, the functional group comprising a quick response group, a continuous support group and a standby group; based on the active power adjustment amount and each functional group, determine the collaborative control scheme of each functional group; based on the collaborative control scheme, perform active power adjustment on the distributed new energy cluster to achieve frequency inertia support.

[0016] In one possible implementation, the processing module is specifically used to calculate, for any monitoring point, the frequency deviation of the monitoring point based on the grid frequency at the current moment and the grid standard frequency; and calculate the frequency change rate of the monitoring point based on the grid frequency at the current moment and the grid frequency at the moment before the current moment.

[0017] In one possible implementation, the processing module is specifically used to determine the PID control parameters of each monitoring point based on the grid capacity of each monitoring point; and calculate the active power adjustment amount of each monitoring point based on the PID control parameters of each monitoring point, as well as the frequency deviation and frequency change rate of each monitoring point.

[0018] In one possible implementation, the processing module is specifically used to determine the power generation output ratio of each photovoltaic unit and each wind power unit based on the output active power and real-time power generation power of each photovoltaic unit and each wind power unit; determine the functional group of each photovoltaic unit and each wind power unit based on the power generation output ratio of each photovoltaic unit and each wind power unit; determine the functional group of each energy storage unit based on the charge state of each energy storage unit and the installed capacity of each energy storage unit; determine each functional group based on the functional group of each photovoltaic unit and each wind power unit, and the functional group of each energy storage unit.

[0019] In a possible implementation, the processing module is specifically used to divide each functional group based on the location information of each functional group, determine multiple regional functional clusters, each regional functional cluster includes a rapid response group, a continuous support group and a standby group; determine the relative position relationship between each regional functional cluster and each monitoring point based on the location information of multiple regional functional clusters and the location information of each monitoring point; determine the active power adjustment amount of each regional functional cluster based on the active power adjustment amount of each monitoring point and the relative position relationship between each regional functional cluster and each monitoring point; determine the active power adjustment amount of each unit in each regional functional cluster based on the active power adjustment amount of each regional functional cluster and the adjustment capacity of the photovoltaic unit, wind power unit and energy storage unit in each regional functional cluster; determine the adjustment time of each unit based on the group of each unit in each functional group; determine the coordinated control scheme of each functional group based on the active power adjustment amount and adjustment time of each unit in each regional functional cluster.

[0020] In a third aspect, an embodiment of the present invention provides an electronic device, comprising a memory and a processor, the memory storing a computer program, the processor being used to call and run the computer program stored in the memory to perform the steps of the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and wherein when the computer program is executed by a processor, the steps of the method described in the first aspect and any possible implementation method of the first aspect are implemented.

[0022] The present invention provides a frequency inertia coordinated control method and device for a distributed new energy cluster. The present invention obtains the frequency deviation and frequency change rate of each monitoring point by analyzing the power grid operation data, and then determines the active power adjustment amount of each monitoring point, and combines the various functional groups in the distributed new energy cluster to distribute power to the active power adjustment amount, determine the coordinated control scheme of the rapid response group, the continuous support group and the standby group, and adjust the active power of the distributed new energy cluster to achieve frequency inertia support. The present invention coordinates the active power of the distributed new energy cluster to change the active output of the photovoltaic unit, the wind power unit and the energy storage unit, so as to achieve frequency inertia support of the power grid and improve the frequency stability of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 paying creative labor.

[0024] Figure 1 It is a flow chart of a frequency-inertia coordinated control method of a distributed new energy cluster provided by an embodiment of the present invention;

[0025] Figure 2 It is a structural schematic diagram of a frequency-inertia collaborative control device for a distributed new energy cluster provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0027] In the description of the present invention, unless otherwise specified, " / " means "or", for example, A / B can mean A or B. "And / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, "at least one" and "plurality" refer to two or more. The words "first", "second", etc. do not limit the quantity and execution order, and the words "first", "second", etc. do not limit them to be different.

[0028] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way for easy understanding.

[0029] In addition, the terms "including" and "having" and any variations thereof mentioned in the description of this application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or modules is not limited to the listed steps or modules, but may optionally include other steps or modules that are not listed, or may optionally include other steps or modules that are inherent to these processes, methods, products or devices.

[0030] In order to make the purpose, technical solutions and advantages of the present invention more clear, the following will be described through specific embodiments in conjunction with the accompanying drawings of the present invention.

[0031] As described in the background technology, new power grids with a high proportion of new energy sources have problems such as low inertia level and difficulty in frequency regulation, resulting in low stability of the power system.

[0032] To solve this technical problem, Figure 1 As shown, an embodiment of the present invention provides a frequency-inertia coordinated control method for a distributed new energy cluster. The method includes steps S101-S106.

[0033] S101. Obtaining grid operation data of each monitoring point in the grid and real-time operation data of the distributed new energy cluster.

[0034] In the embodiment of the present application, the distributed new energy cluster includes a photovoltaic unit, a wind power unit and an energy storage unit.

[0035] In some embodiments, the real-time operation data of the distributed new energy cluster includes the output active power and real-time power generation power of each photovoltaic unit and each wind power unit, and the charge state of each energy storage unit.

[0036] Exemplarily, the output active power is the active power transmitted by the photovoltaic unit and the wind power unit to the power grid.

[0037] Exemplarily, the real-time power generation is the real-time power generation of a photovoltaic unit and a wind power unit.

[0038] Exemplarily, the state of charge of the energy storage unit is the ratio of the remaining power of the energy storage unit to the device capacity.

[0039] In some embodiments, the real-time operation data also includes the output voltage, output current, output reactive power and solar radiation intensity of the photovoltaic unit.

[0040] In some embodiments, the real-time operation data also includes the output voltage, output current, output reactive power, wind speed and wind direction of the wind power unit.

[0041] In some embodiments, the real-time operation data also includes the output voltage, output current, charging and discharging efficiency, etc. of the energy storage unit.

[0042] In some embodiments, the monitoring points are key points in the power grid, such as substations, important load centers, and distributed new energy access points.

[0043] In some embodiments, the grid operation data includes voltage, current, frequency, active power, reactive power, and power factor.

[0044] S102: Determine the frequency deviation and frequency change rate of each monitoring point based on the power grid operation data of each monitoring point.

[0045] In some embodiments, the frequency deviation is the difference between the real-time frequency of the power grid and the standard frequency of the power grid. The standard frequency of the power grid may be the industrial frequency.

[0046] In some embodiments, the frequency change rate is the change amount of the frequency per unit time, indicating the change trend of the frequency over time.

[0047] As a possible implementation manner, step S102 may be specifically implemented as steps S1021 - S1022 .

[0048] S1021. For any monitoring point, based on the current grid frequency and the grid standard frequency, calculate the frequency deviation of the monitoring point.

[0049] Exemplarily, the embodiment of the present invention may determine the frequency deviation based on the following formula.

[0050] Δf=f measured -f nominal ;

[0051] Where: Δf represents the frequency deviation, f measured Indicates the actual frequency measured at the monitoring point. nominal Indicates the standard frequency of the power grid.

[0052] S1022. Calculate the frequency change rate of the monitoring point based on the power grid frequency at the current moment and the power grid frequency at the moment before the current moment.

[0053] Exemplarily, the embodiment of the present invention may determine the frequency change rate based on the following formula.

[0054]

[0055] in: Indicates the rate of change of frequency. current Indicates the frequency at the current moment. previous represents the frequency of the previous moment. Δt represents the time interval between the current moment and the previous moment.

[0056] S103: Determine the active power adjustment amount based on the frequency deviation and frequency change rate of each monitoring point.

[0057] In some embodiments, the active power adjustment amount is the difference between the active power after adjustment and the active power before adjustment.

[0058] As a possible implementation manner, step S103 may be specifically implemented as steps S1031 - S1032 .

[0059] S1031. Determine the PID control parameters of each monitoring point based on the grid capacity of each monitoring point.

[0060] In some embodiments, the PID control parameters include a proportional parameter, an integral parameter, and a derivative parameter.

[0061] For example, the proportional parameter (P) directly affects the response speed of the controller. For monitoring points with larger capacity, the proportional coefficient can be appropriately increased to speed up the response speed.

[0062] Exemplarily, the integral parameter (I) is used to eliminate steady-state errors, but too large an integral effect may cause system oscillation. For monitoring points with larger capacity, the integral coefficient can be appropriately reduced to avoid over-regulation.

[0063] Exemplary, differential parameter (D): The differential term is used to suppress the frequency change rate and improve the stability of the system. For monitoring points with larger capacity, the differential coefficient can be appropriately increased to enhance the anti-interference ability.

[0064] In some embodiments, the grid capacity of a monitoring point is the maximum carrying capacity of a grid in an area where the monitoring point is located.

[0065] S1032. Calculate the active power adjustment amount of each monitoring point based on the PID control parameters of each monitoring point, as well as the frequency deviation and frequency change rate of each monitoring point.

[0066] Exemplarily, the embodiment of the present invention can determine the active power adjustment amount by the following formula.

[0067]

[0068] Where ΔP(t) is the active power adjustment at time t. e(t) is the frequency deviation at time t. K p is the scale parameter. K i is the integration parameter. K d is the differential parameter. is the rate of change of frequency at time t.

[0069] S104: based on the real-time operation data of the distributed new energy cluster, group the distributed new energy and determine each functional group.

[0070] In the embodiment of the present application, the functional groups include a rapid response group, a continuous support group and a standby group.

[0071] Exemplarily, the fast response group is mainly responsible for quickly responding to frequency changes and providing power support in a short period of time. The fast response group should bear a larger instantaneous power adjustment to quickly respond to frequency changes. According to the SOC and maximum power output capacity of each unit, a part of the active power adjustment is allocated to the fast response group.

[0072] Exemplarily, the continuous support group provides power support for a longer period of time to ensure frequency stability. The continuous support group should bear the remaining power adjustment to provide continuous power support. The remaining active power adjustment is allocated to the continuous support group based on the SOC and energy density of each unit.

[0073] For example, the standby group serves as a backup resource to ensure support when the units in other groups cannot continue to work. The standby group should be kept in the best condition and ready to replace the units in other groups at any time. The standby group does not participate in the current power adjustment, but it should be ensured that it can be put into work at any time.

[0074] As a possible implementation manner, step S104 may be specifically implemented as steps S1041 - S1044 .

[0075] S1041. Determine the power generation output ratio of each photovoltaic unit and each wind power unit based on the output active power and the real-time power generation power of each photovoltaic unit and each wind power unit.

[0076] In some embodiments, the power generation output ratio is the ratio of the output active power to the real-time power generation. The power generation output ratio is used to reflect the power generation utilization rate of the photovoltaic unit and the wind power unit. That is, the power generation output ratio can reflect the adjustment capability of the output active power of the photovoltaic unit and the wind power unit. The smaller the power generation output ratio, the more active power can be adjusted; the larger the power generation output ratio, the less active power can be adjusted.

[0077] S1042: Determine the functional group of each photovoltaic unit and each wind power unit based on the power generation output ratio of each photovoltaic unit and each wind power unit.

[0078] Exemplarily, for any photovoltaic unit or wind power unit, if the power generation output ratio of the unit is less than the first ratio, the unit is determined to be a fast response group.

[0079] Exemplarily, if the power generation output ratio of the unit is greater than or equal to the first ratio and less than the second ratio, the unit is determined to be a continuous support group.

[0080] Exemplarily, if the power generation output ratio of the unit is greater than or equal to the second ratio, the unit is determined to be a standby group.

[0081] S1043: Determine the functional group of each energy storage unit based on the charge state of each energy storage unit and the installed capacity of each energy storage unit.

[0082] In some embodiments, the state of charge of the energy storage unit is the ratio of the remaining power of the energy storage unit to the device capacity, which is used to reflect the size of the active power that can be output by the energy storage unit.

[0083] Exemplarily, for any energy storage unit, if the state of charge of the energy storage unit is greater than a first preset value, the energy storage unit is determined to be a fast response group.

[0084] Exemplarily, if the state of charge of the energy storage unit is less than or equal to a first preset value and greater than a second preset value, the energy storage unit is determined to be a continuous support group.

[0085] Exemplarily, if the state of charge of the energy storage unit is less than or equal to a second preset value, the energy storage unit is determined to be a standby group.

[0086] S1044. Determine each functional group based on the functional group of each photovoltaic unit and each wind power unit, and the functional group of each energy storage unit.

[0087] Exemplarily, the embodiment of the present invention can screen the functional groups of each unit, determine each unit in each functional group, and further determine each functional group.

[0088] S105: Determine a coordinated control scheme for each functional group based on the active power adjustment amount and each functional group.

[0089] As a possible implementation manner, step S105 can be specifically implemented as steps S1051-S1056.

[0090] S1051. Divide each functional group based on location information of each functional group to determine a plurality of regional functional clusters.

[0091] In some embodiments, each regional functional cluster includes a rapid response group, a continuous support group, and a standby group.

[0092] Exemplarily, the embodiments of the present invention may use a spatial clustering algorithm (such as K-means, DBSCAN, etc.) to divide similar functional groups into functional clusters in the same region according to the geographical distribution of the functional groups. Ensure that each cluster contains a rapid response group (such as an energy storage station close to the load center), a continuous support group (such as a wind farm with abundant wind resources but slightly farther away), and a backup group (usually used as a redundant backup with flexible location). The embodiments of the present invention may also consider factors such as the grid structure and transmission capacity to optimize and adjust the initially divided clusters to ensure that each cluster can operate independently and support each other.

[0093] S1052: Based on the location information of the plurality of regional function clusters and the location information of each monitoring point, determine the relative location relationship between each regional function cluster and each monitoring point.

[0094] Exemplarily, the embodiment of the present invention can calculate the straight-line distance between the center of the multiple regional functional clusters and each monitoring point based on the location information of the multiple regional functional clusters and the location information of each monitoring point, and determine the relative position relationship based on the straight-line distance.

[0095] As another example, an embodiment of the present invention can calculate the transmission line distance between the center of multiple regional functional clusters and each monitoring point based on the location information of multiple regional functional clusters and the location information of each monitoring point, and determine the relative position relationship based on the transmission line distance.

[0096] Exemplarily, the relative position relationship can be represented as a straight-line distance matrix, or a directional diagram, or a transmission line distance matrix.

[0097] S1053: Determine the active power adjustment amount of each regional functional cluster based on the active power adjustment amount of each monitoring point and the relative position relationship between each regional functional cluster and each monitoring point.

[0098] Exemplarily, for any monitoring point, the embodiment of the present invention can distribute the active power adjustment amount of the monitoring point by weight, distribute it to each regional functional cluster, and adjust it together by each regional functional cluster. The weight of each regional functional cluster represents the distance between each regional functional cluster and the transmission line of the monitoring point, and / or can also be expressed as the adjustment capacity of each regional functional cluster.

[0099] For example, the closer the regional functional cluster is to the monitoring point, the higher its weight is, and the larger the adjustment capacity of the regional functional cluster is, the higher its weight is.

[0100] For example, weight allocation can be performed using the following formula.

[0101]

[0102] Among them, ΔP j is the active power adjustment of the jth monitoring point; ω i is the allocation weight of the i-th regional functional cluster; ΔP i is the active power adjustment of the i-th regional functional cluster.

[0103] Afterwards, for any regional functional cluster, the embodiment of the present invention can add up the active power adjustment amounts of each monitoring point allocated to the regional functional cluster to obtain the active power adjustment amount of the regional functional cluster.

[0104] S1054. Determine the active power adjustment amount of each unit in each regional functional cluster based on the active power adjustment amount of each regional functional cluster and the adjustment capacity of the photovoltaic unit, wind power unit and energy storage unit in each regional functional cluster.

[0105] Exemplarily, the embodiment of the present invention can determine the adjustment capacity of the photovoltaic unit according to the power generation output ratio of the photovoltaic unit and the real-time power generation power.

[0106] Exemplarily, the embodiment of the present invention may determine the adjustment capacity of the wind power unit according to the power generation output ratio of the wind power unit and the real-time power generation power of the wind power unit.

[0107] Illustratively, the embodiment of the present invention may determine the adjustment capacity of the energy storage unit according to the state of charge of the energy storage unit and the installed capacity of the energy storage unit.

[0108] It should be noted that, for any regional functional cluster, the embodiment of the present invention can compare the size relationship between the active power adjustment amount and the sum of the adjustment capacity in the regional functional cluster. If the active power adjustment amount is greater than the sum of the adjustment capacity, it means that the current regulation capacity of the regional functional cluster is relatively small, and it needs to rely on other regional functional clusters or other methods for active support to achieve frequency inertia support.

[0109] If the active power adjustment is less than or equal to the sum of the adjustment capacities, it means that the current regulation capability of the functional cluster in the region is relatively strong, and it can independently provide active support and realize frequency inertia support.

[0110] As a possible implementation method, an embodiment of the present invention can calculate the ratio between the adjustment capacities of each unit in the regional functional cluster, allocate the active power adjustment amount based on the ratio between the adjustment capacities of each unit, and determine the active power adjustment amount of each unit.

[0111] S1055. Determine the adjustment time of each unit based on the group of each unit in each functional group.

[0112] Exemplarily, the quick response group has the shortest adjustment time, the continuous support group has the second longest, and the standby group has the longest. The embodiment of the present invention can be set according to actual conditions, for example, the adjustment time of the quick response group is 1 second, the continuous support group is 5 seconds, and the standby group is 10 seconds.

[0113] S1056. Determine a coordinated control scheme for each functional group based on the active power adjustment amount and adjustment time of each unit in each regional functional cluster.

[0114] Exemplarily, the coordinated control scheme of the functional group includes the active power adjustment amount and adjustment time of each unit in the functional group.

[0115] S106. Based on the collaborative control solution, active power regulation is performed on the distributed new energy cluster to achieve frequency inertia support.

[0116] As a possible implementation manner, step S106 may be specifically implemented as steps S1061 - S1063 .

[0117] S1061. Calculate the reactive power adjustment amount of each unit based on the active power adjustment amount of each unit in the collaborative control scheme and the real-time power factor of each unit.

[0118] Exemplarily, an embodiment of the present invention can calculate the adjusted output active power of each unit based on the active power adjustment amount of each unit and the output active power of each unit, calculate the adjusted output reactive power of each unit based on the adjusted output active power and the real-time power factor, and calculate the reactive power adjustment amount of each unit based on the adjusted output reactive power of each unit and the output reactive power before adjustment.

[0119] S1062. Generate a coordinated control instruction for each unit based on the active power adjustment amount, reactive power adjustment amount and adjustment time of each unit.

[0120] In some embodiments, the coordinated control instruction includes an active power adjustment amount, a reactive power adjustment amount, and an adjustment time.

[0121] S1063. Send a collaborative control instruction to each unit in the distributed new energy cluster.

[0122] This can achieve coordinated control of each unit in the distributed new energy cluster, realize frequency inertia support for the entire power grid, and improve power grid frequency stability.

[0123] As a possible implementation manner, step S106 may also be implemented as steps A1-A4.

[0124] A1. Monitor the power output ratio of each photovoltaic unit and each wind power unit and the charge state of each energy storage unit in the distributed new energy cluster.

[0125] A2. Based on the power output ratio of each photovoltaic unit and each wind power unit and the charge state of each energy storage unit, the regulation capacity of each unit in the distributed new energy cluster is determined.

[0126] A3. Based on the coordinated control instructions of each unit and the adjustment capability of each unit, a check is performed to determine the real-time adjustment status of each unit.

[0127] In some embodiments, the real-time adjustment status is used to indicate whether the current unit has the ability to execute the cooperative control instruction.

[0128] A4. Based on the real-time adjustment status of each unit, update the collaborative control scheme of each functional group.

[0129] It should be noted that due to different weather conditions, the real-time power generation capacity of photovoltaic units and wind power units is complex and changeable. During the execution of the coordinated control scheme, it is necessary to pay attention to real-time monitoring of the power generation of photovoltaic units and wind power units, and to check the adjustment capacity of each unit, and update the coordinated control scheme in time to ensure that the coordinated control scheme can proceed smoothly.

[0130] The present invention provides a frequency inertia collaborative control method for a distributed new energy cluster, which obtains the frequency deviation and frequency change rate of each monitoring point by analyzing the power grid operation data, and then determines the active power adjustment amount of each monitoring point, and combines the various functional groups in the distributed new energy cluster to distribute power to the active power adjustment amount, determine the collaborative control scheme of the rapid response group, the continuous support group and the standby group, and adjust the active power of the distributed new energy cluster to achieve frequency inertia support. The present invention realizes frequency inertia support of the power grid and improves the frequency stability of the power grid by collaboratively controlling the active power of the distributed new energy cluster and collaboratively changing the active output of the photovoltaic unit, the wind power unit and the energy storage unit.

[0131] Optionally, the frequency-inertia coordinated control method of a distributed new energy cluster provided in an embodiment of the present invention further includes steps S201-S206 after step S106.

[0132] S201. Obtain the power grid operation data and real-time operation data of the distributed new energy cluster at the current moment, the power grid operation data and real-time operation data of the distributed new energy cluster for a set period before the current moment, and the weather data and date type for a future period after the current moment.

[0133] S202. Based on the power grid operation data and the real-time operation data of the distributed new energy cluster at the current moment, the power grid operation data and the real-time operation data of the distributed new energy cluster in the set time period before the current moment, and the weather data and date type in the future time period after the current moment, feature extraction is performed to determine the frequency prediction features.

[0134] In some embodiments, the frequency prediction characteristics include power grid characteristics, new energy characteristics, and weather characteristics.

[0135] Exemplarily, grid characteristics: extracting characteristics related to frequency fluctuations from grid operation data, such as historical frequency change rate, load change rate, generator output change, etc.

[0136] New energy characteristics: Extract the historical output power data of each photovoltaic unit and wind power unit, the charging and discharging status of the energy storage unit, etc. from the operating data of the distributed new energy cluster.

[0137] Weather and date features: Convert weather data for future periods (such as wind speed and light intensity forecasts) and date types into numerical features, such as wind speed level, light intensity level, date type code, etc.

[0138] S203: Based on the frequency prediction characteristics and a preset frequency prediction model, determine the predicted frequency of the power grid at each moment in the future period.

[0139] In some embodiments, the preset frequency prediction model is obtained by training a neural network based on the operation data of the power grid and the operation data of the distributed new energy cluster in the historical period, as well as the weather data and date types in the historical period.

[0140] Exemplarily, in an embodiment of the present invention, the frequency prediction characteristics may be input into a preset frequency prediction model to obtain the predicted frequency of the power grid at each moment in the future period.

[0141] S204: Determine the active power adjustment amount at each moment in the future period based on the predicted frequency of the power grid at each moment in the future period.

[0142] S205. Determine a collaborative energy storage solution for the distributed new energy cluster based on the active power adjustment at each moment in the future period.

[0143] In some embodiments, the coordinated energy storage solution includes the active output power of each photovoltaic unit and each wind power unit and the charging and discharging power of each energy storage unit.

[0144] S206. Based on the collaborative energy storage solution, collaboratively control each unit of the distributed new energy cluster to achieve collaborative energy storage.

[0145] It should be noted that the embodiments of the present invention can formulate a collaborative energy storage scheme for a distributed new energy cluster based on the active power adjustment amount. Determine the active output power of each photovoltaic unit and wind power unit at each moment in the future period to maximize the use of renewable energy and meet the needs of the power grid. Determine the charging and discharging power of each energy storage unit to balance the intermittent nature of new energy power generation and the stability of power grid demand. Convert the collaborative energy storage scheme into specific control instructions and send them to each unit in the distributed new energy cluster through the communication network. Monitor the execution of each unit and make necessary adjustments based on real-time feedback. During the implementation process, continuously monitor the system status, including grid frequency, voltage stability, power generation and energy storage conditions of new energy clusters, etc. Evaluate the effectiveness of the collaborative energy storage scheme, including indicators such as frequency stability, new energy utilization, and energy storage efficiency. Continuously optimize the prediction model and control strategy based on the evaluation results.

[0146] In this way, the embodiment of the present invention can predict the grid frequency, and based on the prediction results, the photovoltaic units, wind power units and energy storage units in the grid can be coordinated to store energy in advance, so as to facilitate subsequent frequency adjustment and realize the support of grid frequency inertia.

[0147] Optionally, the frequency-inertia coordinated control method of a distributed new energy cluster provided in an embodiment of the present invention further includes steps S301-S306 before step S203.

[0148] S301. Obtaining power grid operation data and distributed new energy cluster operation data in a historical period, as well as weather data and date types in a historical period.

[0149] S302. Divide the power grid operation data and the distributed new energy cluster operation data in the historical period, as well as the weather data and date types in the historical period, into time windows to determine a plurality of sample data.

[0150] Each sample data includes the grid operation data and the distributed new energy cluster operation data at the first moment, the grid operation data and the distributed new energy cluster operation data for a set period before the first moment, and the weather data and date type for a future period after the first moment. The first moment is any moment in the historical period.

[0151] S303: Extract features from multiple sample data to obtain real-time features at a first moment, historical features before the first moment, and future features after the first moment.

[0152] S304: Generate multiple training samples by taking the real-time features at the first moment and the historical features before the first moment as input and taking the future features after the first moment as output.

[0153] S305: Perform neural network training based on multiple training samples to obtain a preset frequency prediction model.

[0154] In this way, the embodiment of the present invention can perform analysis based on historical data and train a preset frequency prediction model to facilitate the prediction of the power grid frequency.

[0155] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0156] The following is an embodiment of the device of the present invention. For details not described in detail therein, reference may be made to the corresponding method embodiment described above.

[0157] Figure 2The structure diagram of a frequency-inertia cooperative control device of a distributed new energy cluster provided by an embodiment of the present invention is shown. The cooperative control device 400 includes a communication module 401 and a processing module 402 .

[0158] The communication module 401 is used to obtain the grid operation data of each monitoring point in the grid and the real-time operation data of the distributed new energy cluster; the distributed new energy cluster includes photovoltaic units, wind power units and energy storage units.

[0159] Processing module 402 is used to determine the frequency deviation and frequency change rate of each monitoring point based on the power grid operation data of each monitoring point; determine the active power adjustment amount based on the frequency deviation and frequency change rate of each monitoring point; group the distributed new energy based on the real-time operation data of the distributed new energy cluster, and determine each functional group, which includes a rapid response group, a continuous support group and a standby group; determine the collaborative control scheme of each functional group based on the active power adjustment amount and each functional group; based on the collaborative control scheme, perform active power regulation on the distributed new energy cluster to achieve frequency inertia support.

[0160] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A frequency-inertia coordinated control method for a distributed new energy cluster, characterized in that: include: Obtaining grid operation data of each monitoring point in the grid and real-time operation data of a distributed new energy cluster; the distributed new energy cluster includes a photovoltaic unit, a wind power unit and an energy storage unit; Based on the grid operation data of each monitoring point, determine the frequency deviation and frequency change rate of each monitoring point; Determining an active power adjustment amount based on the frequency deviation and frequency change rate of each monitoring point; Based on the real-time operation data of the distributed new energy cluster, the distributed new energy is grouped to determine each functional group, wherein the functional groups include a rapid response group, a continuous support group and a standby group; Based on the active power adjustment amount and each functional group, determining a coordinated control scheme for each functional group; Based on the collaborative control scheme, active power regulation is performed on the distributed new energy cluster to achieve frequency inertia support.

2. The frequency-inertia coordinated control method of a distributed new energy cluster according to claim 1 is characterized in that: The determining of the frequency deviation and the frequency change rate of each monitoring point based on the power grid operation data of each monitoring point includes: For any monitoring point, the frequency deviation of the monitoring point is calculated based on the current grid frequency and the grid standard frequency; Based on the grid frequency at the current moment and the grid frequency at the moment before the current moment, the frequency change rate of the monitoring point is calculated.

3. The frequency-inertia coordinated control method of a distributed new energy cluster according to claim 1 is characterized in that: The determining the active power adjustment amount based on the frequency deviation and the frequency change rate of each monitoring point includes: Based on the grid capacity of each monitoring point, determine the PID control parameters of each monitoring point; Based on the PID control parameters of each monitoring point, as well as the frequency deviation and frequency change rate of each monitoring point, the active power adjustment amount of each monitoring point is calculated.

4. The frequency-inertia coordinated control method of a distributed new energy cluster according to claim 1 is characterized in that: The real-time operation data of the distributed new energy cluster includes the output active power and real-time power generation power of each photovoltaic unit and each wind power unit, and the charge state of each energy storage unit; The distributed new energy is grouped based on the real-time operation data of the distributed new energy cluster to determine each functional group, including: Determine the power output ratio of each photovoltaic unit and each wind power unit based on the output active power and real-time power generation power of each photovoltaic unit and each wind power unit; Determining the functional groups of each photovoltaic unit and each wind power unit based on the power generation output ratio of each photovoltaic unit and each wind power unit; Determine the functional group of each energy storage unit based on the state of charge of each energy storage unit and the installed capacity of each energy storage unit; Based on the functional groups of each photovoltaic unit and each wind power unit, and the functional groups of each energy storage unit, each functional group is determined.

5. The frequency-inertia coordinated control method of a distributed new energy cluster according to claim 1 is characterized in that: The determining of a coordinated control scheme for each functional group based on the active power adjustment amount and each functional group includes: Based on the location information of each functional group, each functional group is divided to determine multiple regional functional clusters, each of which includes a rapid response group, a continuous support group and a standby group; Based on the location information of multiple regional functional clusters and the location information of each monitoring point, determine the relative position relationship between each regional functional cluster and each monitoring point; Based on the active power adjustment amount of each monitoring point and the relative position relationship between each regional functional cluster and each monitoring point, determine the active power adjustment amount of each regional functional cluster; Based on the active power adjustment amount of each regional functional cluster and the adjustment capacity of the photovoltaic unit, wind power unit and energy storage unit in each regional functional cluster, determine the active power adjustment amount of each unit in each regional functional cluster; Determine the adjustment time of each unit based on the group of each unit in each functional group; Based on the active power adjustment amount and adjustment time of each unit in each regional functional cluster, a coordinated control scheme of each functional group is determined.

6. The frequency-inertia coordinated control method of a distributed new energy cluster according to claim 1 is characterized in that: Based on the collaborative control scheme, power regulation is performed on the distributed new energy cluster to achieve frequency inertia support, including: Calculating the reactive power adjustment amount of each unit based on the active power adjustment amount of each unit in the collaborative control scheme and the real-time power factor of each unit; Generate a coordinated control instruction for each unit based on the active power adjustment amount, reactive power adjustment amount and adjustment time of each unit; The collaborative control instruction is sent to each unit in the distributed new energy cluster.

7. The frequency-inertia coordinated control method of a distributed new energy cluster according to claim 1 is characterized in that: Based on the collaborative control scheme, power regulation is performed on the distributed new energy cluster to achieve frequency inertia support, including: Monitor the power output ratio of each photovoltaic unit and each wind power unit in the distributed new energy cluster, and the charge state of each energy storage unit; Based on the power output ratio of each photovoltaic unit and each wind power unit and the charge state of each energy storage unit, the regulation capacity of each unit in the distributed new energy cluster is determined; Based on the coordinated control instructions of each unit and the adjustment capability of each unit, a check is performed to determine the real-time adjustment status of each unit; the real-time adjustment status is used to indicate whether the current unit has the ability to execute the coordinated control instructions; Based on the real-time adjustment of each unit, the coordinated control scheme of each functional group is updated.

8. The frequency-inertia coordinated control method of a distributed new energy cluster according to claim 1 is characterized in that: After the distributed new energy cluster is power regulated based on the collaborative control scheme to achieve frequency inertia support, the method further includes: Obtain the current grid operation data and real-time operation data of distributed new energy clusters, the grid operation data and real-time operation data of distributed new energy clusters in the set period before the current moment, and the weather data and date type in the future period after the current moment; Based on the power grid operation data and the real-time operation data of the distributed new energy cluster at the current moment, the power grid operation data and the real-time operation data of the distributed new energy cluster in a set period before the current moment, and the weather data and date type in the future period after the current moment, feature extraction is performed to determine the frequency prediction feature; Based on the frequency prediction characteristics and a preset frequency prediction model, determining the predicted frequency of the power grid at each moment in the future period; Determining the active power adjustment amount at each moment in the future period based on the predicted frequency of the power grid at each moment in the future period; Based on the active power adjustment at each moment in the future period, determine the coordinated energy storage scheme of the distributed new energy cluster; the coordinated energy storage scheme includes the active output power of each photovoltaic unit and each wind power unit and the charging and discharging power of each energy storage unit; Based on the collaborative energy storage solution, the units of the distributed new energy cluster are collaboratively controlled to achieve collaborative energy storage.

9. The frequency-inertia coordinated control method of a distributed new energy cluster according to claim 1 is characterized in that: Before determining the predicted power grid frequency at each moment in the future period based on the frequency prediction feature and the preset frequency prediction model, the method further includes: Obtain the operation data of the power grid and the distributed new energy cluster in the historical period, as well as the weather data and date types in the historical period; The power grid operation data and the operation data of the distributed new energy cluster in the historical period, as well as the weather data and date types in the historical period, are divided into time windows to determine a plurality of sample data; wherein each sample data includes the power grid operation data and the operation data of the distributed new energy cluster at a first moment, the power grid operation data and the operation data of the distributed new energy cluster in a set period before the first moment, and the weather data and date types in a future period after the first moment; the first moment is any moment in the historical period; Extracting features from the plurality of sample data to obtain real-time features at a first moment, historical features before the first moment, and future features after the first moment; Using the real-time features at the first moment and the historical features before the first moment as input and the future features after the first moment as output, multiple training samples are generated; Based on the multiple training samples, neural network training is performed to obtain the preset frequency prediction model.

10. A frequency-inertia coordinated control device for a distributed new energy cluster, characterized in that: include: A communication module, used to obtain the grid operation data of each monitoring point in the grid, and the real-time operation data of the distributed new energy cluster; the distributed new energy cluster includes a photovoltaic unit, a wind power unit and an energy storage unit; A processing module is used to determine the frequency deviation and frequency change rate of each monitoring point based on the power grid operation data of each monitoring point; determine the active power adjustment amount based on the frequency deviation and frequency change rate of each monitoring point; group the distributed new energy based on the real-time operation data of the distributed new energy cluster, and determine each functional group, wherein the functional group includes a rapid response group, a continuous support group and a standby group; and determine the coordinated control scheme of each functional group based on the active power adjustment amount and each functional group; Based on the collaborative control scheme, active power regulation is performed on the distributed new energy cluster to achieve frequency inertia support.

11. The frequency-inertia coordinated control device of a distributed new energy cluster according to claim 10, characterized in that: The processing module is specifically used to calculate the frequency deviation of any monitoring point based on the grid frequency at the current moment and the grid standard frequency; and calculate the frequency change rate of the monitoring point based on the grid frequency at the current moment and the grid frequency at the moment before the current moment.

12. The frequency-inertia coordinated control device of a distributed new energy cluster according to claim 10, characterized in that: The processing module is specifically used to determine the PID control parameters of each monitoring point based on the power grid capacity of each monitoring point; based on the PID control parameters of each monitoring point, as well as the frequency deviation and frequency change rate of each monitoring point, calculate the active power adjustment amount of each monitoring point.

13. The frequency-inertia coordinated control device of a distributed new energy cluster according to claim 10, characterized in that: The processing module is specifically used to determine the power generation output ratio of each photovoltaic unit and each wind power unit based on the output active power and real-time power generation power of each photovoltaic unit and each wind power unit; determine the functional group of each photovoltaic unit and each wind power unit based on the power generation output ratio of each photovoltaic unit and each wind power unit; determine the functional group of each energy storage unit based on the charge state of each energy storage unit and the installed capacity of each energy storage unit; determine each functional group based on the functional group of each photovoltaic unit and each wind power unit, and the functional group of each energy storage unit.

14. The frequency-inertia coordinated control device of a distributed new energy cluster according to claim 10, characterized in that: The processing module is specifically used to divide each functional group based on the location information of each functional group, determine multiple regional functional clusters, each regional functional cluster includes a rapid response group, a continuous support group and a standby group; determine the relative position relationship between each regional functional cluster and each monitoring point based on the location information of multiple regional functional clusters and the location information of each monitoring point; determine the active power adjustment amount of each regional functional cluster based on the active power adjustment amount of each monitoring point and the relative position relationship between each regional functional cluster and each monitoring point; determine the active power adjustment amount of each unit in each regional functional cluster based on the active power adjustment amount of each regional functional cluster and the adjustment capacity of the photovoltaic unit, wind power unit and energy storage unit in each regional functional cluster; determine the adjustment time of each unit based on the group of each unit in each functional group; Based on the active power adjustment amount and adjustment time of each unit in each regional functional cluster, a coordinated control scheme of each functional group is determined.

15. An electronic device, characterized in that: The electronic device comprises a memory and a processor, wherein the memory stores a computer program, and the processor is used to call and run the computer program stored in the memory to execute the steps of the method according to any one of claims 1 to 9.

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