CN113222233B - Natural gas multi-body energy game analysis method and system - Google Patents
Natural gas multi-body energy game analysis method and system Download PDFInfo
- Publication number
- CN113222233B CN113222233B CN202110481570.7A CN202110481570A CN113222233B CN 113222233 B CN113222233 B CN 113222233B CN 202110481570 A CN202110481570 A CN 202110481570A CN 113222233 B CN113222233 B CN 113222233B
- Authority
- CN
- China
- Prior art keywords
- resource
- main body
- demand
- information
- price
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 title claims abstract description 126
- 239000003345 natural gas Substances 0.000 title claims abstract description 63
- 238000004458 analytical method Methods 0.000 title claims abstract description 42
- 238000000034 method Methods 0.000 claims abstract description 53
- 238000011156 evaluation Methods 0.000 claims abstract description 41
- 230000008569 process Effects 0.000 claims abstract description 27
- 230000008859 change Effects 0.000 claims abstract description 16
- 239000007789 gas Substances 0.000 claims description 68
- 238000005457 optimization Methods 0.000 claims description 15
- 238000013468 resource allocation Methods 0.000 claims description 13
- 230000008901 benefit Effects 0.000 claims description 9
- 230000001105 regulatory effect Effects 0.000 claims description 7
- 238000004519 manufacturing process Methods 0.000 claims description 5
- 238000006467 substitution reaction Methods 0.000 claims description 4
- 238000009826 distribution Methods 0.000 claims description 3
- 238000004088 simulation Methods 0.000 claims description 3
- 230000007613 environmental effect Effects 0.000 claims description 2
- 238000013178 mathematical model Methods 0.000 abstract description 2
- 238000011160 research Methods 0.000 description 7
- 230000006399 behavior Effects 0.000 description 5
- 230000004044 response Effects 0.000 description 3
- 230000007246 mechanism Effects 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000005094 computer simulation Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000013439 planning Methods 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 230000006641 stabilisation Effects 0.000 description 1
- 238000011105 stabilization Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computing arrangements using knowledge-based models
- G06N5/04—Inference or reasoning models
- G06N5/042—Backward inferencing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06315—Needs-based resource requirements planning or analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/067—Enterprise or organisation modelling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
- G06Q30/0202—Market predictions or forecasting for commercial activities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
- G06Q30/0206—Price or cost determination based on market factors
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Human Resources & Organizations (AREA)
- Development Economics (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Finance (AREA)
- Accounting & Taxation (AREA)
- General Physics & Mathematics (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Game Theory and Decision Science (AREA)
- Tourism & Hospitality (AREA)
- Educational Administration (AREA)
- Quality & Reliability (AREA)
- Data Mining & Analysis (AREA)
- Operations Research (AREA)
- Health & Medical Sciences (AREA)
- Artificial Intelligence (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Public Health (AREA)
- Computational Linguistics (AREA)
- Evolutionary Computation (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention provides a natural gas multi-body energy game analysis method and a system, wherein the method comprises the following steps: performing evaluation index analysis on each main body; determining a game relationship between the subjects according to the analysis result; and analyzing the game process among the main bodies and the conditions and influencing factors when the game process reaches an equilibrium state according to the game relationship. The invention can simulate the game relation and game state among the oligopolistic heads of the natural gas market, intuitively and accurately describe the resource quantity fluctuation state and the price adjustment strategy in the game process of the oligopolistic heads through the mathematical model, and further analyze the influence of external environment change on the game strategy of the natural gas energy main body.
Description
Technical Field
The invention belongs to the field of multi-body energy planning, and particularly relates to a natural gas multi-body energy game analysis method and system.
Background
The natural gas market in China is still in a monopoly competition stage, and different market structures can lead enterprises to adopt different competition behaviors, so that different market effects can be necessarily generated. The research on the market competition and game mechanism of the natural gas oligopolistic enterprises has stronger practical significance. At present, most scholars research on natural gas oligopolistic enterprises mainly based on static, complete information and single policy preconditions, and then complete information assumption cannot necessarily exist in reality, so that decisions of the scholars are performed in a limited rationality; meanwhile, due to the fact that the management layer judges the market situation, the production scale of enterprises, whether information is sufficiently symmetrical or not and other conditions, the enterprises often have different expectations, so that the natural gas oligopolistic enterprises actively participate in the market, an optimization and feasible strategy is formulated, and the maximization of self profit is achieved.
At present, research on energy main game in the natural gas market is mainly carried out on the premise of static and complete information and single strategy, game relation and state change among energy main game are difficult to fully reflect, and research results are too ideal.
Disclosure of Invention
Aiming at the problems, the invention provides the natural gas multi-body energy game analysis method and the system, which can simulate the game relation among natural gas energy bodies, analyze and obtain the conditions and influence factors when the whole system reaches an equilibrium state, and further research the influence of the self decision of enterprises on the whole market under different expected decision rules.
A natural gas multi-body energy game analysis method, the method comprising the steps of:
performing evaluation index analysis on each main body;
determining a game relationship between the subjects according to the analysis result;
And analyzing the game process among the main bodies and the conditions and influencing factors when the game process reaches an equilibrium state according to the game relationship.
Preferably, the multi-principal comprises a resource supply-side principal, a resource demand-side principal, a government or regulatory body, and a natural gas energy source substitution-side principal.
Preferably, the evaluation index of the resource supply end main body is evaluated from three aspects of sales volume, market share and benefit; evaluating the evaluation index of the main body of the resource demand end from the aspect of resource cost; the government or regulatory authorities are used to regulate market prices and gate prices.
Preferably, the main game relationship is: the resource supply end main body obtains the number of users, the gas consumption and the affordable price information, analyzes and processes the information through a price adjustment economic method, and transmits the updated information to the resource demand end main body; the resource demand end main body acquires updated user quantity, gas demand and affordable price information provided by the resource supply end main body, determines the gas demand and the resource provider by optimizing resource allocation, and transmits the information to the resource provider; the government and the supervision department control the price of the natural gas within a specified range and then feed back the price to the main body of the resource supply end and the main body of the resource demand end; wherein there is a competing relationship between the resource provider principals.
Preferably, the method for analyzing the game process among the subjects and the conditions and influencing factors when the equilibrium state is reached is as follows:
respectively initializing an environment variable, a resource demand end main body variable and a resource supply end main body variable;
the main body of the resource supply end obtains market information, and determines or updates a sales target according to the market information;
the main body of the resource supply end invokes a supplier optimization model to optimize a marketing strategy, if the price fluctuation range of all resource suppliers is smaller than or equal to a preset value a, the game state reaches an equilibrium state, analysis is terminated, and equilibrium state information is output; if the price change of the resource provider is larger than the preset value a, the resource supply end main body transmits the price, the resource quantity and the supply and demand coefficient information to the resource demand end main body;
After the resource demand end main body acquires the price, the resource quantity and the supply and demand coefficient information of each resource supply end main body, a user optimization model is called to optimize resource allocation, if the demand quantity variation amplitude of all the resource demand end main bodies is smaller than or equal to a preset value b, the game state reaches an equilibrium state, analysis is terminated, and equilibrium state information is output; if the change amplitude of the demand quantity of the resource demand end main body is larger than the preset value b, the resource demand end main body feeds back demand information to the market and the resource supply end main body;
the resource supply end main body acquires the demand information, the competitor information and the market information, and performs market evaluation in combination with a sales target;
and determining or updating a sales target according to the market evaluation result, and iterating the loop.
Preferably, the environmental variables include alternative energy prices, and network transport capacity constraints; the user main body variables comprise the number of users, the gas consumption demand and the price bearing capacity; the resource supply end main body variables comprise resource quantity and cost;
The preset value a is 3%, and the preset value b is 3%;
the demand information includes the demand for gas itself and the resource provider.
Preferably, the resource demand end main body comprises an urban gas company and a direct supply user; the urban gas company comprises an urban gas user group and single urban gas users, and the direct supply users comprise a direct supply user group and single direct supply users; the method is based on the following assumption:
The direct supply user group and the urban gas user group are divided according to cities, the upper limit of the natural gas resource quantity of each city is given, and the gas supply capacity of a pipe network company is simulated;
The demand of single city gas users is determined, the minimum unit city gas users are not simulated and modeled in the model, the gas usage rules of the city gas users are analyzed by using a probability theory and a numerical statistics method, the simulation and modeling are carried out on city gas companies and direct supply users in a scattered point distribution mode, and the natural gas demand of each user is set according to the data of the probability statistics;
After the price is adjusted, the resource supply end main body firstly transmits price information to the government, and after the government approves no problem, the price information is pushed to the market;
When evaluating the marketing condition, the main body of the resource supply end takes the ratio of the resource quantity to the demand quantity as a coefficient for evaluating the shortage degree of the resource supply, when the coefficient is smaller than 1, the supplier feeds back a signal with abundant resources to the market, and when the coefficient is larger than 1, the supplier feeds back a signal with shortage of the resources to the market;
The user proposes a consideration of the intent of the resource purchase: whether the price is acceptable, whether the production and operation can not replace energy sources, whether other surrounding users use natural gas or not, and whether the natural gas is used urgently or not;
the user proposes a consideration of the intent of contracting: whether the price is advantageous, whether it is below the average market price, whether there are other more cost effective resources, which resources are used by other users around, whether natural gas is used urgently.
Preferably, the system comprises the following modules:
the evaluation module is used for performing evaluation index analysis on each main body;
The determining module is used for determining game relations among the main bodies;
And the analysis module is used for analyzing the game process among the main bodies and the conditions and influencing factors when the game process reaches an equilibrium state.
Preferably, the multi-principal comprises a resource supply-side principal, a resource demand-side principal, a government or regulatory body, and a natural gas energy source substitution-side principal.
Preferably, the evaluation module specifically includes: evaluating the evaluation indexes of the resource supply end main body from three aspects of sales volume, market share and benefit; evaluating the evaluation index of the main body of the resource demand end from the aspect of resource cost; the government or the supervision department is used for supervising the market price and the gate price;
The determining module is configured to determine a game relationship between the main bodies specifically as follows: the resource supply end main body obtains the number of users, the gas consumption and the affordable price information, analyzes and processes the information through a price adjustment economic method, and transmits the updated information to the resource demand end main body; the resource demand end main body acquires updated user quantity, gas demand and affordable price information provided by the resource supply end main body, determines the gas demand and the resource provider by optimizing resource allocation, and transmits the information to the resource provider; the government and the supervision department control the price of the natural gas within a specified range and then feed back the price to the main body of the resource supply end and the main body of the resource demand end; wherein, the resource supply end main bodies have competition relation;
The analysis module is used for analyzing the conditions and influencing factors when the game process among the main bodies reaches an equilibrium state, and specifically comprises the following steps: respectively initializing an environment variable, a resource demand end main body variable and a resource supply end main body variable;
the main body of the resource supply end obtains market information, and determines or updates a sales target according to the market information;
the main body of the resource supply end invokes a supplier optimization model to optimize a marketing strategy, if the price fluctuation range of all resource suppliers is smaller than or equal to a preset value a, the game state reaches an equilibrium state, analysis is terminated, and equilibrium state information is output; if the price change of the resource provider is larger than the preset value a, the resource supply end main body transmits the price, the resource quantity and the supply and demand coefficient information to the resource demand end main body;
After the resource demand end main body acquires the price, the resource quantity and the supply and demand coefficient information of each resource supply end main body, a user optimization model is called to optimize resource allocation, if the demand quantity variation amplitude of all the resource demand end main bodies is smaller than or equal to a preset value b, the game state reaches an equilibrium state, analysis is terminated, and equilibrium state information is output; if the change amplitude of the demand quantity of the resource demand end main body is larger than the preset value b, the resource demand end main body feeds back demand information to the market and the resource supply end main body;
the resource supply end main body acquires the demand information, the competitor information and the market information, and performs market evaluation in combination with a sales target;
and determining or updating a sales target according to the market evaluation result, and iterating the loop.
The invention has the following beneficial effects: (1) The method comprises the steps of performing simulation modeling on the game relationship of the natural gas energy main body by applying factor graph theory for the first time, and further considering the influence of urban gas companies, direct supply users, supervision authorities and alternative energy sources on the game relationship on the basis of limited oligopolistic games; (2) The system dynamics theory is applied to the two dimensions of the whole and the individual to systematically analyze the energy game relationship: in the whole market level, the influence of the external environment on the game state of the market is fully considered, key influence factors are quantitatively analyzed, and a market dynamics response model is established; in the energy main body level, weight analysis is carried out on market state parameters and external environment influence factors, the influence of the market state parameters and the external environment influence factors on the energy main body is analyzed according to the influence degree and the response sensitivity, and an energy main body dynamic response model is established; (3) According to the characteristics of gas purchasing behaviors of users, the users are classified into two types of urban gas companies and direct supply users, the market reaction characteristics of each type of users are subjected to clustering analysis, and a differentiated model parameter database is established; (4) The energy game state is studied from two layers of a space dimension and a time dimension: in the space dimension, the influence of gas consumption behaviors between the user and surrounding users is considered, and the trending property and the popular psychology of the user are simulated; in the time dimension, the energy game process can be continuously performed, and when the game state reaches the Nash equilibrium condition, the Nash equilibrium state is broken through by the single main body parameter change, so that a new Nash equilibrium state point is searched again.
In summary, the invention can simulate the game relationship and game state among the oligopolistic of the natural gas market, intuitively and accurately describe the resource quantity fluctuation state and the price adjustment strategy in the game process of the oligopolistic through the mathematical model, and further analyze the influence of the external environment change on the game strategy of the natural gas energy main body. By analyzing the system dynamics characteristic of the oligopolistic gas market for realizing the decision-making goal, the method can provide technical support for enterprise decision making in the natural gas market in China. The technical scheme of the invention is the comprehensive application of a plurality of game relation theories, and comprises a plurality of game research theories such as behavior strategies, coulomb theorem, incomplete information games, main body communication mechanisms, perfect balance of sub-games, repeated games and the like, wherein the research results are more close to the actual energy main body game state, and each main body is a mixed strategy game carried out in the incomplete information state, so that the method is more in line with the actual situation and can better serve the behavior decision of the energy main body.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 shows a flow chart of a gaming relationship analysis method according to an embodiment of the invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Examples
A natural gas multi-principal energy gaming analysis method, the multi-principal comprising a resource supply-side principal, a resource demand-side principal, a government or regulatory body, and a natural gas energy replacement-side principal, the method comprising the steps of:
Performing evaluation index analysis on each main body; evaluating the evaluation indexes of the resource supply end main body from three aspects of sales volume, market share and benefit; evaluating the evaluation index of the main body of the resource demand end from the aspect of resource cost; the government or the supervision department is used for supervising the market price and the gate price;
determining a game relationship between the subjects according to the analysis result; the game relationship of each main body is as follows: the resource supply end main body obtains the number of users, the gas consumption and the affordable price information, analyzes and processes the information through a price adjustment economic method, and transmits the updated information to the resource demand end main body; the resource demand end main body acquires updated user quantity, gas demand and affordable price information provided by the resource supply end main body, determines the gas demand and the resource provider by optimizing resource allocation, and transmits the information to the resource provider; the government and the supervision department control the price of the natural gas within a specified range and then feed back the price to the main body of the resource supply end and the main body of the resource demand end; wherein, the resource supply end main bodies have competition relation;
analyzing the game process among the main bodies and the conditions and influencing factors when the game process reaches an equilibrium state according to the game relationship; the specific method is as shown in fig. 1:
Respectively initializing environment variables (including alternative energy price and pipe network conveying capacity constraint), resource demand end main variables (including user quantity, gas consumption demand quantity and price bearing capacity) and resource supply end main variables (including resource quantity, cost and the like);
the main body of the resource supply end obtains market information, and determines or updates a sales target according to the market information;
The main body of the resource supply end calls a supplier optimization model to optimize a marketing strategy, if the price fluctuation range of all resource suppliers is less than or equal to 3%, the game state reaches an equilibrium state, analysis is terminated, and equilibrium state information is output; if the price change of the resource provider is more than 3%, the resource supply end main body transmits the price, the resource quantity and the supply and demand coefficient information to the resource demand end main body;
After the resource demand end main body acquires the price, the resource quantity and the supply and demand coefficient information of each resource supply end main body, a user optimization model is called to optimize resource allocation, if the demand quantity variation amplitude of all the resource demand end main bodies is less than or equal to 3%, the game state reaches an equilibrium state, analysis is terminated, and equilibrium state information is output; if the change amplitude of the demand quantity of the resource demand end main body is more than 3%, the resource demand end main body feeds back demand information to the market and the resource supply end main body;
the resource supply end main body acquires the demand information (comprising the self gas consumption demand amount and the resource provider), the competitor information and the market information, and carries out market evaluation in combination with a sales target;
and determining or updating a sales target according to the market evaluation result, and iterating the loop.
Further, the resource demand end main body comprises an urban gas company and a direct supply user; the urban gas company comprises an urban gas user group and single urban gas users, and the direct supply users comprise a direct supply user group and single direct supply users; the method is based on the following assumption:
The direct supply user group and the urban gas user group are divided according to cities, the upper limit of the natural gas resource quantity of each city is given, and the gas supply capacity of a pipe network company is simulated;
The demand of single city gas users is determined, the minimum unit city gas users are not simulated and modeled in the model, the gas usage rules of the city gas users are analyzed by using a probability theory and a numerical statistics method, the simulation and modeling are carried out on city gas companies and direct supply users in a scattered point distribution mode, and the natural gas demand of each user is set according to the data of the probability statistics;
After the price is adjusted, the resource supply end main body firstly transmits price information to the government, and after the government approves no problem, the price information is pushed to the market;
When evaluating the marketing condition, the main body of the resource supply end takes the ratio of the resource quantity to the demand quantity as a coefficient for evaluating the shortage degree of the resource supply, when the coefficient is smaller than 1, the supplier feeds back a signal with abundant resources to the market, and when the coefficient is larger than 1, the supplier feeds back a signal with shortage of the resources to the market;
The user proposes a consideration of the intent of the resource purchase: whether the price is acceptable, whether the production and operation can not replace energy sources, whether other surrounding users use natural gas or not, and whether the natural gas is used urgently or not;
the user proposes a consideration of the intent of contracting: whether the price is advantageous, whether it is below the average market price, whether there are other more cost effective resources, which resources are used by other users around, whether natural gas is used urgently.
According to the method for analyzing the natural gas multi-main body game, the invention further provides a natural gas multi-main body energy game analysis system, wherein the multi-main body comprises a resource supply end main body, a resource demand end main body, a government or regulatory department and a natural gas energy substitution end main body, and the system comprises the following modules:
The evaluation module is used for performing evaluation index analysis on each main body; the evaluation indexes of the evaluation module are specifically as follows: evaluating the evaluation indexes of the resource supply end main body from three aspects of sales volume, market share and benefit; evaluating the evaluation index of the main body of the resource demand end from the aspect of resource cost; the government or the supervision department is used for supervising the market price and the gate price
The determining module is used for determining the game relation among the main bodies, and specifically comprises the following steps: the resource supply end main body obtains the number of users, the gas consumption and the affordable price information, analyzes and processes the information through a price adjustment economic method, and transmits the updated information to the resource demand end main body; the resource demand end main body acquires updated user quantity, gas demand and affordable price information provided by the resource supply end main body, determines the gas demand and the resource provider by optimizing resource allocation, and transmits the information to the resource provider; the government and the supervision department control the price of the natural gas within a specified range and then feed back the price to the main body of the resource supply end and the main body of the resource demand end; wherein, the resource supply end main bodies have competition relation;
the analysis module is used for analyzing conditions and influence factors when the game process among the main bodies reaches an equilibrium state, and specifically comprises the following steps: respectively initializing an environment variable, a resource demand end main body variable and a resource supply end main body variable;
the main body of the resource supply end obtains market information, and determines or updates a sales target according to the market information;
The main body of the resource supply end calls a supplier optimization model to optimize a marketing strategy, if the price fluctuation range of all resource suppliers is less than or equal to 3%, the game state reaches an equilibrium state, analysis is terminated, and equilibrium state information is output; if the price change of the resource provider is more than 3%, the resource supply end main body transmits the price, the resource quantity and the supply and demand coefficient information to the resource demand end main body;
After the resource demand end main body acquires the price, the resource quantity and the supply and demand coefficient information of each resource supply end main body, a user optimization model is called to optimize resource allocation, if the demand quantity variation amplitude of all the resource demand end main bodies is less than or equal to 3%, the game state reaches an equilibrium state, analysis is terminated, and equilibrium state information is output; if the change amplitude of the demand quantity of the resource demand end main body is more than 3%, the resource demand end main body feeds back demand information to the market and the resource supply end main body;
the resource supply end main body acquires the demand information, the competitor information and the market information, and performs market evaluation in combination with a sales target;
and determining or updating a sales target according to the market evaluation result, and iterating the loop.
In summary, in the market starting stage: at the resource supply end, the natural gas resource provider discloses resource information, including natural gas resource supply quantity and natural gas sales price; at the resource demand end, users generate natural gas resource demands according to the production and living demands of the users, and the gas supply information of resource suppliers obtained from the market is combined to select natural gas resources, so that the gas purchasing demands are provided for the designated resource suppliers.
In the market gaming stage: the method is characterized in that market price fluctuation is large, user demand fluctuation is obvious, and at a resource supply end, a natural gas resource provider obtains natural gas supply and demand information from the market, wherein the natural gas supply and demand information comprises the total demand of users, the types of the users, the average market price, the resource supply quantity and supply price of competitors. Then, overall evaluation is carried out on market supply and demand conditions, self-operating conditions, competitor competition strategies and the like, price and policy adjustment is carried out according to evaluation results, and updated resource information and policy information are disclosed to the market; at the resource demand end, the user calls a resource allocation optimization model according to the latest resource information and policy information acquired from the market, re-optimizes the gas purchasing demand, and proposes the gas purchasing demand to the designated resource provider. The process will iterate through the loop for a period of time to allow the market to compete sufficiently.
In the market stabilization phase: the characteristic of this stage is that market price fluctuation is small and user demand fluctuation is small. At the resource supply end, after the price and policy adjustment is carried out according to market information, the natural gas selling price is basically maintained unchanged or the fluctuation range is small by the natural gas resource provider; at the resource demand end, after a user invokes a resource configuration optimization model according to the natural gas resource supply information in the market, the gas purchasing demand is basically unchanged. The user initiates a subscription gas contract with the resource provider.
Although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (4)
1. A natural gas multi-body energy game analysis method, characterized in that the method comprises the following steps:
Performing evaluation index analysis on each main body; the main body comprises a resource supply end main body, a resource demand end main body, a government or regulatory body and a natural gas energy substitution end main body; evaluating the evaluation indexes of the resource supply end main body from three aspects of sales volume, market share and benefit; evaluating the evaluation index of the main body of the resource demand end from the aspect of resource cost; the government or the supervision department is used for supervising the market price and the gate price;
determining a game relationship between the subjects according to the analysis result; the game relationship of each main body is as follows: the resource supply end main body obtains the number of users, the gas consumption and the affordable price information, analyzes and processes the information through a price adjustment economic method, and transmits the updated information to the resource demand end main body; the resource demand end main body acquires updated user quantity, gas demand and affordable price information provided by the resource supply end main body, determines the gas demand and the resource provider by optimizing resource allocation, and transmits the information to the resource provider; the government and the supervision department control the price of the natural gas within a specified range and then feed back the price to the main body of the resource supply end and the main body of the resource demand end; wherein, the resource supply end main bodies have competition relation;
Analyzing the game process among the main bodies and the conditions and influencing factors when the game process reaches an equilibrium state according to the game relationship; the method for analyzing the game process among the main bodies and the conditions and influencing factors when the game process reaches an equilibrium state is as follows: respectively initializing an environment variable, a resource demand end main body variable and a resource supply end main body variable; the main body of the resource supply end obtains market information, and determines or updates a sales target according to the market information; the main body of the resource supply end invokes a supplier optimization model to optimize a marketing strategy, if the price fluctuation range of all resource suppliers is smaller than or equal to a preset value a, the game state reaches an equilibrium state, analysis is terminated, and equilibrium state information is output; if the price change of the resource provider is larger than the preset value a, the resource supply end main body transmits the price, the resource quantity and the supply and demand coefficient information to the resource demand end main body; after the resource demand end main body acquires the price, the resource quantity and the supply and demand coefficient information of each resource supply end main body, a user optimization model is called to optimize resource allocation, if the demand quantity variation amplitude of all the resource demand end main bodies is smaller than or equal to a preset value b, the game state reaches an equilibrium state, analysis is terminated, and equilibrium state information is output; if the change amplitude of the demand quantity of the resource demand end main body is larger than the preset value b, the resource demand end main body feeds back demand information to the market and the resource supply end main body; the resource supply end main body acquires the demand information, the competitor information and the market information, and performs market evaluation in combination with a sales target; and determining or updating a sales target according to the market evaluation result, and iterating the loop.
2. The natural gas multi-body energy game analysis method of claim 1, wherein the environmental variables include alternative energy prices, network transport capacity constraints; the main variables of the resource demand end comprise the number of users, the gas consumption demand and the price bearing capacity; the resource supply end main body variables comprise resource quantity and cost;
The preset value a is 3%, and the preset value b is 3%;
the demand information includes the demand for gas itself and the resource provider.
3. The natural gas multi-body energy game analysis method according to claim 1 or 2, wherein the resource demand end body comprises an urban gas company and a direct supply user; the urban gas company comprises an urban gas user group and single urban gas users, and the direct supply users comprise a direct supply user group and single direct supply users; the method is based on the following assumption:
The direct supply user group and the urban gas user group are divided according to cities, the upper limit of the natural gas resource quantity of each city is given, and the gas supply capacity of a pipe network company is simulated;
The demand of single city gas users is determined, the minimum unit city gas users are not simulated and modeled in the model, the gas usage rules of the city gas users are analyzed by using a probability theory and a numerical statistics method, the simulation and modeling are carried out on city gas companies and direct supply users in a scattered point distribution mode, and the natural gas demand of each user is set according to the data of the probability statistics;
After the price is adjusted, the resource supply end main body firstly transmits price information to the government, and after the government approves no problem, the price information is pushed to the market;
When evaluating the marketing condition, the main body of the resource supply end takes the ratio of the resource quantity to the demand quantity as a coefficient for evaluating the shortage degree of the resource supply, when the coefficient is smaller than 1, the supplier feeds back a signal with abundant resources to the market, and when the coefficient is larger than 1, the supplier feeds back a signal with shortage of the resources to the market;
The user proposes a consideration of the intent of the resource purchase: whether the price is acceptable, whether the production and operation can not replace energy sources, whether other surrounding users use natural gas or not, and whether the natural gas is used urgently or not;
the user proposes a consideration of the intent of contracting: whether the price is advantageous, whether it is below the average market price, whether there are other more cost effective resources, which resources are used by other users around, whether natural gas is used urgently.
4. A natural gas multi-body energy game analysis system, the system comprising the following modules:
The evaluation module is used for performing evaluation index analysis on each main body; each main body comprises a resource supply end main body, a resource demand end main body, a government or regulatory body and a natural gas energy source substitution end main body; the evaluation indexes of the evaluation module are specifically as follows: evaluating the evaluation indexes of the resource supply end main body from three aspects of sales volume, market share and benefit; evaluating the evaluation index of the main body of the resource demand end from the aspect of resource cost; the government or the supervision department is used for supervising the market price and the gate price;
The determining module is used for determining game relations among the main bodies; the method comprises the following steps: the resource supply end main body obtains the number of users, the gas consumption and the affordable price information, analyzes and processes the information through a price adjustment economic method, and transmits the updated information to the resource demand end main body; the resource demand end main body acquires updated user quantity, gas demand and affordable price information provided by the resource supply end main body, determines the gas demand and the resource provider by optimizing resource allocation, and transmits the information to the resource provider; the government and the supervision department control the price of the natural gas within a specified range and then feed back the price to the main body of the resource supply end and the main body of the resource demand end; wherein, the resource supply end main bodies have competition relation;
The analysis module is used for analyzing the game process among the main bodies and the conditions and influencing factors when the game process reaches an equilibrium state; the method comprises the following steps: respectively initializing an environment variable, a resource demand end main body variable and a resource supply end main body variable;
the main body of the resource supply end obtains market information, and determines or updates a sales target according to the market information;
the main body of the resource supply end invokes a supplier optimization model to optimize a marketing strategy, if the price fluctuation range of all resource suppliers is smaller than or equal to a preset value a, the game state reaches an equilibrium state, analysis is terminated, and equilibrium state information is output; if the price change of the resource provider is larger than the preset value a, the resource supply end main body transmits the price, the resource quantity and the supply and demand coefficient information to the resource demand end main body;
After the resource demand end main body acquires the price, the resource quantity and the supply and demand coefficient information of each resource supply end main body, a user optimization model is called to optimize resource allocation, if the demand quantity variation amplitude of all the resource demand end main bodies is smaller than or equal to a preset value b, the game state reaches an equilibrium state, analysis is terminated, and equilibrium state information is output; if the change amplitude of the demand quantity of the resource demand end main body is larger than the preset value b, the resource demand end main body feeds back demand information to the market and the resource supply end main body;
the resource supply end main body acquires the demand information, the competitor information and the market information, and performs market evaluation in combination with a sales target;
and determining or updating a sales target according to the market evaluation result, and iterating the loop.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110481570.7A CN113222233B (en) | 2021-04-30 | 2021-04-30 | Natural gas multi-body energy game analysis method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110481570.7A CN113222233B (en) | 2021-04-30 | 2021-04-30 | Natural gas multi-body energy game analysis method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113222233A CN113222233A (en) | 2021-08-06 |
| CN113222233B true CN113222233B (en) | 2024-05-07 |
Family
ID=77090462
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110481570.7A Active CN113222233B (en) | 2021-04-30 | 2021-04-30 | Natural gas multi-body energy game analysis method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113222233B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107172606A (en) * | 2017-06-29 | 2017-09-15 | 南京邮电大学 | A kind of distribution method of green energy resource joint spectrum shared in the wireless network |
| CN109034563A (en) * | 2018-07-09 | 2018-12-18 | 国家电网公司 | A kind of increment power distribution network source net lotus collaborative planning method of multi-agent Game |
| CN109286187A (en) * | 2018-10-19 | 2019-01-29 | 国网宁夏电力有限公司经济技术研究院 | A kind of microgrid towards multiagent balance of interest economic load dispatching method a few days ago |
| CN109919452A (en) * | 2019-02-15 | 2019-06-21 | 三峡大学 | A kind of electric power based on multi-agent Game-Gas Comprehensive energy resource system joint planing method |
| CN110210712A (en) * | 2019-05-05 | 2019-09-06 | 三峡大学 | It is a kind of to consider uncertain and multi-agent Game integrated energy system planing method |
| CN111062514A (en) * | 2019-11-14 | 2020-04-24 | 国网能源研究院有限公司 | Power system planning method and system |
-
2021
- 2021-04-30 CN CN202110481570.7A patent/CN113222233B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107172606A (en) * | 2017-06-29 | 2017-09-15 | 南京邮电大学 | A kind of distribution method of green energy resource joint spectrum shared in the wireless network |
| CN109034563A (en) * | 2018-07-09 | 2018-12-18 | 国家电网公司 | A kind of increment power distribution network source net lotus collaborative planning method of multi-agent Game |
| CN109286187A (en) * | 2018-10-19 | 2019-01-29 | 国网宁夏电力有限公司经济技术研究院 | A kind of microgrid towards multiagent balance of interest economic load dispatching method a few days ago |
| CN109919452A (en) * | 2019-02-15 | 2019-06-21 | 三峡大学 | A kind of electric power based on multi-agent Game-Gas Comprehensive energy resource system joint planing method |
| CN110210712A (en) * | 2019-05-05 | 2019-09-06 | 三峡大学 | It is a kind of to consider uncertain and multi-agent Game integrated energy system planing method |
| CN111062514A (en) * | 2019-11-14 | 2020-04-24 | 国网能源研究院有限公司 | Power system planning method and system |
Non-Patent Citations (1)
| Title |
|---|
| 基于多主体动态博弈的天然气定价模型研究;张培鑫;《中国优秀硕士学位论文全文数据库 工程科技Ⅰ辑》;第B019-10页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113222233A (en) | 2021-08-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Wang et al. | Deep reinforcement learning method for demand response management of interruptible load | |
| Chen et al. | An energy sharing game with generalized demand bidding: Model and properties | |
| CN112651770B (en) | Load declaration optimization method and system for power selling merchants in power spot market | |
| Wang et al. | Agent and system dynamics-based hybrid modeling and simulation for multilateral bidding in electricity market | |
| Guerci et al. | Agent-based modeling and simulation of competitive wholesale electricity markets | |
| Peng et al. | Multi-objective optimal strategy for generating and bidding in the power market | |
| CN113032995A (en) | Electric power market simulation optimization and operation method, system and simulation platform | |
| Chen et al. | Customized rebate pricing mechanism for virtual power plants using a hierarchical game and reinforcement learning approach | |
| CN116862551A (en) | New energy consumption price decision method considering user privacy protection | |
| CN108921425A (en) | A kind of method, system and the server of asset item classifcation of investment | |
| Fu et al. | Bike-sharing inventory management for market expansion | |
| Zhang et al. | Soft actor–critic algorithm featured residential demand response strategic bidding for load aggregators | |
| Jang et al. | Deep reinforcement learning with planning guardrails for building energy demand response | |
| Wang et al. | Multi-agent simulation for strategic bidding in electricity markets using reinforcement learning | |
| Liu et al. | A novel electricity load forecasting based on probabilistic least absolute shrinkage and selection operator-Quantile regression neural network | |
| CN114169916A (en) | Market member quotation strategy making method suitable for novel power system | |
| Jain et al. | A Multi-Agent based simulator for strategic bidding in day-ahead energy market | |
| CN113222233B (en) | Natural gas multi-body energy game analysis method and system | |
| Wang et al. | Multi-reservoir system operation theory and practice | |
| Huang et al. | Dynamic performance assessment system for Green tourism supply chain | |
| Zhao et al. | Design and application of genetic algorithm based on signal game and newsboy model for optimizing supply chain | |
| Yin et al. | An optimization method of product function configuration based on value analysis | |
| Lau et al. | A reinforcement learning algorithm developed to model GenCo strategic bidding behavior in multidimensional and continuous state and action spaces | |
| Sičaja et al. | Evaluation of load forecast model performance in Croatian DSO | |
| Xue et al. | Online Procurement and Inventory Technology Based on Cloud Computing System |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |