CN111680420A - Simulation system dynamics model for industrial policy influence and implementation method thereof - Google Patents
Simulation system dynamics model for industrial policy influence and implementation method thereof Download PDFInfo
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Abstract
The invention discloses a simulation system dynamics model influenced by an industrial policy and an implementation method thereof, which are characterized in that based on a parallel management method of average fuel consumption and new energy automobile integral of passenger vehicle enterprises (a double integral industrial policy for short) issued by the Ministry of industry and belief, system dynamics modeling is respectively carried out on six modules (the productivity, the productivity utilization rate, the total output, the total research and development investment and the total profit and loss of new energy automobiles and fuel oil automobiles), each index data for policy operation is obtained, the index data is imported into a model for system dynamics simulation and analysis, the fact that the government adopts abnormally strict key index control at the initial stage of policy implementation is clear, the yield of the old technology can be limited to a greater extent or the new technology can be promoted to be put into production, the stepwise gradually strict technical performance indexes are set, and the government can help to realize the inhibition of the old technology by setting the target performance indexes, and the government can be, The mechanism underlying the industry policy supported by new technology.
Description
Technical Field
The invention relates to the technical field of industrial policy simulation systems, in particular to a dynamic model of a simulation system influenced by an industrial policy and an implementation method thereof.
Background
The use of the clean energy automobile has great significance for improving the domestic ecological environment, particularly the air quality. However, at present, the development of new energy automobiles in China has the problems of insufficient control of core technologies and the like, and particularly, the phenomena of excessive closure of basic technologies and poor quality and quality performance of new energy automobiles are particularly prominent, but the management strategy and the operation problems of traditional fuel oil and new energy technologies of domestic automobile enterprises are behind the phenomena.
According to the new energy industry planning, in the first stage of development of the new energy automobile industry, namely 2008-2010, most policy tools are used in the marketization stage of an innovative value chain, mainly including regulations, control and financial finance; 2011-2015 in the second stage of industry development, policy tools are mainly distributed at both research and development and market, and the two-stage national level has released about 50 policies to be implemented, but the direct promotion of the policy tools to the industry is still very limited. Whether the industrial policy tool can directly influence the management of the enterprise on the new and old automobile technologies and the actual operation decisions such as capacity, yield and the like are one of the keys for solving the current industrial development problems. In 2017, the Ministry of industry and Ministry of industry released and implemented the policy of parallel management of average fuel consumption of passenger vehicle enterprises and new energy automobile integral (called 'double integral' for short), and the industrial policy tool has the policy guidance and punishment restriction of old technology efficiency improvement and yield limitation and new technology yield increase and efficiency improvement by using the energy efficiency characteristics of integral quantification technology and setting a target value, and has universal applicability in multiple fields of innovation technology adoption, energy conservation and emission reduction, resource problem solution and the like.
The invention content is as follows:
the invention provides a dynamic model of a simulation system influenced by an industrial policy and an implementation method thereof, which are used for solving the defects of the prior art.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a dynamic model of a simulation system influenced by an industrial policy and an implementation method thereof comprise the following steps:
step 1, firstly, by using a vensim software, respectively analyzing the yield, the productivity utilization rate, the total yield, the total research and development investment and the total profit and loss of a new energy automobile and a fuel automobile to increase auxiliary variables and constants (including fuel consumption integral, fuel consumption actual values and the like), obtaining a technical operation submodule and a technical research and development submodule related to the auxiliary variables, and an industrial policy influence traditional fuel automobile technical management cause-and-effect loop diagram, and feeding back the diagram to a previous display module.
And 2, aiming at two services of a fuel automobile and a new energy automobile commonly owned by an automobile enterprise, based on causal loop analysis of a technical operation submodule and a technical research and development submodule under the influence of an integral policy tool, a system dynamics model of 'influence of a production policy on technical management and operation of the automobile enterprise' is constructed, a key function is established, and the key of function definition is how the policy influences the technical management and operation of the automobile enterprise.
And 3, acquiring index data for policy operation, setting parameters, taking the annual report data of the Jili automobile in 2017 as parameter standards by the model, and taking the values of the productivity, the productivity utilization rate, the total output, the integral actual value, the integral standard reaching value, the integral proportion requirement of the new energy automobile and the integral of the new energy automobile in unit automobile type.
And 4, carrying out simulation analysis on the influence of the industrial policy to obtain two situations of high and low market demands of the fuel automobile, namely research and development investment of the fuel automobile under different demand situations, an actual value of average fuel consumption, an integral of average fuel consumption under different demand situations, and capacity utilization rate of the fuel automobile under different demand situations.
And 5, setting two different learning effect conditions aiming at the research and development investment of the fuel consumption, representing the research and development capability difference characteristics among enterprises, and finally obtaining the average fuel consumption actual value and the average fuel consumption integral under different learning effect conditions.
Further, S1 is to establish horizontal variables, auxiliary variables and constants for simulation and analysis, and the simulator can establish a plurality of variables and cause-effect loop analysis by predicting the result, so as to obtain more accurate policy suggestions.
Further, S4 considers the preference of the domestic market for fuel automobiles and the growth process of the brand sales of private automobiles, and the fuel automobile market demand of the model-set simulated object gradually increases from 150 ten thousand per year.
Furthermore, the simulator can obtain the influence conditions of the industrial policies under different parameters by comparing a plurality of groups of simulation results and detection results.
Further, the simulation result can be saved and downloaded by the simulator for comparison.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the dynamic model of the simulation system influenced by the industrial policy and the implementation method thereof, a plurality of sub-items related to the industrial policy are taken as analysis targets, and the existing data are combined, so that the model is more practical, the error is smaller, and the test result is more accurate.
2. By using the system dynamics model, the newly added variables and the deleted variables are very flexible, the simulated result displays images of all the variables, a simulator can modify data according to the simulated images, policy simulation under different conditions is carried out, and a more reasonable result is selected as a decision reference.
3. The system dynamics model is adopted to carry out policy analysis on the capacity, the capacity utilization rate, the total output, the total research and development investment and the total profit and loss of the new energy automobile and the fuel oil automobile respectively, and the system is favorable for the government to make a more reasonable industrial policy according to the development practice.
Drawings
FIG. 1 is a block diagram of a policy framework for the double-point industry
FIG. 2 is a diagram of a causal relationship analysis of technical operation sub-modules
FIG. 3 is a diagram of a causal relationship analysis of technology development sub-modules
FIG. 4 is a causal circuit diagram of the technical management of a traditional fuel automobile influenced by policy
FIG. 5 is a high-low two kinds of situation diagrams of market demands of fuel automobiles
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Some terms of art designed in this embodiment are explained below.
System dynamics: the method is a cross-disciplinary research method suitable for recognizing and analyzing dynamic complex systems, describes and analyzes the behavior of a time-varying system by designing a stable information feedback structure, and discusses relevant strategies on the basis of simulation and optimization.
The system comprises the following steps: a complex of interacting units.
And (3) feedback: the relationship between the output and input of the same unit or the same sub-block in the system.
The horizontal variable: the accumulation state of the representative model is mainly composed of five parts, namely: input rate, output rate, streamlines, variable names, and equation codes.
Auxiliary variables: the auxiliary level variable performs a complete feedback loop.
A cause and effect circuit diagram: a closed loop diagram formed by connecting two or more causal relationships qualitatively describes the causal relationships between variables in the system.
A dynamic model of a simulation system influenced by an industrial policy and an implementation method thereof comprise the following steps:
step 1, firstly, by using a vensim software, respectively analyzing the yield, the productivity utilization rate, the total yield, the total research and development investment and the total profit and loss of a new energy automobile and a fuel automobile to increase auxiliary variables and constants (including fuel consumption integral, fuel consumption actual values and the like), obtaining a technical operation submodule and a technical research and development submodule related to the auxiliary variables, and an industrial policy influence traditional fuel automobile technical management cause-and-effect loop diagram, and feeding back the diagram to a previous display module.
And 2, aiming at two services of a fuel automobile and a new energy automobile commonly owned by an automobile enterprise, based on causal loop analysis of a technical operation submodule and a technical research and development submodule under the influence of an integral policy tool, a system dynamics model of 'influence of a production policy on technical management and operation of the automobile enterprise' is constructed, a key function is established, and the key of function definition is how the policy influences the technical management and operation of the automobile enterprise.
And 3, acquiring index data for policy operation, setting parameters, taking the annual report data of the Jili automobile in 2017 as parameter standards by the model, and taking the values of the productivity, the productivity utilization rate, the total output, the integral actual value, the integral standard reaching value, the integral proportion requirement of the new energy automobile and the integral of the new energy automobile in unit automobile type.
And 4, carrying out simulation analysis on the influence of the industrial policy to obtain two situations of high and low market demands of the fuel automobile, namely research and development investment of the fuel automobile under different demand situations, an actual value of average fuel consumption, an integral of average fuel consumption under different demand situations, and capacity utilization rate of the fuel automobile under different demand situations.
And 5, setting two different learning effect conditions aiming at the research and development investment of the fuel consumption, representing the research and development capability difference characteristics among enterprises, and finally obtaining the average fuel consumption actual value and the average fuel consumption integral under different learning effect conditions.
The method takes a plurality of sub-items related to an industrial policy as analysis targets, combines the existing data, enables the model to be more practical, has smaller errors and more accurate test results, uses a system dynamics model, is flexible in adding and deleting variables, displays each variable by the simulated result in an image, enables a simulator to modify data according to the simulated image, carries out policy simulation under different conditions, selects reasonable results as decision reference, carries out policy analysis on the capacity, capacity utilization rate, total output, total research and development investment and total shortage of the new energy automobile and the fuel automobile respectively, and is beneficial to the government to make a more reasonable industrial policy according to the development practice.
As shown in fig. 1, the double integral industry policy framework diagram relates to 8 indexes, namely, an average fuel consumption target value, an average fuel consumption scalar value, a passenger vehicle production capacity or import quantity new energy vehicle integral scalar value, an average fuel consumption integral, a new energy vehicle integral, an average fuel consumption actual value, a new energy vehicle production or import quantity and a new energy vehicle integral actual value.
As shown in fig. 2, the causal relationship analysis diagram of the technical operation submodule relates to 7 indexes of fuel automobile productivity, fuel automobile yield, fuel consumption integral, operation decision, market demand, capacity utilization rate and business profit.
As shown in fig. 3, the causal relationship analysis chart of the technology development submodule relates to 5 indexes of an actual fuel consumption value, an integral fuel consumption, a fuel automobile yield, business profit and development investment.
As shown in fig. 4, the cause and effect circuit diagram for the technical management of the traditional fuel automobile influenced by policies relates to 10 indexes of fuel automobile productivity, fuel automobile yield, fuel consumption integral, operation decision, capacity utilization rate, research and development investment, actual value of fuel consumption, business profit, market demand and fuel consumption standard value.
The system dynamics model is further described below.
System dynamics includes two important concepts, storage volume and flow rate, i.e., a level variable, which may represent the condition of a system variable at a particular time, and a rate variable, which represents how fast a level variable changes, which may be changed by the rate variable.
The method comprises the following specific steps:
1. determining a level variable, setting an initial value for the level variable, and determining the outflow and inflow of the level variable.
2. And determining the relation among each horizontal variable, each rate variable, each auxiliary variable and each constant, and expressing the relation by a formula.
3. Time units, e.g., year, month, day, are determined.
4. And determining a time interval and simulating the starting and stopping time of the operation.
The system dynamics modeling flow is described in detail below:
take a dynamic model of the system that industrial policies affect the technical management and operation of automobile enterprises as an example:
as shown in fig. 5, the steps are as follows:
1. establishing a system dynamics model
The method comprises the steps of finding out horizontal variables, speed variables, auxiliary variables and constants of a fuel automobile and a new energy automobile respectively, enabling the model to be composed of 4 types of variables, namely inventory, speed variables, auxiliary variables and constants, and enabling the quantity of the variables to be 10 inventory, 14 speed variables, 22 auxiliary variables and 5 constants respectively, and establishing the model.
2. The key function definition, as shown in table 1:
TABLE 1
The variables are related as follows:
fuel automobile development investment coefficient is basic coefficient (1+ fuel automobile integral factor adjusting value is 10%)
Average actual fuel consumption value ═ basic consumption value ([ total investment/basic investment ] of fuel automobile research & development (-0.15))
New energy automobile integral standard value (fuel automobile output) new energy automobile integral proportion requirement
New energy automobile model unit integral
3. The parameters were set as shown in tables 2 and 3:
TABLE 2
TABLE 3
4. System dynamics simulation and analysis
Taking the year as a step length, simulating 60 time units in a simulation period, and simulating the dynamic model of the technical management system of the automobile enterprise influenced by the industrial policy by adopting Vensim PLE software at the initial time of 0. On the basis of the utilization of the capacity and yield reality data of the simulated enterprise object, by changing the initial storage value such as the capacity utilization rate and the like, the constant values such as the research and development investment basic coefficient and the like in a reasonable range and the sensitivity test of the functional relation between the total automobile output and the profit and loss of a unit, the behavior trends of key variables such as the automobile capacity, the average fuel consumption and the like are consistent, and the model constructed by the method has the advantages of robustness and significance of a simulation result.
It will be apparent to those skilled in the art that various changes in scope can be made in accordance with the above teachings and concepts related to the industrial policy and all such changes are intended to be included within the scope of the present invention as defined in the appended claims.
Claims (5)
1. A dynamic model of a simulation system influenced by an industrial policy and an implementation method thereof are characterized by comprising the following steps:
s1, firstly, using vensim software to respectively analyze the yield, the yield utilization rate, the total yield, the total research and development investment and the total profit and loss of the new energy automobile and the fuel automobile to increase auxiliary variables and constants (including fuel consumption integral, fuel consumption actual values and the like), so as to obtain a technical operation submodule and a technical research and development submodule related to the auxiliary variables, and an industrial policy influence cause-and-effect loop diagram of the traditional fuel automobile technical management, and feed the diagram back to the previous display module;
s2, aiming at two services of a fuel automobile and a new energy automobile commonly operated by an automobile enterprise, based on causal loop analysis of a technical operation submodule and a technical research and development submodule under the influence of an integral policy tool, a system dynamics model of 'technical management and operation of the automobile enterprise are influenced by an industrial policy' is constructed, a key function is established, and the key of function definition is how the policy influences the technical management and operation of the automobile enterprise;
s3, acquiring index data for policy operation, setting parameters, and taking the productivity, the productivity utilization rate, the total output, the integral actual value, the integral standard reaching value, the integral proportion requirement of the new energy automobile and the integral value of the new energy automobile unit automobile model according to the annual report data of the Jili automobile in 2017 as parameter standards by the model;
s4, carrying out simulation analysis on the influence of the industrial policy to obtain two situations of high and low market demands of the fuel automobile, namely research and development investment of the fuel automobile under different demand situations, an actual value of average fuel consumption, an average fuel consumption integral under different demand situations, and capacity utilization rate of the fuel automobile under different demand situations;
s5, setting two different learning effect conditions aiming at the research and development investment of fuel consumption, representing the research and development capability difference characteristics among enterprises, and finally obtaining the average fuel consumption actual value and the average fuel consumption integral under different learning effect conditions.
2. The industrial policy impact simulation system dynamics model and the implementation method thereof as claimed in claim 1, wherein S1 is performed by establishing horizontal variables, auxiliary variables and constants for simulation and analysis, and the simulator can establish a plurality of causal loop analyses by creating a plurality of variables through prediction results to obtain more accurate policy recommendations.
3. The industrial policy impact simulation system dynamics model and the implementation method thereof as claimed in claim 2, wherein S4 considers the preference of domestic market for fuel-powered vehicles and the increase process of civil vehicle brand sales, and the fuel-powered vehicle market demand of the model setting object is gradually increased from 150 thousands/year.
4. The industrial policy impact simulation system dynamics model and the implementation method thereof as claimed in claim 1, wherein the simulator can obtain the industrial policy impact under different parameters by comparing the multiple sets of simulation results and detection results.
5. The industrial policy impact simulation system dynamics model and implementation method thereof as claimed in claim 1, wherein simulation results can be saved and downloaded by other simulators for comparison.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113034053A (en) * | 2021-04-29 | 2021-06-25 | 福建引征科技有限公司 | Modeling method based on matching and evaluation between policy information and service object |
| CN113569323A (en) * | 2021-08-03 | 2021-10-29 | 清华大学 | Dynamic modeling method for territorial space planning system for realizing planning scene simulation |
| CN113609706A (en) * | 2021-08-25 | 2021-11-05 | 东北大学秦皇岛分校 | Simulation system dynamics model for influence of regulation and control policy on tourism industry and implementation method thereof |
| CN114626570A (en) * | 2021-12-07 | 2022-06-14 | 国网天津市电力公司 | Power carbon emission trajectory analysis method and device |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113034053A (en) * | 2021-04-29 | 2021-06-25 | 福建引征科技有限公司 | Modeling method based on matching and evaluation between policy information and service object |
| CN113569323A (en) * | 2021-08-03 | 2021-10-29 | 清华大学 | Dynamic modeling method for territorial space planning system for realizing planning scene simulation |
| CN113609706A (en) * | 2021-08-25 | 2021-11-05 | 东北大学秦皇岛分校 | Simulation system dynamics model for influence of regulation and control policy on tourism industry and implementation method thereof |
| CN114626570A (en) * | 2021-12-07 | 2022-06-14 | 国网天津市电力公司 | Power carbon emission trajectory analysis method and device |
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Application publication date: 20200918 |