Electric energy substitution path determination method and device and nonvolatile storage medium

Abstract

The invention discloses an electric energy substitution path determination method and device and a nonvolatile storage medium. The method comprises the following steps: constructing a system dynamics model; setting initial values corresponding to a plurality of influence factors for the system dynamics model; on the basis of the system dynamics model, by adjusting the initial values corresponding to the multiple influence factors, the influence degrees of the multiple influence factors on multiple preset paths are predicted, and the influence degrees corresponding to the multiple paths are determined; based on the influence degrees corresponding to the plurality of paths, simulating the plurality of paths by adopting a multi-path simulation technology to obtain simulation results corresponding to the plurality of paths; based on the simulation results corresponding to the plurality of paths, determining carbon emissions corresponding to the plurality of paths; and selecting the path with the carbon emission meeting a preset condition in the plurality of paths as a target path. The method solves the technical problems that the current electric energy replacement path selection lacks systematic consideration, and economic benefits and environmental protection benefits are difficult to optimize at the same time.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of new energy, in particular to a method and device for determining a path of electric energy substitution and a nonvolatile storage medium. BACKGROUND

[0002] In the promotion and application field of electric energy substitution technology, currently, the performance and cost-effectiveness of the technology itself are mainly concerned, but there is a lack of systematic consideration in path selection, especially in optimizing economic benefits and environmental benefits. Traditional methods often focus on the analysis of a single factor, such as only considering the cost-effectiveness of the technology or only evaluating the direct effect of the policy, without fully considering the comprehensive influence of multiple factors such as policy, technological progress and market dynamics. There is a lack of prediction ability for the long-term trend of electric energy substitution technology promotion, and it is difficult to provide sufficient forward-looking guidance for urban electrification development planning. For example, it is difficult to accurately predict the promotion speed and range of electric energy substitution technology under different policies, technological progress and market environment.

[0003] In summary, there is a lack of systematic consideration in the selection of electric energy substitution technology promotion paths, and it is difficult to optimize economic benefits and environmental benefits at the same time.

[0004] In view of the above problems, no effective solution has been proposed so far. SUMMARY

[0005] The embodiments of the present application provide a method and device for determining a path of electric energy substitution and a nonvolatile storage medium to at least solve the technical problem that the current electric energy substitution path selection lacks systematic consideration and it is difficult to optimize economic benefits and environmental benefits at the same time.

[0006] According to an aspect of an embodiment of the present application, a method for determining a path of electric energy substitution is provided, comprising: constructing a system dynamics model; setting initial values corresponding to a plurality of influence factors for the system dynamics model, wherein the plurality of influence factors include time factors, technology factors and market factors; based on the system dynamics model, predicting the influence degree of the plurality of influence factors on a plurality of preset paths by adjusting the initial values corresponding to the plurality of influence factors, respectively, determining the influence degree corresponding to each of the plurality of paths, wherein the influence degree corresponding to any one of the plurality of paths includes the influence degree of the plurality of influence factors on the corresponding path; based on the influence degree corresponding to each of the plurality of paths, using a multi-path simulation technology to simulate the plurality of paths to obtain simulation results corresponding to each of the plurality of paths; based on the simulation results corresponding to each of the plurality of paths, determining the carbon emission amount corresponding to each of the plurality of paths; selecting a path with a carbon emission amount satisfying a preset condition from the plurality of paths as a target path.

[0007] Optionally, the system dynamics model is constructed, including: obtaining boundary conditions, wherein the boundary conditions include a running period of the model, an environmental boundary, and a running data boundary; determining a correlation between time factors, technical factors, and market factors; establishing an equation set, wherein the equation set includes a carbon emission calculation equation, an energy consumption calculation equation, and an energy consumption rate calculation equation; and determining the system dynamics model based on the correlation and the equation set.

[0008] Optionally, initial values of the plurality of influence factors are set for the system dynamics model, including: collecting current values of the plurality of influence factors; removing abnormal data in the current values of the plurality of influence factors to obtain target values of the plurality of influence factors; and determining the initial values of the plurality of influence factors based on the target values of the plurality of influence factors.

[0009] Optionally, based on the system dynamics model, the influence degrees of the plurality of influence factors on the plurality of paths are predicted by adjusting the initial values of the plurality of influence factors, and the influence degrees of the plurality of paths are determined, including: obtaining reference results of the plurality of paths; adjusting the initial values of the plurality of influence factors based on the system dynamics model to obtain a plurality of results of the plurality of paths; and determining the influence degrees of the plurality of paths based on the reference results of the plurality of paths and the plurality of results of the plurality of paths.

[0010] Optionally, based on the influence degrees of the plurality of paths, the plurality of paths are simulated using a multi-path simulation technology to obtain simulation results of the plurality of paths, including: establishing simulation scenarios of the plurality of paths based on the influence degrees of the plurality of paths; simulating the plurality of paths based on the simulation scenarios of the plurality of paths, collecting output data after simulation of the plurality of paths, and obtaining the simulation results of the plurality of paths.

[0011] Optionally, based on the simulation results of the plurality of paths, carbon emissions of the plurality of paths are determined, including: extracting carbon emission sequences of the plurality of paths based on the simulation results of the plurality of paths; and determining the carbon emissions of the plurality of paths based on the carbon emission sequences of the plurality of paths.

[0012] According to another aspect of the embodiments of the present application, there is also provided a path determination device for electric energy substitution, comprising: a construction module configured to construct a system dynamics model; a setting module configured to set initial values of a plurality of influence factors corresponding to the system dynamics model, wherein the plurality of influence factors comprise a time factor, a technology factor and a market factor; a prediction module configured to predict influence degrees of the plurality of influence factors on a plurality of preset paths by adjusting the initial values of the plurality of influence factors corresponding to the system dynamics model, and determine influence degrees of the plurality of paths corresponding to the plurality of influence factors, wherein the influence degree of any one path in the plurality of paths comprises influence degrees of the plurality of influence factors on the corresponding path; a simulation module configured to simulate the plurality of paths by using a multi-path simulation technology based on the influence degrees of the plurality of paths corresponding to the plurality of influence factors, and obtain simulation results of the plurality of paths corresponding to the plurality of influence factors; a determination module configured to determine carbon emission amounts of the plurality of paths corresponding to the plurality of influence factors based on the simulation results of the plurality of paths corresponding to the plurality of influence factors; and a selection module configured to select a path with a carbon emission amount satisfying a preset condition in the plurality of paths as a target path.

[0013] According to still another aspect of the embodiments of the present application, there is also provided a non-volatile storage medium comprising a stored program, wherein the non-volatile storage medium is configured to execute any one of the path determination methods for electric energy substitution when the program is run.

[0014] According to yet another aspect of the embodiments of the present application, there is also provided a computer device comprising a processor, wherein the processor is configured to execute any one of the path determination methods for electric energy substitution when a program is run.

[0015] According to still another aspect of the embodiments of the present application, there is also provided a computer program product comprising a computer program, wherein the computer program is configured to implement any one of the path determination methods for electric energy substitution when executed by a processor.

[0016] In the embodiment of the present application, the path determination method for electric energy replacement is adopted, a system dynamics model is constructed, initial values corresponding to a plurality of influence factors are set for the system dynamics model, wherein the plurality of influence factors include time factor, technical factor and market factor, the influence degree of the plurality of influence factors on the plurality of preset paths is predicted by adjusting the initial values corresponding to the plurality of influence factors based on the system dynamics model, the influence degree corresponding to each of the plurality of paths is determined, wherein the influence degree corresponding to any one of the plurality of paths includes the influence degree of the plurality of influence factors on the corresponding path, the plurality of paths are simulated by using the multi-path simulation technology based on the influence degree corresponding to each of the plurality of paths, the simulation results corresponding to each of the plurality of paths are obtained, the carbon emission of each of the plurality of paths is determined based on the simulation results corresponding to each of the plurality of paths, and the path with the carbon emission meeting the preset condition is selected as the target path, so that the purpose of selecting a suitable path by comprehensively considering multiple aspects is achieved, thereby realizing the technical effect of improving the path selection rate and effect, and further solving the technical problem that the current electric energy replacement path selection lacks systematic consideration and is difficult to simultaneously optimize economic benefit and environmental benefit. BRIEF DESCRIPTION OF DRAWINGS

[0017] The accompanying drawings, which are included to provide a further understanding of the present application and are incorporated in and constitute a part of this application, illustrate embodiments of the present application and serve to explain the present application. In the drawings:

[0018] Figure 1 Fig. 1 shows a hardware structure block diagram of a computer terminal for implementing the path determination method for electric energy replacement;

[0019] Figure 2 Fig. 2 is a flowchart of the path determination method for electric energy replacement according to the embodiment of the present application;

[0020] Figure 3 Fig. 3 is a structure block diagram of the path determination device for electric energy replacement according to the embodiment of the present application. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should fall within the scope of protection of the present application.

[0022] It should be noted that the terms "first", "second", and the like in the description and in the claims of the present application and the above-described accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a particular chronological or sequential order. It should be understood that the data thus used can be interchanged under appropriate circumstances so that the embodiments of the application described herein can be implemented in other than the order illustrated or described herein. Furthermore, the terms "comprise" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or apparatus that includes a list of steps or units is not necessarily limited to those steps or units that are clearly listed, but can include other steps or units that are not clearly listed or inherent to such processes, methods, products, or apparatuses.

[0023] According to an embodiment of the present application, a method embodiment of a method for determining a path for electric energy substitution is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown herein.

[0024] The method embodiment provided by the embodiment one of the present application can be executed in a mobile terminal, a computer terminal, or a similar computing device. Figure 1 A hardware structure block diagram of a computer terminal for implementing a method for determining a path for electric energy substitution is shown. As shown in Figure 1 , the computer terminal 10 can include one or more processors (the processor can include but is not limited to a microprocessor MCU or a programmable logic device FPGA processing device) (shown in 102a, 102b,..., 102n), a memory 104 for storing data. In addition, it can also include a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which can be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. Those skilled in the art can understand that Figure 1 The structure shown is only schematic, which does not limit the structure of the above-mentioned electronic device. For example, the computer terminal 10 can also include more or fewer components than those shown in Figure 1 , or have a different configuration than that shown in Figure 1 .

[0025] It should be noted that the one or more processors and / or other data processing circuitry described above can be referred to herein generally as "data processing circuitry". The data processing circuitry can be embodied in whole or in part as software, hardware, firmware, or any combination thereof. In addition, the data processing circuitry can be a single standalone processing module, or incorporated in whole or in part within any of the other elements of the computer terminal 10. As referred to in embodiments of the present application, the data processing circuitry acts as a processor to control, for example, the selection of the variable resistance terminal path in connection with the interface.

[0026] The memory 104 can be used to store software programs of application software and modules, such as program instructions / data storage means corresponding to the path determination method of electric energy substitution in embodiments of the present application. The processor executes the software programs and modules stored in the memory 104 to perform various functional applications and data processing, i.e. to implement the path determination method of electric energy substitution of the application program described above. The memory 104 can include a high-speed random access memory, and can also include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some examples, the memory 104 can further include a memory remotely arranged with respect to the processor, which can be connected to the computer terminal 10 through a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0027] The display can be, for example, a touch screen type liquid crystal display (LCD) that can enable a user to interact with the user interface of the computer terminal 10.

[0028] Figure 2 is a flowchart of the path determination method of electric energy substitution provided according to embodiments of the present application, as shown in Figure 2 The method comprises the following steps:

[0029] Step S202, constructing a system dynamics model.

[0030] In this step, the scope and boundaries of the model can be determined first, including which variables and processes should be included in the model and which can be ignored. Information about the behavior of the system, the relationship between variables and historical data is collected, the causal chain is established, and the system flow diagram is determined. Understand the direct and indirect relationships between variables and how they dynamically influence each other over time. The causal relationship diagram between variables can be constructed using arrows and loop structures to show the feedback mechanisms within the system. According to the system flow diagram, mathematical equations describing the behavior of the system are set, including differential equations or difference equations. The equations can reflect the dynamic relationship between variables and how they are affected by external factors.

[0031] Building a system dynamics model can provide insights into how a system responds to internal and external changes, offering solutions to complex problems. In practice, multiple iterations and adjustments can be made until the model accurately reflects the true behavior of the system.

[0032] In step S204, initial values corresponding to each of the plurality of influence factors are set for the system dynamics model, wherein the plurality of influence factors include a time factor, a technology factor, and a market factor.

[0033] In this step, initial values of the plurality of influence factors (including time factor, technology factor, and market factor) are set for the system dynamics model. The time factor generally includes the starting point of the model, the simulation time length, and the time step. A time point with sufficient historical data can be selected as the starting point of the model, which helps to effectively fit and verify the model. The simulation time length can be set as the total time required for the model to run, which should be based on the time scale of the system dynamics you want to study, such as several years or even decades. Define the time increment of the model in each iteration. For fast-changing systems, the step size can be set smaller; for slow-changing systems, a larger step size can be used. The technology factor can include technology maturity, technology update rate, technology efficiency, technology cost, etc. The technology maturity can set the maturity level of the current technology, which can be expressed in percentage or index. The technology update rate is the speed at which new technologies are adopted, which can be quantified by the average update period or the annual update proportion. Technology efficiency refers to the efficiency of technology in converting resources or performing tasks, which may affect energy consumption, productivity, or service quality. Technology cost includes the cost of technology research and development, deployment, and maintenance, as well as the cost changes that may occur with technology progress. Market factors include demand, supply, price, competition, etc. Market demand can be set as the demand level for electricity replacement technology in the initial period, which can be based on historical sales data or market research and prediction results. Market supply defines the availability of electricity replacement technology on the market, considering production capacity, inventory, and distribution network. Relevant data can be collected from historical records, industry reports, market surveys, and expert interviews. Use statistical methods or expert opinions to estimate those parameters that cannot be directly measured. Check whether the set initial values are reasonable and consistent with reality, avoiding setting extreme or impossible values.

[0034] In system dynamics modeling, setting the correct initial values is crucial for the reliability and predictive ability of the model. Therefore, it is recommended to fully consider historical trends, industry standards, and expert opinions when setting these values to ensure that the model accurately reflects the dynamic characteristics of the system.

[0035] Step S206, based on the system dynamics model, by adjusting the initial value of each of the plurality of influence factors, the influence degree of the plurality of influence factors on the plurality of preset paths is predicted, and the influence degree corresponding to each of the plurality of paths is determined, wherein the influence degree corresponding to any one path in the plurality of paths includes the influence degree of each of the plurality of influence factors on the corresponding path.

[0036] In this step, based on the system dynamics model, the influence degree of the plurality of influence factors on the preset paths is predicted by adjusting the initial value of each of the plurality of influence factors. The plurality of preset paths in the model can be determined, and each path represents the evolution path of the system under different decisions or external conditions. Specific scenarios are designed for each path, including time factors, technical factors, market factors, etc., to ensure that each scenario has unique variable settings. For each path, multiple simulations are run, and the initial value of the influence factor is adjusted each time to explore the behavior of the system under different conditions. Observe how changes in influence factors change the results of the path, and identify which factors have a significant impact on the path. Use statistical methods to quantify the influence degree of each influence factor on the path results, such as by calculating the percentage of index changes or using sensitivity analysis. Compare the influence of different factors under different paths to identify which factors play a key role in a particular path.

[0037] Sensitivity analysis is a key tool for identifying which factors have the greatest impact on system performance, helping decision-makers prioritize resource allocation. Through system dynamics modeling, a deep understanding of complex systems can be achieved, and future states under different conditions can be predicted, providing strong support for strategy development and planning.

[0038] Step S208, based on the influence degree corresponding to each of the plurality of paths, a multi-path simulation technique is used to simulate the plurality of paths, and simulation results corresponding to each of the plurality of paths are obtained.

[0039] In this step, independent simulation is run for each path, keeping other conditions unchanged except for path-specific influence factors. In each simulation, reasonable parameter variability is introduced to simulate real-world uncertainty, which can be achieved through Monte Carlo simulation and other methods. Key output data after simulation of each path is recorded, including but not limited to economic benefits, technical efficiency, market acceptance, and environmental impact.

[0040] The simulation results of different paths can be compared to identify the path that performs best in meeting specific goals such as reducing costs, improving efficiency, or reducing environmental footprint. Based on the comparative analysis, adjust the model parameters or path settings to optimize the decision to achieve better results. According to the results of the comparative analysis, modify the model or path settings to more accurately reflect the actual situation and decision-making intentions.

[0041] Step S210, based on the simulation results of each of the multiple paths, determine the carbon emissions of each of the multiple paths.

[0042] In this step, based on the simulation results of each of the multiple paths, the carbon emissions of each of the multiple paths can be determined using standardized carbon emission calculation methods such as Life Cycle Assessment (LCA), carbon footprint calculation or specific industry carbon emission standards. For each path, the energy consumption, technology use and market dynamic data in the model output are applied to calculate the carbon emissions of the entire path.

[0043] The total carbon emissions of each path are summarized, the carbon emission trends of different paths are analyzed, and the factors that significantly affect carbon emission reduction (such as energy efficiency improvement, clean energy replacement, policy support, etc.) are identified. By comparing the carbon emissions of all paths, the path with the lowest carbon emissions under the condition of meeting other objectives (such as economic benefits, technical feasibility) is determined. Considering long-term goals, the sustainability of the path is evaluated, and whether the path can continue to reduce carbon emissions under changing market and policy conditions.

[0044] Step S212, select the path with carbon emissions meeting the preset condition as the target path.

[0045] In this step, all paths can be sorted by carbon emissions from low to high. Paths with carbon emissions lower than or equal to the preset condition are selected as preliminary "green" or low-carbon path candidates. The selected paths are analyzed in depth, considering not only carbon emission indicators but also economic benefits, social benefits and technical feasibility. Multi-index decision analysis methods (such as AHP, fuzzy comprehensive evaluation, etc.) can be used to score the paths that meet the conditions and determine the final best low-carbon path.

[0046] The above steps can greatly improve the selection efficiency of the path to replace electric energy, and screen out the development path that best meets the environmental protection requirements, while taking into account economic benefits and social development goals.

[0047] As an optional embodiment, the system dynamics model is constructed, including: obtaining boundary conditions, wherein the boundary conditions include the running period of the model, the environmental boundary and the running data boundary; determining the correlation between time factors, technology factors and market factors; establishing an equation set, wherein the equation set includes a carbon emission calculation equation, an energy consumption calculation equation and an energy consumption rate calculation equation; based on the correlation and the equation set, determine the system dynamics model.

[0048] Optionally, the boundary conditions are the foundational framework for the model run, including the model run duration, environmental boundaries, and operational data boundaries. Define the start and end times of the model simulation, as well as the time step. Set the environmental conditions for the model run, such as energy prices, policies and regulations, market supply and demand, etc., which should remain constant or change according to predefined rules during the simulation process of the model. Determine the data range involved in the model, including the start and end time of historical data, the update frequency of data, and the time span of predicted data. Analyze how time affects the development and adoption of technology, such as the improvement of technology maturity over time and the decrease of technology cost over time. Explore how technological progress affects market supply and demand, consumer preferences, and product pricing, and how market feedback in turn affects technological development. Understand how market dynamics (such as demand growth, competitive situation) are affected by environmental boundaries (such as policy restrictions, resource constraints), and how environmental boundaries shape market behavior. After determining these relationships, a system of equations describing the system dynamics can be established, including:

[0049] Carbon emission calculation equation: This equation is used to calculate the total carbon emissions in the system, usually based on energy consumption, carbon emission factors, and possible carbon sink effects.

[0050] Energy consumption calculation equation: Defines the dynamic changes in energy consumption in the system, which may involve energy demand, supply, efficiency, and consumption patterns.

[0051] Energy consumption rate calculation equation: Describes the change of energy consumption rate over time, technological progress and market behavior, which can be used to predict the growth rate of future energy demand.

[0052] Then build the causal relationship and system flow diagram, write the differential equation or difference equation describing the dynamic behavior of the system. Integrate all equations and causal relationships into a system dynamics model, test whether the model can accurately reflect the dynamic characteristics of the system, including historical data fitting and future prediction accuracy test.

[0053] Finally, the system dynamics model should fully reflect the complex interactions between time, technology, market factors and carbon emissions, providing data-based insights and strategic recommendations for decision-makers.

[0054] As an optional embodiment, set the initial value of each corresponding influence factor in the system dynamics model, including: collecting the current value of each corresponding influence factor; eliminating abnormal data in the current value of each corresponding influence factor to obtain the target value of each corresponding influence factor; determining the initial value of each corresponding influence factor based on the target value of each corresponding influence factor.

[0055] Optionally, data can be collected from multiple reliable sources to ensure that all influencing factors are covered, including but not limited to technical parameters, market dynamics, policy environment, and environmental factors. Recent data should be selected, and for long-term running models, a data updating mechanism should be set to ensure that model inputs always reflect the latest situation. Statistical methods such as box plots, Z-scores, or IQR (Interquartile Range) can be used to identify and mark outliers in the data set. Then, remove abnormal data, check the consistency and integrity of the data, avoid missing values or inconsistent dimensions, and ensure the availability of the data. It is necessary to ensure that the collected data sources are reliable, and strict data cleaning is carried out to prevent false data from distorting the model.

[0056] Through these steps, high-quality data can be collected and prepared to provide a solid input basis for system dynamics models, thus more accurately predicting and evaluating system behavior under different factors.

[0057] As an optional embodiment, based on the system dynamics model, by adjusting the initial values of each of the plurality of influencing factors, the influence degree of the plurality of influencing factors on the plurality of preset paths is predicted, and the influence degree corresponding to each of the plurality of paths is determined, comprising: obtaining the reference result corresponding to each of the plurality of paths; based on the system dynamics model, adjusting the initial value corresponding to each of the plurality of influencing factors to obtain a plurality of results corresponding to each of the plurality of paths; based on the reference result corresponding to each of the plurality of paths and the plurality of results corresponding to each of the plurality of paths, the influence degree corresponding to each of the plurality of paths is determined.

[0058] Optionally, the current values of the influencing factors collected (after data cleaning and outlier removal) are used as the initial values of the model, ensuring that the model reflects the current state. In the case of keeping all initial values of influencing factors unchanged, the model is run to obtain the reference results under each path. These results will serve as a reference point for subsequent analysis. A series of change schemes are designed for each influencing factor, such as increasing, decreasing, or changing the settings of certain parameters, to explore their impact on the results of different paths. Each influencing factor can also be adjusted individually, or multiple factors can be adjusted simultaneously to form different scenarios. Based on the adjusted influencing factors, the model is run multiple times, with one or a group of factors adjusted each time, and a plurality of results under different paths are collected. Compare the adjusted results under each path with the reference results to observe the differences. For each adjustment, calculate the percentage change or other quantitative indicators of the results to represent the influence degree of the change in the influencing factors on the results. According to the quantitative results of the influence degree, the influencing factors are sorted to identify the top few factors that have the greatest impact on the path results.

[0059] As an optional embodiment, based on the influence degree corresponding to each of the plurality of paths, a multi-path simulation technology is used to simulate the plurality of paths to obtain simulation results corresponding to each of the plurality of paths, including: based on the influence degree corresponding to each of the plurality of paths, establishing a simulation scenario corresponding to each of the plurality of paths; based on the simulation scenario corresponding to each of the plurality of paths, simulating the plurality of paths, collecting output data after simulation of each of the plurality of paths, and obtaining simulation results corresponding to each of the plurality of paths.

[0060] Optionally, one or more simulation scenarios are designed for each path according to the influence degree. Each scenario should reflect different hypothetical conditions when the path is implemented, such as best, average or worst case. For each simulation scenario, adjust the parameters in the model according to the scenario setting, such as policy strength, technology progress rate, market growth rate, etc. Ensure that the initial conditions of the model are consistent at the beginning of each simulation scenario. Run the model independently for each simulation scenario of each path to ensure that the conditions and parameters of each simulation accurately reflect the scenario setting. During the simulation process, record the key data output by the model, including but not limited to carbon emissions, energy consumption, economic benefit indicators, etc. The simulation results of each path can be summarized and compared to identify the impact of the path and scenario on system behavior under different scenarios.

[0061] Based on the analysis of the results of the previous round of simulation, adjust the model parameters or scenario settings to more accurately reflect the real world situation or the needs of the decision maker. Repeat the above steps until a stable and satisfactory simulation result is obtained, which can provide strong support for decision making.

[0062] Through the above steps, an effective system dynamics model can be established and run to provide strong support for the analysis and decision making of complex systems. The simulation results of each path will help decision makers understand the long-term impact of different strategies, so as to make the best choice in multi-objective optimization.

[0063] As an optional embodiment, based on the simulation results corresponding to each of the plurality of paths, the carbon emissions corresponding to each of the plurality of paths are determined, including: based on the simulation results corresponding to each of the plurality of paths, extracting carbon emission sequences corresponding to each of the plurality of paths; based on the carbon emission sequences corresponding to each of the plurality of paths, determining the carbon emissions corresponding to each of the plurality of paths.

[0064] Optionally, after the system dynamics model is run, the carbon emission related data is parsed from the model output. This typically includes the carbon emission data at each time step, as well as other relevant environmental and economic indicators. The parsed carbon emission data is arranged in chronological order to form the carbon emission sequence for each path. The sequence should include all carbon emissions within the model run period, ensuring data continuity and completeness. For each path, the cumulative carbon emissions within the entire model run period is calculated. This can be obtained by summing the carbon emissions at each time step in the carbon emission sequence. Additionally, the average carbon emissions for each path can be calculated, which is typically helpful in understanding the overall carbon emission characteristics of the path. The average carbon emissions can be obtained by dividing the cumulative carbon emissions by the number of time steps. The peak time point of carbon emissions and its corresponding carbon emissions in each path are identified, which is crucial for assessing the difficulty of carbon emission control in the short term. The carbon emission trend of each path is analyzed to identify whether the carbon emissions present an increasing, decreasing, or fluctuating trend over time, which helps to assess the effectiveness of long-term carbon emission management. The carbon emissions of all paths can be compared to identify the path with the lowest carbon emissions or the best emission reduction effect. The paths can also be evaluated according to the degree of improvement in carbon emission trends.

[0065] Through the above steps, the carbon emissions of different paths can be systematically evaluated and compared, ensuring that the complex interactions of multiple factors are considered in the evaluation process, which can improve the targeting and success probability of the strategy.

[0066] It should be noted that, for the foregoing method embodiments, in order to simply describe, they are all expressed as a series of action combinations, but those skilled in the art should know that the present application is not limited by the order of the described actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the present application.

[0067] Through the above description of the embodiments, those skilled in the art can clearly understand that the path determination method of electric energy replacement according to the above embodiments can be realized by means of software and the necessary general hardware platform, of course, it can also be realized by hardware, but in many cases the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a plurality of instructions for causing an end device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present application.

[0068] According to the embodiment of the present application, the electric energy alternative path determination device for implementing the above-mentioned electric energy alternative path determination method is also provided, Figure 3 is a structural block diagram of the electric energy alternative path determination device provided by the embodiment of the present application, as shown in the figure, the electric energy alternative path determination device comprises a construction module 302, a setting module 304, a prediction module 306, a simulation module 308, a determination module 310 and a selection module 312, and the following will explain the electric energy alternative path determination device. Figure 3

[0069] The construction module 302 is used for constructing a system dynamics model.

[0070] The setting module 304 is connected with the construction module 302, and is used for setting initial values corresponding to a plurality of influence factors respectively for the system dynamics model, wherein the plurality of influence factors comprises time factor, technical factor and market factor.

[0071] The prediction module 306 is connected with the setting module 304, and is used for predicting influence degrees of the plurality of influence factors on a plurality of preset paths by adjusting the initial values corresponding to the plurality of influence factors respectively based on the system dynamics model, and determining influence degrees corresponding to the plurality of paths respectively, wherein the influence degree corresponding to any one path in the plurality of paths comprises influence degrees of the plurality of influence factors on the corresponding path respectively.

[0072] The simulation module 308 is connected with the prediction module 306, and is used for simulating the plurality of paths by using multi-path simulation technology based on the influence degrees corresponding to the plurality of paths respectively, and obtaining simulation results corresponding to the plurality of paths respectively.

[0073] The determination module 310 is connected with the simulation module 308, and is used for determining carbon emission amounts corresponding to the plurality of paths respectively based on the simulation results corresponding to the plurality of paths respectively.

[0074] The selection module 312 is connected with the determination module 310, and is used for selecting a path with a carbon emission amount satisfying a preset condition as a target path from the plurality of paths.

[0075] It should be noted that the above-mentioned construction module 302, setting module 304, prediction module 306, simulation module 308, determination module 310 and selection module 312 correspond to steps S202 to S212 in the embodiment, and the plurality of modules have the same instances and application scenarios as the corresponding steps, but are not limited to the above-mentioned disclosed contents. It should be noted that the above-mentioned modules as a part of the device can run in the computer terminal 10 provided by the embodiment.

[0076] ​Embodiments of the present application can provide a computer device. Optionally, in the embodiments, the computer device can be located in at least one of a plurality of network devices of a computer network. The computer device comprises a memory and a processor.

[0077] The memory can be configured to store software programs and modules, such as program instructions / modules of the path determination method and device for electric energy replacement according to embodiments of the present application. The processor can execute various functions and data processing by running the software programs and modules stored in the memory, i.e., implement the path determination method for electric energy replacement. The memory can include a high-speed random access memory, and can further include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some examples, the memory can further include remote memories arranged remotely relative to the processor, which can be connected to the computer terminal through a network. Examples of the network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0078] The processor can call information and applications stored in the memory through the transmission device to perform the following steps: constructing a system dynamics model; setting initial values corresponding to a plurality of influence factors for the system dynamics model, wherein the plurality of influence factors include a time factor, a technology factor, and a market factor; based on the system dynamics model, predicting the influence degree of the plurality of influence factors on a plurality of preset paths by adjusting the initial values corresponding to the plurality of influence factors, respectively, determining the influence degree corresponding to each of the plurality of paths, wherein the influence degree corresponding to any one of the plurality of paths includes the influence degree of the plurality of influence factors on the corresponding path, respectively; based on the influence degree corresponding to each of the plurality of paths, simulating the plurality of paths by using a multi-path simulation technology to obtain simulation results corresponding to each of the plurality of paths, respectively; based on the simulation results corresponding to each of the plurality of paths, respectively, determining carbon emissions corresponding to each of the plurality of paths, respectively; and selecting a path with carbon emissions satisfying a preset condition from the plurality of paths as a target path.

[0079] Optionally, the processor can further execute program codes of the following steps: constructing the system dynamics model, comprising: obtaining boundary conditions, wherein the boundary conditions include a running period of the model, an environmental boundary, and a running data boundary; determining the correlation between the time factor, the technology factor, and the market factor; establishing an equation set, wherein the equation set includes a carbon emission calculation equation, an energy consumption calculation equation, and an energy consumption rate calculation equation; and determining the system dynamics model based on the correlation and the equation set.

[0080] Optionally, the processor can further execute program codes of the following steps: setting initial values of the plurality of influence factors in the system dynamics model, including: collecting current values of the plurality of influence factors; removing abnormal data in the current values of the plurality of influence factors to obtain target values of the plurality of influence factors; and determining the initial values of the plurality of influence factors based on the target values of the plurality of influence factors.

[0081] Optionally, the processor can further execute program codes of the following steps: predicting the influence degree of the plurality of influence factors on the plurality of paths based on the system dynamics model by adjusting the initial values of the plurality of influence factors, and determining the influence degree of the plurality of paths, including: obtaining reference results of the plurality of paths; adjusting the initial values of the plurality of influence factors based on the system dynamics model to obtain a plurality of results of the plurality of paths; and determining the influence degree of the plurality of paths based on the reference results of the plurality of paths and the plurality of results of the plurality of paths.

[0082] Optionally, the processor can further execute program codes of the following steps: simulating the plurality of paths based on the influence degree of the plurality of paths by using a multi-path simulation technology to obtain simulation results of the plurality of paths, including: establishing simulation scenarios of the plurality of paths based on the influence degree of the plurality of paths; and simulating the plurality of paths based on the simulation scenarios of the plurality of paths, collecting output data of the plurality of paths after simulation, and obtaining the simulation results of the plurality of paths.

[0083] Optionally, the processor can further execute program codes of the following steps: determining carbon emissions of the plurality of paths based on the simulation results of the plurality of paths, including: extracting carbon emission sequences of the plurality of paths based on the simulation results of the plurality of paths; and determining the carbon emissions of the plurality of paths based on the carbon emission sequences of the plurality of paths.

[0084] The embodiment of the present application provides a method for determining a path of electric energy replacement, a system dynamics model is constructed, initial values corresponding to a plurality of influence factors are set for the system dynamics model, wherein the plurality of influence factors include time factors, technical factors and market factors, the influence degrees of the plurality of influence factors on a plurality of preset paths are predicted by adjusting the initial values corresponding to the plurality of influence factors based on the system dynamics model, the influence degrees corresponding to the plurality of paths are determined, wherein the influence degree corresponding to any one path in the plurality of paths includes the influence degrees of the plurality of influence factors on the corresponding path, the plurality of paths are simulated by using a multi-path simulation technology based on the influence degrees corresponding to the plurality of paths, and simulation results corresponding to the plurality of paths are obtained, the carbon emission amounts corresponding to the plurality of paths are determined based on the simulation results corresponding to the plurality of paths, and a path with a carbon emission amount meeting a preset condition is selected as a target path, so that the purpose of selecting a suitable path by comprehensively considering multiple aspects is achieved, the technical effects of improving the path selection rate and the effect are achieved, and the technical problem that the current electric energy replacement path selection lacks systematic consideration and is difficult to simultaneously optimize economic benefits and environmental protection benefits is solved.

[0085] Those skilled in the art can understand that all or part of the steps in the above-mentioned various methods of the embodiment can be completed by instructing the hardware related to the terminal device through a program, and the program can be stored in a nonvolatile storage medium, and the storage medium can include a flash disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0086] The embodiment of the present application further provides a nonvolatile storage medium.

[0087] Optionally, in the embodiment, the nonvolatile storage medium can be located in any one of computer terminals in a computer terminal group in a computer network, or in any one of mobile terminals in a mobile terminal group.

[0088] Optionally, in the embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: constructing a system dynamics model; setting initial values of a plurality of influence factors corresponding to the system dynamics model, wherein the plurality of influence factors include a time factor, a technology factor, and a market factor; predicting, based on the system dynamics model, influence degrees of the plurality of influence factors on a plurality of preset paths by adjusting the initial values of the plurality of influence factors, and determining influence degrees of the plurality of paths, wherein the influence degree of any one path in the plurality of paths includes influence degrees of the plurality of influence factors on the corresponding path; simulating, based on the influence degrees of the plurality of paths, the plurality of paths by using a multi-path simulation technology to obtain simulation results of the plurality of paths; determining carbon emission amounts of the plurality of paths based on the simulation results of the plurality of paths; and selecting a path with a carbon emission amount satisfying a preset condition as a target path.

[0089] Optionally, in the embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: constructing a system dynamics model, including: obtaining boundary conditions, wherein the boundary conditions include a running period of the model, an environmental boundary, and a running data boundary; determining a correlation relationship among the time factor, the technology factor, and the market factor; and establishing an equation set, wherein the equation set includes a carbon emission amount calculation equation, an energy consumption amount calculation equation, and an energy consumption rate calculation equation; and determining the system dynamics model based on the correlation relationship and the equation set.

[0090] Optionally, in the embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: setting initial values of a plurality of influence factors corresponding to the system dynamics model, including: collecting current values of the plurality of influence factors; removing abnormal data in the current values of the plurality of influence factors to obtain target values of the plurality of influence factors; and determining the initial values of the plurality of influence factors based on the target values of the plurality of influence factors.

[0091] Optionally, in the embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: predicting, based on the system dynamics model, influence degrees of the plurality of influence factors on a plurality of preset paths by adjusting the initial values of the plurality of influence factors, and determining influence degrees of the plurality of paths, including: obtaining reference results of the plurality of paths; adjusting the initial values of the plurality of influence factors based on the system dynamics model to obtain a plurality of results of the plurality of paths; and determining the influence degrees of the plurality of paths based on the reference results of the plurality of paths and the plurality of results of the plurality of paths.

[0092] Optionally, in the embodiment, the nonvolatile storage medium is configured to store program code for performing the following steps: based on the influence degree of each of the plurality of paths, simulating the plurality of paths by using a multi-path simulation technology to obtain simulation results corresponding to each of the plurality of paths, including: based on the influence degree of each of the plurality of paths, establishing a simulation scenario corresponding to each of the plurality of paths; and based on the simulation scenario corresponding to each of the plurality of paths, simulating the plurality of paths, collecting output data after simulation of each of the plurality of paths, and obtaining simulation results corresponding to each of the plurality of paths.

[0093] Optionally, in the embodiment, the nonvolatile storage medium is configured to store program code for performing the following steps: based on the simulation results corresponding to each of the plurality of paths, determining the carbon emission amount corresponding to each of the plurality of paths, including: based on the simulation results corresponding to each of the plurality of paths, extracting a carbon emission sequence corresponding to each of the plurality of paths; and based on the carbon emission sequence corresponding to each of the plurality of paths, determining the carbon emission amount corresponding to each of the plurality of paths.

[0094] The embodiment of the present application also provides a computer program product, including a computer program, and optionally, when the computer program is executed by a processor, the computer program can realize the following steps: constructing a system dynamics model; setting initial values of a plurality of influence factors corresponding to each of the plurality of influence factors for the system dynamics model, wherein the plurality of influence factors include a time factor, a technology factor and a market factor; based on the system dynamics model, predicting the influence degree of the plurality of influence factors on a plurality of preset paths by adjusting the initial values of the plurality of influence factors corresponding to each of the plurality of influence factors, and determining the influence degree of each of the plurality of paths, wherein the influence degree of any one path in the plurality of paths includes the influence degree of each of the plurality of influence factors on the corresponding path; based on the influence degree of each of the plurality of paths, simulating the plurality of paths by using a multi-path simulation technology to obtain simulation results corresponding to each of the plurality of paths; based on the simulation results corresponding to each of the plurality of paths, determining the carbon emission amount corresponding to each of the plurality of paths; and selecting a path with a carbon emission amount satisfying a preset condition in the plurality of paths as a target path.

[0095] The above-mentioned serial numbers of the embodiments of the present application are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0096] In the above-mentioned embodiments of the present application, the description of each embodiment has its own emphasis, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0097] In several embodiments provided in the present application, it should be understood that the disclosed technology can be implemented by other means. Among them, the above-mentioned device embodiments are only schematic, for example, the division of the units can be a logical function division, and actual implementation can have another division mode, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed each other can be through some interface, indirect coupling or communication connection between units or modules, which can be electrical or other forms.

[0098] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or they can be distributed to multiple units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0099] In addition, each functional unit in each embodiment of the present application can be integrated into a processing unit, or each unit can exist physically, or two or more units can be integrated into one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0100] The integrated unit, if realized in the form of a software functional unit and sold or used as an independent product, can be stored in a non-volatile storage medium. Based on this understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0101] The above is only the preferred embodiment of the present application. It should be pointed out that for ordinary skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, and these improvements and refinements should be considered as the protection scope of the present application.

Claims

1. A method for determining the path of electricity substitution, characterized in that, include: Construct a system dynamics model; The system dynamics model is given initial values ​​for each of the multiple influencing factors, including time factors, technical factors, and market factors. Based on the system dynamics model, by adjusting the initial values ​​of the multiple influencing factors, the degree of influence of the multiple influencing factors on the multiple preset paths is predicted, and the degree of influence of each of the multiple paths is determined. The degree of influence of any path among the multiple paths includes the degree of influence of the multiple influencing factors on the corresponding path. Based on the degree of influence of each of the multiple paths, multi-path simulation technology is used to simulate the multiple paths and obtain the simulation results corresponding to each of the multiple paths. Based on the simulation results corresponding to each of the multiple paths, the carbon emissions corresponding to each of the multiple paths are determined. The path whose carbon emissions meet the preset conditions among the multiple paths is selected as the target path.

2. The method according to claim 1, characterized in that, The construction of the system dynamics model includes: Obtain boundary conditions, wherein the boundary conditions include the model's runtime, environmental boundaries, and runtime data boundaries; Determine the relationship between the time factor, the technological factor, and the market factor; Establish a set of equations, which includes equations for calculating carbon emissions, energy consumption, and energy consumption rate. Based on the aforementioned correlation and the aforementioned set of equations, the system dynamics model is determined.

3. The method according to claim 1, characterized in that, The step of setting initial values ​​for multiple influencing factors for the system dynamics model includes: Collect the current values ​​corresponding to each of the multiple influencing factors; By removing outliers from the current values ​​of each of the multiple influencing factors, the target values ​​of each of the multiple influencing factors are obtained. Based on the target values ​​corresponding to each of the multiple influencing factors, the initial values ​​corresponding to each of the multiple influencing factors are determined.

4. The method according to claim 1, characterized in that, The process of predicting the degree of influence of the multiple influencing factors on multiple preset paths by adjusting the initial values ​​of each of the multiple influencing factors based on the system dynamics model, and determining the degree of influence of each of the multiple paths, includes: Obtain the benchmark results corresponding to each of the multiple paths; Based on the system dynamics model, the initial values ​​of the multiple influencing factors are adjusted to obtain multiple results corresponding to the multiple paths. Based on the baseline results corresponding to each of the multiple paths and the multiple results corresponding to each of the multiple paths, the degree of influence corresponding to each of the multiple paths is determined.

5. The method according to claim 1, characterized in that, Based on the respective impact levels of the multiple paths, multi-path simulation technology is used to simulate the multiple paths, obtaining simulation results for each of the multiple paths, including: Based on the degree of influence of each of the multiple paths, simulation scenarios corresponding to each of the multiple paths are established. Based on the simulation scenarios corresponding to each of the multiple paths, simulations are performed on the multiple paths, and the output data after the simulation runs of each of the multiple paths are collected to obtain the simulation results corresponding to each of the multiple paths.

6. The method according to claim 1, characterized in that, The determination of the carbon emissions corresponding to each of the multiple paths based on the simulation results of each path includes: Based on the simulation results corresponding to each of the multiple paths, the carbon emission sequences corresponding to each of the multiple paths are extracted; Based on the carbon emission sequences corresponding to each of the multiple paths, the carbon emission amount corresponding to each of the multiple paths is determined.

7. A path determination device for electricity substitution, characterized in that, include: Modules are used to build system dynamics models; The setting module is used to set initial values ​​for multiple influencing factors for the system dynamics model, wherein the multiple influencing factors include time factors, technical factors and market factors; The prediction module is used to predict the degree of influence of the multiple influencing factors on multiple preset paths by adjusting the initial values ​​of each of the multiple influencing factors based on the system dynamics model, and to determine the degree of influence of each of the multiple paths. The degree of influence of any path among the multiple paths includes the degree of influence of each of the multiple influencing factors on the corresponding path. The simulation module is used to simulate the multiple paths based on the degree of influence of each path, using multi-path simulation technology, and obtain the simulation results corresponding to each of the multiple paths. The determination module is used to determine the carbon emissions corresponding to each of the multiple paths based on the simulation results corresponding to each of the multiple paths. The selection module is used to select the path whose carbon emissions meet preset conditions from the multiple paths as the target path.

8. A non-volatile storage medium, characterized in that, The non-volatile storage medium includes a stored program, wherein, when the program is executed, it controls the device containing the non-volatile storage medium to perform the power substitution path determination method according to any one of claims 1 to 6.

9. A computer device, characterized in that, include: Memory and processor The memory stores computer programs; The processor is configured to execute a computer program stored in the memory, wherein when the computer program is executed, the processor performs the path determination method for electrical energy substitution as described in any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the path determination method for electrical energy substitution as described in any one of claims 1 to 6.

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