Wind-solar-thermal-storage coordination-based advanced pre-control method and system for high-proportion renewable energy power grid

Abstract

Disclosed in the present invention are a wind-solar-thermal-storage coordination-based advanced pre-control method and system for a high-proportion renewable energy power grid. The method comprises: establishing an automatic generation control (AGC) system control zone at a power grid dispatching and control center; performing advanced pre-control scanning on wind-solar-thermal-storage resources according to a fixed cycle, so as to periodically acquire data for advanced pre-control; calculating a renewable energy generation pre-control deviation and a power load pre-control deviation; calculating power grid regulation advanced pre-control requirements; determining pre-control regulation capabilities of the wind-solar-thermal-storage resources, and calculating reserve distribution coefficients of different types of pre-control regulation capabilities; on the basis of the power grid regulation pre-control requirements, the pre-control regulation capabilities and the corresponding reserve distribution coefficients, determining whether it is necessary to activate advanced pre-control; and on the basis of a determination result, allocating the corresponding pre-control requirements and allocating regulation units. Compared with a traditional method, the present invention can optimize power grid regulation requirements, and improve the safe operation level of a power grid.

Description

A method and system for coordinated and advanced control of high-proportion renewable energy power grids using wind, solar, thermal, and energy storage technologies. Technical Field

[0001] This invention relates to a method and system for coordinated and advanced control of wind, solar, thermal, and energy storage, and more particularly to a method and system for coordinated and advanced control of wind, solar, thermal, and energy storage in a high-proportion renewable energy power grid, belonging to the field of active power control technology for power systems. Background Technology

[0002] With the construction of more and more new energy bases, the difficulty of fully absorbing new energy sources while ensuring safe and stable operation and active power control performance is gradually increasing, which also places higher demands on grid dispatching and active power control. The rapid growth of new energy installed capacity and the concentrated distribution of new energy resources, which limits the grid's peak-shaving capacity, have led to power curtailment issues in some regions. To promote the orderly and rational absorption of new energy, industry scholars have conducted in-depth research on key technical issues such as new energy power prediction, new energy acceptance capacity assessment, dispatching and control modes after the concentrated integration of intermittent energy sources like new energy, and automatic generation control strategies that include both new energy and conventional energy.

[0003] As the proportion of new energy in the power and electricity of the grid continues to increase, the impact of new energy power plants on the power balance and frequency security of the grid is becoming increasingly significant. To ensure the frequency security and stability of the grid with a high proportion of new energy and to support the priority consumption of new energy, it is necessary to fully utilize the regulation capabilities of various resources (wind, solar, thermal, and energy storage, etc.) across the entire grid. Therefore, the Automatic Generation Control (AGC) application in the EMS system (hereinafter referred to as the dispatching system) of the dispatching and control agency performs unified optimization across the entire grid. Based on the frequency security operation threshold of the entire grid, it conducts proactive control, comprehensively considers the regulation capabilities of various regulation resources in the current grid, and judges whether the grid needs to carry out proactive control based on the prediction results and prediction deviations of future load and new energy power changes. By coordinating the reserve distribution of slow regulation resources and fast regulation resources, and through the proactive control of slow resources, the grid frequency operation security is ensured, and the grid's safe and reliable power supply capability is improved.

[0004] In existing technologies, there are issues where a high proportion of renewable energy power grids experience rapid changes in renewable energy power due to weather factors such as high temperatures and snow, leading to insufficient regulation capacity of conventional thermal power units. This can result in the inability to quickly eliminate power imbalances in the power grid, affecting the safe operation of the power grid. Summary of the Invention

[0005] Purpose of the invention: The purpose of this invention is to provide a method and system for advanced control of high-proportion renewable energy power grids that integrates wind, solar, thermal, and energy storage, thereby optimizing grid regulation requirements and improving grid safety.

[0006] Technical solution: The present invention provides a method for advanced control of high-proportion renewable energy power grids through wind, solar, thermal, and energy storage coordination, comprising:

[0007] (1) Establish an automatic generation control system (AGC) control area in the power grid dispatch control center to implement closed-loop control of wind, solar, thermal and energy storage resources within the dispatch control area to ensure that the power grid frequency and tie line power are within the preset planned value range; the wind, solar, thermal and energy storage resources include thermal power units, new energy stations and energy storage stations;

[0008] (2) The wind, solar, thermal and energy storage resources are scanned in advance by AGC at fixed intervals to periodically acquire data for advance control; the data includes actual sampling data of new energy power generation in a single control cycle, actual sampling data of electricity load in a single control cycle, predicted data of new energy power generation and predicted data of electricity load;

[0009] (3) Calculate the new energy power generation pre-control deviation based on the actual sampling data and the predicted data of new energy power generation in a single pre-control period; calculate the power load pre-control deviation based on the actual sampling data and the predicted data of the power grid load in a single pre-control period; and calculate the power grid regulation advance pre-control demand based on the new energy power generation pre-control deviation and the power load pre-control deviation.

[0010] (4) Based on the adjustment rate of wind, solar, thermal and energy storage resources obtained by AGC, determine the pre-control adjustment capability of wind, solar, thermal and energy storage resources. The pre-control adjustment capability includes: slow adjustment resources, minute-level medium-speed adjustment resources and second-level fast adjustment resources, and calculate the reserve distribution coefficient of different types of pre-control adjustment capabilities.

[0011] (5) Based on the grid regulation advance control demand, advance control regulation capacity and corresponding reserve distribution coefficient, determine whether it is necessary to start advance control; and based on the judgment result, allocate the corresponding advance control demand and the regulation unit.

[0012] Furthermore, the new energy power generation forecast data and electricity load forecast data mentioned in step (2) are obtained from the power grid dispatch system;

[0013] The data for the predicted new energy power generation covers the period from the current moment to one hour in the future.

[0014] The electricity load forecast data has a data period from the current moment to one hour in the future.

[0015] The actual sampling data of new energy power generation and electricity consumption load in a single pre-control cycle is obtained by collecting actual sampling data from several sampling points of the historical operation sampling data of new energy power generation and electricity consumption load in the previous pre-control cycle based on a preset sampling interval.

[0016] Further, step (3) involves calculating the new energy power generation pre-control deviation based on the actual sampled data and predicted data of new energy power generation for a single pre-control cycle, including:

[0017] Invalid data in the actual sampling data of new energy power generation in a single pre-control period are cleaned from three aspects: measurement quality level, data invariance, and obvious data anomalies, in order to eliminate invalid measurement data and form a valid new energy power generation sampling data sequence X for a single pre-control period: X=[x1,x2,...,x N (1)

[0018] Where N is the sequence length;

[0019] Based on the effective new energy power generation sampling data sequence X of a single pre-control period, the slope K of the first-order linear fitting result of the actual sampling data of new energy power generation in a single pre-control period is obtained by using the first-order linear fitting method. s and intercept B s ;

[0020] Based on new energy power generation forecast data, the slope and intercept for 5-minute and 15-minute forecasts are obtained for different data lengths, as shown in the following formulas:

[0021] In the formula: y0 is the prediction result for the current point, y a For predicting the outcome at future moments, t0 and t a For the current time and the predicted future time, a=1 represents the next 5 minutes, a=2 represents the next 15 minutes, (t a ,y a (t0, y0) and (t0, y0) form a linear function; K a This represents the slope of the prediction result. When a = 1, it indicates the slope of the prediction result for the next 5 minutes; when a = 2, it indicates the slope of the prediction result for the next 15 minutes. a It is the intercept of the prediction result. When a=1, it means the intercept of the prediction result in the next 5 minutes. When a=2, it means the intercept of the prediction result in the next 15 minutes.

[0022] The pre-control deviation of new energy power generation for the next two time periods is calculated using the following formula:

[0023] Where: ΔN a This represents the pre-control deviation of new energy generation in the future time period. When a=1, it means the pre-control deviation of new energy generation in the next 5 minutes. When a=2, it means the pre-control deviation of new energy generation in the next 15 minutes.

[0024] Further, step (3), which involves calculating the pre-control deviation of the power load based on the actual sampled data of the power grid load and the predicted data of the power load in a single pre-control cycle, includes:

[0025] Invalid data in the actual electricity load sampling data of a single pre-control cycle is cleaned from four aspects: measurement quality level, data invariance, data mutation, and obvious data anomalies. Invalid measurement data is eliminated to form a valid electricity load sampling data sequence for a single pre-control cycle, expressed by the following formula: L=[l1,l2,...,l N (4)

[0026] Where N is the sequence length; based on the effective power load sampling data sequence L of a single pre-control cycle, a linear fitting method is used to obtain the slope M of the linear fitting result of the power load sampling data of a single pre-control cycle. s and intercept Q s ;

[0027] Based on electricity load forecast data, the slope and intercept for 5-minute and 15-minute forecasts were obtained for different data lengths, respectively. The calculation methods are as follows:

[0028] In the formula: z0 is the prediction result for the current point, z a For predicting the outcome at future moments, t0 and t a For the current time and the predicted future time, a=1 represents the next 5 minutes, a=2 represents the next 15 minutes, and (t) a ,z a (t0, z0) and (t0, z0) form a linear function; M a Q represents the slope of the prediction result. When a = 1, it indicates the slope of the prediction result for the next 5 minutes; when a = 2, it indicates the slope of the prediction result for the next 15 minutes. a It is the intercept of the prediction result. When a=1, it means the intercept of the prediction result in the next 5 minutes. When a=2, it means the intercept of the prediction result in the next 15 minutes.

[0029] The formula for calculating the predicted adjustment deviation of electricity load for the next two time periods is as follows:

[0030] Where: ΔL a This represents the energy load control deviation for future time periods. When a = 1, it indicates the energy load control deviation for the next 5 minutes. When a = 2, it indicates the energy load control deviation for the next 15 minutes.

[0031] Further, step (3), which involves calculating the grid regulation advance control demand based on the new energy power generation pre-control deviation and the electricity load pre-control deviation, includes: ΔP a =ΔNa -ΔL a (7)

[0032] Where, when a = 1, ΔP a ΔP represents the power grid regulation and advance control demand in the next 5 minutes, when a = 2. a This indicates the need for proactive control of power grid regulation in the next 15 minutes.

[0033] Further, step (4) includes:

[0034] (41) For thermal power units whose regulation rate is more than 1.5% of the installed capacity per minute lower than the rated regulation rate, they are identified as slow regulation resources. The regulation capacity of the slow regulation resources is shown in the following formula:

[0035] In the formula: P h The adjustment rate for slow-adjustment resources is denoted by n, where n is the number of slow-adjustment resource units; r i Let P be the rated speed of the i-th unit. uh For the regulating capacity of the unit, L ui The adjustment limit for the i-th unit, G i Let P be the real-time active power of the i-th generating unit. dh For the unit's regulating capacity, L di This is the lower limit of the regulation for the i-th generating unit;

[0036] (42) For thermal power units and new energy power plants whose regulation rate exceeds 1.5% of the installed capacity per minute of the rated regulation rate, they are determined to be minute-level medium-speed regulation resources; the regulation capacity and regulation rate of thermal power units in the minute-level medium-speed regulation resources are calculated as shown in Equation (8), and the regulation capacity and regulation rate of new energy power plants in the minute-level medium-speed regulation resources are calculated as shown in Equation (9):

[0037] In the formula: S n For the total regulation rate of new energy power stations, N j S is the regulation rate of the j-th renewable energy power station. un For the upward regulation capacity of new energy power stations, W j S represents the upper limit for the regulation of the j-th renewable energy power station. For renewable energy power stations that are not subject to power curtailment, this value is equal to the real-time active power value of the renewable energy power station. dn For the down-regulation capacity of new energy power plants, P j Let V be the real-time active power value of the j-th renewable energy power station. j The lower limit for regulation of the j-th renewable energy power station shall not be less than 5% of the station's installed capacity;

[0038] (43) For an energy storage station capable of a second-level response, it is determined to be a second-level fast-adjustment resource. The adjustment capability of the second-level fast-adjustment resource is calculated as shown in Equation (10):

[0039] In the formula: F c Let C be the total regulation rate of the energy storage stations, m be the number of energy storage stations, and C be the total regulation rate of the energy storage stations. b Let F be the regulation rate of the b-th energy storage station, calculated at 100% installed capacity per minute. uc For the total upward adjustment capacity of the energy storage station, H b This is the upper limit for regulation of the b-th energy storage station, typically F, which is the installed capacity of the energy storage. dc M represents the overall downregulation capacity of the energy storage station. b P is the lower limit of regulation for the b-th energy storage station. b Let be the real-time active power value of the b-th energy storage unit;

[0040] (44) Calculate the reserve distribution coefficients for slow-speed regulation resources, minute-level medium-speed regulation resources, and second-level fast-speed regulation resources respectively:

[0041] In the formula: P Index S index and F index These are the reserve distribution coefficients for slow-speed adjustment resources, minute-level medium-speed adjustment resources, and second-level fast-speed adjustment resources, respectively.

[0042] Further, step (5) includes:

[0043] Calculate the pre-control demand thresholds for different time periods of the current power grid using the control center frequency safety threshold fRL:

[0044] In the formula: f is the real-time frequency value of the power grid, Bias is the frequency demand coefficient of the power grid, f P1 and f P2 The pre-control thresholds are 5 minutes and 15 minutes, respectively;

[0045] If the advance control requirements for the two time periods calculated by equation (7) are both lower than the corresponding advance control requirement threshold, then it is determined that no advance control is required for the current time period.

[0046] If equation (7) calculates that the advance control demand for two time periods exceeds the advance control demand threshold, then the advance control demand threshold of the shorter time period shall be used for control.

[0047] If step (7) determines that advance control needs to be initiated for the next 5 minutes, the advance control demand will be prioritized for allocation to minute-level medium-speed adjustment resources, and the remaining portion will be allocated to slow-speed adjustment resources.

[0048] If step (7) determines that advance control needs to be initiated for the next 15 minutes, the advance control demand will be prioritized for allocation to second-level fast adjustment resources, and the remaining portion will be allocated to minute-level medium-speed adjustment resources.

[0049] The allocation strategy for the regulating units includes:

[0050] When starting minute-level medium-speed regulation resources to participate in advanced pre-control, the overall regulation demand of this resource type is allocated according to the proportion of the actual regulation rate;

[0051] When slow-regulating resources are initiated to participate in proactive control, the overall regulation demand for this resource type is allocated proportionally according to the size of the regulation margin.

[0052] Furthermore, the method also includes: when initiating 5-minute advance control, based on the allocated advance control demand, it is also necessary to consider the second-level rapid adjustment of the resource reserve distribution coefficient, specifically:

[0053] If the proactive demand is directed towards increased output, and the reserve distribution coefficient of resources that can be rapidly adjusted within seconds is less than the upper reserve qualification threshold, then the total proactive demand is calculated as follows: ΔP redis =ΔP i-middle +(F target -F index )×(F uc +F dc (13)

[0054] Where: ΔP i-middle For the advanced control demand obtained from the allocation of resources for medium-speed regulation, F target To rapidly adjust the target reserve distribution coefficient of resources within seconds, F index To enable rapid adjustment of the reserve distribution coefficient of resources within seconds, F uc For the total upward adjustment capacity of the energy storage station, F dc This refers to the overall downward regulation capacity of the energy storage station;

[0055] If the proactive control demand is in the direction of reduced output, and the reserve distribution coefficient of resources that can be rapidly adjusted within seconds is less than the lower reserve qualification threshold, then the total proactive control demand is calculated as follows: ΔP redis =ΔP i-middle +(F index -F target )×(F uc +F dc (14)

[0056] When initiating 15-minute advance control, in addition to allocating the advance control demand, it is also necessary to consider the reserve distribution coefficient of minute-level medium-speed regulation resources, specifically:

[0057] If the proactive control demand is in the direction of increased output, and the reserve distribution coefficient of minute-level medium-speed regulation resources is less than the upper reserve qualification threshold, then the total proactive control demand is calculated as follows: ΔP redis =ΔP i-slow +(S target -S index )×(S un +S dn (15)

[0058] Where: ΔP i-slow To achieve the advanced control of demand by slowly adjusting resource allocation, S target S is the target reserve distribution coefficient for medium-speed regulation resources. index S is the reserve distribution coefficient for minute-level medium-speed regulation resources. un For the upward regulation capacity of new energy power stations, S dn For the downward regulation capacity of new energy power plants;

[0059] If the proactive control demand is in the direction of reduced output, and the reserve distribution coefficient of minute-level medium-speed regulation resources is less than the lower reserve qualification threshold, then the total proactive control demand is calculated as follows: ΔP redis =ΔP i-slow +(S index -S target )×(S un +S dn (16).

[0060] Furthermore, the method also includes the following steps during the rolling implementation of proactive control: if proactive control was initiated in the previous cycle and is no longer required in the current cycle, the control objectives of the previous cycle continue to be executed; if proactive control was initiated in the previous cycle and is still required in the current cycle, the control results of the current cycle are used to overwrite the control results of the previous cycle; if the control objectives of the current cycle are opposite to those of the previous cycle, all control objectives of the previous cycle are first suspended, and then the control objectives of the current cycle are executed.

[0061] Based on the same inventive concept, this invention also provides a high-proportion renewable energy grid wind-solar-thermal-storage coordinated advanced control system, comprising:

[0062] The initialization module is used to establish an Automatic Generation Control (AGC) control area in the power grid dispatch and control center, and to implement closed-loop control of wind, solar, thermal, and energy storage resources within the dispatch and management scope to ensure that the power grid frequency and tie-line power are within the preset planned values; the wind, solar, thermal, and energy storage resources include thermal power units, new energy power plants, and energy storage stations;

[0063] The data acquisition and prediction module is used to perform advanced pre-control scanning of the wind, solar, thermal and energy storage resources at fixed cycles through AGC, and periodically acquire data for advanced pre-control; the data includes actual sampling data of new energy power generation in a single pre-control cycle, actual sampling data of electricity load in a single pre-control cycle, predicted data of new energy power generation and predicted data of electricity load;

[0064] The demand calculation module is used to calculate the pre-control deviation of new energy power generation based on the actual sampling data and predicted data of new energy power generation in a single pre-control period; to calculate the pre-control deviation of power load based on the actual sampling data and predicted data of power grid load in a single pre-control period; and to calculate the pre-control demand of power grid regulation based on the pre-control deviation of new energy power generation and the pre-control deviation of power load.

[0065] The resource allocation module is used to determine the pre-control adjustment capability of wind, solar, thermal and energy storage resources based on the adjustment rate of wind, solar, thermal and energy storage resources obtained by AGC. The pre-control adjustment capability includes: slow adjustment resources, minute-level medium-speed adjustment resources and second-level fast adjustment resources, and calculates the reserve distribution coefficient of each type of pre-control adjustment capability.

[0066] The allocation module is used to determine whether to activate advanced control based on the grid's advanced control requirements, control and regulation capabilities, and corresponding reserve distribution coefficients; and to allocate the corresponding control requirements and regulating units based on the determination results.

[0067] Beneficial effects: Compared with existing technologies, this invention proposes an AGC (Automatic Generation Control) proactive control strategy. By combining the hourly results of new energy power and grid load forecasts, AGC analyzes the changing patterns of grid power imbalance. Combined with the real-time analysis of the regulation capabilities of regulation resources within the dispatch range, it utilizes regulation resources with slow regulation rates and low regulation costs for proactive control. This allows for the early balancing of the grid's rapid regulation needs caused by rapid changes in new energy and load in the future. At the same time, it optimizes the reserve distribution of resources with excellent regulation performance, ensuring the safe operation of grid frequency and improving the grid's safe and reliable power supply capabilities. Attached Figure Description

[0068] Figure 1 is a schematic diagram of the method flow of the present invention;

[0069] Figure 2 is a schematic diagram of the actual power output curve fitting of the new energy source according to an embodiment of the present invention;

[0070] Figure 3 is a schematic diagram of the first-order curve fitting of the new energy prediction results according to an embodiment of the present invention;

[0071] Figure 4 is a flowchart illustrating an embodiment of the method of the present invention. Detailed Implementation

[0072] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0073] As shown in Figure 1, the high-proportion renewable energy grid wind-solar-thermal-storage coordinated advanced control method of this embodiment includes:

[0074] (1) Establish an automatic generation control system (AGC) control area in the power grid dispatch control center to implement closed-loop control of wind, solar, thermal and energy storage resources within the dispatch control area to ensure that the power grid frequency and tie line power are within the preset planned value range; the wind, solar, thermal and energy storage resources include thermal power units, new energy stations and energy storage stations;

[0075] (2) The wind, solar, thermal and energy storage resources are scanned in advance by AGC at fixed intervals to periodically acquire data for advance control; the data includes actual sampling data of new energy power generation in a single control cycle, actual sampling data of electricity load in a single control cycle, predicted data of new energy power generation and predicted data of electricity load;

[0076] (3) Calculate the new energy power generation pre-control deviation based on the actual sampling data and the predicted data of new energy power generation in a single pre-control period; calculate the power load pre-control deviation based on the actual sampling data and the predicted data of the power grid load in a single pre-control period; and calculate the power grid regulation advance pre-control demand based on the new energy power generation pre-control deviation and the power load pre-control deviation.

[0077] (4) Based on the adjustment rate of wind, solar, thermal and energy storage resources obtained by AGC, determine the pre-control adjustment capability of wind, solar, thermal and energy storage resources. The pre-control adjustment capability includes: slow adjustment resources, minute-level medium-speed adjustment resources and second-level fast adjustment resources, and calculate the reserve distribution coefficient of each type of pre-control adjustment capability.

[0078] (5) Based on the grid regulation advance control demand, advance control regulation capacity and corresponding reserve distribution coefficient, determine whether it is necessary to start advance control; and based on the judgment result, allocate the corresponding advance control demand and the regulation unit.

[0079] Specifically, in step (1), in response to the frequency and tie-line control requirements of a high-proportion renewable energy grid, an AGC control area is generally established in the grid dispatch control center (hereinafter referred to as the dispatch center). This area is mainly responsible for implementing closed-loop control of conventional wind, solar, thermal, and energy storage within the dispatch control area. The control objective of the conventional AGC control area is to ensure that the grid frequency and tie-line power are near the planned values, while absorbing as much renewable energy as possible.

[0080] In step (2), the conventional AGC performs advanced pre-control scanning at a fixed cycle (e.g., once every 5 minutes) to periodically acquire the basic real-time data and prediction result data required for advanced pre-control, including:

[0081] Forecast data for new energy power generation, with a data period from the current moment to one hour in the future;

[0082] Electricity load forecast data within the power grid dispatch area, with a data period from the current moment to the next hour;

[0083] The actual sampling data of renewable energy generation and electricity load for a single pre-control cycle is obtained by collecting actual sampling data from several sampling points of the historical operation sampling data of renewable energy generation and electricity load in the previous pre-control cycle based on a preset sampling interval. Specifically, if the historical operation sampling data of renewable energy generation and electricity load in the past cycle is sampled every 5 seconds, and the pre-control cycle is 5 minutes, then the number of historical operation sampling data points for the cycle is 60.

[0084] In step (3), based on the obtained actual power generation sampling results of new energy in each pre-control period, the validity of the power generation sampling values ​​is first judged. Invalid data in the actual power generation sampling data of new energy in a single pre-control period is cleaned from three aspects: measurement quality level, data invariance, and obvious data anomalies, so as to eliminate invalid measurement data and form a valid new energy power generation data sequence for a single pre-control period, which can be expressed by the following formula: X=[x1,x2,...,x N (1)

[0085] Based on the cleaned and valid new energy power generation sampling data sequence X of a single pre-control period, a linear fitting method is used to obtain the slope K of the linear fitting result of the new energy power generation sampling data of the past period. s and intercept B s As shown in Figures 2 and 3;

[0086] Based on the forecast data for new energy power generation, the slope and intercept can be obtained for 5 minutes and 15 minutes respectively, depending on the length of the forecast data. The calculation method is as follows:

[0087] In the formula: y0 is the prediction result for the current point, y a For predicting the outcome at future moments, t0 and t a For the current time and the predicted future time, a=1 represents the next 5 minutes, a=2 represents the next 15 minutes, (t a ,y a (t0, y0) and (t0, y0) form a linear function; K aThis represents the slope of the prediction result. When a = 1, it indicates the slope of the prediction result for the next 5 minutes; when a = 2, it indicates the slope of the prediction result for the next 15 minutes. a It is the intercept of the prediction result. When a=1, it means the intercept of the prediction result in the next 5 minutes. When a=2, it means the intercept of the prediction result in the next 15 minutes.

[0088] By obtaining the slope and intercept of the predicted renewable energy generation results, and the slope and intercept of the actual operation and predicted results over the past 5 minutes, the predicted adjustment deviation of renewable energy generation for the next two time periods can be obtained. The calculation formula is as follows:

[0089] Where: ΔN a This represents the pre-control deviation of new energy generation in the future time period. When a=1, it means the pre-control deviation of new energy generation in the next 5 minutes. When a=2, it means the pre-control deviation of new energy generation in the next 15 minutes.

[0090] Furthermore, based on the historical actual operating data of the power grid load and the future forecast results, the pre-control deviation of the power load is calculated.

[0091] Based on the actual power generation sampling results of new energy sources obtained for each pre-control period, the validity of the electricity load sampling values ​​is first judged. Invalid data in the actual electricity load sampling data of a single pre-control period is cleaned from four aspects: measurement quality level, data invariance, data mutation, and obvious data anomalies. This process eliminates invalid measurement data, forming a valid load electricity data sequence for a single pre-control period, which can be expressed by the following formula: L=[l1,l2,...,l N (4)

[0092] Based on the cleaned, effective electricity load sampling data sequence L of a single pre-control cycle, a linear fitting method is used to obtain the slope M of the linear fitting result of the electricity load sampling data of the previous cycle. s and intercept Q s ;

[0093] Based on the predicted electricity load data, the slope and intercept for 5-minute and 15-minute periods can be obtained for different data lengths. The calculation methods are as follows:

[0094] In the formula: z0 is the prediction result for the current point, z a For predicting the outcome at future moments, t0 and t a For the current time and the predicted future time, a=1 represents the next 5 minutes, a=2 represents the next 15 minutes, and (t) a ,z a (t0, z0) and (t0, z0) form a linear function; Ma Q represents the slope of the prediction result. When a = 1, it indicates the slope of the prediction result for the next 5 minutes; when a = 2, it indicates the slope of the prediction result for the next 15 minutes. a It is the intercept of the prediction result. When a=1, it means the intercept of the prediction result in the next 5 minutes. When a=2, it means the intercept of the prediction result in the next 15 minutes.

[0095] By obtaining the slope and intercept of the predicted electricity load and the slope and intercept of the actual operation and predicted results over the past 5 minutes, the predicted adjustment deviation of the electricity load for the next three time periods can be obtained. The calculation formula is as follows:

[0096] Where: ΔL a This represents the energy load control deviation for future time periods. When a = 1, it indicates the energy load control deviation for the next 5 minutes. When a = 2, it indicates the energy load control deviation for the next 15 minutes.

[0097] Based on the calculated pre-control deviations of new energy sources and electricity load, the pre-control demand for power grid regulation in the next 5 minutes and 15 minutes can be obtained. The calculation method is shown in equation (7): ΔP a =ΔN a -ΔL a (7)

[0098] In step (4), after fulfilling the pre-control requirements for grid regulation, the pre-control regulation capabilities of different types of resources (wind, solar, thermal, and energy storage) are calculated. The regulation capabilities are divided into three levels: slow-regulation resources, minute-level medium-speed regulation resources, and second-level fast-regulation resources. The regulation capabilities of resources are statistically analyzed in real time according to different resource types.

[0099] Thermal power units whose regulation rate is more than 1.5% of the installed capacity per minute lower than the rated regulation rate are categorized as slow regulation resources. The regulation capacity of these resources is statistically analyzed using the following formula:

[0100] In the formula: P h The adjustment rate for slow-adjustment resources is denoted by n, where n is the number of slow-adjustment resource units; r i Let P be the rated speed of the i-th unit. uh For the regulating capacity of the unit, L ui The adjustment limit for the i-th unit, G i Let P be the real-time active power of the i-th generating unit. dh For the unit's regulating capacity, L di This is the lower limit of the regulation for the i-th unit.

[0101] For thermal power units and new energy power plants whose regulation rate exceeds 1.5% of the installed capacity per minute of the rated regulation rate, this type of resource is recorded as minute-level medium-speed regulation resource. For thermal power units, the calculation method for their regulation capacity and regulation rate is shown in equation (8). For new energy power plants, the calculation method for their regulation capacity and regulation rate is shown in equation (9).

[0102] In the formula: S n For the total regulation rate of new energy power stations, N j S is the regulation rate of the j-th renewable energy power station. un For the upward regulation capacity of new energy power stations, W j S represents the upper limit for the regulation of the j-th renewable energy power station. For renewable energy power stations that are not subject to power curtailment, this value is equal to the real-time active power value of the renewable energy power station. dn For the down-regulation capacity of new energy power plants, P j Let V be the real-time active power value of the j-th renewable energy power station. j The lower limit for regulation of the j-th renewable energy power station shall not be less than 5% of the station's installed capacity.

[0103] For electrochemical energy storage regulation resources with a second-level response, denoted as second-level fast regulation resources, the regulation capability of second-level fast regulation resources is calculated as shown in equation (10):

[0104] In the formula: F c Let C be the total regulation rate of the energy storage stations, m be the number of energy storage stations, and C be the total regulation rate of the energy storage stations. b Let F be the regulation rate of the b-th energy storage station, calculated at 100% installed capacity per minute. uc For the total upward adjustment capacity of the energy storage station, H b This is the upper limit for regulation of the b-th energy storage station, typically F, which is the installed capacity of the energy storage. dc M represents the overall downregulation capacity of the energy storage station. b P is the lower limit of regulation for the b-th energy storage station. b Let be the real-time active power value of the b-th energy storage.

[0105] After obtaining the adjustment rates and upper and lower adjustment capacities of three types of resources—slow-speed adjustment resources, minute-level medium-speed adjustment resources, and second-level fast-speed adjustment resources—the reserve distribution factors of the three types of resources are calculated separately, as shown in Equation (11):

[0106] In the formula: P Index S index and F index These are the reserve distribution coefficients for three types of resources: slow-speed adjustment resources, minute-level medium-speed adjustment resources, and second-level fast-speed adjustment resources.

[0107] In step (5), after the control center AGC obtains the power grid pre-control demand for the next 5 minutes and 15 minutes, as well as the real-time regulation capacity and reserve distribution coefficient of the three types of power grid regulation resources, the next step is to determine whether it is necessary to start the advanced pre-control.

[0108] According to the BAAL standard proposed by the North American Reliability Committee, the pre-control demand thresholds for different time periods of the current power grid can be obtained through the control center frequency safety threshold fRL. The calculation method is as follows:

[0109] In the formula: f is the real-time frequency value of the power grid, Bias is the frequency demand coefficient of the power grid, f P1 f P2 The pre-control thresholds are 5 minutes and 15 minutes, respectively;

[0110] If the advance control requirements for the two time periods calculated by formula (7) are both lower than the corresponding advance control requirement threshold, then it is considered that no advance control is required for the current time period.

[0111] If, according to formula (7), the two time periods have a pre-control demand exceeding the pre-control demand threshold, then the pre-control demand threshold of the shorter time period shall be used for control.

[0112] Once it is determined whether to enable proactive control, the corresponding proactive control requirements will be allocated according to different proactive control periods.

[0113] If step (7) indicates that advance control needs to be initiated for the next 5 minutes, then the advance control demand will be allocated to minute-level medium-speed adjustment resources first, and the remaining portion will be allocated to slow-speed adjustment resources.

[0114] If step (7) indicates that advance control needs to be initiated for the next 15 minutes, then the advance control requirement will be prioritized for allocation to second-level fast adjustment resources, and the remaining portion will be allocated to minute-level medium-speed adjustment resources.

[0115] If a 5-minute advance control mechanism is activated, in addition to allocating the advance control demand, it is also necessary to consider rapidly adjusting the reserve distribution coefficient of resources, specifically:

[0116] If the proactive demand is directed towards increased output, and the reserve distribution coefficient for rapidly adjusting resources is less than the upper reserve qualification threshold (e.g., 0.3), then the total proactive demand is calculated as follows: ΔP redis =ΔP i-middle +(F target -F index )×(F uc +F dc (13)

[0117] Where: ΔPi-middle For the advanced control demand obtained from the allocation of resources for medium-speed regulation, F target To quickly adjust the target reserve distribution coefficient of resources.

[0118] If the proactive demand is directed towards reducing output, and the reserve distribution coefficient for rapid resource adjustment is less than the lower reserve qualification threshold (e.g., 0.3), then the total proactive demand is calculated as follows: ΔP redis =ΔP i-middle +(F index -F target )×(F uc +F dc (14)

[0119] If a 15-minute advance control is initiated, in addition to allocating the advance control demand, the reserve distribution coefficient of minute-level medium-speed resources also needs to be considered, specifically:

[0120] If the proactive demand is in the direction of increased power output, and the reserve distribution coefficient of medium-speed regulation resources is less than the upper reserve qualification threshold (e.g., 0.3), then the total proactive demand is calculated as follows: ΔP redis =ΔP i-slow +(S target -S index )×(S un +S dn (15)

[0121] Where: ΔP i-slow To achieve the advanced control of demand by slowly adjusting resource allocation, S target The target reserve distribution coefficient for medium-speed regulation resources.

[0122] If the proactive control demand is in the direction of reduced output, and the reserve distribution coefficient of medium-speed regulation resources is less than the lower reserve qualification threshold (e.g., 0.3), then the total proactive control demand is calculated as follows: ΔP redis =ΔP i-slow +(S index -S target )×(S un +S dn (16).

[0123] After determining the overall pre-controlled demand for the resource category, it is then allocated to the various units participating in the regulation within the resource. The allocation strategy is as follows:

[0124] When medium-speed regulation resources are activated to participate in advanced control, the overall regulation demand for this resource type is allocated according to the proportion of the actual regulation rate.

[0125] When slow-speed adjustment resources are activated to participate in proactive control, the overall adjustment demand for this resource type is allocated according to the proportion of adjustment margin.

[0126] Furthermore, this embodiment also includes the following: during the rolling implementation of proactive control, if proactive control was initiated in the previous cycle and is no longer required in the current cycle, the control objective of the previous cycle continues to be executed; if proactive control was initiated at a certain point in the previous cycle and is still required in the current cycle, the control result of the current cycle overwrites the control result of the previous cycle. If the proactive control objective of the current cycle is opposite to the proactive control objective of the previous cycle, all control objectives of the previous cycle are first suspended, and then the control objective of the current cycle is executed. The flowchart of this embodiment is shown in Figure 4.

[0127] High-proportion renewable energy power grids are prone to large fluctuations in power generation due to weather factors. Meanwhile, conventional thermal power units are gradually being phased out due to policy factors, and their regulation capabilities struggle to balance rapid power changes caused by high temperatures, snow, and other weather conditions, posing a significant threat to grid operational safety. This invention proposes an AGC (Automatic Generation Control) pre-control method. Based on minute- to hourly forecasts of renewable energy power and grid load, it analyzes the trend of net load power changes in the grid. Combined with real-time analysis of the regulation capabilities of resources within the dispatch range, it utilizes slow-speed, low-cost regulation resources for pre-control. This proactively balances the rapid regulation demands of future renewable energy and load changes with slower-speed resources, while optimizing the reserve distribution of high-performance regulation resources. This improves the grid's safe and reliable power supply capacity, enhances grid operational safety, and promotes the safe and prioritized consumption of renewable energy.

[0128] Based on the same inventive concept, this embodiment also provides a high-proportion renewable energy grid wind-solar-thermal-storage coordinated advanced control system, including:

[0129] The initialization module is used to establish an Automatic Generation Control (AGC) control area in the power grid dispatch and control center, and to implement closed-loop control of wind, solar, thermal, and energy storage resources within the dispatch and management scope to ensure that the power grid frequency and tie-line power are within the preset planned values; the wind, solar, thermal, and energy storage resources include thermal power units, new energy power plants, and energy storage stations;

[0130] The data acquisition and prediction module is used to perform advanced pre-control scanning of the wind, solar, thermal and energy storage resources at fixed cycles through AGC, and periodically acquire data for advanced pre-control; the data includes actual sampling data of new energy power generation in a single pre-control cycle, actual sampling data of electricity load in a single pre-control cycle, predicted data of new energy power generation and predicted data of electricity load;

[0131] The demand calculation module is used to calculate the pre-control deviation of new energy power generation based on the actual sampling data and predicted data of new energy power generation in a single pre-control period; to calculate the pre-control deviation of power load based on the actual sampling data and predicted data of power grid load in a single pre-control period; and to calculate the pre-control demand of power grid regulation based on the pre-control deviation of new energy power generation and the pre-control deviation of power load.

[0132] The resource allocation module is used to determine the pre-control adjustment capability of wind, solar, thermal and energy storage resources based on the adjustment rate of wind, solar, thermal and energy storage resources obtained by AGC. The pre-control adjustment capability includes: slow adjustment resources, minute-level medium-speed adjustment resources and second-level fast adjustment resources, and calculates the reserve distribution coefficient of each type of pre-control adjustment capability.

[0133] The allocation module is used to determine whether to activate advanced control based on the grid's advanced control requirements, control and regulation capabilities, and corresponding reserve distribution coefficients; and to allocate the corresponding control requirements and regulating units based on the determination results.

[0134] In another implementation example, the aforementioned high-proportion renewable energy grid wind-solar-thermal-storage coordinated advanced control system includes: a processor, wherein the processor is used to execute the aforementioned program modules stored in memory, including: an initialization module, a data acquisition and prediction module, a demand calculation module, a resource allocation module, and an allocation module.

[0135] The present invention has been described according to preferred embodiments. It should be understood that the above embodiments do not limit the present invention in any way. All technical solutions obtained by equivalent substitution or equivalent transformation fall within the protection scope of the present invention.

Claims

1. A method for coordinated and proactive control of high-proportion renewable energy power grids using wind, solar, thermal, and energy storage, characterized in that, include: (1) Establish an automatic generation control system (AGC) control area in the power grid dispatch control center to implement closed-loop control of wind, solar, thermal and energy storage resources within the dispatch control area to ensure that the power grid frequency and tie line power are within the preset planned value range; the wind, solar, thermal and energy storage resources include thermal power units, new energy stations and energy storage stations; (2) The wind, solar, thermal and energy storage resources are scanned in advance by AGC at fixed intervals to periodically acquire data for advance control; the data includes actual sampling data of new energy power generation in a single control cycle, actual sampling data of electricity load in a single control cycle, predicted data of new energy power generation and predicted data of electricity load; (3) Calculate the new energy power generation pre-control deviation based on the actual sampling data and the predicted data of new energy power generation in a single pre-control cycle; Based on the actual sampled data of power grid load and the predicted data of power load in a single pre-control cycle, the pre-control deviation of power load is calculated; and the pre-control demand of power grid regulation is calculated based on the pre-control deviation of new energy power generation and the pre-control deviation of power load. (4) Based on the adjustment rate of wind, solar, thermal and energy storage resources obtained by AGC, determine the pre-control adjustment capability of wind, solar, thermal and energy storage resources. The pre-control adjustment capability includes: slow adjustment resources, minute-level medium-speed adjustment resources and second-level fast adjustment resources, and calculate the reserve distribution coefficient of each type of pre-control adjustment capability. (5) Based on the grid regulation advance control demand, advance control regulation capacity and corresponding reserve distribution coefficient, determine whether it is necessary to start advance control; and based on the judgment result, allocate the corresponding advance control demand and the regulation unit.

2. The high-proportion renewable energy power grid wind-solar-thermal-storage coordinated advanced control method according to claim 1, characterized in that, The new energy power generation forecast data and electricity load forecast data mentioned in step (2) are obtained from the power grid dispatch system; The data for the predicted new energy power generation covers the period from the current moment to one hour in the future. The electricity load forecast data has a data period from the current moment to one hour in the future. The actual sampling data of new energy power generation and electricity consumption load in a single pre-control cycle is obtained by collecting actual sampling data from several sampling points of the historical operation sampling data of new energy power generation and electricity consumption load in the previous pre-control cycle based on a preset sampling interval.

3. The high-proportion renewable energy power grid wind-solar-thermal-storage coordinated advanced control method according to claim 1, characterized in that, Step (3) involves calculating the pre-control deviation of new energy power generation based on actual sampling data and predicted data of new energy power generation in a single pre-control cycle, including: Invalid data in the actual sampling data of new energy power generation in a single pre-control period are cleaned from three aspects: measurement quality level, data invariance, and obvious data anomalies, in order to eliminate invalid measurement data and form a valid new energy power generation sampling data sequence X for a single pre-control period: X=[x1,x2,...,x N ] (1) Where N is the sequence length; Based on the effective new energy power generation sampling data sequence X of a single pre-control period, the slope K of the first-order linear fitting result of the actual sampling data of new energy power generation in a single pre-control period is obtained by using the first-order linear fitting method. s and intercept B s ; Based on new energy power generation forecast data, the slope and intercept for 5-minute and 15-minute forecasts are obtained for different data lengths, as shown in the following formulas: In the formula: y0 is the prediction result for the current point, y a For predicting the outcome at future moments, t0 and t a For the current time and the predicted future time, a=1 represents the next 5 minutes, a=2 represents the next 15 minutes, (t a ,y a (t0, y0) and (t0, y0) form a linear function; K a This represents the slope of the prediction result. When a = 1, it indicates the slope of the prediction result for the next 5 minutes; when a = 2, it indicates the slope of the prediction result for the next 15 minutes. a It is the intercept of the prediction result. When a=1, it means the intercept of the prediction result in the next 5 minutes. When a=2, it means the intercept of the prediction result in the next 15 minutes. The pre-control deviation of new energy power generation for the next two time periods is calculated using the following formula: Where: ΔN a This represents the pre-control deviation of new energy generation in the future time period. When a=1, it means the pre-control deviation of new energy generation in the next 5 minutes. When a=2, it means the pre-control deviation of new energy generation in the next 15 minutes.

4. The high-proportion renewable energy power grid wind-solar-thermal-storage coordinated advanced control method according to claim 3, characterized in that, Step (3) involves calculating the load pre-control deviation based on the actual sampled data and predicted data of the power grid load in a single pre-control cycle, including: Invalid data in the actual electricity load sampling data of a single pre-control cycle is cleaned from four aspects: measurement quality bit, data invariance, data abrupt change, and obvious data anomalies. This process eliminates invalid measurement data and forms a valid electricity load sampling data sequence for a single pre-control cycle, expressed by the following formula: L＝[l1,l2,...,l N ] (4) Where N is the sequence length; based on the effective power load sampling data sequence L of a single pre-control cycle, a linear fitting method is used to obtain the slope M of the linear fitting result of the power load sampling data of a single pre-control cycle. s and intercept Q s ; Based on electricity load forecast data, the slope and intercept for 5-minute and 15-minute forecasts were obtained for different data lengths, respectively. The calculation methods are as follows: In the formula: z0 is the prediction result for the current point, z a For predicting the outcome at future moments, t0 and t a For the current time and the predicted future time, a=1 represents the next 5 minutes, a=2 represents the next 15 minutes, and (t) a ,z a (t0, z0) and (t0, z0) form a linear function; M a Q represents the slope of the prediction result. When a = 1, it indicates the slope of the prediction result for the next 5 minutes; when a = 2, it indicates the slope of the prediction result for the next 15 minutes. a It is the intercept of the prediction result. When a=1, it means the intercept of the prediction result in the next 5 minutes. When a=2, it means the intercept of the prediction result in the next 15 minutes. The formula for calculating the predicted adjustment deviation of electricity load for the next two time periods is as follows: Where: ΔL a This represents the energy load control deviation for future time periods. When a = 1, it indicates the energy load control deviation for the next 5 minutes. When a = 2, it indicates the energy load control deviation for the next 15 minutes.

5. The high-proportion renewable energy power grid wind-solar-thermal-storage coordinated advanced control method according to claim 4, characterized in that, Step (3) involves calculating the grid regulation advance control demand based on the new energy power generation pre-control deviation and the electricity load pre-control deviation, including: ΔP a =ΔN a -ΔL a (7) Where, when a = 1, ΔP a ΔP represents the power grid regulation and advance control demand in the next 5 minutes, when a = 2. a This indicates the need for proactive control of power grid regulation in the next 15 minutes.

6. The method for coordinated and proactive control of high-proportion new energy power grid wind, solar, thermal, and energy storage as described in claim 1, characterized in that, Step (4) includes: (41) For thermal power units whose regulation rate is more than 1.5% of the installed capacity per minute lower than the rated regulation rate, they are identified as slow regulation resources. The regulation capacity of the slow regulation resources is shown in the following formula: In the formula: P h The adjustment rate for slow-adjustment resources is denoted by n, where n is the number of slow-adjustment resource units; r i Let P be the rated speed of the i-th unit. uh For the regulating capacity of the unit, L ui The adjustment limit for the i-th unit, G i Let P be the real-time active power of the i-th generating unit. dh For the unit's regulating capacity, L di This is the lower limit of the regulation for the i-th generating unit; (42) For thermal power units and new energy power plants whose regulation rate exceeds 1.5% of the installed capacity per minute of the rated regulation rate, they are determined to be minute-level medium-speed regulation resources; the regulation capacity and regulation rate of thermal power units in the minute-level medium-speed regulation resources are calculated as shown in Equation (8), and the regulation capacity and regulation rate of new energy power plants in the minute-level medium-speed regulation resources are calculated as shown in Equation (9): In the formula: S n For the total regulation rate of new energy power stations, N j S is the regulation rate of the j-th renewable energy power station. un For the upward regulation capacity of new energy power stations, W j S represents the upper limit for the regulation of the j-th renewable energy power station. For renewable energy power stations that are not subject to power curtailment, this value is equal to the real-time active power value of the renewable energy power station. dn For the down-regulation capacity of new energy power plants, P j Let V be the real-time active power value of the j-th renewable energy power station. j The lower limit for regulation of the j-th renewable energy power station shall not be less than 5% of the station's installed capacity; (43) For an energy storage station capable of a second-level response, it is determined to be a second-level fast-adjustment resource. The adjustment capability of the second-level fast-adjustment resource is calculated as shown in Equation (10): In the formula: F c Let C be the total regulation rate of the energy storage stations, m be the number of energy storage stations, and C be the total regulation rate of the energy storage stations. b Let F be the regulation rate of the b-th energy storage station, calculated at 100% installed capacity per minute. uc For the total upward adjustment capacity of the energy storage station, H b This is the upper limit for regulation of the b-th energy storage station, typically F, which is the installed capacity of the energy storage. dc M represents the overall downregulation capacity of the energy storage station. b P is the lower limit of regulation for the b-th energy storage station. b Let be the real-time active power value of the b-th energy storage unit; (44) Calculate the reserve distribution coefficients for slow-speed regulation resources, minute-level medium-speed regulation resources, and second-level fast-speed regulation resources respectively: In the formula: P Index S index and F index These are the reserve distribution coefficients for slow-speed adjustment resources, minute-level medium-speed adjustment resources, and second-level fast-speed adjustment resources, respectively.

7. The method for coordinated and advanced control of high-proportion new energy power grid wind, solar, thermal, and energy storage as described in claim 5, is characterized in that, Step (5) includes: Calculate the pre-control demand thresholds for different time periods of the current power grid using the control center frequency safety threshold fRL: In the formula: f is the real-time frequency value of the power grid, Bias is the frequency demand coefficient of the power grid, f P1 and f P2 The pre-control thresholds are 5 minutes and 15 minutes, respectively; If the advance control requirements for the two time periods calculated by equation (7) are both lower than the corresponding advance control requirement threshold, then it is determined that no advance control is required for the current time period. If equation (7) calculates that the advance control demand for two time periods exceeds the advance control demand threshold, then the advance control demand threshold of the shorter time period shall be used for control. If step (7) determines that advance control needs to be initiated for the next 5 minutes, the advance control demand will be prioritized for allocation to minute-level medium-speed adjustment resources, and the remaining portion will be allocated to slow-speed adjustment resources. If step (7) determines that advance control needs to be initiated for the next 15 minutes, the advance control demand will be prioritized for allocation to second-level fast adjustment resources, and the remaining portion will be allocated to minute-level medium-speed adjustment resources. The allocation strategy for the regulating units includes: When starting minute-level medium-speed regulation resources to participate in advanced pre-control, the overall regulation demand of this resource type is allocated according to the proportion of the actual regulation rate; When slow-regulating resources are initiated to participate in proactive control, the overall regulation demand for this resource type is allocated proportionally according to the size of the regulation margin.

8. The method for coordinated and proactive control of high-proportion new energy power grid wind, solar, thermal, and energy storage as described in claim 7, is characterized in that, The method further includes: When initiating a 5-minute advance control measure, in addition to allocating the advance control demand, it is also necessary to consider the reserve distribution coefficient of resources that can be adjusted rapidly within seconds. Specifically: If the proactive control demand is in the direction of increased output, and the reserve distribution coefficient of resources that can be rapidly adjusted within seconds is less than the upper reserve qualification threshold, then the calculation method for the total proactive control demand is as follows: ΔP redis =ΔP i-middle +(F target -F index )×(F uc +F dc ) (13) Where: ΔP i-middle For the advanced control demand obtained from the allocation of resources for medium-speed regulation, F target To rapidly adjust the target reserve distribution coefficient of resources within seconds, F index To enable rapid adjustment of the reserve distribution coefficient of resources within seconds, F uc For the total upward adjustment capacity of the energy storage station, F dc This refers to the overall downward regulation capacity of the energy storage station; If the proactive control demand is in the direction of reduced output, and the reserve distribution coefficient of the second-level rapid adjustment resources is less than the lower reserve qualification threshold, then the calculation method for the total proactive control demand is as follows: ΔP redis =ΔP i-middle +(F index -F target )×(F uc +F dc ) (14) When initiating 15-minute advance control, in addition to allocating the advance control demand, it is also necessary to consider the reserve distribution coefficient of minute-level medium-speed regulation resources, specifically: If the proactive control demand is in the direction of increased power output, and the reserve distribution coefficient of minute-level medium-speed regulation resources is less than the upper reserve qualification threshold, then the calculation method for the total proactive control demand is as follows: ΔP redis =ΔP i-slow +(S target -S index )×(S un +S dn ) (15) Where: ΔP i-slow To achieve the advanced control of demand by slowly adjusting resource allocation, S target S is the target reserve distribution coefficient for medium-speed regulation resources. index S is the reserve distribution coefficient for minute-level medium-speed regulation resources. un For the upward regulation capacity of new energy power stations, S dn For the downward regulation capacity of new energy power plants; If the proactive control demand is in the direction of reduced output, and the reserve distribution coefficient of minute-level medium-speed regulation resources is less than the lower reserve qualification threshold, then the calculation method for the total proactive control demand is as follows: ΔP redis =ΔP i-slow +(S index -S target )×(S un +S dn ) (16)。 9. The method for coordinated and proactive control of high-proportion new energy power grid wind, solar, thermal, and energy storage as described in claim 1, characterized in that, The method further includes the following steps during the rolling implementation of proactive control: if proactive control was initiated in the previous cycle and is no longer required in the current cycle, the control objectives of the previous cycle will continue to be executed; if proactive control was initiated in the previous cycle and is still required in the current cycle, the control results of the current cycle will be used to overwrite the control results of the previous cycle; if the control objectives of the current cycle are opposite to those of the previous cycle, all control objectives of the previous cycle will be suspended first, and then the control objectives of the current cycle will be executed.

10. A high-proportion renewable energy grid wind-solar-thermal-storage coordinated advanced control system, characterized in that, include: The initialization module is used to establish an Automatic Generation Control (AGC) control area in the power grid dispatch and control center, and to implement closed-loop control of wind, solar, thermal, and energy storage resources within the dispatch and management scope to ensure that the power grid frequency and tie-line power are within the preset planned values; the wind, solar, thermal, and energy storage resources include thermal power units, new energy power plants, and energy storage stations; The data acquisition and prediction module is used to perform advanced pre-control scanning of the wind, solar, thermal and energy storage resources at fixed cycles through AGC, and periodically acquire data for advanced pre-control; the data includes actual sampling data of new energy power generation in a single pre-control cycle, actual sampling data of electricity load in a single pre-control cycle, predicted data of new energy power generation and predicted data of electricity load; The demand calculation module is used to calculate the pre-control deviation of new energy power generation based on the actual sampling data and the predicted data of new energy power generation for a single pre-control cycle. Based on the actual sampled data of power grid load and the predicted data of power load in a single pre-control cycle, the pre-control deviation of power load is calculated; and the pre-control demand of power grid regulation is calculated based on the pre-control deviation of new energy power generation and the pre-control deviation of power load. The resource allocation module is used to determine the pre-control adjustment capability of wind, solar, thermal and energy storage resources based on the adjustment rate of wind, solar, thermal and energy storage resources obtained by AGC. The pre-control adjustment capability includes: slow adjustment resources, minute-level medium-speed adjustment resources and second-level fast adjustment resources, and calculates the reserve distribution coefficient of each type of pre-control adjustment capability. The allocation module is used to determine whether to activate advanced control based on the grid's advanced control requirements, control and regulation capabilities, and corresponding reserve distribution coefficients; and to allocate the corresponding control requirements and regulating units based on the determination results.

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