Frequency modulation standby optimization and check method, system and device based on alternate optimization, and medium

Abstract

The invention discloses a frequency modulation standby optimization and check method, system, equipment and medium based on alternate optimization, and relates to the technical field of power grid dispatching automation, and the method comprises the steps: collecting the real-time data of a power grid, constructing an optimization model with a minimum adjustment action as a target, employing an alternate optimization sequential decision algorithm for solving, and generating a unit output adjustment scheme. And in combination with future scene parameters input by the user, prospectively checking the standby capability and generating a checking result, integrating an adjustment scheme, the checking result and system state information, and performing visual display through a graphical interface to assist the user in making a decision. According to the method, full-process closed-loop management from data perception, intelligent optimization and safety check to prospective early warning is realized, and the configuration efficiency of frequency modulation standby, the scientificity of decision making and the active early warning capability of the system are remarkably improved on the premise of ensuring the safety of the power grid.

Description

Technical Field

[0001] This invention relates to the field of power grid dispatch automation technology, specifically to a method, system, equipment, and medium for frequency regulation reserve optimization and verification based on alternating optimization. Background Technology

[0002] With the increasing penetration of renewable energy in the power system, the frequency stability of the power grid faces unprecedented challenges. Primary frequency regulation reserve, as the first line of defense for maintaining power grid frequency stability, is directly related to the precision and intelligence of its management, which in turn affects the safe and stable operation of the power grid. Traditional frequency regulation reserve management mainly relies on the experience and judgment of dispatchers combined with offline computing tools. Although panoramic reserve monitoring functions based on real-time monitoring systems have been developed in recent years, enabling real-time display of unit reserve capacity, there are still significant shortcomings in optimization decision-making and forward-looking verification. Existing technologies are usually limited to static assessments of the current operating status, lacking the ability to optimize and adjust unit output combinations online, and also unable to effectively simulate the impact of future planned operations on the system's frequency regulation reserve.

[0003] The current technology has shortcomings in three main aspects: First, existing systems lack built-in intelligent decision-making algorithms, making it impossible to automatically generate an optimized scheme that minimizes the number of generating units to be adjusted and causes the least change to the grid's operating state while meeting backup requirements. This results in low dispatching efficiency and a lack of economy. Second, traditional methods are limited to verifying the adequacy of backup in the current state. They cannot rigorously check the power balance and cross-sectional safety of the optimized scheme, nor can they conduct forward-looking safety assessments of future changes in operating modes, making dispatching decisions lack a global security perspective and foresight. Finally, existing systems mainly rely on data listing and fail to present the complex optimization and verification process and results through intuitive visualization, increasing the understanding and decision-making burden on dispatchers. Summary of the Invention

[0004] In view of the above-mentioned existing problems, the present invention provides a method, system, equipment and medium for frequency regulation reserve optimization and verification based on alternating optimization, in order to solve the problems that the existing technology cannot provide targeted unit output optimization schemes, cannot assess the impact of future changes on primary frequency regulation reserve, is time-consuming and prone to errors, and is difficult to adapt to the rapid frequency adjustment needs of the power grid after a high proportion of new energy is connected.

[0005] To address the aforementioned technical problems, a frequency modulation reserve optimization and verification method based on alternating optimization is proposed, including: The system collects and integrates real-time power grid operation status data to obtain an operation status dataset. Based on this dataset, it constructs an optimization decision-making model aimed at minimizing adjustment actions. An alternating optimization sequential decision-making algorithm is used to solve the model, and through evaluation and adjustment, unit output adjustment schemes are generated. The system receives user-inputted future scenario simulation parameters, constructs a future operation status dataset, and uses the alternating optimization sequential decision-making algorithm to perform forward-looking verification of reserve capacity for future states, generating verification results. The unit output adjustment schemes, the verification results of the future operation status dataset, and system status information are integrated and visualized through a graphical decision-making interface to assist users in decision-making.

[0006] As a preferred embodiment of the frequency regulation reserve optimization and verification method based on alternating optimization described in this invention, the method of obtaining the operating status dataset includes reading the power-on status, real-time output value and primary frequency regulation reserve capacity from the reserve monitoring module of the real-time monitoring system. The system retrieves the unit output limit data updated and reported by each power plant based on actual operating conditions from the scheduling and planning system, and aligns and merges the data in memory to obtain the operating status dataset.

[0007] As a preferred embodiment of the frequency regulation reserve optimization and verification method based on alternating optimization described in this invention, the step of solving the model using the alternating optimization sequential decision algorithm includes: based on predefined unit adjustment characteristics, screening the initial set of all running units, excluding units that do not participate in the adjustment, and obtaining a set of candidate adjustment units; For the units in the candidate adjustment unit set, the units are dynamically prioritized according to their adjustment characteristics and the current system's backup demand type to determine the order of adjustment. Initiate an iterative optimization process. Based on the results of dynamic priority sorting, select a specific type of unit from the candidate adjustment unit set in the current round for virtual output adjustment and calculate the initial adjustment amount. After completing the virtual adjustment, update the system status based on all the initial adjustment amounts and perform a backup capacity check to determine whether the backup requirements are met. When the backup capacity verification is passed, all preliminary adjustment quantities are integrated and output as a unit output adjustment scheme; when it fails, the candidate adjustment unit set is updated and iterative optimization continues.

[0008] As a preferred embodiment of the frequency regulation reserve optimization and verification method based on alternating optimization described in this invention, the step of solving the model using the alternating optimization sequential decision algorithm further includes: performing system balance constraint verification on the unit output adjustment scheme, and evaluating whether the implementation of the current scheme will lead to an imbalance between the total power generation and the total load demand of the system; when the system balance constraint verification finds an imbalance risk, the balance compensation strategy is activated, and a compensation unit is selected from the units outside the candidate adjustment unit set and the compensation adjustment amount is calculated; The compensation adjustment amount is superimposed with the unit output adjustment scheme to generate a balanced correction scheme. The balanced correction scheme is then checked for system safety constraints to assess whether the current scheme will lead to the power exceeding the limit of key transmission sections in the power grid. When the system safety constraint check finds a risk of exceeding the limit, the safety correction strategy is activated to adjust or cancel the adjustment amount of the unit in the scheme that causes the cross section to exceed the limit. For the new backup gap generated by the safety correction, the balance compensation strategy is called or the alternating optimization sequential decision algorithm is returned to supplement the optimization and generate the scheme after safety correction.

[0009] As a preferred embodiment of the frequency regulation reserve optimization and verification method based on alternating optimization described in this invention, the dynamic priority ranking includes: determining a priority ranking strategy based on the sign of the current primary frequency regulation reserve demand; when the current primary frequency regulation reserve demand is greater than zero, the unit with the smallest adjustment evaluation function value among the units that can be quickly adjusted upwards is selected first; when the current primary frequency regulation reserve demand is less than zero, and it is necessary to increase the reserve for downward adjustment, the unit with the smallest adjustment evaluation function value among the units that can be quickly adjusted downwards is selected first, and units that are under maintenance, in standby status, or have already won bids in the remaining frequency regulation service are removed from the initial unit set to obtain the final candidate adjustment units; The iterative optimization process includes: when the system needs to increase the reserve capacity, selecting a unit that can increase its output from the candidate adjustment units in the current round, virtually adjusting the output of the selected unit, and the adjustment amount is the initial adjustment amount of the current unit; and selecting a unit that can decrease its output from the candidate adjustment units in the current round, virtually adjusting the output of the selected unit, and the adjustment amount is the initial adjustment amount of the current unit. After completing the adjustment of a pair of units, the adjusted unit is removed from the candidate adjustment units. The unit selection criteria are expressed as follows: in, This refers to the unit number within the adjustable unit set that can have its output increased. This represents the upper limit of the output of unit i. This represents the real-time output value of unit i. The operating capacity of unit i. This is the reserve coefficient for primary frequency regulation. This refers to the unit number within the adjustable unit set whose output can be reduced. This represents the real-time output value of unit j. Let J be the operating capacity of unit j.

[0010] As a preferred embodiment of the frequency regulation reserve optimization and verification method based on alternating optimization described in this invention, the system balance constraint verification includes: determining the relationship between the current total power generation and total load of the power grid; if the total power generation is greater than the total load, verifying whether the difference between the sum of the upward output of all generating units and the sum of the downward output of all generating units is less than zero; if the total power generation is less than the total load, verifying whether the difference is greater than zero; if the condition is met, the system balance constraint verification passes; otherwise, it is determined that the current scheme will lead to power imbalance, and the verification fails. The constraints are expressed as follows: in, The total number of rounds required to complete iterative optimization and backup verification; The system safety constraint verification includes reading all section constraint formulas that include unit output as a factor from the real-time grid section database, substituting the unit output values ​​in the balanced correction scheme into each section constraint formula for calculation, and comparing the calculation results with the power limit given for the current section. If all calculation results are less than the matching section limit, the system safety constraint verification is passed; otherwise, it is determined that there is a risk of section exceeding the limit, and the verification fails. The cross-sectional constraint formula is expressed as: in, This is the function for calculating the cross-sectional power flow. This is the new output value of unit i after optimization and adjustment. This is the new output value of unit j after optimization and adjustment. This is the power limit for the cross section.

[0011] As a preferred embodiment of the frequency regulation reserve optimization and verification method based on alternating optimization described in this invention, the step of performing forward verification of reserve capacity includes: providing a human-machine interface, receiving simulation parameters about the future state of the unit input by the dispatcher, modifying the current operating state dataset, generating a future operating state dataset, and using the future operating state dataset as input to re-execute the alternating optimization sequential decision algorithm for calculation, outputting the reserve verification result for the current future scenario, and determining whether a new optimization adjustment scheme needs to be generated; The visualization includes displaying the maximum value of the primary frequency regulation reserve of the entire network under the current operating state and the future simulation state, and comparing it with the assessment requirements, in the form of numerical and percentage bar charts; listing the current unit output adjustment plan or the plan after safety correction in the form of a table; identifying the limiting units that have become optimization bottlenecks due to their own state limitations in the unit list or system diagram through color highlighting and special icons; and giving the final verification conclusion in the form of text labels on the interface.

[0012] The beneficial effects of this preferred technical solution are as follows: by introducing system safety constraint verification and safety correction strategies, the cross-sectional safety constraints of the power grid are embedded into the optimization decision-making process, which can automatically identify and avoid adjustment schemes that may cause line overload, and find alternative generating units for compensation, thereby realizing automatic and precise prevention and control of power grid safety risks and greatly improving the safety of decision-making in complex power grid environments.

[0013] As a preferred embodiment of the frequency modulation backup optimization and verification system based on alternating optimization described in this invention, it is characterized by including a data acquisition and integration module, an alternating optimization calculation module, a multiple security constraint verification module, a future scenario simulation verification module, and a visualization decision support module.

[0014] The data acquisition and integration module is used to gather key information on the unit startup status, real-time output, output limit, and primary frequency regulation reserve capacity of the entire network. After cleaning, alignment, and fusion processing, the operating status dataset is obtained.

[0015] The alternating optimization calculation module is used to receive the operating status dataset and the backup requirements issued by the superior. Through the built-in alternating optimization sequential decision algorithm, it automatically performs unit classification, dynamic priority sorting, and iterative optimization calculation.

[0016] The multi-safety constraint verification module is used to perform power balance verification and grid safety verification. When the verification fails, it triggers the balance compensation strategy and safety correction strategy to automatically modify the scheme and output a safe and feasible final adjustment scheme that simultaneously meets the backup requirements, power balance and network security constraints.

[0017] The future scenario simulation and verification module is used to construct a future operating state dataset based on parameters, and call alternating optimization calculation and multiple security constraint verification to perform a pre-assessment of the power grid's frequency regulation reserve capability at future moments.

[0018] The visualization decision support module is used to present the optimization and verification process and results to the dispatcher in an intuitive form using graphics, tables, and color highlighting, and to provide clear decision suggestions.

[0019] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of a method for frequency modulation backup optimization and verification based on alternating optimization.

[0020] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a method for frequency modulation backup optimization and verification based on alternating optimization.

[0021] The beneficial effects of this invention are as follows: By automatically collecting and fusing multi-source data in real time in memory, this invention constructs an operational status dataset, laying a reliable data foundation for optimization decisions and establishing an optimization model aimed at minimizing adjustment actions, significantly improving the accuracy of decision-making and the economy of operation. Through dynamic priority ranking and iterative optimization algorithms based on unit regulation characteristics, it achieves optimal combination optimization of heterogeneous regulation resources, prioritizing the use of high-quality resources with fast response and low cost, ensuring rapid convergence while improving the configuration efficiency of frequency regulation reserves and the quality of system regulation. Furthermore, by introducing a dual verification mechanism and compensation correction strategy based on system balance constraints and grid safety constraints, it automatically eliminates the power imbalance and cross-section over-limit risks that may be caused by the optimization scheme during the decision-making stage, achieving a mandatory unification of optimization objectives and grid safety constraints, and eliminating secondary operational risks. Through future scenario simulation functions, it promotes the transformation of the dispatching mode from passive response to proactive early warning, and combined with a graphical decision-making interface, it presents complex results intuitively, greatly reducing the cognitive load of dispatchers and improving human-machine collaboration efficiency and the level of decision-making intelligence. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 The above is a flowchart of a frequency modulation backup optimization and verification method based on alternating optimization, which is provided as an embodiment of the present invention.

[0024] Figure 2 This is a schematic diagram of the sequential decision-making algorithm based on alternating optimization, which is provided as an embodiment of the present invention for frequency modulation reserve optimization and verification method.

[0025] Figure 3 This is a schematic diagram of a visualization interface design for a frequency modulation backup optimization and verification method based on alternating optimization, provided as an embodiment of the present invention.

[0026] Figure 4 The present invention provides a system scheme flowchart for a frequency modulation backup optimization and verification system based on alternating optimization, which is an embodiment of the present invention. Detailed Implementation

[0027] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0028] Example 1, referring to Figure 1 As an embodiment of the present invention, a frequency modulation reserve optimization and verification method based on alternating optimization is provided, comprising: S100: Collect and integrate real-time operating status data of the power grid to obtain an operating status dataset, and based on the operating status dataset, construct an optimization decision model with the goal of minimizing adjustment actions.

[0029] S200: The alternating optimization sequential decision algorithm is used to solve the model, and through evaluation and adjustment, a unit output adjustment scheme is generated. The future scenario simulation parameters input by the user are received, a future operating state dataset is constructed, and the alternating optimization sequential decision algorithm is called to perform a forward-looking verification of the backup capacity of the future state and generate the verification results.

[0030] S300: Integrates the unit output adjustment scheme, the verification results of the future operating status dataset, and the system status information, and displays them visually through a graphical decision-making interface to assist users in making decisions.

[0031] It should be noted that the real-time acquisition and fusion of multi-source data has laid a solid and reliable data foundation for the decision-making model. The core alternating optimization sequential decision-making algorithm, with its dynamic priority ranking and iterative virtual adjustment mechanism, can efficiently match the unit regulation characteristics with system requirements, maximize the utilization efficiency of frequency regulation resources, and improve the engineering practicality of the scheme and the safety of power grid operation by introducing coupled verification of system balance and safety constraints and automatic correction closed loop.

[0032] Example 2, refer to Figures 1-3 This is a second embodiment of the present invention, which provides a frequency modulation reserve optimization and verification method based on alternating optimization, including: In this embodiment of the application, in step S100, obtaining the running status dataset includes steps S101 to S103: S101: Obtain the start-up status, real-time output value, and primary frequency regulation standby capacity data of all hydropower units and thermal power units in the entire network from the panoramic standby monitoring module of the real-time monitoring system (OCS) of the dispatch center.

[0033] S102: Obtain the upper limit of unit output data updated and reported by each power plant based on the actual operating conditions of the units from the Dispatch and Planning System (DCCS).

[0034] S103: Integrate these two types of data to form a complete operating status dataset that includes unit identification, real-time output, output limit, and operating capacity information.

[0035] In an optional implementation, in step S100, obtaining the operating status dataset further includes acquiring real-time data from OCS / DCCS, querying historical databases, obtaining regulation performance parameters of similar units under similar operating conditions, combining ultra-short-term wind power and photovoltaic power prediction data, predicting upcoming power fluctuations, and incorporating the prediction information as a virtual reserve demand or regulation pressure indicator into the dataset.

[0036] In another optional implementation, in step S100, obtaining the operating status dataset may further include collecting operating data of the same object from multiple independent data sources such as OCS, DCCS, PMU and power plant side systems, and removing abnormal data through data cleaning, time series alignment and consistency verification techniques to form the operating status dataset.

[0037] In this embodiment of the application, in step S200, the step of solving the model using the alternating optimization sequential decision algorithm includes employing a specific sequential decision method based on unit regulation characteristic classification and bidirectional alternating adjustment, specifically including steps S201~S203: S201: Based on the response speed (fast / slow) and the adjustment direction (up / down), the units are divided into four categories, and different weighting coefficients are assigned to each category of units to construct an adjustment evaluation function; The four types of units include: units that can be rapidly adjusted upwards (hydropower units and gas turbine units), units that can be rapidly adjusted downwards (pumped storage units), units that can be rapidly adjusted upwards (coal-fired power units), and units that can be rapidly adjusted downwards (nuclear power units). The regulation evaluation function for each type of unit is expressed as follows: in, Let h be the adjustment evaluation function for unit h. For the unit number, To adjust the potential weighting coefficient, This represents the upper limit of the output of unit h. This represents the real-time output value of unit h. To adjust the cost weighting coefficient, This is the reserve coefficient for primary frequency regulation. The operating capacity of unit h is [value]. Let i be the adjustment cost of unit i.

[0038] S202: Based on the sign of the standby requirement, select the unit with the best evaluation function value in the corresponding category, perform dynamic priority sorting, and form a candidate queue; Based on the sign of the current primary frequency regulation reserve requirement, a priority ranking strategy is determined. If the current primary frequency regulation reserve requirement is greater than zero, the unit with the smallest adjustment evaluation function value among the units that can be quickly adjusted upwards is selected first. If the current primary frequency regulation reserve requirement is less than zero, and it is necessary to increase the reserve for downward adjustment, the unit with the smallest adjustment evaluation function value among the units that can be quickly adjusted downwards is selected first. From the initial unit set, units that are under maintenance, in standby status, or have already won bids in the remaining frequency regulation service are removed to obtain the final candidate adjustment units.

[0039] S203: Initiate the iterative process. In each round, select the optimal unit from the queue of units with increased potential and adjust its output to the reserve critical value. Then, select the optimal unit from the queue of units with decreased potential and adjust it in the opposite direction. After each round, immediately check whether the reserve requirement is met. If not, update the queue and continue iterating. When the system needs to increase its reserve capacity, one unit that can increase its output is selected from the candidate units for adjustment in the current round, and the output of the selected unit is virtually adjusted to [the required level]. The adjustment amount is the initial adjustment amount for the current unit. From the candidate units for adjustment in the current round, units that can reduce output are selected, and the output of the selected units is virtually adjusted to... The adjustment amount is the initial adjustment amount for the current unit. After the adjustment of a pair of units is completed, the adjusted unit is removed from the candidate adjustment units. The unit selection criteria are expressed as follows: in, This refers to the unit number within the adjustable unit set that can have its output increased. This represents the upper limit of the output of unit i. This represents the real-time output value of unit i. The operating capacity of unit i. The primary frequency regulation reserve factor is 10% for hydropower units and 6% for thermal power units. This refers to the unit number within the adjustable unit set whose output can be reduced. This represents the real-time output value of unit j. Let J be the operating capacity of unit j.

[0040] In an optional implementation, in step S200, the method of using the alternating optimization sequential decision algorithm to solve the model further includes monitoring and recording the actual performance of each unit in responding to frequency regulation commands over a period of time. When optimization is required, the units are directly sorted in descending order according to their historical performance indicators (average regulation rate) to generate a candidate queue based on the current required adjustment direction (upward or downward).

[0041] In another optional implementation, in step S200, the step of using the alternating optimization sequential decision algorithm to solve the model may further include, before the optimization begins, collecting service bids from each unit participating in primary frequency regulation standby, generating a candidate queue in order of bids from low to high, and transforming the iterative optimization process into prioritizing the use of units with lower bids under the premise of meeting standby requirements, until the requirements are met.

[0042] Furthermore, in step S200, the power output adjustment scheme of the generating unit includes steps S211~S213: S211: Perform system balance constraint verification on the unit output adjustment scheme, and assess whether the implementation of the current scheme will lead to an imbalance between the total power generation and total load demand of the system; when the system balance constraint verification finds an imbalance risk, the balance compensation strategy is activated, and a compensation unit is selected from the units outside the candidate adjustment unit set and the compensation adjustment amount is calculated.

[0043] S212: The compensation adjustment amount is superimposed with the unit output adjustment scheme to generate a balanced correction scheme, and the balanced correction scheme is checked for system safety constraints to assess whether the current scheme will cause the power of key transmission sections in the power grid to exceed the limit.

[0044] S213: When the system safety constraint check finds a risk of exceeding the limit, the safety correction strategy is activated to adjust or cancel the adjustment amount of the single unit in the scheme that causes the section to exceed the limit. For the new backup gap caused by the safety correction, the balance compensation strategy is called or the alternating optimization sequential decision algorithm is returned to supplement the optimization and generate the scheme after safety correction.

[0045] It should be noted that, in the embodiments of this application, the balance compensation strategy in step S211 includes steps A1 to A3: A1: Determine the relationship between the current total power generation and total load of the power grid.

[0046] A2: When the total power generation is greater than the total load, check whether the difference between the sum of the upward output of all units and the sum of the downward output of all units is less than zero; when the total power generation is less than the total load, check whether the difference is greater than zero. The constraints are expressed as follows: in, The total number of rounds to complete iterative optimization and backup verification.

[0047] A3: When the above conditions are met, the system balance constraint check passes; otherwise, it is determined that the current scheme will lead to power imbalance and the check fails. When the power balance check fails, the remaining units (units that have not entered n rounds of iterative optimization and standby check) are called to increase or decrease their output to supplement the power balance deficit.

[0048] In an optional implementation, in step S211, the balance compensation strategy further includes, when the main optimization scheme causes power imbalance, directly calling a dedicated balancing unit to increase / decrease output according to the magnitude of the imbalance at a preset adjustment rate until the system power is restored to balance.

[0049] In another optional implementation, in step S211, the balance compensation strategy may further include issuing instructions to eligible large industrial users when the main optimization scheme results in the power generation being less than the load (resulting in a power deficit), reducing the load by a specific amount as agreed in the contract, and using virtual upward adjustment of output to make up for the power deficit and achieve balance.

[0050] Furthermore, in this embodiment of the application, in step S212, the system security constraint verification includes steps B1 to B4: B1: Read all section constraint formulas that include unit output as a factor from the real-time grid section library; The cross-sectional constraint formula is expressed as: in, This is the function for calculating the cross-sectional power flow. This is the new output value of unit i after optimization and adjustment. This is the new output value of unit j after optimization and adjustment.

[0051] B2: Substitute the output values ​​of each unit in the balanced and corrected scheme into the constraint formula of each section for calculation.

[0052] B3: Compare the calculation results of each formula with the power limit given for that cross-section. The formula is expressed as: in, This is the function for calculating the cross-sectional power flow. This is the new output value of unit i after optimization and adjustment. This is the new output value of unit j after optimization and adjustment. This is the power limit for the cross section.

[0053] B4: If all calculation results are less than the corresponding section limit, the system safety constraint check is passed; otherwise, it is determined that there is a risk of section exceeding the limit, the check fails, and the section check fails. If the section check fails, the unit adjustment amount related to the section exceeding the limit needs to be discarded, and the remaining units (units that have not entered n rounds of iterative optimization and standby check) are called to increase or decrease the output to supplement the primary frequency regulation standby deficit.

[0054] In an optional implementation, in step S212, the system safety constraint verification further includes, after identifying the over-limit section, determining a switching operation scheme that can alleviate the power flow of the section through analysis and calculation, changing the power flow distribution of the power grid, and after executing this network topology change, the original unit adjustment scheme that caused the over-limit may no longer be over-limit, and thus be retained.

[0055] In another optional implementation, in step S212, the system safety constraint verification may further include, when the cross-section is found to exceed the limit, without changing the unit output scheme, sending a control command to the FACTS device, dynamically adjusting the voltage, phase or impedance parameters of the installation point, actively controlling the power flow magnitude through the restricted cross-section, and returning it to within the safety limit.

[0056] It should be further noted that, in step S200, the forward verification of backup capability includes steps S221 to S224: S221: Provides a human-machine interface to receive dispatcher input regarding the future status of the unit, including unit start-up and shutdown simulation, real-time height limit change simulation, and real-time output change simulation. The simulation includes: unit start-up and shutdown simulation, which specifies one or more units to be scheduled to start or stop in the future; real-time height limit change simulation, which specifies one or more units to adjust their upper limit output value in DCCS in the future; and real-time output change simulation, which specifies one or more units to adjust their output value according to the power generation plan in the future.

[0057] S222: Based on parameters, modify the current running state dataset to generate a future running state dataset that simulates the future.

[0058] S223: Take the future running state dataset as input and call the alternating optimization sequential decision algorithm again for calculation.

[0059] S224: Output alternative verification results for the current future scenario, and determine whether a new optimization and adjustment scheme needs to be generated.

[0060] In step S300, the visualization display includes steps S301 to S304: S301: Displays the maximum value of the primary frequency regulation reserve of the entire network under the current operating conditions and future simulation conditions, and compares it with the assessment requirements, in the form of numerical and percentage bar charts.

[0061] S302: List in tabular form the name of each unit to be adjusted, its output value before adjustment, its output value after adjustment, and the adjustment amount in the unit output adjustment plan or the safety correction plan.

[0062] S303: In the unit list or system diagram, key limiting units that become optimization bottlenecks due to their own status limitations are identified by color highlighting or special icons.

[0063] S304: The final verification conclusion shall be given in a prominent position on the interface in the form of a text label, including whether the reserve is sufficient or insufficient, and the shortfall value shall be given when the conclusion is insufficient.

[0064] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

[0065] Example 3, referring to Figure 4 This is the third embodiment of the present invention. This embodiment provides a frequency modulation backup optimization and verification system based on alternating optimization, including a data acquisition and integration module, an alternating optimization calculation module, a multiple security constraint verification module, a future scenario simulation verification module, and a visualization decision support module.

[0066] The data acquisition and integration module is used to gather key information on the unit startup status, real-time output, output limit, and primary frequency regulation reserve capacity of the entire network. After cleaning, alignment, and fusion processing, the operating status dataset is obtained.

[0067] The alternating optimization calculation module is used to receive the operating status dataset and the backup requirements issued by the superior. Through the built-in alternating optimization sequential decision algorithm, it automatically performs unit classification, dynamic priority sorting, and iterative optimization calculation.

[0068] The multi-safety constraint verification module is used to perform power balance verification and grid safety verification. When the verification fails, it triggers the balance compensation strategy and safety correction strategy to automatically modify the scheme and output a safe and feasible final adjustment scheme that simultaneously meets the backup requirements, power balance and network security constraints.

[0069] The future scenario simulation and verification module is used to construct a future operating state dataset based on parameters, and call alternating optimization calculation and multiple security constraint verification to perform a pre-assessment of the power grid's frequency regulation reserve capability at future moments.

[0070] The visualization decision support module is used to present the optimization and verification process and results to the dispatcher in an intuitive form using graphics, tables, and color highlighting, and to provide clear decision suggestions.

[0071] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

[0072] Example 4, the fourth embodiment of the present invention, differs from the previous three embodiments in that: If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0073] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0074] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0075] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

Claims

1. A frequency modulation reserve optimization and verification method based on alternating optimization, characterized in that: include, Collect and integrate real-time operating status data of the power grid to obtain an operating status dataset, and construct an optimization decision model based on the operating status dataset with the goal of minimizing adjustment actions; The alternating optimization sequential decision algorithm is used to solve the model, and through evaluation and adjustment, a unit output adjustment scheme is generated. The future scenario simulation parameters input by the user are received to construct a future operating state dataset. The alternating optimization sequential decision algorithm is called to perform a forward verification of the backup capacity of the future state and generate the verification results. The system integrates unit output adjustment plans, verification results of future operating status datasets, and system status information, and displays them visually through a graphical decision-making interface to assist users in making decisions.

2. The frequency modulation reserve optimization and verification method based on alternating optimization as described in claim 1, characterized in that: The acquisition of the operating status dataset includes reading the power-on status, real-time output value, and primary frequency regulation backup capacity from the backup monitoring module of the real-time monitoring system. The system retrieves the unit output limit data updated and reported by each power plant based on actual operating conditions from the scheduling and planning system, and aligns and merges the data in memory to obtain the operating status dataset.

3. The frequency modulation reserve optimization and verification method based on alternating optimization as described in claim 2, characterized in that: The method of solving the model using the alternating optimization sequential decision algorithm includes: based on the predefined unit adjustment characteristics, screening the initial set of all running units, excluding units that do not participate in the adjustment, and obtaining a set of candidate adjustment units; For the units in the candidate adjustment unit set, the units are dynamically prioritized according to their adjustment characteristics and the current system's backup demand type to determine the order of adjustment. Initiate the iterative optimization process, and based on the results of dynamic priority sorting, select candidate units from the candidate adjustment unit set in the current round for virtual output adjustment, and calculate the preliminary adjustment amount; After completing the virtual adjustment, update the system status based on all the initial adjustment amounts and perform a backup capacity check to determine whether the backup requirements are met. When the backup capacity verification is passed, all preliminary adjustment quantities are integrated and output as a unit output adjustment scheme; when it fails, the candidate adjustment unit set is updated and iterative optimization continues.

4. The frequency modulation reserve optimization and verification method based on alternating optimization as described in claim 3, characterized in that: The method of using the alternating optimization sequential decision algorithm to solve the model also includes: performing system balance constraint verification on the unit output adjustment scheme, and assessing whether the implementation of the current scheme will lead to an imbalance between the total power generation and the total load demand of the system; when the system balance constraint verification finds an imbalance risk, the balance compensation strategy is activated, and a compensation unit is selected from the units outside the candidate adjustment unit set and the compensation adjustment amount is calculated. The compensation adjustment amount is superimposed with the unit output adjustment scheme to generate a balanced correction scheme. The balanced correction scheme is then checked for system safety constraints to assess whether the current scheme will lead to the power exceeding the limit of key transmission sections in the power grid. When the system safety constraint check finds a risk of exceeding the limit, the safety correction strategy is activated to adjust or cancel the adjustment amount of the unit in the scheme that causes the cross section to exceed the limit. For the new backup gap generated by the safety correction, the balance compensation strategy is called or the alternating optimization sequential decision algorithm is returned to supplement the optimization and generate the scheme after safety correction.

5. The frequency modulation reserve optimization and verification method based on alternating optimization as described in claim 4, characterized in that: The dynamic priority ranking includes determining a priority ranking strategy based on the sign of the current primary frequency regulation reserve requirement. When the current primary frequency regulation reserve requirement is greater than zero, the unit with the smallest adjustment evaluation function value among the units that can be quickly adjusted upwards is selected first. When the current primary frequency regulation reserve requirement is less than zero, and it is necessary to increase the reserve for downward adjustment, the unit with the smallest adjustment evaluation function value among the units that can be quickly adjusted downwards is selected first. Furthermore, units that are under maintenance, in standby status, or have already won bids in the remaining frequency regulation services are removed from the initial unit set to obtain the final candidate adjustment units. The iterative optimization process includes: when the system needs to increase the reserve capacity, selecting a unit that can increase its output from the candidate adjustment units in the current round, virtually adjusting the output of the selected unit, and the adjustment amount is the initial adjustment amount of the current unit; and selecting a unit that can decrease its output from the candidate adjustment units in the current round, virtually adjusting the output of the selected unit, and the adjustment amount is the initial adjustment amount of the current unit. After completing the adjustment of a pair of units, the adjusted unit is removed from the candidate adjustment units. The unit selection criteria are expressed as follows: in, This refers to the unit number within the adjustable unit set that can have its output increased. This represents the upper limit of the output of unit i. This represents the real-time output value of unit i. The operating capacity of unit i. This is the reserve coefficient for primary frequency regulation. This refers to the unit number within the adjustable unit set whose output can be reduced. This represents the real-time output value of unit j. Let J be the operating capacity of unit j.

6. The frequency modulation reserve optimization and verification method based on alternating optimization as described in claim 5, characterized in that: The system balance constraint verification includes determining the relationship between the current total power generation and the total load of the power grid. If the total power generation is greater than the total load, the system balance constraint verification is performed by subtracting the total output reduction of all generating units from the total output reduction of all generating units and checking whether the difference is less than zero. If the total power generation is less than the total load, the system balance constraint verification is performed by checking whether the difference is greater than zero. If the conditions are met, the system balance constraint verification is passed; otherwise, it is determined that the current scheme will lead to power imbalance and the verification is not passed. The constraints are expressed as follows: in, The total number of rounds required to complete iterative optimization and backup verification; The system safety constraint verification includes reading all section constraint formulas that include unit output as a factor from the real-time grid section database, substituting the unit output values ​​in the balanced correction scheme into each section constraint formula for calculation, and comparing the calculation results with the power limit given for the current section. If all calculation results are less than the matching section limit, the system safety constraint verification is passed; otherwise, it is determined that there is a risk of section exceeding the limit, and the verification fails. The cross-sectional constraint formula is expressed as: in, This is the function for calculating the cross-sectional power flow. This is the new output value of unit i after optimization and adjustment. This is the new output value of unit j after optimization and adjustment. This is the power limit for the cross section.

7. The frequency modulation reserve optimization and verification method based on alternating optimization as described in claim 6, characterized in that: The aforementioned standby capability forward verification includes providing a human-machine interface, receiving simulation parameters about the future state of the unit input by the dispatcher, modifying the current operating state dataset, generating a future operating state dataset, and using the future operating state dataset as input to re-execute the alternating optimization sequential decision algorithm for calculation, outputting the standby verification result for the current future scenario, and determining whether a new optimization adjustment scheme needs to be generated. The visualization includes displaying the maximum value of the primary frequency regulation reserve of the entire network under the current operating state and the future simulation state, and comparing it with the assessment requirements, in the form of numerical and percentage bar charts; listing the current unit output adjustment plan or the plan after safety correction in the form of a table; identifying the limiting units that have become optimization bottlenecks due to their own state limitations in the unit list or system diagram through color highlighting and special icons; and giving the final verification conclusion in the form of text labels on the interface.

8. A frequency modulation reserve optimization and verification system based on alternating optimization, employing the frequency modulation reserve optimization and verification method based on alternating optimization as described in any one of claims 1 to 7, characterized in that, It includes a data acquisition and integration module, an alternating optimization calculation module, a multiple security constraint verification module, a future scenario simulation verification module, and a visualization decision support module; The data acquisition and integration module is used to collect key information on the unit start-up status, real-time output, output limit and primary frequency regulation reserve capacity of the entire network. After cleaning, alignment and fusion processing, the operating status dataset is obtained. The alternating optimization calculation module is used to receive the operating status dataset and the backup requirements issued by the superior, and automatically perform unit classification, dynamic priority sorting and iterative optimization calculation through the built-in alternating optimization sequential decision algorithm. The multi-safety constraint verification module is used to perform power balance verification and grid safety verification. When the verification fails, it triggers the balance compensation strategy and safety correction strategy to automatically modify the scheme and output a safe and feasible final adjustment scheme that simultaneously meets the backup requirements, power balance and network security constraints. The future scenario simulation and verification module is used to construct a future operating state dataset based on parameters, and call alternating optimization calculation and multiple security constraint verification to perform a pre-assessment of the power grid's frequency regulation reserve capability at future moments. The visualization decision support module is used to present the optimization and verification process and results to the dispatcher in an intuitive form using graphics, tables, and color highlighting, and to provide clear decision suggestions.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the frequency modulation backup optimization and verification method based on alternating optimization as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the frequency modulation backup optimization and verification method based on alternating optimization as described in any one of claims 1 to 7.

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