CN116680862A - Simulation method and device of electric power market system model and nonvolatile storage medium - Google Patents
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Abstract
The invention discloses a simulation method and device of an electric power market system model and a nonvolatile storage medium. Wherein the method comprises the following steps: acquiring object characteristics of a plurality of objects in an electric power market system; according to object characteristics of a plurality of objects, discrete simulation models corresponding to the plurality of objects are respectively established, wherein the discrete simulation models corresponding to the plurality of objects respectively correspond to simulation time steps, and the simulation time steps represent simulation time spans of the corresponding discrete simulation models; determining the time points of interaction of the discrete simulation models corresponding to the objects based on the simulation time steps respectively corresponding to the discrete simulation models corresponding to the objects; and at the time point, the simulation results of the discrete simulation models corresponding to the objects are interacted to obtain a target simulation result. The invention solves the technical problem that the simulation model of the electric power market system in the related technology is difficult to obtain an accurate simulation result.
Description
Technical Field
The invention relates to the field of power markets, in particular to a simulation method and device of a power market system model and a nonvolatile storage medium.
Background
At present, the electric power market is increasingly widely applied in production and life, and the simulation method of the electric power market system model can play an important role in supporting the safe and economic operation of an electric power energy system. The simulation method of the electric power market system model is low in cost and high in safety, and the decision process can be more reasonable, so that the simulation method of the electric power market system model is important to the electric power market, but in the related technology, the electric power market system is difficult to model because of high complexity, and the modeling result cannot achieve a good simulation effect because the complexity and high interactivity of the electric power market system are not considered in a conventional modeling mode.
In view of the above problems, no effective solution has been proposed at present.
Disclosure of Invention
The embodiment of the invention provides a simulation method and device of an electric power market system model and a nonvolatile storage medium, which at least solve the technical problem that the simulation model of the electric power market system in the related technology is difficult to obtain an accurate simulation result.
According to an aspect of the embodiment of the present invention, there is provided a simulation method of an electric power market system model, including: acquiring object characteristics of a plurality of objects in an electric power market system; according to the object characteristics of the objects, discrete simulation models corresponding to the objects are respectively established, wherein the discrete simulation models corresponding to the objects respectively correspond to simulation time steps, and the simulation time steps represent simulation time spans of the corresponding discrete simulation models; determining a time point of interaction of the discrete simulation models corresponding to the objects based on the simulation time step sizes respectively corresponding to the discrete simulation models corresponding to the objects; and at the time point, the simulation results of the discrete simulation models corresponding to the objects are interacted to obtain a target simulation result.
Optionally, at the time point, interacting simulation results of the discrete simulation models corresponding to the multiple objects to obtain a target simulation result, including: and at the time point, opening the data interaction interfaces of the discrete simulation models corresponding to the objects to perform one-time simulation data interaction until the simulation of the discrete simulation models is finished, and obtaining the target simulation result.
Optionally, the determining, based on the simulation time steps corresponding to the discrete simulation models corresponding to the plurality of objects, a time point at which the discrete simulation models corresponding to the plurality of objects interact includes: determining a first simulation time step corresponding to a first discrete simulation model and a second simulation time step corresponding to a second discrete simulation model under the condition that the discrete simulation models corresponding to the plurality of objects comprise the first discrete simulation model and the second discrete simulation model; and determining the time point at which the discrete simulation models corresponding to the objects interact according to the least common multiple of the first simulation time step and the second simulation time step.
Optionally, the method further comprises: determining a third simulation time step corresponding to a third discrete simulation model under the condition that the discrete simulation models corresponding to the plurality of objects further comprise the third discrete simulation model; determining a first target time step according to the least common multiple of the first simulation time step and the second simulation time step, wherein the first target time step is the least common multiple of the first simulation time step and the second simulation time step; and determining the time point of interaction of the discrete simulation models corresponding to the objects according to the least common multiple of the first target time step and the third simulation time step.
Optionally, the determining, based on the simulation time steps corresponding to the discrete simulation models corresponding to the plurality of objects, a time point at which the discrete simulation models corresponding to the plurality of objects interact includes: determining the least common multiple of the simulation time steps corresponding to the discrete simulation models corresponding to the objects respectively to obtain the target time step, wherein the target time step is a preset multiple of the least common multiple; and determining the time point according to the target time step.
Optionally, at the time point, interacting simulation results of the discrete simulation models corresponding to the multiple objects to obtain a target simulation result, including: respectively simulating the discrete simulation models corresponding to the objects between the previous time point and the current time point of the simulation process to obtain a plurality of groups of discrete simulation data, wherein the current time point is the moment when the discrete simulation models corresponding to the objects perform simulation data interaction, and the previous time point is the moment when the discrete simulation models corresponding to the objects perform simulation data interaction last time; at the current time point, opening the data interaction interfaces of the discrete simulation models corresponding to the objects; based on the matching relation between the data types of the multiple groups of discrete simulation data and the interface types of the data interaction interfaces of the discrete simulation models corresponding to the multiple objects, the multiple groups of discrete simulation data are interacted between the discrete simulation models corresponding to the multiple objects through the data interaction interfaces; closing the data interaction interface between the current time point and the next time point, wherein the next time point is the moment when the discrete simulation models corresponding to the objects perform simulation data interaction next time; repeating the simulation process until the simulation of the discrete simulation models corresponding to the objects is finished, and obtaining the target simulation result.
Optionally, the establishing discrete simulation models corresponding to the plurality of objects according to the object characteristics of the plurality of objects respectively includes: establishing a plurality of first simulation models corresponding to the plurality of objects respectively based on object characteristics of the plurality of objects, wherein the plurality of first simulation models are used for simulating respective types of the plurality of objects and interaction relations among the objects respectively; establishing a plurality of second simulation models respectively corresponding to the plurality of objects based on object characteristics of the plurality of objects and a machine learning algorithm, wherein the plurality of second simulation models are respectively used for simulating behaviors of the plurality of objects; and establishing a plurality of discrete simulation models respectively corresponding to the plurality of objects according to the plurality of first simulation models and the plurality of second simulation models.
Optionally, at the time point, interacting simulation results of the discrete simulation models corresponding to the multiple objects to obtain a target simulation result, including: configuring the discrete simulation models corresponding to the objects into a plurality of hosts, wherein the hosts are in one-to-one correspondence with the discrete simulation models corresponding to the objects; and respectively simulating the discrete simulation models corresponding to the plurality of objects in a plurality of hosts to obtain the target simulation result, wherein the plurality of hosts perform simulation data interaction through the discrete simulation models corresponding to the plurality of objects in the simulation process.
According to another aspect of the embodiment of the present invention, there is also provided a simulation apparatus of an electric power market system model, including: the first acquisition module is used for acquiring object characteristics of a plurality of objects in the electric power market system; the building module is used for respectively building discrete simulation models corresponding to the objects according to the object characteristics of the objects, wherein the discrete simulation models corresponding to the objects respectively correspond to simulation time steps, and the simulation time steps represent simulation time spans of the corresponding discrete simulation models; the determining module is used for determining the time points of interaction of the discrete simulation models corresponding to the objects based on the simulation time steps respectively corresponding to the discrete simulation models corresponding to the objects; and the second acquisition module is used for interacting simulation results of the discrete simulation models corresponding to the objects at the time points to obtain target simulation results.
According to still another aspect of the embodiment of the present invention, there is further provided a nonvolatile storage medium, where the nonvolatile storage medium includes a stored program, and when the program runs, the device where the nonvolatile storage medium is controlled to execute the simulation method of the electric power market system model according to any one of the above.
In the embodiment of the invention, the object characteristics of a plurality of objects in the electric power market system are acquired firstly, then the discrete simulation models corresponding to the plurality of objects are respectively built according to the object characteristics of the plurality of objects, wherein the discrete simulation models corresponding to the plurality of objects respectively correspond to simulation time steps, the simulation time steps represent the simulation time spans of the corresponding discrete simulation models, then the time points of interaction of the discrete simulation models corresponding to the plurality of objects are determined based on the simulation time steps respectively corresponding to the discrete simulation models corresponding to the plurality of objects, and then the simulation results of the discrete simulation models corresponding to the plurality of objects are interacted at the time points of interaction to obtain the target simulation results. Because the time step of the simulation corresponding to the discrete simulation models corresponding to the objects can be determined, the time point of interaction of the discrete simulation models corresponding to the objects can be conveniently and rapidly determined, and the simulation results of the discrete simulation models corresponding to the objects can be conveniently and rapidly interacted at the time point, so that the technical effect that the discrete simulation models in the electric power market system can be conveniently and rapidly interacted during simulation is realized, and the technical problem that the simulation model of the electric power market system in the related technology is difficult to obtain accurate simulation results is solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
FIG. 1 is a block diagram of the hardware architecture of a computer terminal for implementing a simulation method for an electric power market system model;
FIG. 2 is a flow chart of a simulation method of an electric power market system model provided according to an embodiment of the present application;
fig. 3 is a block diagram of a simulation apparatus of an electric power market system model according to an embodiment of the present application.
Detailed Description
In order that those skilled in the art will better understand the present application, a technical solution in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
According to an embodiment of the present invention, there is provided a simulation method embodiment of an electric power market system model, it being noted that the steps shown in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is shown in the flowchart, in some cases the steps shown or described may be performed in an order different from that shown or described herein.
The method according to the first embodiment of the present application may be implemented in a mobile terminal, a computer terminal or a similar computing device. Fig. 1 shows a hardware block diagram of a computer terminal for implementing a simulation method of a power market system model. As shown in fig. 1, the computer terminal 10 may include one or more (shown as processor 102a, processor 102b, … …, processor 102 n) processors (which may include, but are not limited to, a microprocessor MCU or a processing device such as a programmable logic device FPGA) and a memory 104 for storing data. In addition, the method may further include: a display, an input/output interface (I/O interface), a Universal Serial BUS (USB) port (which may be included as one of the ports of the BUS), a network interface, a power supply, and/or a camera. It will be appreciated by those of ordinary skill in the art that the configuration shown in fig. 1 is merely illustrative and is not intended to limit the configuration of the electronic device described above. For example, the computer terminal 10 may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.
It should be noted that the one or more processors and/or other data processing circuits described above may be referred to herein generally as "data processing circuits. The data processing circuit may be embodied in whole or in part in software, hardware, firmware, or any other combination. Furthermore, the data processing circuitry may be a single stand-alone processing module or incorporated, in whole or in part, into any of the other elements in the computer terminal 10. As referred to in embodiments of the application, the data processing circuit acts as a processor control (e.g., selection of the path of the variable resistor termination connected to the interface).
The memory 104 may be used to store software programs and modules of application software, such as program instructions/data storage devices corresponding to the simulation method of the power market system model in the embodiment of the present application, and the processor executes the software programs and modules stored in the memory 104, thereby executing various functional applications and data processing, that is, implementing the simulation method of the power market system model of the application program. Memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory located remotely from the processor, which may be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The display may be, for example, a touch screen type Liquid Crystal Display (LCD) that may enable a user to interact with a user interface of the computer terminal 10.
In order to reasonably simulate the electric power market system, the application provides a simulation method shown in fig. 2, and fig. 2 is a flow diagram of a simulation method of an electric power market system model according to an embodiment of the application, wherein the method comprises the following steps:
Step S202, object characteristics of a plurality of objects in the electric power market system are obtained.
In the above step S202 of the present invention, the plurality of objects in the power market system may be referred to as an interactive operation ontology applicable to the power market simulation scenario, and the interactive operation between the interactive operation ontology and the interactive operation ontology may include price, power, division, market members, disc, period, contract, winning result, etc. Wherein, the price can include declaration electricity price, clearing electricity price and settlement electricity price; the market members include buyers, sellers and operating institutions; the operating mechanism may include a market operating mechanism and a system operating mechanism; a disc contains a plurality of time periods; the bilateral contracts may include peak segment bilateral contracts, flat segment bilateral contracts, valley segment bilateral contracts; the winning bid results may include market member results, round winning bid results, time period winning bid results. Alternatively, object features of a plurality of objects may be represented as:
Σ＝(I、M、S、F、O)；
where Σ represents an individual or element at any level (corresponding to the object above, I, M, S, F, O in brackets characterizing the object's object characteristics); i represents an individual input set, O represents an individual output set; m is a static model representing the intrinsic properties of an individual, which may include the following properties: globally unique identification, type, parameter set, interface, and subset; s is a set of states for an individual; f is a set of functions of an individual that can be used to describe the dynamic behavior of the individual. By acquiring object features of a plurality of objects, condition information of the plurality of objects can be accurately determined.
Step S204, according to the object characteristics of the plurality of objects, discrete simulation models corresponding to the plurality of objects are respectively built, wherein the discrete simulation models corresponding to the plurality of objects respectively correspond to simulation time steps, and the simulation time steps represent simulation time spans of the corresponding discrete simulation models.
In the technical solution provided in the step S204, the discrete simulation models corresponding to the plurality of objects respectively correspond to a simulation time step, that is, the simulation time step is an inherent attribute of the discrete simulation model corresponding to the plurality of objects. The simulation time step represents a simulation time span of the corresponding discrete simulation model, i.e. the simulation time step is a time interval from the start of simulation to the first output of simulation data of the corresponding discrete simulation model or a time interval from the current output of simulation data to the next output of simulation data of the corresponding discrete simulation model. According to the object characteristics of the plurality of objects, discrete simulation models corresponding to the plurality of objects one by one can be respectively established.
As an alternative embodiment, building discrete simulation models corresponding to the plurality of objects according to object characteristics of the plurality of objects, respectively, includes: based on object characteristics of a plurality of objects, establishing a plurality of first simulation models corresponding to the plurality of objects respectively, wherein the plurality of first simulation models are used for simulating respective types of the plurality of objects and interaction relations among the objects respectively; establishing a plurality of second simulation models corresponding to the plurality of objects respectively based on object characteristics of the plurality of objects and a machine learning algorithm, wherein the plurality of second simulation models are used for simulating behaviors of the plurality of objects respectively; and establishing a plurality of discrete simulation models respectively corresponding to the plurality of objects according to the plurality of first simulation models and the plurality of second simulation models.
In this embodiment, the plurality of first simulation models corresponding to the plurality of objects may be static models, where the static models are characterized in that the models rarely change, and the plurality of first simulation models may be used to simulate respective types of the plurality of objects and interactions between the objects, that is, the types of the plurality of objects corresponding to the first simulation models and interactions between the objects may be determined through the plurality of first simulation models. Wherein the types of the plurality of objects may include a power generation device, a power transmission device, and a power use device, and the interaction relationship between the objects includes a transaction relationship between the objects. The second simulation models corresponding to the objects can be dynamic models, and the dynamic models are characterized in that the dynamic models are changed frequently, the second simulation models can be used for simulating the behaviors of the objects corresponding to the second simulation models, and the behaviors of the objects comprise sales behaviors, purchasing behaviors and using behaviors. The types, interaction relations and behaviors of the corresponding objects can be represented by combining the first simulation models and the second simulation models, namely, the characteristics of the objects in the electric power market system can be completely represented, so that the discrete simulation models which are respectively corresponding to the objects are accurate and complete and are built according to the first simulation models and the second simulation models.
Alternatively, the first simulation model and the second simulation model may be built based on the following alternative embodiments:
1) A passive behavioral knowledge model (equivalent to the first simulation model above) of the participation of market members in the power market based on fuzzy ensemble theory is established. The passive behavioral knowledge model is described in terms of IF a THEN B, where a is the front piece and B is the back piece. According to the application, a passive behavior knowledge model of participation of market members in the electric power market based on fuzzy ensemble theory is adopted to describe the participation of the market members in the demand response process.
2) An active decision behavior model (corresponding to the second simulation model above) of the participation of market members in the power market based on the reinforcement learning algorithm is established. The reinforcement learning algorithm takes the market clearing result as main input data and takes the quotation decision of the market member as main output data. And (3) through carrying out multiple iterations with the market trading environment, mastering the market quotation rule and obtaining the optimal quotation strategy.
Step S206, determining the interaction time points of the discrete simulation models corresponding to the objects based on the simulation time steps corresponding to the discrete simulation models corresponding to the objects.
In the technical solution provided in the above step S206 of the present invention, because the simulation time steps corresponding to the discrete simulation models corresponding to the objects may be different, and the discrete simulation models corresponding to the objects need to output simulation data at a certain time and receive simulation data of other models from other models at the same time, the time point when the discrete simulation models corresponding to the objects interact can be determined, and then interaction between the discrete simulation models corresponding to the objects is realized at the time point. Optionally, at a time other than the time point, the data interaction interfaces of the discrete simulation models corresponding to the multiple objects may be closed, where each model independently performs a simulation operation in the process of closing the data interaction interfaces.
As an optional embodiment, determining a time point at which the discrete simulation models corresponding to the plurality of objects interact based on the simulation time steps respectively corresponding to the discrete simulation models corresponding to the plurality of objects includes: determining a first simulation time step corresponding to the first discrete simulation model and a second simulation time step corresponding to the second discrete simulation model under the condition that the discrete simulation models corresponding to the plurality of objects comprise the first discrete simulation model and the second discrete simulation model; and determining the time points of interaction of the discrete simulation models corresponding to the objects according to the least common multiple of the first simulation time step and the second simulation time step.
In this embodiment, the least common multiple of the first simulation time step and the second simulation time step may characterize a minimum time interval in which the first discrete simulation model and the second discrete simulation model may output simulation data outwardly at the same point in time. According to the least common multiple of the first simulation time step and the second simulation time step, the determined time points at which the discrete simulation models corresponding to the objects interact can ensure that the discrete simulation models corresponding to the objects output simulation data at the same time point at the same time, so that the discrete simulation models corresponding to the objects can interact data at the same time point. By the embodiment, the time point of interaction of the discrete simulation models corresponding to the objects can be accurately and quickly determined.
As an alternative embodiment, the method may further include the steps of: determining a third simulation time step corresponding to a third discrete simulation model under the condition that the discrete simulation models corresponding to the plurality of objects further comprise the third discrete simulation model; determining a first target time step according to the least common multiple of the first simulation time step and the second simulation time step, wherein the first target time step is the least common multiple of the first simulation time step and the second simulation time step; and determining the time point of interaction of the discrete simulation models corresponding to the objects according to the least common multiple of the first target time step and the third simulation time step.
In this alternative embodiment, in the case that at least three objects are included in the electric power market system, the number of discrete simulation models corresponding to the at least three objects is at least three, which corresponds to the introduction of a newly added discrete simulation model, i.e., a third discrete simulation model, in addition to the first discrete simulation model and the second discrete simulation model in the above embodiment. Alternatively, the third discrete simulation model may be a plurality of models, i.e. equivalent to the introduction of a plurality of objects in the power market system, one for each newly introduced object.
At this time, since the first target time step between the first discrete simulation model and the second discrete simulation model has been obtained in the solution process of the preamble, in the case that the third discrete simulation model is newly introduced, the newly determined least common multiple can be used as a new time interval for performing simulation data interaction by determining the least common multiple between the first target time step and the simulation time step of the newly added discrete simulation model, thereby determining a time point of the simulation data interaction, that is, the new time interval between the time points of the simulation data interaction as the new least common multiple. In this way, the calculation amount can be reduced, and the time point of interaction of the discrete simulation models corresponding to the plurality of objects can be rapidly determined.
As an optional embodiment, determining a time point at which the discrete simulation models corresponding to the plurality of objects interact based on the simulation time steps corresponding to the discrete simulation models corresponding to the plurality of objects respectively may further adopt the following manner: determining the least common multiple of simulation time steps corresponding to the discrete simulation models corresponding to the objects respectively to obtain a target time step, wherein the target time step is a preset multiple of the least common multiple; and determining a time point according to the target time step.
In this embodiment, the least common multiple of the simulation time steps corresponding to the discrete simulation models respectively may be defined as a micro step, the target time step is a macro step, and the time length of the macro step is a multiple of the micro step. The discrete simulation models corresponding to a plurality of objects can be set to interact once every micro step, and the target simulation result obtained by the interaction mode is more accurate. The discrete simulation models corresponding to a plurality of objects can be set to interact once every macro step, the operation required by the process of obtaining the target simulation result through the interaction mode is smaller, and the target simulation result can be obtained rapidly.
Step S208, at the time point of interaction, the simulation results of the discrete simulation models corresponding to the objects are interacted to obtain the target simulation results.
In the technical scheme provided in the step S208, the time point of interaction is the time point when the discrete simulation models corresponding to the objects can interact. And at the interaction time point, the simulation results of the discrete simulation models corresponding to the objects are interacted, so that the interacted target simulation results can be conveniently obtained.
As an optional embodiment, at the above time point, the interaction is performed on simulation results of the discrete simulation models corresponding to the plurality of objects to obtain target simulation results, including: and at the time point, opening the data interaction interfaces of the discrete simulation models corresponding to the objects to perform one-time simulation data interaction until the simulation of the discrete simulation models is finished, and obtaining a target simulation result.
Optionally, in the simulation process of the electric power market system, a plurality of time points can be determined, when the simulation time reaches a certain time point in the plurality of time points, respective data interaction interfaces of the discrete simulation models corresponding to the plurality of objects are opened and simulation data interaction is performed once, until the simulation of the plurality of discrete simulation models is finished, multiple interactions can be performed between the discrete simulation models in the simulation process, and a target simulation result meeting the conditions is obtained.
Through the step S202 to the step S208, object characteristics of a plurality of objects in the electric power market system are obtained, and then discrete simulation models corresponding to the plurality of objects are respectively built according to the object characteristics of the plurality of objects, wherein the discrete simulation models corresponding to the plurality of objects respectively correspond to simulation time steps, the simulation time steps represent simulation time spans of the corresponding discrete simulation models, then time points at which the discrete simulation models corresponding to the plurality of objects interact are determined based on the simulation time steps respectively corresponding to the discrete simulation models corresponding to the plurality of objects, and then simulation results of the discrete simulation models corresponding to the plurality of objects are interacted at the time points to obtain target simulation results. Because the time step of the simulation corresponding to the discrete simulation models corresponding to the objects can be determined, the simulation results of the discrete simulation models corresponding to the objects can be conveniently interacted at the time point, the technical effect that the discrete simulation models in the power market system can be conveniently interacted in simulation is realized, and the technical problem that the discrete simulation models in the power market system in the related technology are difficult to interact in simulation is solved.
It should be noted that, the discrete simulation model corresponding to the plurality of objects may be an individual model, where the individual model may be referred to as an agent-based model or a multi-agent system, and the individual model is a calculation model for simulating actions and interactions of an agent with autonomous consciousness (independent individual or a common group, such as an organization, a team). If the discrete simulation models corresponding to the objects perform data interaction in real time, the complexity of model simulation is greatly increased, and the simulation result of the whole power market system cannot be obtained at a later time. Therefore, the application proposes to perform data interaction between the discrete simulation models corresponding to the objects based on the determined time point, and does not perform interaction in the time beyond the specific time point, so that the simulation efficiency of the whole power market system is greatly improved, the simulation result of the simulation of the whole power market system is still accurate, and the interaction behavior between the objects in the power market system is not completely ignored.
In the above embodiment or the alternative embodiment, the basic principle of information interaction between individuals with different time characteristics is to observe consistency of simulation time. Thus, for an individual's time-marching function, interactions must be performed in a reasonable time window in order to ensure the correctness of the simulated causality. Considering that in the simulation based on the model of the individual, the execution of the behaviors of the individual are independent and parallel, and the minimum time window of the information interaction of the individual is called macro step size. After a macro step, the output variable is sent to the input variable interface with the same name. There may be multiple microsteps within a macro-step.
The present application is directed to the above embodimentsThe following detailed description is provided. Individual sigma with three different speeds 1 ，Σ 2 ，Σ 3 For example, these 3 individuals have different simulation time steps λ 1 ，λ 2 ，λ 3 At t 0 Time is initialized. The first simulation interaction occurs at Σ 1 Sum sigma 2 Between them, the interaction time is t 1，2 At the moment Σ 1 Advances by i steps, Σ 2 J steps are advanced. Thus t 1，2 ＝i×λ 1 ＝j×λ 2 . At t 1，2，3 At this time, information interaction (triggering individual response behavior by discrete event simulation) is performed between each of 3 individuals, at which time Σ 2 Sum sigma 3 N and k steps are advanced, respectively. Here, t 1，2，3 Is lambda 1 ，λ 2 ，λ 3 And t is the least common multiple of 1，2，3 ＝n×i×λ 1 ＝n×j×λ 2 ＝k×λ 3 。
For multiple individual interaction problems with different simulation steps, the application employs the following interaction time window or set definition: the interaction time window for any two individuals should satisfy the time relationship shown in the following condition, where T is the set of interaction times between individuals, and λ 'and λ "are the time steps of the individuals, provided that T can divide λ' and T can divide λ".
And providing time control service of simulation experiments in the process of initializing a simulation platform, calculating the obtained simulation step length data of the individuals to obtain an interaction time window between the individuals, and injecting the interaction time window into the individuals. The interaction time window information comprises interaction time (corresponding to the time point) and information such as interaction objects of the interaction time, an individual obtaining the information has the capability of self-propelling simulation time, and a time agent of a third party is not required to realize propelling of multiple individual simulation times through high-frequency interaction.
As an optional embodiment, at a time point, interacting simulation results of the discrete simulation models corresponding to the plurality of objects to obtain a target simulation result, including: respectively simulating the discrete simulation models corresponding to the objects between the previous time point and the current time point of the simulation process to obtain a plurality of groups of discrete simulation data, wherein the current time point is the moment when the discrete simulation models corresponding to the objects perform simulation data interaction, and the previous time point is the moment when the discrete simulation models corresponding to the objects perform simulation data interaction last time; at the current time point, opening the data interaction interfaces of the discrete simulation models corresponding to the objects; based on the matching relation between the data types of the plurality of groups of discrete simulation data and the interface types of the data interaction interfaces of the discrete simulation models corresponding to the plurality of objects, the plurality of groups of discrete simulation data are interacted between the discrete simulation models corresponding to the plurality of objects through the data interaction interfaces; closing a data interaction interface between a current time point and a next time point, wherein the next time point is the moment when the discrete simulation model corresponding to the objects performs simulation data interaction next time; repeating the simulation process until the simulation of the discrete simulation models corresponding to the objects is finished, and obtaining a target simulation result.
It should be noted that, the discrete simulation models corresponding to the objects include a function set, and the function set defines the update modes of the states and the variables. The individual designed by the application comprises three main functions in the function set of the model: a time advance function, a state transfer function, an output function. Wherein the time-marching function defines the logic time (corresponding to the time point above) of the individual at the next simulation step; the state transfer function defines the state of the next simulation step of the individual, and the state comprises opening and closing; the output function defines the calculation method of the individual output value.
As an optional embodiment, at the above-mentioned time point for data interaction, interaction is performed on simulation results of the discrete simulation models corresponding to the plurality of objects to obtain target simulation results, including: configuring discrete simulation models corresponding to a plurality of objects into a plurality of hosts, wherein the hosts correspond to the discrete simulation models corresponding to the objects one by one; and respectively simulating the discrete simulation models corresponding to the plurality of objects in the plurality of hosts to obtain a target simulation result, wherein the plurality of hosts perform simulation data interaction through the discrete simulation models corresponding to the plurality of objects in the simulation process.
In this embodiment, distributed simulation software may be installed in multiple hosts, so as to implement the creation and simulation of discrete simulation models corresponding to multiple objects. The distributed simulation software can realize distributed individual modeling, namely, not only can establish discrete simulation models corresponding to a plurality of objects, but also can realize interaction among the discrete simulation models corresponding to the plurality of objects, so that the discrete simulation models corresponding to the plurality of objects are simulated in a plurality of hosts respectively, and an accurate discrete simulation model corresponding to the plurality of objects can be established, thereby obtaining an accurate target simulation result.
It should be noted that, the discrete simulation model corresponding to the plurality of objects may be an individual model, unlike the traditional equation-based analytical modeling method, the complex electric power energy system simulation based on the individual model is a distributed simulation method, and the modeling method is closer to the real world. The bottom-up modeling mode is easier to understand for readers and researchers, so that the individual modeling is a more natural modeling method, and is very suitable for distributed modeling, solving and simulation. However, not all models in a complex power energy system may be decoupled into completely independent individual models, especially considering the solution problem of the models, such as a centralized individual relying on a large amount of information in a common system operation scenario. Common crew combination problems, economic dispatch problems, etc. are a centralized model that requires a coordinator or intermediary to play the role in the power market, such as a power dispatching or trading facility, etc. Bilateral power transactions corresponding to centralized market clearing are independent of the individual behavior of the centralized optimization clearing house and can be understood as a pure decentralized individual model. It can be considered that a distributed model and a centralized model often coexist in a complex electric power energy system. From the technical choice of simulation, the interaction mode of the system can be compatible with the two main models at the same time, and the distributed simulation software can realize the compatibility of the two main models.
It should also be noted that the distributed simulation software may be disposed on a simulation platform, and the simulation platform may be disposed on a host. The contents of the simulation platform main body comprise a simulation initialization function, an interactive protocol management function, a simulation service function, a simulation behavior definition function and the like. The design of the simulation initialization function is very important for developing simulation research. Often for some exploratory simulation tasks, researchers often need to design different parameters and simulation schemes and execute simulation flows. Therefore, in order to simplify the simulation process, different configuration schemes are designed into independent simulation experiments, and special experiment management agents are arranged to control the execution of multiple experiments of the whole simulation. The experimental information fragment is described through an XML file, and one complete simulation study comprises a plurality of simulation experiments, and different parameters are configured for each experiment to simulate. Similarly, parameters appropriate for the agent's own situation are also configured for the different agents in each experiment.
It should be noted that, for simplicity of description, the foregoing method embodiments are all described as a series of acts, but it should be understood by those skilled in the art that the present invention is not limited by the order of acts described, as some steps may be performed in other orders or concurrently in accordance with the present invention. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required for the present invention.
From the above description of the embodiments, it will be clear to those skilled in the art that the simulation method of the electric power market system model according to the above embodiments may be implemented by means of software plus a necessary general hardware platform, and of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method of the various embodiments of the present invention.
According to an embodiment of the present invention, there is further provided a simulation apparatus of a power market system model for implementing the simulation method of a power market system model, and fig. 3 is a block diagram of a simulation apparatus of a power market system model according to an embodiment of the present invention, and as shown in fig. 3, the simulation apparatus of a power market system model includes: the first obtaining module 302, the establishing module 304, the determining module 306 and the second obtaining module 308 are described below as a simulation device of the electric power market system model.
A first obtaining module 302, configured to obtain object characteristics of a plurality of objects in the electric power market system;
the establishing module 304 is connected to the first obtaining module 302, and is configured to respectively establish discrete simulation models corresponding to the plurality of objects according to object features of the plurality of objects, where the discrete simulation models corresponding to the plurality of objects respectively correspond to simulation time steps, and the simulation time steps represent simulation time spans of the corresponding discrete simulation models;
the determining module 306 is connected to the establishing module 304, and is configured to determine a time point at which the discrete simulation models corresponding to the plurality of objects interact based on the simulation time steps corresponding to the discrete simulation models corresponding to the plurality of objects, respectively;
the second obtaining module 308 is connected to the determining module 306, and is configured to interact with simulation results of the discrete simulation models corresponding to the plurality of objects at a time point to obtain a target simulation result.
It should be noted that, the first obtaining module 302, the establishing module 304, the determining module 306 and the second obtaining module 308 correspond to steps S202 to S208 in the embodiment, and the four modules are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to those disclosed in the above embodiments. It should be noted that the above-described module may be operated as a part of the apparatus in the computer terminal 10 provided in the embodiment.
Embodiments of the present invention may provide a computer device, optionally in this embodiment, the computer device may be located in at least one network device of a plurality of network devices of a computer network. The computer device includes a memory and a processor.
The memory may be used to store software programs and modules, such as program instructions/modules corresponding to the simulation method and apparatus of the electric power market system model in the embodiment of the present invention, and the processor executes the software programs and modules stored in the memory, thereby executing various functional applications and data processing, that is, implementing the simulation method of the electric power market system model. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory may further include memory remotely located relative to the processor, which may be connected to the computer terminal via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The processor may call the information and the application program stored in the memory through the transmission device to perform the following steps: acquiring object characteristics of a plurality of objects in an electric power market system; according to object characteristics of a plurality of objects, discrete simulation models corresponding to the plurality of objects are respectively established, wherein the discrete simulation models corresponding to the plurality of objects respectively correspond to simulation time steps, and the simulation time steps represent simulation time spans of the corresponding discrete simulation models; determining the time points of interaction of the discrete simulation models corresponding to the objects based on the simulation time steps respectively corresponding to the discrete simulation models corresponding to the objects; and at a time point, the simulation results of the discrete simulation models corresponding to the objects are interacted to obtain a target simulation result.
Optionally, the above processor may further execute program code for: at a time point, interacting simulation results of the discrete simulation models corresponding to the objects to obtain a target simulation result, wherein the method comprises the following steps: and at a time point, opening the data interaction interfaces of the discrete simulation models corresponding to the objects to perform one-time simulation data interaction until the simulation of the discrete simulation models is finished, and obtaining a target simulation result.
Optionally, the above processor may further execute program code for: determining a time point at which the discrete simulation models corresponding to the plurality of objects interact based on the simulation time steps respectively corresponding to the discrete simulation models corresponding to the plurality of objects, including: determining a first simulation time step corresponding to the first discrete simulation model and a second simulation time step corresponding to the second discrete simulation model under the condition that the discrete simulation models corresponding to the plurality of objects comprise the first discrete simulation model and the second discrete simulation model; and determining the time points of interaction of the discrete simulation models corresponding to the objects according to the least common multiple of the first simulation time step and the second simulation time step.
Optionally, the above processor may further execute program code for: determining a third simulation time step corresponding to a third discrete simulation model under the condition that the discrete simulation models corresponding to the plurality of objects further comprise the third discrete simulation model; determining a first target time step according to the least common multiple of the first simulation time step and the second simulation time step, wherein the first target time step is the least common multiple of the first simulation time step and the second simulation time step; and determining the time point of interaction of the discrete simulation models corresponding to the objects according to the least common multiple of the first target time step and the third simulation time step.
Optionally, the above processor may further execute program code for: determining a time point at which the discrete simulation models corresponding to the plurality of objects interact based on the simulation time steps respectively corresponding to the discrete simulation models corresponding to the plurality of objects, including: determining the least common multiple of simulation time steps corresponding to the discrete simulation models corresponding to the objects respectively to obtain a target time step, wherein the target time step is a preset multiple of the least common multiple; and determining a time point according to the target time step.
Optionally, the above processor may further execute program code for: at a time point, interacting simulation results of the discrete simulation models corresponding to the objects to obtain a target simulation result, wherein the method comprises the following steps: respectively simulating the discrete simulation models corresponding to the objects between the previous time point and the current time point of the simulation process to obtain a plurality of groups of discrete simulation data, wherein the current time point is the moment when the discrete simulation models corresponding to the objects perform simulation data interaction, and the previous time point is the moment when the discrete simulation models corresponding to the objects perform simulation data interaction last time; at the current time point, opening the data interaction interfaces of the discrete simulation models corresponding to the objects; based on the matching relation between the data types of the plurality of groups of discrete simulation data and the interface types of the data interaction interfaces of the discrete simulation models corresponding to the plurality of objects, the plurality of groups of discrete simulation data are interacted between the discrete simulation models corresponding to the plurality of objects through the data interaction interfaces; closing a data interaction interface between a current time point and a next time point, wherein the next time point is the moment when the discrete simulation model corresponding to the objects performs simulation data interaction next time; repeating the simulation process until the simulation of the discrete simulation models corresponding to the objects is finished, and obtaining a target simulation result.
Optionally, the above processor may further execute program code for: according to the object characteristics of the plurality of objects, respectively establishing discrete simulation models corresponding to the plurality of objects, including: based on object characteristics of a plurality of objects, establishing a plurality of first simulation models corresponding to the plurality of objects respectively, wherein the plurality of first simulation models are used for simulating respective types of the plurality of objects and interaction relations among the objects respectively; establishing a plurality of second simulation models corresponding to the plurality of objects respectively based on object characteristics of the plurality of objects and a machine learning algorithm, wherein the plurality of second simulation models are used for simulating behaviors of the plurality of objects respectively; and establishing a plurality of discrete simulation models respectively corresponding to the plurality of objects according to the plurality of first simulation models and the plurality of second simulation models.
Optionally, the above processor may further execute program code for: at a time point, interacting simulation results of the discrete simulation models corresponding to the objects to obtain a target simulation result, wherein the method comprises the following steps: configuring discrete simulation models corresponding to a plurality of objects into a plurality of hosts, wherein the hosts correspond to the discrete simulation models corresponding to the objects one by one; and respectively simulating the discrete simulation models corresponding to the plurality of objects in the plurality of hosts to obtain a target simulation result, wherein the plurality of hosts perform simulation data interaction through the discrete simulation models corresponding to the plurality of objects in the simulation process.
By adopting the embodiment of the invention, a scheme of a simulation method of an electric power market system model is provided. Acquiring object characteristics of a plurality of objects in an electric power market system; according to object characteristics of a plurality of objects, discrete simulation models corresponding to the plurality of objects are respectively established, wherein the discrete simulation models corresponding to the plurality of objects respectively correspond to simulation time steps, and the simulation time steps represent simulation time spans of the corresponding discrete simulation models; determining the time points of interaction of the discrete simulation models corresponding to the objects based on the simulation time steps respectively corresponding to the discrete simulation models corresponding to the objects; and at a time point, the simulation results of the discrete simulation models corresponding to the objects are interacted to obtain a target simulation result. Therefore, the purpose is achieved, and the technical problem that a plurality of discrete simulation models in an electric power market system are difficult to interact in the simulation process in the related technology is solved.
Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be implemented by a program for instructing a terminal device to execute on associated hardware, the program may be stored in a non-volatile storage medium, and the storage medium may include: flash disk, read-Only Memory (ROM), random-access Memory (Random Access Memory, RAM), magnetic or optical disk, and the like.
Embodiments of the present invention also provide a nonvolatile storage medium. Alternatively, in the present embodiment, the above-described nonvolatile storage medium may be used to store program codes executed by the simulation method of the electric power market system model provided by the above-described embodiment.
Alternatively, in this embodiment, the above-mentioned nonvolatile storage medium may be located in any one of the computer terminals in the computer terminal group in the computer network, or in any one of the mobile terminals in the mobile terminal group.
Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: acquiring object characteristics of a plurality of objects in an electric power market system; according to object characteristics of a plurality of objects, discrete simulation models corresponding to the plurality of objects are respectively established, wherein the discrete simulation models corresponding to the plurality of objects respectively correspond to simulation time steps, and the simulation time steps represent simulation time spans of the corresponding discrete simulation models; determining the time points of interaction of the discrete simulation models corresponding to the objects based on the simulation time steps respectively corresponding to the discrete simulation models corresponding to the objects; and at a time point, the simulation results of the discrete simulation models corresponding to the objects are interacted to obtain a target simulation result.
Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: at a time point, interacting simulation results of the discrete simulation models corresponding to the objects to obtain a target simulation result, wherein the method comprises the following steps: and at a time point, opening the data interaction interfaces of the discrete simulation models corresponding to the objects to perform one-time simulation data interaction until the simulation of the discrete simulation models is finished, and obtaining a target simulation result.
Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: determining a time point at which the discrete simulation models corresponding to the plurality of objects interact based on the simulation time steps respectively corresponding to the discrete simulation models corresponding to the plurality of objects, including: determining a first simulation time step corresponding to the first discrete simulation model and a second simulation time step corresponding to the second discrete simulation model under the condition that the discrete simulation models corresponding to the plurality of objects comprise the first discrete simulation model and the second discrete simulation model; and determining the time points of interaction of the discrete simulation models corresponding to the objects according to the least common multiple of the first simulation time step and the second simulation time step.
Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: determining a third simulation time step corresponding to a third discrete simulation model under the condition that the discrete simulation models corresponding to the plurality of objects further comprise the third discrete simulation model; determining a first target time step according to the least common multiple of the first simulation time step and the second simulation time step, wherein the first target time step is the least common multiple of the first simulation time step and the second simulation time step; and determining the time point of interaction of the discrete simulation models corresponding to the objects according to the least common multiple of the first target time step and the third simulation time step.
Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: determining a time point at which the discrete simulation models corresponding to the plurality of objects interact based on the simulation time steps respectively corresponding to the discrete simulation models corresponding to the plurality of objects, including: determining the least common multiple of simulation time steps corresponding to the discrete simulation models corresponding to the objects respectively to obtain a target time step, wherein the target time step is a preset multiple of the least common multiple; and determining a time point according to the target time step.
Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: at a time point, interacting simulation results of the discrete simulation models corresponding to the objects to obtain a target simulation result, wherein the method comprises the following steps: respectively simulating the discrete simulation models corresponding to the objects between the previous time point and the current time point of the simulation process to obtain a plurality of groups of discrete simulation data, wherein the current time point is the moment when the discrete simulation models corresponding to the objects perform simulation data interaction, and the previous time point is the moment when the discrete simulation models corresponding to the objects perform simulation data interaction last time; at the current time point, opening the data interaction interfaces of the discrete simulation models corresponding to the objects; based on the matching relation between the data types of the plurality of groups of discrete simulation data and the interface types of the data interaction interfaces of the discrete simulation models corresponding to the plurality of objects, the plurality of groups of discrete simulation data are interacted between the discrete simulation models corresponding to the plurality of objects through the data interaction interfaces; closing a data interaction interface between a current time point and a next time point, wherein the next time point is the moment when the discrete simulation model corresponding to the objects performs simulation data interaction next time; repeating the simulation process until the simulation of the discrete simulation models corresponding to the objects is finished, and obtaining a target simulation result.
Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: according to the object characteristics of the plurality of objects, respectively establishing discrete simulation models corresponding to the plurality of objects, including: based on object characteristics of a plurality of objects, establishing a plurality of first simulation models corresponding to the plurality of objects respectively, wherein the plurality of first simulation models are used for simulating respective types of the plurality of objects and interaction relations among the objects respectively; establishing a plurality of second simulation models corresponding to the plurality of objects respectively based on object characteristics of the plurality of objects and a machine learning algorithm, wherein the plurality of second simulation models are used for simulating behaviors of the plurality of objects respectively; and establishing a plurality of discrete simulation models respectively corresponding to the plurality of objects according to the plurality of first simulation models and the plurality of second simulation models.
Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: at a time point, interacting simulation results of the discrete simulation models corresponding to the objects to obtain a target simulation result, wherein the method comprises the following steps: configuring discrete simulation models corresponding to a plurality of objects into a plurality of hosts, wherein the hosts correspond to the discrete simulation models corresponding to the objects one by one; and respectively simulating the discrete simulation models corresponding to the plurality of objects in the plurality of hosts to obtain a target simulation result, wherein the plurality of hosts perform simulation data interaction through the discrete simulation models corresponding to the plurality of objects in the simulation process.
The foregoing embodiment numbers of the present application are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present application, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed technology may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of units may be a logic function division, and there may be another division manner in actual implementation, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a non-volatile storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (10)
1. A simulation method of an electric power market system model, comprising:
acquiring object characteristics of a plurality of objects in an electric power market system;
according to the object characteristics of the objects, discrete simulation models corresponding to the objects are respectively established, wherein the discrete simulation models corresponding to the objects respectively correspond to simulation time steps, and the simulation time steps represent simulation time spans of the corresponding discrete simulation models;
determining a time point of interaction of the discrete simulation models corresponding to the objects based on the simulation time step sizes respectively corresponding to the discrete simulation models corresponding to the objects;
and at the time point, the simulation results of the discrete simulation models corresponding to the objects are interacted to obtain a target simulation result.
2. The method according to claim 1, wherein the step of interacting simulation results of the discrete simulation models corresponding to the plurality of objects at the time point to obtain a target simulation result includes:
And at the time point, opening the data interaction interfaces of the discrete simulation models corresponding to the objects to perform one-time simulation data interaction until the simulation of the discrete simulation models is finished, and obtaining the target simulation result.
3. The method of claim 1, wherein the determining a point in time at which the discrete simulation models corresponding to the plurality of objects interact based on the simulation time steps respectively corresponding to the discrete simulation models corresponding to the plurality of objects comprises:
determining a first simulation time step corresponding to a first discrete simulation model and a second simulation time step corresponding to a second discrete simulation model under the condition that the discrete simulation models corresponding to the plurality of objects comprise the first discrete simulation model and the second discrete simulation model;
and determining the time point at which the discrete simulation models corresponding to the objects interact according to the least common multiple of the first simulation time step and the second simulation time step.
4. A method according to claim 3, further comprising:
determining a third simulation time step corresponding to a third discrete simulation model under the condition that the discrete simulation models corresponding to the plurality of objects further comprise the third discrete simulation model;
Determining a first target time step according to the least common multiple of the first simulation time step and the second simulation time step, wherein the first target time step is the least common multiple of the first simulation time step and the second simulation time step;
and determining the time point of interaction of the discrete simulation models corresponding to the objects according to the least common multiple of the first target time step and the third simulation time step.
5. The method of claim 3, wherein the determining a point in time at which the discrete simulation models corresponding to the plurality of objects interact based on the simulation time steps respectively corresponding to the discrete simulation models corresponding to the plurality of objects comprises:
determining the least common multiple of the simulation time steps corresponding to the discrete simulation models corresponding to the objects respectively to obtain the target time step, wherein the target time step is a preset multiple of the least common multiple;
and determining the time point according to the target time step.
6. The method according to claim 1, wherein the step of interacting simulation results of the discrete simulation models corresponding to the plurality of objects at the time point to obtain a target simulation result includes:
Respectively simulating the discrete simulation models corresponding to the objects between the previous time point and the current time point of the simulation process to obtain a plurality of groups of discrete simulation data, wherein the current time point is the moment when the discrete simulation models corresponding to the objects perform simulation data interaction, and the previous time point is the moment when the discrete simulation models corresponding to the objects perform simulation data interaction last time;
at the current time point, opening the data interaction interfaces of the discrete simulation models corresponding to the objects;
based on the matching relation between the data types of the multiple groups of discrete simulation data and the interface types of the data interaction interfaces of the discrete simulation models corresponding to the multiple objects, the multiple groups of discrete simulation data are interacted between the discrete simulation models corresponding to the multiple objects through the data interaction interfaces;
closing the data interaction interface between the current time point and the next time point, wherein the next time point is the moment when the discrete simulation models corresponding to the objects perform simulation data interaction next time;
repeating the simulation process until the simulation of the discrete simulation models corresponding to the objects is finished, and obtaining the target simulation result.
7. The method according to claim 1, wherein the establishing discrete simulation models corresponding to the plurality of objects according to the object characteristics of the plurality of objects, respectively, includes:
establishing a plurality of first simulation models corresponding to the plurality of objects respectively based on object characteristics of the plurality of objects, wherein the plurality of first simulation models are used for simulating respective types of the plurality of objects and interaction relations among the objects respectively;
establishing a plurality of second simulation models respectively corresponding to the plurality of objects based on object characteristics of the plurality of objects and a machine learning algorithm, wherein the plurality of second simulation models are respectively used for simulating behaviors of the plurality of objects;
and establishing a plurality of discrete simulation models respectively corresponding to the plurality of objects according to the plurality of first simulation models and the plurality of second simulation models.
8. The method according to any one of claims 1 to 7, wherein the interacting simulation results of the discrete simulation models corresponding to the plurality of objects at the time point to obtain a target simulation result includes:
configuring the discrete simulation models corresponding to the objects into a plurality of hosts, wherein the hosts are in one-to-one correspondence with the discrete simulation models corresponding to the objects;
And respectively simulating the discrete simulation models corresponding to the plurality of objects in a plurality of hosts to obtain the target simulation result, wherein the plurality of hosts perform simulation data interaction through the discrete simulation models corresponding to the plurality of objects in the simulation process.
9. An apparatus for simulating an electric power market system model, comprising:
the first acquisition module is used for acquiring object characteristics of a plurality of objects in the electric power market system;
the building module is used for respectively building discrete simulation models corresponding to the objects according to the object characteristics of the objects, wherein the discrete simulation models corresponding to the objects respectively correspond to simulation time steps, and the simulation time steps represent simulation time spans of the corresponding discrete simulation models;
the determining module is used for determining the time points of interaction of the discrete simulation models corresponding to the objects based on the simulation time steps respectively corresponding to the discrete simulation models corresponding to the objects;
and the second acquisition module is used for interacting simulation results of the discrete simulation models corresponding to the objects at the time points to obtain target simulation results.
10. A non-volatile storage medium, characterized in that the non-volatile storage medium comprises a stored program, wherein the program, when run, controls a device in which the non-volatile storage medium is located to perform the simulation method of the power market system model according to any one of claims 1 to 8.
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