Time-series simulation method and system for massive power plants and substations, and related apparatus

Abstract

The present application belongs to the technical field of power plant and substation simulation. Disclosed are a time-series simulation method and system for massive power plants and substations, and a related apparatus. The method comprises: on the basis of an input power plant and substation model and according to a parameter attribute classification, constructing a parameter module system, and on the basis of parameter types, establishing different parameter module classes; on the basis of a set theme of a simulation application scenario, evaluating the complexity of a required parameter module, and using the parameter module system and the parameter module classes to generate a parameter module set; constructing a time-series computing simulator including parameter module set assignment, a unified computing module and a time advancement module; and cyclically receiving simulation events and assigning values, updating the parameter module set on the basis of the assigned values, and synchronizing updated parameter module set data to the time-series computing simulator, so that the time-series computing simulator performs unified computing and outputs a power plant and substation simulation result. The method supports long-timescale time-series simulation computing and does not require independent parallel computing within each device, thereby alleviating parallel computing pressure and improving the computing efficiency and resource utilization.

Description

A time-series simulation method, system, and related devices for massive power plants.

[0001] Cross-references to related applications

[0002] This application is based on and claims priority to Chinese Patent Application No. 202411043964.4, filed on July 31, 2024, entitled “A Time Series Simulation Method, System and Related Device for Massive Plants and Stations”, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This application relates to the field of plant simulation technology, and in particular to a time-series simulation method, system and related devices for massive plants. Background Technology

[0004] In the field of power plant simulation technology, most current simulations are based on single-time-section cross-sections. The models exhibit two extremes of oversimplification and overcomplication, resulting in poor flexibility, low computational efficiency, and difficulty in handling simulation event interruptions. With the deepening construction of new power systems, in order to ensure that simulation analysis can cover all possible operating conditions, it is necessary to consider massive combinations of power plants and stations and flexible simulation model accuracy, leading to an exponential increase in simulation computation.

[0005] With the accelerated construction of power systems and the increasing proportion of renewable energy, the control targets of power systems are shifting from a few homogeneous large-capacity synchronous generators on the source side to massive heterogeneous resources widely distributed across the power generation, grid, load, and storage sides, resulting in exponential growth in scale. The construction of new power systems is highly dependent on simulation technology. Plant simulation, as a crucial component of full-dimensional, full-scenario, and full-process power system simulation, exhibits characteristics of de-typicalization. To ensure that simulation analysis can cover all possible operating conditions, it is necessary to consider massive combinations of plant configurations and higher accuracy of simulation models, leading to an exponential increase in simulation computation.

[0006] In practical engineering applications, individual plant models are calculated independently. If serial calculation is used for massive plant simulations, the calculation speed is slow and the instruction processing process cannot be interrupted to immediately process new instructions. If parallel calculation is used, a large amount of hardware resources need to be purchased, which is costly.

[0007] Summary of the Invention

[0008] To address the problems existing in the prior art, this application proposes a time-series simulation method, system, and related devices for massive power plants. This method supports long-scale time-series simulation calculations and eliminates the need for independent parallel calculations within each device, thereby alleviating the pressure of parallel computing and improving computational efficiency and resource utilization.

[0009] To solve the above-mentioned technical problems, the technical solution adopted in this application is as follows:

[0010] Firstly, this application provides a time-series simulation method for massive power plants, including:

[0011] Based on the input plant model, a parameter module system is constructed according to parameter attributes, and different parameter module classes are established according to parameter types;

[0012] Based on the set simulation application scenario theme, assess the complexity of the required parameter modules, and generate a parameter module set using the parameter module system and parameter module class;

[0013] A time-series computation simulator is constructed, which includes a parameter module set assignment, a unified calculation module, and a time advancement module. Simulation events are received and assigned values ​​in a loop. The parameter module set is updated based on the assignment. The updated parameter module set data is synchronized to the time-series computation simulator, which then calculates and outputs the plant simulation results.

[0014] As a further improvement to this application, the step of constructing a parameter module system based on parameter attributes according to the input plant model, and establishing different parameter module classes according to parameter types, includes:

[0015] The selected power grid involves analyzing the substation models and operational data, and establishing the topological relationship between the substation models and the power grid models. The substation models include substation container and equipment models. The substation container includes the substation's own parameter set, including the substation's unique identifier, substation name, substation's highest voltage level, the power grid to which the substation belongs, and substation diagram name. The equipment models include the equipment's own attribute parameters and the relationship between substations and equipment. The equipment's own attribute parameters include generator models, capacitive reactor models, transformer models, and load models.

[0016] The parameter module system is constructed according to the equipment type, and different parameter module classes are established according to the parameter type; the parameter module classes include electrical parameter module class, mechanical parameter module class, and coupling parameter module class.

[0017] As a further improvement to this application, the step of evaluating the complexity of the required parameter modules based on the set simulation application scenario theme, and generating a parameter module set using the parameter module system and parameter module class, includes:

[0018] Based on typical simulation scenarios, extract parameter modules related to the simulation scenarios to construct a basic parameter module set, and evaluate the complexity of the module parameter set.

[0019] Select the basic parameter module set with the closest complexity, assemble the required parameter modules into a set, and generate the parameter module set.

[0020] As a further improvement to this application, the parameter generation module set is followed by:

[0021] If the automatically generated set of parameter modules does not meet the requirements of this simulation, then the parameters are modified and supplemented based on the automatically generated set;

[0022] Hardware resources, including computing and storage resources, are flexibly allocated based on the complexity of the scenario.

[0023] As a further improvement to this application, the module parameter set complexity evaluation method is as follows: C n (n)=∑γ n ω2>ω1 ω1+ω2=1

[0024] Among them, C n (n) represents the complexity of the application scenario parameter module set, which is the sum of the complexities of all n generators, γ n c represents the complexity of a generator n within the power plant model; static_n The single static parameter class complexity required for generator n is c. dynamic_n The single dynamic parameter class complexity required for generator n; c s_total The sum of static parameter complexity, c d_total The sum of dynamic parameter complexity is configured to normalize the overall complexity of static and dynamic classes; ω1 and ω2 are the weight coefficients of static and dynamic classes.

[0025] As a further improvement to this application, the construction of the time series computing simulator, which includes parameter module set assignment, unified calculation module, and time advancement module, comprises:

[0026] The time progression module records the progression time;

[0027] The parameter module set assignment updates the parameters of various plant and station equipment within the parameter module set based on simulation events. The unified calculation module refers to the parameter module classifying the calculations required within a single time section. Each dynamic parameter module generates a unified calculation module, and the static parameter module participates in the input and output of the calculation.

[0028] A certain attribute of different devices using the same parameter module class is used for timing calculation within the corresponding unified calculation module.

[0029] As a further improvement to this application, the step of cyclically receiving simulation events and assigning values, and updating the parameter module set based on the assignments, includes:

[0030] In this scenario, the simulated event is receiving instructions from the master station.

[0031] After receiving instructions from the main station, the instructions are parsed.

[0032] The relevant parameters in the update command parsing are updated. The adjustment type is assigned and updated according to the actual situation. The target value is determined based on the upper and lower limits of the static parameters. If the target value issued by the master station command is within its upper and lower limits, the target value is directly assigned and updated to the value issued by the master station command; otherwise, the target value is updated to its upper and lower limits according to the actual situation.

[0033] The single-step value in the update is the adjustment amount calculated once, which is the fixed adjustment rate of the static parameter, or the single-step value is updated in each round of processing.

[0034] As a further improvement to this application, the updated parameter module set data is synchronized to the timing simulation simulator, which then uniformly calculates and outputs the plant simulation results, including:

[0035] The time-series computation simulator receives and parses simulation events, and updates the parameter module set accordingly. As time progresses, the updated parameters are synchronized to the unified computation module at fixed time intervals for computation.

[0036] By decoupling the parameter module assignment and update process from the time-series calculation process through a time-series calculation simulator, a simulation event interruption mechanism is introduced. By updating the parameter module assignment, the calculation module can directly process the latest simulation event in the next moment.

[0037] The time-series simulation results at all times are obtained and used as output for interaction with the power grid simulation.

[0038] Secondly, this application provides a time-series simulation system for massive power plants, including:

[0039] The parameter module system construction module is configured to build a parameter module system based on the parameter attributes of the input plant model, and to create different parameter module classes according to the parameter type;

[0040] The parameter module set generation module is configured to evaluate the complexity of the required parameter modules based on the set simulation application scenario theme, and generate a parameter module set using the parameter module system and parameter module class;

[0041] The unified calculation module is configured to build a time-series calculation simulator that includes parameter module set assignment, unified calculation module and time advancement module; it cyclically receives simulation events and assigns values, updates the parameter module set based on the assignment, and synchronizes the updated parameter module set data to the time-series calculation simulator, which then uniformly calculates and outputs the plant simulation results.

[0042] Thirdly, this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the timing simulation method for massive power plants.

[0043] Fourthly, this application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the timing simulation method for massive power plants.

[0044] Fifthly, this application provides a computer program product, the computer program product including computer instructions, wherein the computer instructions instruct a computer to execute the timing simulation method for massive power plants.

[0045] The advantages of this application over the prior art are as follows:

[0046] This application proposes a time-series simulation method for massive plant sites. It constructs a parameter module system and generates parameter module sets based on the simulation application scenario. Hardware resources are allocated as needed according to the complexity of the parameter module sets, allowing for flexible selection of the refinement level of the model parameters for each device participating in the simulation. A time-series calculation simulator decouples the parameter module assignment and update process from the time-series calculation process, introducing a simulation event interruption mechanism. Updating parameter module assignments allows the calculation module to directly process the latest simulation event in the next moment. Furthermore, a unified time-series simulation calculation method is proposed, supporting long-scale time-series simulation calculations without requiring independent parallel calculations within each device, thus alleviating parallel computing pressure and improving computational efficiency and resource utilization. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the following description of the relevant technical solutions in the embodiments of this application or the prior art is provided with accompanying drawings. It should be understood that the accompanying drawings described below are only for the purpose of clearly illustrating some embodiments of the technical solutions in this application. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0048] Figure 1 is a flowchart of a timing simulation method for massive power plants provided in this application;

[0049] Figure 2. A time-series simulation method and system for massive power plants;

[0050] Figure 3 shows the parameter module system and the architecture of the basic parameter module set.

[0051] Figure 4 shows the automatic generation process of the parameter module set;

[0052] Figure 5. Construction of unified computing module and modular unified computing;

[0053] Figure 6 shows the parameter module set assignment and update;

[0054] Figure 7. Schematic diagram of the timing simulation simulator calculating and outputting results;

[0055] Figure 8. System structure diagram of the massive plant simulation system;

[0056] Figure 9 shows a timing simulation device for massive power plants provided in this application;

[0057] Figure 10 is a schematic diagram of an electronic device provided in this application. Detailed Implementation

[0058] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application. The step numbers in the following embodiments are set only for ease of explanation, and there is no limitation on the order between the steps. The execution order of each step in the embodiments can be adaptively adjusted according to the understanding of those skilled in the art.

[0059] In the description of this application, unless otherwise expressly defined, terms such as "setup," "installation," and "connection" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this application in conjunction with the specific content of the technical solution.

[0060] Terminology Explanation:

[0061] AGC (Automatic Generation Control): Its main function is to control the output of generators in the power system in order to maintain the frequency stability of the power system.

[0062] AVC (Automatic Voltage Control): Its purpose is to maintain the voltage stability of the power system. An AVC system automatically adjusts the generator output voltage to meet the voltage requirements of the power system. When the power system voltage is lower than expected, AVC automatically increases the generator output voltage; conversely, when the voltage is too high, AVC automatically decreases the generator output voltage.

[0063] Plant simulation: Plant simulation involves various types of plants such as power plants and substations, focusing on simulating changes in the status of equipment within the plant. For example, it can simulate the response of AGC and AVC control commands issued by the master station to the generators in the substation.

[0064] As shown in Figure 1, this application provides a time-series simulation method for massive power plants, including the following steps:

[0065] S100: Based on the input plant model, a parameter module system is constructed according to parameter attributes, and different parameter module classes are established according to parameter types.

[0066] S200 assesses the complexity of required parameter modules based on the set simulation application scenario theme, and generates a parameter module set using the parameter module system and parameter module class;

[0067] S300: Construct a timing calculation simulator that includes parameter module set assignment, unified calculation module, and time advancement module; cyclically receive simulation events and assign values, update the parameter module set based on the assignment, synchronize the updated parameter module set data to the timing calculation simulator, and have the timing calculation simulator uniformly calculate and output the plant simulation results.

[0068] This application proposes a time-series simulation method for massive power plants. The main principle is to construct a parameter module system and generate parameter module sets according to the simulation application scenario. Hardware resources are allocated as needed based on the complexity of the parameter module sets, and the fineness of the model parameters of each device participating in the simulation calculation is flexibly selected. The parameter module assignment and update process is decoupled from the time-series calculation process through a time-series calculation simulator. A simulation event interruption mechanism is introduced, allowing the calculation module to directly process the latest simulation event in the next moment by updating the parameter module assignment. Furthermore, a unified time-series simulation calculation method is proposed, supporting long-scale time-series simulation calculations and eliminating the need for independent parallel calculations within each device. This alleviates the pressure of parallel computing, improves computational efficiency and resource utilization, and provides a practical simulation tool for massive and diverse power plants in new power systems to participate in full-dimensional, full-scenario, and full-process power system simulations.

[0069] Furthermore, by constructing a parameter module system categorized by parameter attributes and establishing different parameter module classes based on parameter types, this approach makes the model more modular, easier to manage, and more extensible. The parameter module set is dynamically generated based on the theme of the simulation application scenario and the complexity of the required parameter modules. This flexibility allows the simulation system to quickly adjust the model complexity according to different simulation needs.

[0070] The features of the time-series computing simulator include:

[0071] Decoupling assignment and calculation: The assignment and update process of the parameter module is decoupled from the timing calculation process, which improves the system's flexibility and response speed.

[0072] Simulation event interruption mechanism: By introducing a simulation event interruption mechanism, parameter module assignments can be updated in real time based on events during the simulation process, making the simulation results closer to the actual situation.

[0073] Unified computing method: It supports time-series simulation calculations on long time scales, reduces the need for independent parallel computing within each device, thereby reducing the pressure of parallel computing and improving computing efficiency and resource utilization.

[0074] Modular design makes the system easy to expand and maintain, and allows for rapid adjustment of model complexity to meet different simulation needs. It supports diverse simulation applications, such as power grid dispatcher training and source-grid-load-storage interaction simulation. By decoupling the assignment and calculation processes, the system's response speed and computational efficiency are improved.

[0075] Introducing a simulation event interruption mechanism makes the simulation process more realistic and improves the accuracy of the simulation results. A unified computation method reduces the need for parallel computing, alleviates computational pressure, and improves resource utilization.

[0076] In summary, this time-series simulation method for massive power plants achieves an efficient, flexible, and practical simulation system through modular modeling and the design of a time-series computation simulator, providing strong support for the operation and management of power systems.

[0077] The modular modeling and calculation method of this approach can develop a large-scale power plant simulation system that is fast, flexible, and efficient in utilizing resources. It can support power grid dispatcher training, source-grid-load-storage interaction simulation, AGC / AVC software testing, and power plant operator training. The related software products can be promoted to the control center for application, resulting in significant economic benefits.

[0078] The present application will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0079] This application proposes a time-series simulation method for massive power plants, including the following steps:

[0080] First, a parameter module system is constructed based on the parameter attributes of the input plant model;

[0081] Then, based on the set simulation application scenario theme, the complexity of the required parameter modules is evaluated, and a parameter module set is automatically generated;

[0082] A time-series calculation simulator is then constructed, which includes parameter module set assignment, unified calculation module and time advancement module. The simulator receives simulation events in a loop and updates the parameter module set. The data is synchronized to the time-series calculation simulator for unified calculation and output of plant simulation results.

[0083] This paper proposes a method for constructing a time-series computation simulator for massive plant simulation. The time-series computation simulator includes a parameter module set assignment, a unified computation module, and a time advancement module. By decoupling the parameter module assignment and update process from the time-series computation process through the time-series computation simulator, a simulation event interruption mechanism is introduced. By updating the parameter module assignment, the computation module can directly process the latest simulation event in the next moment, solving the problem that the traditional serial computation method for massive plant simulation cannot interrupt the instruction processing process to receive new instructions in real time.

[0084] A unified computational method for time-series simulation of massive plant simulation is proposed, which supports long-scale time-series simulation computation and eliminates the need for independent parallel computation within each device. This significantly reduces the number of parallel computation threads for single-parameter modules, alleviates the pressure of parallel computation, and improves computational efficiency and resource utilization.

[0085] Figure 2 illustrates a time-series simulation method for massive power plants. The method includes the following steps:

[0086] (1) Obtain plant model data and construct a parameter module system;

[0087] (2) Set the theme of the simulation application scenario;

[0088] (3) Automatically generate parameter module sets;

[0089] (4) Construct a time-series computing simulator;

[0090] (5) Receive simulation events in a loop and assign values ​​to the parameter module set;

[0091] (6) The timing simulation simulator calculates and outputs the results.

[0092] Specifically, step (1) involves acquiring plant model data and constructing a parameter module system. This includes:

[0093] This process involves analyzing the substation models and operational data related to the selected power grid, and establishing the topological relationships between the substation models and the power grid models. The substation model includes substation containers and equipment models. A substation container refers to the set of parameters for the substation itself, including its unique identifier, name, highest voltage level, the power grid it belongs to, and its diagram name. Equipment models refer to the generator models, capacitor reactor models, transformer models, load models, etc., contained within the substation. Besides the equipment's own attribute parameters, this also includes the relationships between the substation and the equipment.

[0094] Figure 3 shows the architecture diagram for the parameter module system and the basic parameter module set. The parameter module system is constructed according to the device type, and different parameter module classes are established according to the parameter type.

[0095] Taking a thermal power plant as an example, the core equipment of the power plant is the generator. Generator unit parameters can be divided into electrical parameter modules, mechanical parameter modules, and coupling parameter modules. Among them, electrical parameters are the most commonly used in power system simulation calculations. Based on whether they have time-series characteristics, they can be further divided into static parameters and dynamic parameters. Static parameters are the attribute parameters of the generator participating in the power flow section at a single moment in the simulation, such as generator measurements, power upper and lower limit parameters, and state parameters for participation in AGC and AVC. Dynamic parameters are the attribute parameters of the generator participating in multi-timescale time-series simulation calculations, such as ramp rate (power rise and fall rate) and transient parameters. Mechanical parameter modules vary depending on the type of thermal power unit and include boiler parameter modules, turbine parameter modules, etc. Coupling parameters are the coupling relationship parameters connecting various modules. They can describe the numerical correlation of certain parameters in several module classes, or they can convert certain parameters of several module classes into equivalent parameters in another module class, which is used to simplify parameters and reduce model complexity. For example, the parameters in the boiler parameter module class and the turbine parameter module class can be equivalent to the ramp rate in the electrical parameter module class.

[0096] Step (2) involves setting the simulation application scenario theme and evaluating the required model complexity. Specifically, this includes:

[0097] As shown in Figure 3, based on typical simulation scenarios, the parameter modules related to the simulation scenarios are extracted to construct a basic parameter module set, and the complexity of the module parameter set is evaluated to prepare for the automatic generation of the parameter module set in step (3).

[0098] One specific complexity calculation method is given in the embodiments of this application: C n (n)=∑γ n ω2>ω1 ω1+ω2=1

[0099] Among them, C n (n) represents the complexity of the application scenario parameter module set, which is the sum of the complexities of all n generators, γ n c represents the complexity of a generator n within the power plant model; static_n The single static parameter class complexity required for generator n is c. dynamic_n The single dynamic parameter class complexity required for generator n; c s_total The sum of static parameter complexity, c d_total The total complexity of the dynamic parameters is configured to normalize the overall complexity of both static and dynamic classes. ω1 and ω2 are the weight coefficients of the static and dynamic classes, respectively. Since the simulation calculations involving dynamic parameters are complex and require consideration of time progression, the weight of ω2 is much greater than that of ω1, and their sum is 1, ensuring that the complexity γ is minimized. n The value is between 0 and 1.

[0100] Complexity calculations can also be performed using other methods known in the art, and this application does not impose any specific limitations.

[0101] Step (3) involves automatically generating a set of parameter modules. Specifically, it includes:

[0102] The principle of automatically generating parameter module sets is shown in Figure 4, which illustrates the automatic generation process of parameter module sets. Based on the simulation application scenario theme set in step (2), the complexity of the required modules is evaluated, and the basic parameter module set with the closest complexity is selected.

[0103] If the automatically generated set of parameter modules does not meet the requirements of this simulation, parameter modules can be manually modified and supplemented based on the automatically generated set.

[0104] The required parameter modules are grouped into a set to generate a parameter module set. Hardware resources such as computing resources and storage resources are flexibly allocated according to the complexity of the scenario to achieve efficient use of resources and avoid resource waste or performance bottlenecks.

[0105] The basis and method for hardware resource allocation are shown in Table 1. Ec, Hc, Em, Hm, Ed, and Hd in the table are various "hardware resource allocation complexity coefficients", which can be flexibly set by the user according to specific circumstances.

[0106] Table 1 Hardware Resource Allocation Method

[0107] Step (4) involves constructing a time-series computing simulator. Specifically, this includes:

[0108] The time series computation simulator includes a time progression module, a parameter module set assignment module, and a unified computation module.

[0109] Among them, parameter module set assignment refers to updating the parameters of various plant equipment in the parameter module set according to simulation events.

[0110] The unified calculation module refers to the classification of the calculation steps required within a single time section according to the parameter module. Each dynamic parameter module generates a unified calculation module. The static parameter module, as a necessary parameter of the calculation module, is not used as a basis for division and only participates in the input and output of the calculation.

[0111] A certain type of attribute of different devices using the same parameter module class can be directly calculated in the corresponding unified calculation module. This proposes the concept of modular unified calculation, instead of calculating separately for each plant or device as a whole.

[0112] This application takes a generator as an example, as shown in Figure 5. Figure 5 is a flowchart of the unified calculation module construction and modular unified calculation process. The parameter module sets of generator a and generator n both have generator ramping parameter modules, thus forming a unified ramping calculation module. In the simulation calculation, the ramping parameters of generator a and generator n are traversed, and a single ramping calculation is performed on them. After this calculation is completed, time advances to traverse generator a and generator n again and perform a single ramping calculation. Subsequently, the calculation continues to be performed cyclically according to the time sequence.

[0113] Step (5) involves cyclically receiving simulation events and assigning values ​​to the parameter module set. Since the unified calculation module is composed of parameter modules, the result of assigning and updating the parameter module set will be synchronized to the unified calculation module.

[0114] Taking the AGC software testing application scenario as an example, Figure 6 shows the parameter module set assignment and update process. In this scenario, the simulation event is receiving a master station command, which is generally a generator power ramp-up command. After receiving the master station command, the command is parsed to obtain the generator and power adjustment target value corresponding to the master station command. The relevant parameters in the ramp-up parameter module of the generator are updated, the ramp-up status is assigned and updated to "ramp-up", and the adjustment type is assigned and updated according to the actual situation to "linear ramp-up", "one-step", "following the adjustment curve", etc. The target value is determined based on the upper and lower limits of the generator's static parameters.

[0115] If the target value issued by the master station command is within its upper and lower limits, the target value is directly assigned and updated to the value issued by the master station command; otherwise, the target value is updated to its upper and lower limits according to the actual situation. The single-step value is the adjustment amount calculated in a single operation. It can be the fixed adjustment rate of the static parameter, or it can be updated in the unified calculation module each round of processing the ramp parameters according to the actual adjustment curve of the generator.

[0116] Step (6) involves the timing simulation simulator calculating and outputting the results. Specifically, this includes:

[0117] As shown in Figure 7, the time-series computation simulator receives and parses simulation events (master station commands) and updates the parameter module set. As time t advances, the updated parameters are synchronized to the unified computation module at fixed time intervals for computation.

[0118] Taking the unified ramp calculation module as an example, t1 to t8 in the diagram represent time points with equal time intervals. First, the ramp status bit of the generator's parameter module set is obtained to determine whether the generator needs ramp calculation at time t-1. If the status bit is ramp-related, ramp parameter processing is performed to obtain the ramp target value and single-step value. The generator's power at the next time t is then calculated using the formula. P ae (t)=P ae (t-1)+P astep (t)

[0119] P ae (t) represents the power of generator a at time t, P ae (t-1) represents the power of generator a at time t-1 (the time before time t), P astep (t) represents the single-step value of the generator ramping parameter module at time t.

[0120] Then, the next generator ramp-up calculation is performed, and so on for other generators. Figure 7 shows the schematic diagram of the timing simulation simulator calculating and outputting the results. By traversing all generators, the power of all generators at time t is obtained, and the power of all generators at time t is sent back to the power grid simulation or the master station simulation. Then, the ramp-up calculation at time t+1 is performed, thereby obtaining the timing simulation results at all times, which are used as output to interact with the power grid simulation.

[0121] Because the unified calculation module and the parameter module assignment are decoupled, a simulation event interruption mechanism can be introduced. That is, when multiple simulation events that perform different operations on the same plant equipment are received in succession, the parameter module assignment can be updated so that the calculation module can directly process the latest simulation event in the next moment without having to complete the previous simulation event.

[0122] In addition, due to the use of a unified computing module, independent parallel computing within each device is no longer required. The number of parallel computing threads in the single-parameter module for massive power plant simulation is reduced from n to 1 (where n is the number of power plants), improving resource utilization and providing a practical simulation tool for massive and diverse power plants in new power systems to participate in full-dimensional, full-scenario, and full-process power system simulation.

[0123] Based on the above method, as shown in Figure 8, a massive plant simulation system can be constructed. The parameter module system construction module generates a parameter module system based on the parameter attributes of the input plant model; the parameter module set generation module automatically generates a parameter module set based on the set simulation application scenario theme; the time-series calculation simulator includes a parameter module set assignment module, a unified calculation module, and a time progression module, decoupling the parameter processing process from the calculation process, supporting long-scale time-series simulation calculations; the input / output module supports inputting simulation events and outputting simulation results.

[0124] This application proposes a method for constructing a parameter module system and automatically generating parameter module sets for massive power plant simulation. The method generates a parameter module system based on parameter attributes according to the selected power grid power plant model, generates a parameter module set according to the simulation application scenario, and allocates hardware resources as needed based on the complexity of the parameter module set.

[0125] This application enables the controllability of the precision of the parameters of each equipment model participating in the simulation calculation through an automated and intelligent parameter module set generation process and resource allocation method, thereby improving the flexibility of massive plant simulation calculations and the diversity of application scenarios. At the same time, it realizes efficient management and utilization of hardware resources, avoiding the problems of resource waste or performance bottlenecks.

[0126] As shown in Figure 9, the second objective of this application is to provide a time-series simulation system for massive power plants, including:

[0127] The parameter module system construction module 100 is configured to construct a parameter module system based on the parameter attributes of the input plant model, and to establish different parameter module classes according to the parameter type.

[0128] The parameter module set generation module 200 is configured to evaluate the complexity of the required parameter modules based on the set simulation application scenario theme, and generate a parameter module set using the parameter module system and parameter module class.

[0129] The unified calculation module 300 is configured to construct a time-series calculation simulator that includes parameter module set assignment, unified calculation module and time advancement module; it cyclically receives simulation events and assigns values, updates the parameter module set based on the assignment, synchronizes the updated parameter module set data to the time-series calculation simulator, and the time-series calculation simulator uniformly calculates and outputs the plant simulation results.

[0130] In the parameter module system construction module 100, a parameter module system is constructed according to parameter attributes based on the input plant model, and different parameter module classes are established according to parameter types, including:

[0131] The selected power grid involves analyzing the substation models and operational data, and establishing the topological relationship between the substation models and the power grid models. The substation models include substation container and equipment models. The substation container includes the substation's own parameter set, including the substation's unique identifier, substation name, substation's highest voltage level, the power grid to which the substation belongs, and substation diagram name. The equipment models include the equipment's own attribute parameters and the relationship between substations and equipment. The equipment's own attribute parameters include generator models, capacitive reactor models, transformer models, and load models.

[0132] The parameter module system is constructed according to the equipment type, and different parameter module classes are established according to the parameter type; the parameter module classes include electrical parameter module class, mechanical parameter module class, and coupling parameter module class.

[0133] The parameter module set generation module 200, based on the set simulation application scenario theme, evaluates the complexity of the required parameter modules and generates a parameter module set using the parameter module system and parameter module classes, including:

[0134] Based on typical simulation scenarios, extract parameter modules related to the simulation scenarios to construct a basic parameter module set, and evaluate the complexity of the module parameter set.

[0135] Select the basic parameter module set with the closest complexity, assemble the required parameter modules into a set, and generate the parameter module set.

[0136] The unified computing module 300 constructs a time-series computing simulator, including parameter module set assignment, a unified computing module, and a time advancement module, comprising:

[0137] The time progression module records the progression time;

[0138] The parameter module set assignment updates the parameters of various plant and station equipment within the parameter module set based on simulation events. The unified calculation module refers to the parameter module classifying the calculations required within a single time section. Each dynamic parameter module generates a unified calculation module, and the static parameter module participates in the input and output of the calculation.

[0139] A certain attribute of different devices using the same parameter module class is used for timing calculation within the corresponding unified calculation module.

[0140] In the unified computing module 300, simulation events are received and assigned values ​​in a loop, and the parameter module set is updated based on the assigned values, including:

[0141] In this scenario, the simulated event is receiving instructions from the master station.

[0142] After receiving instructions from the main station, the instructions are parsed.

[0143] The relevant parameters in the update command parsing are updated. The adjustment type is assigned and updated according to the actual situation. The target value is determined based on the upper and lower limits of the static parameters. If the target value issued by the master station command is within its upper and lower limits, the target value is directly assigned and updated to the value issued by the master station command; otherwise, the target value is updated to its upper and lower limits according to the actual situation.

[0144] The single-step value in the update is the adjustment amount calculated once, which is the fixed adjustment rate of the static parameter, or the single-step value is updated in each round of processing.

[0145] In the unified calculation module 300, the updated parameter module set data is synchronized to the time series calculation simulator, which then uniformly calculates and outputs the plant simulation results, including:

[0146] The time-series computation simulator receives and parses simulation events, and updates the parameter module set accordingly. As time progresses, the updated parameters are synchronized to the unified computation module at fixed time intervals for computation.

[0147] By decoupling the parameter module assignment and update process from the time-series calculation process through a time-series calculation simulator, a simulation event interruption mechanism is introduced. By updating the parameter module assignment, the calculation module can directly process the latest simulation event in the next moment.

[0148] The time-series simulation results at all times are obtained and used as output for interaction with the power grid simulation.

[0149] The system is based on the aforementioned time-series simulation method for massive power plants.

[0150] This application proposes a method for constructing a parameter module system and automatically generating parameter module sets for massive power plant simulation. The method generates a parameter module system based on parameter attributes according to the selected power grid power plant model, generates a parameter module set according to the simulation application scenario, and allocates hardware resources as needed based on the complexity of the parameter module set.

[0151] A method for constructing a time-series computation simulator for massive plant simulation is proposed. The time-series computation simulator includes a parameter module set assignment, a unified calculation module, and a time progression module. By decoupling the parameter module assignment and update process from the time-series computation process through the time-series computation simulator, a simulation event interruption mechanism is introduced.

[0152] Furthermore, the method of this application provides a unified calculation method for time-series simulation of massive plant simulations, which supports long-term time-series simulation calculations and eliminates the need for independent parallel calculations within each device.

[0153] As shown in Figure 10, a third objective of this application embodiment is to provide an electronic device, including a memory 701, a processor 702, and a computer program stored in the memory 701 and executable on the processor. When the processor executes the computer program, it implements the timing simulation method for massive power plants. It also includes a communication interface 703 and a bus 704.

[0154] The fourth objective of this application is to provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the timing simulation method for massive power plants.

[0155] A fifth objective of this application is to provide a computer program product comprising computer instructions, wherein the computer instructions instruct a computer to execute the timing simulation method for massive power plants.

[0156] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means that implement the functions specified in one or more flowcharts and / or one or more block diagrams.

[0157] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable apparatus, provide steps for implementing the functions specified in one or more flowcharts and / or one or more block diagrams.

[0158] This application may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application may take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, readable storage media, optical storage, etc.) containing computer-usable program code.

[0159] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in one or more flowchart illustrations and / or one or more block diagrams.

[0160] Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this application.

[0161] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application and not to limit them. Although this application has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of this application. Any modifications or equivalent substitutions that do not depart from the spirit and scope of this application should be covered within the protection scope of the claims of this application.

Claims

1. A time sequence simulation method for mass substation, wherein, The method comprises the following steps: According to the input power station model, the parameter module system is constructed according to the parameter attribute classification, and different parameter module classes are established according to the parameter type; According to the set simulation application scene theme, the required parameter module complexity is evaluated, and the parameter module set is generated by using the parameter module system and the parameter module class; A time sequence calculation simulator including parameter module set assignment, unified calculation module and time advancing module is constructed; simulation events are received and assigned in a loop, the parameter module set is updated based on the assignment, and the updated parameter module set data is synchronized to the time sequence calculation simulator, which uniformly calculates and outputs the power station simulation results.

2. The mass substation oriented time sequence simulation method according to claim 1, wherein, The parameter module system is constructed according to the input power station model, and different parameter module classes are established according to the parameter type, which comprises the following steps: The selected power grid related power station model and operation data are parsed, and the topological correlation between the power station model and the power grid model is established; the power station model comprises a power station container and a device model; the power station container comprises a power station itself parameter set, including a power station unique identifier, a power station name, a power station maximum voltage level, a power station belonging power grid, and a power station graph name; the device model comprises device itself attribute parameters, and the correlation between the power station and the device; the device itself attribute parameters include a generator model, a capacitive reactor model, a transformer model and a load model; According to the device type, the parameter module system is constructed, and different parameter module classes are established according to the parameter type; the parameter module class comprises an electrical parameter module class, a mechanical parameter module class and a coupling parameter module class.

3. The mass substation oriented time sequence simulation method according to claim 1, wherein, According to the set simulation application scene theme, the required parameter module complexity is evaluated, and the parameter module set is generated by using the parameter module system and the parameter module class, which comprises the following steps: According to the typical simulation scene, the related parameter module of the simulation scene is extracted to construct a basic parameter module set, and the module parameter set complexity is evaluated; The closest basic parameter module set is selected, the required parameter modules are combined into a set, and the parameter module set is generated.

4. The mass substation oriented time sequence simulation method according to claim 3, wherein, After the parameter module set is generated, the following steps are further included: If the automatically generated parameter module set does not meet the simulation requirements, the parameters are modified and supplemented based on the automatically generated set; And according to the scene complexity, the hardware resources including computing resources and storage resources are flexibly allocated.

5. The mass substation oriented time sequence simulation method according to claim 3, wherein, The module parameter set complexity evaluation method is: C n (n) = ∑γ n ω2>ω1 ω1+ω2=1 where C n (n) represents the application scenario parameter module set complexity, which is the accumulation of the complexity of all n generators, γ n represents the complexity of a certain generator n in the station model; c static_n is the single static parameter class complexity required by the generator n, c dynamic_n is the single dynamic parameter class complexity required by the generator n; c s_total is the static parameter complexity sum, c d_total is the dynamic parameter complexity sum, configured to normalize the overall complexity of the static and dynamic classes; ω1 and ω2 are the static class and dynamic class weight coefficients.

6. The mass substation oriented time sequence simulation method according to claim 1, wherein, The time sequence calculation simulator including parameter module set assignment, unified calculation module and time advancing module is constructed, which comprises the following steps: The time advancing module records the advancing time; The parameter module set assignment updates the parameters of each type of power station device in the parameter module set according to the simulation event; the unified calculation module refers to the calculation required by the parameter module in a single time section; each dynamic parameter module generates a unified calculation module, and the input and output of the static parameter module participate in the calculation; The same type of attribute of different devices using the same parameter module class is calculated in the corresponding unified calculation module.

7. The mass substation oriented time sequence simulation method according to claim 1, wherein, The simulation event in this scene is to receive the main station instruction; After receiving the main station instruction, the instruction is parsed; ​ The related parameters in the update instruction analysis are adjusted and updated according to the actual situation, and the target value is judged according to the upper and lower limits of the static parameters. If the target value of the master station instruction is within the upper and lower limits, the target value is directly updated to the value of the master station instruction; otherwise, the target value is updated to the upper and lower limit value according to the actual situation. The single-step value in the update is the single calculation adjustment amount, which is the fixed value of the static parameter upper speed rate, or the single-step value is updated every round of processing.

8. The mass substation oriented time sequence simulation method of claim 1 wherein, The updated parameter module set data is synchronized to the time sequence calculation simulator, which uniformly calculates and outputs the plant station simulation results, including: The time sequence calculation simulator receives and analyzes the simulation events, and updates the parameter module set; With the time advancing, the updated parameters are synchronized to the unified calculation module at fixed time intervals and are calculated; The parameter module assignment update process and the time sequence calculation process are decoupled through the time sequence calculation simulator, the simulation event interruption mechanism is introduced, and the latest simulation event is directly processed by the next time calculation module by updating the parameter module assignment; The time sequence simulation results of all time points are obtained as the output and the power grid simulation interaction.

9. A mass substation oriented time sequence simulation system, wherein, It includes: A parameter module system construction module configured to construct a parameter module system according to the input plant station model based on parameter attributes, and to establish different parameter module classes according to parameter types; A parameter module set generation module configured to evaluate the required parameter module complexity according to the set simulation application scenario theme, and to generate a parameter module set using the parameter module system and parameter module classes; A unified calculation module configured to construct a time sequence calculation simulator including parameter module set assignment, unified calculation module and time advancing module; receive simulation events and assign values in a loop, update the parameter module set based on the assignment, and synchronize the updated parameter module set data to the time sequence calculation simulator, which uniformly calculates and outputs the plant station simulation results.

10. An electronic device, comprising: The computer readable storage medium stores a computer program, and the computer program is executed by the processor to realize the time sequence simulation method for a large number of power plants and substations according to any one of claims 1-8.

11. A computer readable storage medium, wherein, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to realize the time sequence simulation method for a large number of power plants and substations according to any one of claims 1-8.

12. A computer program product comprising computer instructions, wherein, The computer instructions instruct the computer to execute the time sequence simulation method for a large number of power plants and substations according to any one of claims 1-8.

Images