Method, system and storage medium for collaboration between power, telecommunications and natural gas companies

Abstract

The present invention discloses a method, system and storage medium for collaboration between electric power, telecommunication and natural gas companies, and belongs to the technical field of communication network optimization in an electric-gas integrated energy system, including: constructing an optimization model between electric power companies and telecommunication operators; constructing an optimization model between electric power company agents and natural gas companies. An iterative algorithm is used to solve the optimization model between electric power companies and telecommunication operators, and the optimization model between electric power company agents and natural gas companies, to obtain a global optimal optimization result. The optimization results include: the payment plan formulated by the electric power company to the telecommunication operator, the transmission power ratio allocated by the telecommunication operator to the relay service, the demand ratio of the gas-to-electricity service of the electric power company, and the retail price of the gas-to-electricity service of the natural gas company. The present invention can reduce the costs of each electric power company while increasing the profits of telecommunication operators and natural gas companies.

Description

Technical Field

[0001] The present invention belongs to the technical field of communication network optimization in an electric-gas integrated energy system, and in particular to a method, system and storage medium for collaboration among electric power, telecommunications and natural gas companies. Background Art

[0002] Energy is the basic guarantee for the survival and development of human society. With the rapid development of the global economy, energy shortage and environmental pollution have become global problems. How to ensure the continuous supply of energy and reduce environmental pollution while maintaining stable economic growth has become a key issue of common concern to all countries. Building a clean, low-carbon, safe and efficient modern energy system is the goal and requirement of the energy revolution. Against this background, many scholars at home and abroad have carried out research on the electric-gas integrated energy system. Its essence is to interconnect energy resources and use their complementary advantages to solve the energy crisis, so as to no longer pursue the production, transportation and supply of a single energy source.

[0003] In the user-side communication network of the smart grid, a large amount of load data is forwarded through the data aggregation unit (DAU) at the same time, and the transmission channel will have problems such as network congestion, path loss and electromagnetic interference. In the process of wireless transmission, due to the loss of data packets in information transmission, the load forecasting accuracy of the power company will be affected, and the cost of the power company will also increase with the increase of load forecast deviation. With the rapid development of information and communication technology, advanced communication technologies such as cooperative relay technology and cognitive radio technology can be used in communication networks to increase the information transmission rate and thus reduce data packet loss. In addition, in the research on information transmission in the user-side communication network of the smart grid, some scholars have proposed that real-time two-way communication between power companies and users can be achieved by purchasing relay services from telecom operators, so as to reduce the cost of power companies, compensate for channel fading, and improve data transmission rate and reliability.

[0004] Under the direct load control mode, power companies purchase AGC services from the ancillary service market based on load tracking deviations. The high unit price of AGC services will increase the cost burden of power companies. my country's abundant natural gas resources provide sufficient gas sources for natural gas power generation, and the power generation characteristics of natural gas can effectively alleviate the pressure of energy conservation and emission reduction and meet the peak load requirements of the power grid. Benefiting from the advantages of low pollutant emissions, high energy conversion efficiency, low construction investment and operation and maintenance costs, the comprehensive cost of natural gas power generation is lower than that of coal-fired power. In addition, the cost of gas power generation can be channeled through electricity prices, so that natural gas power generation companies can retain a certain marginal profit, creating good conditions for the development and application of gas power generation. Therefore, it is of vital significance to use the gas-to-power technology and AGC regulation services of natural gas companies to jointly make up for the load tracking deviation on the demand side. Summary of the invention

[0005] Based on this, the present invention provides a collaborative method, system and storage medium between power, telecommunications and natural gas companies, and collaboratively optimizes the payment plans of each power company, the transmission power ratio allocated to relay services by telecommunications operators, the demand ratio of gas-to-electricity services of power companies, and the retail price of gas-to-electricity services of natural gas companies, so as to provide a feasible technical solution for relay-based collaborative transmission in the communication network of the electric-gas integrated energy system and gas-to-electricity energy transactions between natural gas companies and power companies, and ultimately achieve the goal of reducing the costs of each power company while increasing the profits of telecommunications operators and natural gas companies.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0007] Collaborative approaches between electricity, telecommunications and gas companies, including:

[0008] Obtain the first initial parameter, the second initial parameter and the third initial parameter; wherein the first initial parameter includes the reserved power cost of the power company, the fitting coefficient of the load tracking deviation, the transmission bandwidth of the DAU, the probability of correct transmission of information from the gateway to the user, the rate at which information reaches the DAU, the channel gain from the DAU to the gateway and from the relay to the gateway, the transmission power of the DAU, the retail price of the AGC service, and the total power of the base station of the telecom operator; the second initial parameter includes the total bandwidth of the telecom operator, the base price of the telecom service of the telecom operator, the number of DAUs in the base station, and the channel gain from the relay to the control center; the third initial parameter includes the total natural gas reserves of the natural gas company, the ratio coefficient of the natural gas retail price of the natural gas company to the retail price of the gas-to-electricity service, and the heat rate curve coefficient in engineering practice;

[0009] Based on the first initial parameter, the payment scheme of each power company, the transmission power ratio allocated by the telecom operator to the relay service, the demand ratio of the gas-to-electricity service of the power company, and the retail price of the gas-to-electricity service of the natural gas company, with the goal of minimizing the cost of each power company, the payment scheme of each power company and the demand ratio of the gas-to-electricity service of the power company are respectively decision variables, and the respective first optimization target model and the third optimization target model are established;

[0010] According to the second initial parameter, the payment scheme of each power company and the transmission power ratio allocated by the telecom operator to the relay service, with the goal of maximizing the revenue of the telecom operator and the transmission power ratio allocated by the telecom operator to the relay service as the decision variable, a second optimization target model is established;

[0011] According to the third initial parameter, the payment scheme of each power company, the transmission power ratio allocated by the telecom operator to the relay service, the demand ratio of the gas-to-electricity service of the power company and the retail price of the gas-to-electricity service of the natural gas company, the fourth optimization target model is established with the goal of maximizing the profit of the natural gas company and the retail price of the gas-to-electricity service of the natural gas company as the decision variable;

[0012] An iterative algorithm is used to solve the first optimization target model and the second optimization target model to obtain a superior game equilibrium solution; the superior game equilibrium solution includes the payment scheme of each power company in the first optimization target model and the transmission power ratio allocated to the relay service by the telecommunications operator in the second optimization target model;

[0013] Substitute the upper-level game equilibrium solution into the third and fourth optimization target models, and use an iterative algorithm to solve the third and fourth optimization target models to obtain the lower-level game equilibrium solution. The lower-level game equilibrium solution includes the demand ratio of the power company's gas-to-electricity service in the third optimization target model and the retail price of the natural gas company's gas-to-electricity service in the fourth optimization target model;

[0014] Substitute the lower-level game equilibrium solution into the first and second optimization target models, use the iterative algorithm to solve the first optimization target model and the second optimization target model to obtain a new upper-level game equilibrium solution, use the new upper-level game equilibrium solution to obtain a new lower-level game equilibrium solution through the above steps, and judge whether the obtained overall game equilibrium solution is consistent with the result of the previous overall game equilibrium solution. If they are consistent, it is the global optimal, otherwise, perform a loop iteration of this step.

[0015] A global optimal optimization result is determined, wherein the global optimal optimization result is composed of a constant upper-level game equilibrium solution and a constant lower-level game equilibrium solution.

[0016] A further improvement of this method is that the steps of constructing the first optimization target model are as follows:

[0017] Through the statistical analysis method of direct load control error, the power cost model of power company i (i∈N={1,2,……,N}) is established:

[0018]

[0019] in, is the reserved electricity cost of power company i, m i represents the payment plan of power company i, Q irepresents the direct load control error that power company i needs to compensate for due to data packet loss during information transmission, ρ1 represents the retail price of gas-to-electricity service of natural gas company, ρ2 represents the retail price of AGC service, and β is the demand ratio of gas-to-electricity service of power company;

[0020] According to the statistical analysis of direct load control error, the direct load control error that power company i needs to compensate due to data packet loss during information transmission can be expressed as:

[0021] Q i =aP i l -b

[0022] Among them, a and b are the fitting coefficients after statistical analysis of direct load control error, P i l is the packet loss rate of power company i.

[0023] There is a two-way communication between the power company and the user. The packet loss rate under the DF cooperative relay transmission strategy is constructed. Without loss of generality, only the packet loss during the downlink transmission process is considered. The packet loss rate of power company i is expressed as:

[0024]

[0025] Among them, T in is the rate at which information reaches the DAU, It is defined as the information receiving rate of gateway i under the DF cooperative relay strategy, and g is the probability of correct information transmission from the gateway to the user.

[0026] From DAU i When the DF cooperative relay transmission mode is adopted to gateway i, the information receiving rate of gateway i is expressed as:

[0027]

[0028] Where W is DAU i The transmission bandwidth, DAU i The information transmission power, Assigned to DAU by telecom operators i The relay transmission power, DAU i Channel gain to gateway i, is the channel gain from relay to gateway i, DAU i Channel gain to the relay.

[0029]

[0030] Among them, m i It represents the payment plan that the power company i has made for the telecom operator. is the sum of payment plans formulated for all power companies, N represents the set of power companies (i∈N={1,2,…,i,…,N}), α represents the proportion of transmission power allocated by the telecom operator to the relay service, and p represents the total power of the telecom operator.

[0031] In summary, the first optimization target model is the cost model of power company i:

[0032]

[0033] The first optimization target model constraint condition is:

[0034] 0<α<1

[0035] 0<β<1

[0036]

[0037] in, It is allocated to DAU by telecom operators i The maximum relay transmission power.

[0038] A further improvement of this method is that the steps of constructing the second optimization target model are as follows:

[0039] Since telecom operators provide both traditional telecom services and relay services, their overall revenue can be expressed as:

[0040] maxV(α)=max(V u +V r )

[0041] Among them, V u represents the revenue from telecom services of telecom operators, V r Represents the revenue generated by the telecom operator's relay business.

[0042] The revenue from telecommunications services of telecommunications operators can be expressed as:

[0043] V u =ω r (W r -NW)ln(1+(1-α)ph Rd )

[0044] Among them, ω r is the base price of telecommunication services of telecommunication operators, W ris the total bandwidth of the telecom operator, the power company has a one-to-one correspondence with DAU, N is the number of DAU, h Rd is the channel gain from the telecom operator’s base station to the control center.

[0045] The revenue from the telecom operator's relay service can be expressed as:

[0046]

[0047] In summary, the second optimization target model is the revenue model of telecom operators:

[0048]

[0049] The second optimization objective model constraint condition is:

[0050] 0<α<1

[0051]

[0052] A further improvement of this method is that the steps of constructing the third optimization target model are as follows:

[0053] The power company agent represents the interests of all power companies and minimizes the sum of the costs of all power companies. The cost function of the power company agent can be expressed as:

[0054]

[0055] Among them, Z i represents the electricity cost function of power company i;

[0056] In summary, the third optimization target model is the cost model of the power company agent:

[0057]

[0058] The third optimization target model constraint condition is:

[0059] 0<α<1

[0060] 0<β<1

[0061]

[0062] A further improvement of this method is that the steps of constructing the fourth optimization target model are as follows:

[0063] Since the natural gas company sells both natural gas services and gas-to-electricity services, its overall revenue is expressed as:

[0064] maxU=max(U g +UG2P )

[0065] Among them, U g represents the revenue from gas sales services of natural gas companies, U G2P Revenue from the sale of gas-to-electricity services to natural gas companies;

[0066] The revenue of a natural gas company from selling natural gas services can be expressed as:

[0067] U g =(C all -ψ)ρ g

[0068] Among them, C all represents the total natural gas reserves of the natural gas company, ρ g is the retail price of natural gas, and ψ represents the amount of natural gas required by the natural gas company to provide gas-to-electricity services.

[0069]

[0070] in, It is a proportional coefficient between the retail price of natural gas and the retail price of gas-to-electricity service;

[0071] The relationship between natural gas consumption and output power is as follows:

[0072] ψ=a1+a2P out +a3(P out ) 2

[0073] Among them, P out is the power generation of the gas-to-electricity equipment, and a1, a2, and a3 are the thermal rate curve coefficients in engineering practice.

[0074] The power generation of the gas-to-electricity equipment of the natural gas company is the power consumption required by the power company agent, which can be expressed as:

[0075]

[0076] The revenue from the gas-to-electricity service sold by natural gas companies can be expressed as:

[0077]

[0078] In summary, the fourth optimization target model is the revenue model of the natural gas company:

[0079]

[0080] in,

[0081] The fourth optimization target model constraint condition is:

[0082] 0<α<1

[0083] 0<β<1

[0084]

[0085] A collaborative system between electricity, telecommunications and natural gas companies, including:

[0086] A parameter acquisition module, used to acquire a first initial parameter, a second initial parameter and a third initial parameter; wherein the first initial parameter includes the reserved power cost of the power company, the fitting coefficient of the load tracking deviation, the transmission bandwidth of the DAU, the probability of correct transmission of information from the gateway to the user, the rate at which information reaches the DAU, the channel gain from the DAU to the gateway and from the relay to the gateway, the transmission power of the DAU, the retail price of the AGC service, and the total power of the base station of the telecom operator; the second initial parameter includes the total bandwidth of the telecom operator, the base price of the telecom service of the telecom operator, the number of DAUs in the base station, and the channel gain from the relay to the control center; the third initial parameter includes the total natural gas reserves of the natural gas company, the ratio coefficient of the natural gas retail price of the natural gas company to the retail price of the gas-to-electricity service, and the heat rate curve coefficient in engineering practice;

[0087] A first model building module is used to establish a first optimization target model based on the first initial parameters, the payment schemes of each power company, the transmission power ratio allocated to the relay service by the telecommunications operator, the demand ratio of the gas-to-electricity service of the power company, and the retail price of the gas-to-electricity service of the natural gas company, with the goal of minimizing the cost of each power company and the payment schemes of each power company as decision variables;

[0088] A second model building module is used to establish a second optimization target model based on the second initial parameters, the payment schemes of each power company and the transmission power ratio allocated to the relay service by the telecommunications operator, with the goal of maximizing the revenue of the telecommunications operator and the transmission power ratio allocated to the relay service by the telecommunications operator as a decision variable;

[0089] A third model building module is used to establish a third optimization target model based on the first initial parameters, the payment plans of various power companies, the transmission power ratio allocated to the relay service by the telecommunications operator, the demand ratio of the gas-to-electricity service of the power company, and the retail price of the gas-to-electricity service of the natural gas company, with the goal of minimizing the agent cost of the power company and the demand ratio of the gas-to-electricity service of the power company as the decision variable;

[0090] a fourth model building module, for establishing a fourth optimization target model based on the third initial parameter, the payment schemes of various power companies, the transmission power ratio allocated to the relay service by the telecommunications operator, the demand ratio of the gas-to-electricity service of the power company, and the retail price of the gas-to-electricity service of the natural gas company, with the goal of maximizing the revenue of the natural gas company and the retail price of the gas-to-electricity service of the natural gas company as the decision variable;

[0091] A first solution module is used to solve the first optimization target model and the second optimization target model by using an iterative algorithm to obtain a superior game equilibrium solution. The superior game equilibrium solution includes the payment scheme of each power company in the first optimization target model and the transmission power ratio allocated to the relay service by the telecom operator in the second optimization target model;

[0092] The second solution module is used to substitute the upper-level game equilibrium solution into the third and fourth optimization target models, and use an iterative algorithm to solve the third and fourth optimization target models to obtain a lower-level game equilibrium solution. The lower-level game equilibrium solution includes the demand ratio of the power company's gas-to-electricity service in the third optimization target model and the retail price of the natural gas company's gas-to-electricity service in the fourth optimization target model;

[0093] The third solving module is used to substitute the lower-level game equilibrium solution into the first and second optimization target models, and adopt an iterative algorithm to solve the first optimization target model and the second optimization target model to obtain a new upper-level game equilibrium solution. The new upper-level game equilibrium solution is used to obtain a new lower-level game equilibrium solution through the method described in the second solving module, and it is judged whether the obtained overall game equilibrium solution is consistent with the result of the previous overall game equilibrium solution. If they are consistent, it is the global optimal, and if they are inconsistent, this step is repeated in a loop.

[0094] The optimization result determination module is used to determine the global optimal optimization result, wherein the global optimal optimization result is composed of a constant upper-level game equilibrium solution and a constant lower-level game equilibrium solution.

[0095] A storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-mentioned method for collaboration among power, telecommunications and natural gas companies.

[0096] Due to the adoption of the above technical solution, the technical progress achieved by the present invention is:

[0097] The present invention discloses a method, system and storage medium for collaboration between power companies, telecommunications companies and natural gas companies, including: constructing an optimization model between power companies and telecommunications operators; the optimization model between power companies and telecommunications operators includes a first optimization target model and a second optimization target model; constructing an optimization model between power company agents and natural gas companies; the optimization model between power company agents and natural gas companies includes a third optimization target model and a fourth optimization target model. An iterative algorithm is used to solve the optimization model between power companies and telecommunications operators and the optimization model between power company agents and natural gas companies to obtain a global optimal optimization result. The optimization result includes: the payment plan formulated by the power company to the telecommunications operator, the transmission power ratio allocated to the relay service by the telecommunications operator, the demand ratio of the gas-to-electricity service of the power company, and the retail price of the gas-to-electricity service of the natural gas company. The present invention uses the AGC regulation service and the gas-to-electricity technology of the natural gas company to jointly compensate for the load tracking deviation on the demand side, which can reduce the cost of each power company while increasing the benefits of the telecommunications operator and the natural gas company. BRIEF DESCRIPTION OF THE DRAWINGS

[0098] In order to more clearly explain the operating principle and technical solutions of the present invention, the following briefly introduces the drawings required for the operating principle and the technologies used. Obviously, the drawings described below are only some operating examples of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0099] Figure 1 This is a system structure diagram between a power company, a telecommunications operator, and a natural gas company in an embodiment of the present invention;

[0100] Figure 2 This is a diagram of the interactive relationship between the power company, telecommunication operator, and natural gas company in an embodiment of the present invention;

[0101] Figure 3 A flowchart of a collaborative optimization method between a power company, a telecommunications operator, and a natural gas company according to an embodiment of the present invention;

[0102] Figure 4 This is a structural diagram of an interaction model between a power company, a telecommunications operator, and a natural gas company according to an embodiment of the present invention;

[0103] Figure 5 The present invention is a flowchart of an embodiment of the present invention using an iterative algorithm to optimize the solution. DETAILED DESCRIPTION

[0104] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0105] In this application, "DAU" means data concentrator unit and "AGC" means automatic generation control.

[0106] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0107] The system structure between power companies, telecom operators and gas companies is as follows Figure 1 shown.

[0108] Power company: The power company communicates with the user-side gateway in real time through the DAU. The gateway collects control information from the DAU for demand-side regulation. Due to the loss of data packets during the information collection process, the demand-side regulation will be biased. The cost of the power company will increase as the regulation deviation increases. Therefore, the power company needs to formulate a payment plan for the telecom operator to purchase the telecom operator's relay service to help it forward control information, thereby reducing the packet loss rate, increasing the information transmission rate, and ultimately reducing the cost of the power company. It should be pointed out that the multiple power companies in the system are in a non-cooperative game relationship. Each power company competes for the relay transmission power allocated to it by the telecom operator by formulating different payment plans.

[0109] Telecom operators: Telecom operators include relay services and their own telecommunications services. Telecom operators make trade-offs between relay services and telecommunications services based on their own interests and maximize their own profits by deciding the proportion of transmission power allocated to relay services.

[0110] Power company agents: Power company agents represent the interests of all power companies. During the operation of the power grid, power company agents achieve the goal of minimizing the costs of all power companies by formulating the demand ratio of gas-to-electricity services of power companies.

[0111] Natural gas companies: Natural gas companies include natural gas sales business and gas-to-electricity sales business. Under the background of "dual carbon", natural gas power generation has good application and development prospects. Natural gas companies maximize their own profits by setting retail prices for gas-to-electricity services.

[0112] The interactive relationship between power companies, telecom operators and gas companies is as follows: Figure 2 The idea of ​​the collaborative optimization method between the power company, telecommunications operator, and natural gas company in this embodiment is as follows:

[0113] Establish an interactive model between power companies and telecom operators to achieve two-way interaction between power companies and telecom operators. In the two-way interaction between power companies and telecom operators, telecom operators are often the main role in the formulation of transaction mechanisms. Generally, telecom operators first determine the transmission power ratio allocated to relay services on the premise of maximizing profits, and power companies respond to the transmission power ratio allocated to relay services by telecom operators. On the basis of meeting exchange requirements, power companies determine payment plans to minimize the costs of power companies. In actual interactions, the payment plans of various power companies will in turn affect the formulation of the transmission power ratio allocated to relay services by telecom operators. The interaction between the two constitutes a game model and eventually forms a dynamic equilibrium. The behaviors between the two are sequential, so in actual interactions, telecom operators are leaders and power companies are followers, and the strategy choice of one party will have a direct impact on the benefits and costs of the other party. Finally, a balance is reached between maximizing the benefits of telecom operators and minimizing the costs of power companies. The interactive model between power companies and telecom operators includes a first optimization target model established with power companies as followers and a second optimization target model established with telecom operators as leaders.

[0114] An interactive model between power company agents and natural gas companies is established to achieve two-way interaction between power company agents and natural gas companies. In the interactive process between power company agents and natural gas companies, on the premise of maximizing the benefits of natural gas companies, natural gas companies first determine the retail price of gas-to-electricity services, and power company agents determine the demand ratio of gas-to-electricity services of power companies based on the retail price of gas-to-electricity services of natural gas companies. In actual interaction, the demand ratio of gas-to-electricity services of power companies will in turn affect the formulation of the retail price of gas-to-electricity services of natural gas companies. The interaction between the two constitutes a game model and eventually forms a dynamic equilibrium. There is also a sequence of behaviors between the two. Therefore, in actual interaction, natural gas companies are leaders and power company agents are followers, and the strategy choice of one party will have a direct impact on the benefits and costs of the other party. Finally, an equilibrium is reached between maximizing the benefits of natural gas companies and minimizing the costs of power company agents. The interactive model between power company agents and natural gas companies includes a third optimization target model established with power company agents as followers and a fourth optimization target model established with natural gas companies as leaders.

[0115] The collaborative optimization method among the power company, telecommunications operator and natural gas company in this embodiment is as follows:

[0116] Figure 3 Flow chart of the collaborative optimization method between power companies and telecommunications operators according to an embodiment of the present invention. Figure 3 , the collaborative optimization method between the power company, the telecommunications operator, and the natural gas company of the embodiment includes:

[0117] Step S1: Obtain a first initial parameter, a second initial parameter, and a third initial parameter.

[0118] The first initial parameters include the reserved power cost of the power company, the fitting coefficient of the load tracking deviation, the transmission bandwidth of the DAU, the probability of correct transmission of information from the gateway to the user, the rate at which information reaches the DAU, the channel gain from the DAU to the gateway and from the relay to the gateway, the transmission power of the DAU, the retail price of the AGC service, and the total power of the base station of the telecom operator; the second initial parameters include the total bandwidth of the telecom operator, the base price of the telecom service of the telecom operator, the number of DAUs in the base station, and the channel gain from the relay to the control center; the third initial parameters include the total natural gas reserves of the natural gas company, the ratio coefficient of the natural gas retail price of the natural gas company to the retail price of the gas-to-electricity service, and the heat rate curve coefficient in engineering practice.

[0119] Step S2: Based on the first initial parameters, the payment plans of various power companies, the proportion of transmission power allocated to relay services by telecom operators, the demand proportion of gas-to-electricity services of power companies, and the retail price of gas-to-electricity services of natural gas companies, a first optimization target model is established with the goal of minimizing the cost of each power company and the payment plans of each power company as decision variables.

[0120] In this step, the statistical analysis method of direct load control error is used to describe the cost model of each power company. In addition to its own operating costs, power companies also have to pay for the cost of purchasing relay services. In order to reduce the packet loss rate during information transmission, power companies need to purchase relay services from telecom operators to help them forward information. Telecom operators first determine the proportion of transmission power allocated to relay services. Each power company is in a non-cooperative game relationship, and they compete for the transmission power allocated to them by telecom operators by formulating different payment plans.

[0121] In the interaction between power companies and telecom operators, for power company i, the decision variable is the payment plan m of power company i. i , the first optimization target model is:

[0122] Firstly, the power cost model of power company i (i∈N={1,2,……,N}) is established by using the statistical analysis method of direct load control error:

[0123]

[0124] in, is the reserved power cost of power company i (￥), m i represents the payment plan of power company i (￥), Q i represents the direct load control error (MW) that power company i needs to compensate for due to data packet loss during information transmission, ρ1 represents the retail price of gas-to-electricity service of the natural gas company (￥ / MW), ρ2 represents the retail price of AGC service (￥ / MW), and β is the demand ratio of gas-to-electricity service of the power company.

[0125] According to the statistical analysis of direct load control error, the direct load control error that power company i needs to compensate due to data packet loss during information transmission can be expressed as:

[0126] Q i =aP i l -b

[0127] Among them, a and b are the fitting coefficients after statistical analysis of direct load control error, P i l is the packet loss rate of power company i.

[0128] There is two-way communication between the power company and the user, and the packet loss rate under the DF cooperative relay transmission strategy is constructed. Without loss of generality, only the packet loss during the downlink transmission process is considered, and the packet loss rate of power company i is expressed as:

[0129]

[0130] Among them, T in is the rate at which information reaches the DAU (Mbit / s), It is defined as the information receiving rate (Mbit / s) of gateway i under the DF cooperative relay strategy, and g is the probability of correct information transmission from the gateway to the user.

[0131] From DAU i When the DF cooperative relay transmission mode is adopted to gateway i, the information receiving rate of gateway i is expressed as:

[0132]

[0133] Where W is DAU i The transmission bandwidth (Hz), DAU i Information transmission power (W), Assigned to DAU by telecom operators i Relay transmission power (W), is the channel gain from DAUi to gateway i (dB), is the channel gain from relay to gateway i (dB), is the channel gain from DAUi to the relay (dB).

[0134]

[0135] Among them, m i It represents the payment plan that the power company i has made for the telecom operator. The sum of payment schemes formulated for all power companies (￥), N represents the set of power companies (i∈N={1,2,…,i,…,N}), α represents the proportion of transmission power allocated to relay services by telecom operators, and p represents the total power of telecom operators (W).

[0136] In summary, the first optimization target model is the cost model of power company i:

[0137]

[0138] The first optimization target model constraint condition is:

[0139] 0<α<1

[0140] 0<β<1

[0141]

[0142] in, It is allocated to DAU by telecom operators i Maximum relay transmission power (W).

[0143] Step S3: Based on the second initial parameter, the payment plan of each power company and the transmission power ratio allocated by the telecom operator to the relay service, with the goal of maximizing the profit of the telecom operator, the transmission power ratio allocated by the telecom operator to the relay service is used as the decision variable, and a second optimization target model is established.

[0144] In this step, the base station of the telecom operator is the main infrastructure for providing relay services to various power companies. A proportion α of the total power of the telecom operator is allocated to the relay service to help the power company transmit control information more efficiently, and a proportion (1-α) is allocated to the telecom service to maintain the telecom operator's own telecom services.

[0145] In the interaction process between the power company and the telecom operator, for the telecom operator, the decision variable is the transmission power ratio α allocated by the telecom operator to the relay service, and the second optimization target model is:

[0146] Considering that telecom operators provide both traditional telecom services and relay services, their overall revenue can be expressed as:

[0147] maxV(α)=max(V u +V r )

[0148] Among them, V u represents the revenue (￥) from the telecommunication services of telecommunication operators, V r Represents the revenue (￥) generated by the telecommunications operator’s relay services.

[0149] The revenue from telecommunications services of telecommunications operators can be expressed as:

[0150] V u =ω r (W r -NW)ln(1+(1-α)ph Rd )

[0151] Among them, ω r is the base price of telecommunication services of telecommunication operators (￥ / Mbps), W r is the total bandwidth of the telecom operator (Hz), the power company has a one-to-one correspondence with DAU, N is the number of DAU, h Rd is the channel gain (dB) from the telecom operator’s base station to the control center.

[0152] The revenue from the telecom operator's relay service can be expressed as:

[0153]

[0154] In summary, the second optimization target model is the revenue model of telecom operators:

[0155]

[0156] The second optimization objective model constraint condition is:

[0157] 0<α<1

[0158]

[0159] After step S2 and step S3, an interaction model between the power company and the telecommunication operator including the first optimization target model and the second optimization target model is obtained.

[0160] Step S4: Based on the first initial parameters, the payment plans of various power companies, the proportion of transmission power allocated to relay services by telecom operators, the demand ratio of gas-to-electricity services of power companies, and the retail price of gas-to-electricity services of natural gas companies, a third optimization target model is established with the goal of minimizing the cost of power company agents and the demand ratio of gas-to-electricity services of the power companies as the decision variable.

[0161] In this step, the cost function of the power company agent is composed of the sum of the costs of each power company. The power company agent fully represents the interests of each power company in the system. The power company agent achieves the goal of minimizing the sum of the costs of all power companies in the system by formulating the demand ratio of the power company's gas-to-electricity service.

[0162] In the interaction process between the power company agent and the natural gas company, for the power company agent, the decision variable is the demand ratio of the power company's gas-to-electricity service, and the third optimization target model is:

[0163] The power company agent represents the interests of all power companies, and its purpose is to minimize the sum of the costs of all power companies. The cost function of the power company agent can be expressed as:

[0164]

[0165] Among them, Z i represents the electricity cost function of power company i.

[0166] In summary, the third optimization target model is the cost model of the power company agent:

[0167]

[0168] The third optimization target model constraint condition is:

[0169] 0<α<1

[0170] 0<β<1

[0171]

[0172] Step S5: Based on the third initial parameter, the payment plan of each power company, the transmission power ratio allocated to the relay service by the telecom operator, the demand ratio of the gas-to-electricity service of the power company and the retail price of the gas-to-electricity service of the natural gas company, with the goal of maximizing the profit of the natural gas company and the retail price of the gas-to-electricity service of the natural gas company as the decision variable, a fourth optimization objective model is established.

[0173] In this step, the natural gas company has two businesses: selling natural gas and selling gas-to-electricity services. The natural gas company needs to make a trade-off between the natural gas sales business and the gas-to-electricity sales business. The natural gas company maximizes its profits by setting the retail price of the gas-to-electricity services.

[0174] In the interaction between the power company agent and the natural gas company, for the natural gas company, the decision variable is the retail price of the natural gas company's gas-to-electricity service, and the fourth optimization objective model is:

[0175] Considering that the natural gas company sells both natural gas services and gas-to-electricity services, its overall revenue is expressed as:

[0176] maxU=max[U g +U G2P ]

[0177] Among them, U g represents the revenue (￥) from gas sales services of natural gas companies, U G2P Revenue from selling gas-to-electricity services to natural gas companies (￥).

[0178] The revenue of a natural gas company from selling natural gas services can be expressed as:

[0179] U g =(C all -ψ)ρ g

[0180] Among them, C all Represents the total natural gas reserves of the natural gas company (m 3 ), ρ g is the retail price of natural gas (￥ / m 3 ), ψ represents the amount of natural gas required by the natural gas company to provide gas-to-electricity services (m 3 ).

[0181]

[0182] in, It is a proportional coefficient between the retail price of natural gas and the retail price of gas-to-electricity services.

[0183] The relationship between natural gas consumption and output power is as follows:

[0184] ψ=a1+a2P out +a3(P out ) 2

[0185] Among them, P out is the power generation capacity of the gas-to-electricity equipment (MW), a1, a2, a3 are the thermal rate curve coefficients in engineering practice.

[0186] The power generation of the gas-to-electricity equipment of the natural gas company is the power consumption required by the power company agent, which can be expressed as:

[0187]

[0188] The revenue from the gas-to-electricity service sold by natural gas companies can be expressed as:

[0189]

[0190] In summary, the fourth optimization target model is the revenue model of the natural gas company:

[0191]

[0192] in,

[0193] The fourth optimization target model constraint condition is:

[0194] 0<α<1

[0195] 0<β<1

[0196]

[0197] After step S4 and step S5, the interaction model of the power company agent and the natural gas company including the third optimization target model and the fourth optimization target model is obtained.

[0198] The optimization model between power companies, telecom operators and gas companies is as follows: Figure 4 shown.

[0199] Next, an iterative algorithm is used to optimize and solve the interaction model between the power company and the telecom operator, and the interaction model between the power company agent and the natural gas company. The solution ideas are shown in steps S6, S7 and S8. The specific process of optimization and solution is as follows: Figure 5 As shown. In the interactive model between power companies and telecom operators, the interactive strategy is solved iteratively, and the transmission power ratio of the telecom operator to the relay service and the payment plan of the power company that responds to the relay transmission power allocation ratio interact. In the interactive model between power company agents and natural gas companies, the interactive strategy is solved iteratively, and the retail price of the gas-to-electricity service of the natural gas company and the demand ratio of the gas-to-electricity service of the power company that responds to the retail price interact. The interactive model between power companies and telecom operators, and the interactive model between power company agents and natural gas companies can well promote the benign interaction between various power companies, telecom operators, and natural gas companies, and ultimately achieve a win-win situation.

[0200] Step S6: using an iterative algorithm to solve the first optimization target model and the second optimization target model to obtain a higher-level game equilibrium solution, which includes the payment schemes of each power company in the first optimization target model and the transmission power ratio allocated to the relay service by the telecom operator in the second optimization target model.

[0201] Step S7: Substitute the upper-level game equilibrium solution into the third and fourth optimization target models, and use an iterative algorithm to solve the third and fourth optimization target models to obtain a lower-level game equilibrium solution. The lower-level game equilibrium solution includes the demand ratio of the power company's gas-to-electricity service in the third optimization target model and the retail price of the natural gas company's gas-to-electricity service in the fourth optimization target model.

[0202] Step S8: Substitute the lower-level game equilibrium solution into the first and second optimization target models, and use an iterative algorithm to solve the first optimization target model and the second optimization target model to obtain a new upper-level game equilibrium solution. Use the new upper-level game equilibrium solution to obtain a new lower-level game equilibrium solution through step S7, and judge whether the obtained overall game equilibrium solution is consistent with the result of the previous overall game equilibrium solution. If they are consistent, it is the global optimal solution. If not, perform a loop iteration of this step.

[0203] Step S9: Determine a global optimal optimization result, wherein the global optimal optimization result is composed of a constant upper-level game equilibrium solution and a constant lower-level game equilibrium solution.

[0204] The collaborative optimization method of this embodiment considering the power company, telecommunication operator, and natural gas company has the following advantages:

[0205] In the direct load control mode, the power grid releases control information to adjust the power load on the demand side. Due to the loss of data packets during information transmission, the demand side regulation will produce deviations. The power cost of the power company will increase with the increase of regulation deviation. Some scholars have proposed to use cooperative relay technology to help power companies forward control information to reduce the packet loss rate and ultimately reduce the cost of the power company. In addition, it should be pointed out that the relay facilities that assist power companies in communication mainly include general relays and base stations of telecom operators as relays. The existing technology mainly focuses on solving the problems of power allocation and bandwidth allocation of relays in smart grid communication networks, while a single AGC service is used to compensate for the load tracking deviation on the demand side. Since the unit price of AGC service is much higher than the unit price of electricity, and the purchase volume of AGC service depends on the reliability of information transmission in the communication network, this undoubtedly brings great pressure to the smart grid communication network. In this scheme, the gas-to-electricity technology of natural gas companies is introduced. Benefiting from the advantages of low pollutant emissions, high energy conversion efficiency, low construction investment and operation and maintenance costs, the comprehensive cost of natural gas power generation is lower than that of AGC services, creating good conditions for the development and application of gas-to-electricity. Against the backdrop of the country’s vigorous advocacy of “dual carbon”, utilizing natural gas companies’ gas-to-electricity technology and AGC mediation services to jointly compensate for the load tracking deviation on the demand side will help ease the pressure on the power grid’s communication network, further reducing the costs of power companies while increasing the profits of telecom operators and natural gas companies.

[0206] This embodiment performs collaborative optimization for power companies, telecom operators, and natural gas companies, and considers the interests of the three parties from their own perspectives. Its optimization model is very different from most studies. In the interactive model between power companies and telecom operators, the power companies are in a non-cooperative game relationship. Each power company purchases relay services from telecom operators to help them forward control information by formulating their own payment plans. In order to maximize their own interests, telecom operators determine the proportion of transmission power allocated to relay services. In the interactive model between power company agents and natural gas companies, power company agents represent the interests of all power companies in the system, and determine their own gas-to-electricity service demand ratio based on the retail price of gas-to-electricity services of natural gas companies, thereby minimizing the costs of each power company. Natural gas companies determine the optimal retail price of gas-to-electricity services based on the premise of maximizing their own profits. Considering the reserved power cost of the power company, the fitting coefficient of the load tracking deviation, the transmission bandwidth of the DAU, the probability of correct transmission of information from the gateway to the user, the rate at which information reaches the DAU, the channel gain from the DAU to the gateway and from the relay to the gateway, the transmission power of the DAU, the retail price of the AGC service, and the total power of the telecom operator's base station, the first optimization target model with the minimum cost of the power company as the objective function is established. Considering the total bandwidth of the telecom operator, the base price of the telecom operator's telecom service, the DAU in the base station U The second optimization target model is established with the maximum profit of telecom operators as the objective function under multiple factors such as the number of relays and the channel gain from relays to the control center. The power company agent represents the profit of all power companies in the system. Considering the cost of each power company, the third optimization target model is established with the minimum cost of the power company agent as the objective. As a clean energy, compared with coal-fired power generation, gas-to-electricity technology has great advantages in reducing carbon emissions. Considering the total natural gas reserves of natural gas companies, the ratio coefficient of natural gas retail prices of natural gas companies to the retail price of gas-to-electricity services, and the heat rate curve coefficient in engineering practice, the fourth optimization target model is established with the maximum profit of natural gas as the objective function.

[0207] For power companies, each power company obtains the relay power of telecom operators through non-cooperative game competition to help them forward control information, which effectively solves the data congestion and data packet loss problems caused by the simultaneous transmission of a large amount of control information. To a certain extent, it reduces the communication pressure of smart grids and helps reduce the costs of power companies. For telecom operators, it is necessary to make a trade-off between their own telecom services and relay services, allocate a certain proportion of the total power of base stations to relay services to obtain payment from power companies, and maximize the benefits of telecom operators by optimizing the allocation ratio of relay power allocated to relay services. For power company agents, they represent the interests of all power companies in the system and minimize their own costs by deciding the demand ratio of gas-to-electricity services. Using gas-to-electricity services and AGC services to jointly compensate for load tracking deviations is more selective than relying solely on AGC services for compensation, and has a certain positive effect on alleviating the communication pressure of smart grids. For natural gas companies, selling certain gas-to-electricity services to power companies broadens the source of income, and maximizes their own income by setting the retail price of gas-to-electricity services. The optimization model can well promote the benign interaction between power companies, telecom operators and natural gas companies, improve the reliability of smart grid communication network operation, and use gas-to-electricity services and AGC services to jointly compensate for load tracking deviations, which helps alleviate the communication pressure of smart grids and reduce the costs of power companies. This optimization model can achieve a win-win situation for power companies, telecom operators and natural gas companies.

[0208] A system based on the above-mentioned collaborative approach between power, telecommunications and natural gas companies includes:

[0209] A parameter acquisition module, a first model construction module, a second model construction module, a third model construction module, a fourth model construction module, a first solution module, a second solution module, a third solution module and an optimization result determination module.

[0210] The parameter acquisition module acquires the first initial parameter, the second initial parameter and the third initial parameter; wherein the first initial parameter includes the reserved power cost of the power company, the fitting coefficient of the load tracking deviation, the transmission bandwidth of the DAU, the probability of correct transmission of information from the gateway to the user, the rate at which information reaches the DAU, the channel gain from the DAU to the gateway and from the relay to the gateway, the transmission power of the DAU, the retail price of the AGC service, and the total power of the base station of the telecom operator; the second initial parameter includes the total bandwidth of the telecom operator, The telecom operator's telecom service base price, the number of DAUs in the base station, and the channel gain from the relay to the control center; the third initial parameters include the total natural gas reserves of the natural gas company, the ratio coefficient of the natural gas retail price of the natural gas company to the retail price of the gas-to-electricity service, and the heat rate curve coefficient in engineering practice; the first model building module is based on the first initial parameters, the payment plans of each power company, the transmission power ratio allocated to the relay service by the telecom operator, the demand ratio of the gas-to-electricity service of the power company, and the retail price of the gas-to-electricity service of the natural gas company, with the goal of minimizing the cost of each power company and the payment plan of each power company as the decision variable, to establish a first optimization target model; the second model building module is based on the second initial parameters, the payment plans of each power company and the transmission power ratio allocated to the relay service by the telecom operator The transmission power ratio is used to maximize the revenue of the telecommunications operator, and the transmission power ratio allocated to the relay service by the telecommunications operator is used as a decision variable to establish a second optimization target model; the third model construction module is based on the first initial parameters, the payment plans of various power companies, the transmission power ratio allocated to the relay service by the telecommunications operator, the demand ratio of the gas-to-electricity service of the power company, and the retail price of the gas-to-electricity service of the natural gas company, with the goal of minimizing the agent cost of the power company, and the demand ratio of the gas-to-electricity service of the power company as the decision variable to establish a third optimization target model; the fourth model construction module is based on the third initial parameters, the payment plans of various power companies, the transmission power ratio allocated to the relay service by the telecommunications operator, the demand ratio of the gas-to-electricity service of the power company, and the retail price of the gas-to-electricity service of the natural gas company, with the goal of maximizing the revenue of the natural gas company, and the retail price of the gas-to-electricity service of the natural gas company as the decision variable to establish a fourth optimization target model; the first solution module uses an iterative algorithm to solve the first optimization target model and the second optimization target model to obtain a superior game equilibrium solution. The upper-level game equilibrium solution includes the payment plan of each power company in the first optimization target model and the transmission power ratio allocated to the relay service by the telecom operator in the second optimization target model; the second solution module substitutes the upper-level game equilibrium solution into the third and fourth optimization target models, and uses an iterative algorithm to solve the third and fourth optimization target models to obtain the lower-level game equilibrium solution.The lower-level game equilibrium solution includes the demand ratio of the power company's gas-to-electricity service in the third optimization target model and the retail price of the natural gas company's gas-to-electricity service in the fourth optimization target model; the third solution module substitutes the lower-level game equilibrium solution into the first and second optimization target models, and uses an iterative algorithm to solve the first optimization target model and the second optimization target model to obtain a new upper-level game equilibrium solution. The new upper-level game equilibrium solution is used to obtain a new lower-level game equilibrium solution through the method described in the second solution module, and it is determined whether the obtained overall game equilibrium solution is consistent with the result of the previous overall game equilibrium solution. If they are consistent, it is the global optimal solution. If they are inconsistent, this step is repeated in a loop; the optimization result determination module determines the global optimal optimization result, and the global optimal optimization result is composed of a constant upper-level game equilibrium solution and a constant lower-level game equilibrium solution.

[0211] A storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-mentioned method for collaboration among power, telecommunications and natural gas companies.

[0212] The storage medium is a storage chip that can read and write binary data, and can be one or more of RAM, ROM or random access memory.

[0213] The embodiments described above are merely descriptions of preferred implementation modes of the present invention, and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for collaboration between power, telecommunications and natural gas companies, characterized in that: include: Obtain the first initial parameter, the second initial parameter and the third initial parameter; wherein the first initial parameter includes the reserved power cost of the power company, the fitting coefficient of the load tracking deviation, the transmission bandwidth of the DAU, the probability of correct transmission of information from the gateway to the user, the rate at which information reaches the DAU, the channel gain from the DAU to the gateway and from the relay to the gateway, the transmission power of the DAU, the retail price of the AGC service, and the total power of the base station of the telecom operator; the second initial parameter includes the total bandwidth of the telecom operator, the base price of the telecom service of the telecom operator, the number of DAUs in the base station, and the channel gain from the relay to the control center; the third initial parameter includes the total natural gas reserves of the natural gas company, the ratio coefficient of the natural gas retail price of the natural gas company to the retail price of the gas-to-electricity service, and the heat rate curve coefficient in engineering practice; Based on the first initial parameter, the payment scheme of each power company, the transmission power ratio allocated by the telecom operator to the relay service, the demand ratio of the gas-to-electricity service of the power company, and the retail price of the gas-to-electricity service of the natural gas company, with the goal of minimizing the cost of each power company, the payment scheme of each power company and the demand ratio of the gas-to-electricity service of the power company are respectively decision variables, and the respective first optimization target model and the third optimization target model are established; According to the second initial parameter, the payment scheme of each power company and the transmission power ratio allocated by the telecom operator to the relay service, with the goal of maximizing the revenue of the telecom operator and the transmission power ratio allocated by the telecom operator to the relay service as the decision variable, a second optimization target model is established; According to the third initial parameter, the payment scheme of each power company, the transmission power ratio allocated by the telecom operator to the relay service, the demand ratio of the gas-to-electricity service of the power company and the retail price of the gas-to-electricity service of the natural gas company, the fourth optimization target model is established with the goal of maximizing the profit of the natural gas company and the retail price of the gas-to-electricity service of the natural gas company as the decision variable; An iterative algorithm is used to solve the first optimization target model and the second optimization target model to obtain a superior game equilibrium solution; the superior game equilibrium solution includes the payment scheme of each power company in the first optimization target model and the transmission power ratio allocated to the relay service by the telecommunications operator in the second optimization target model; Substituting the upper-level game equilibrium solution into the third and fourth optimization target models, and solving the third and fourth optimization target models by an iterative algorithm to obtain a lower-level game equilibrium solution; the lower-level game equilibrium solution includes the demand ratio of the gas-to-electricity service of the power company in the third optimization target model and the retail price of the gas-to-electricity service of the natural gas company in the fourth optimization target model; Substitute the lower-level game equilibrium solution into the first and second optimization target models, use an iterative algorithm to solve the first optimization target model and the second optimization target model to obtain a new upper-level game equilibrium solution, use the new upper-level game equilibrium solution to obtain a new lower-level game equilibrium solution through the above steps, and judge whether the obtained overall game equilibrium solution is consistent with the previous overall game equilibrium solution result. If they are consistent, it is the global optimal solution. If they are inconsistent, perform a loop iteration of this step; Determine a global optimal optimization result, wherein the global optimal optimization result is composed of a constant upper-level game equilibrium solution and a constant lower-level game equilibrium solution; The steps of constructing the first optimization target model are as follows: Through the statistical analysis method of direct load control error, the power cost model of power company i (i∈N={1,2,......,N}) is established: in, is the reserved electricity cost of power company i, m i represents the payment plan of power company i, Q i represents the direct load control error that power company i needs to compensate for due to data packet loss during information transmission, ρ1 represents the retail price of gas-to-electricity service of natural gas company, ρ2 represents the retail price of AGC service, and β is the demand ratio of gas-to-electricity service of power company; According to the statistical analysis of direct load control error, the direct load control error that power company i needs to compensate due to data packet loss during information transmission can be expressed as: Q i =aP i l -b Among them, a and b are the fitting coefficients after statistical analysis of direct load control error, P i l is the packet loss rate of power company i; There is two-way communication between the power company and the user. The packet loss rate under the DF cooperative relay transmission strategy is constructed. Without loss of generality, only the packet loss during the downlink transmission process is considered. The packet loss rate of power company i is expressed as: Among them, T in is the rate at which information reaches the DAU, It is defined as the information receiving rate of gateway i under the DF cooperative relay strategy, and g is the probability of correct information transmission from the gateway to the user; From DAU i When the DF cooperative relay transmission mode is adopted to gateway i, the information receiving rate of gateway i is expressed as: Where W is DAU i The transmission bandwidth, DAU i The information transmission power, Assigned to DAU by telecom operators i The relay transmission power, DAU i Channel gain to gateway i, is the channel gain from relay to gateway i, DAU i Channel gain to the relay; Among them, m i It represents the payment plan that the power company i has made for the telecom operator. is the sum of payment schemes formulated by all power companies, N represents the set of power companies (i∈N={1,2,......,i,......,N}), α represents the proportion of transmission power allocated by the telecom operator to the relay service, and p represents the total power of the telecom operator; In summary, the first optimization target model is the cost model of power company i: The first optimization target model constraint condition is: 0＜α＜1 0＜β＜1 Among them, p i R max It is allocated to DAU by telecom operators i The maximum relay transmission power.

2. The method for collaboration among power, telecommunications and natural gas companies according to claim 1, characterized in that: The steps of constructing the second optimization target model are as follows: Since telecom operators provide both traditional telecom services and relay services, their overall revenue can be expressed as: maxV(α)=max(V u +V r ) Among them, V u represents the revenue from telecom services of telecom operators, V r It represents the revenue from the relay services of telecom operators; The revenue from telecommunications services of telecommunications operators can be expressed as: V u nω r (W r -NW)ln(1+(1-α)ph Rd ) Among them, ω r is the base price of telecommunication services of telecommunication operators, W r is the total bandwidth of the telecom operator, the power company has a one-to-one correspondence with DAU, N is the number of DAU, h Rd is the channel gain from the telecom operator’s base station to the control center; The revenue from the telecom operator's relay service can be expressed as: In summary, the second optimization target model is the revenue model of the telecom operator: The second optimization objective model constraint condition is: 0＜α＜1 3. The method for collaboration among power, telecommunications and natural gas companies according to claim 2, characterized in that: The steps of constructing the third optimization target model are as follows: The power company agent represents the interests of all power companies and minimizes the sum of the costs of all power companies. The cost function of the power company agent can be expressed as: Among them, Z i represents the electricity cost function of power company i; In summary, the third optimization target model is the cost model of the power company agent: The third optimization target model constraint condition is: 0＜α＜1 0＜β＜1 4. The method for collaboration among power, telecommunications and natural gas companies according to claim 3, characterized in that: The steps of constructing the fourth optimization target model are as follows: Since the natural gas company sells both natural gas services and gas-to-electricity services, its overall revenue is expressed as: maxU=max(U g +U G2P ) Among them, U g represents the revenue from gas sales services of natural gas companies, U G2P Revenue from the sale of gas-to-electricity services to natural gas companies; The revenue of a natural gas company from selling natural gas services can be expressed as: U g =(C all -ψ)ρ g Among them, C all represents the total natural gas reserves of the natural gas company, ρ g is the retail price of natural gas, ψ represents the amount of natural gas required by the natural gas company to provide gas-to-electricity services; in, It is a proportional coefficient between the retail price of natural gas and the retail price of gas-to-electricity service; The relationship between natural gas consumption and output power is as follows: ψ=a1+a2P out +a3(P out ) 2 Among them, P out is the power generation of the gas-to-electricity equipment, a1, a2, a3 are the heat rate curve coefficients in engineering practice; The power generation of the gas-to-electricity equipment of the natural gas company is the power consumption required by the power company agent, which can be expressed as: The revenue from the gas-to-electricity service sold by natural gas companies can be expressed as: In summary, the fourth optimization target model is the revenue model of the natural gas company: in, The fourth optimization target model constraint condition is: 0＜α＜1 0＜β＜1 5. A collaborative system between power, telecommunications and natural gas companies, characterized by: include: A parameter acquisition module, used to acquire a first initial parameter, a second initial parameter and a third initial parameter; wherein the first initial parameter includes the reserved power cost of the power company, the fitting coefficient of the load tracking deviation, the transmission bandwidth of the DAU, the probability of correct information transmission from the gateway to the user, the rate at which information reaches the DAU, the channel gain from the DAU to the gateway and from the relay to the gateway, the transmission power of the DAU, the retail price of the AGC service, and the total power of the base station of the telecom operator; the second initial parameter includes the total bandwidth of the telecom operator, the base price of the telecom service of the telecom operator, the number of DAUs in the base station, and the channel gain from the relay to the control center; the third initial parameter includes the total natural gas reserves of the natural gas company, the ratio coefficient of the natural gas retail price of the natural gas company to the retail price of the gas-to-electricity service, and the heat rate curve coefficient in engineering practice; A first model building module is used to establish a first optimization target model based on the first initial parameters, the payment schemes of each power company, the transmission power ratio allocated to the relay service by the telecommunications operator, the demand ratio of the gas-to-electricity service of the power company, and the retail price of the gas-to-electricity service of the natural gas company, with the goal of minimizing the cost of each power company and the payment schemes of each power company as decision variables; A second model building module is used to establish a second optimization target model based on the second initial parameters, the payment schemes of each power company and the transmission power ratio allocated to the relay service by the telecommunications operator, with the goal of maximizing the revenue of the telecommunications operator and the transmission power ratio allocated to the relay service by the telecommunications operator as a decision variable; A third model building module is used to establish a third optimization target model based on the first initial parameters, the payment plans of various power companies, the transmission power ratio allocated to the relay service by the telecommunications operator, the demand ratio of the gas-to-electricity service of the power company, and the retail price of the gas-to-electricity service of the natural gas company, with the goal of minimizing the agent cost of the power company and the demand ratio of the gas-to-electricity service of the power company as the decision variable; a fourth model building module, for establishing a fourth optimization target model based on the third initial parameter, the payment schemes of various power companies, the transmission power ratio allocated to the relay service by the telecommunications operator, the demand ratio of the gas-to-electricity service of the power company, and the retail price of the gas-to-electricity service of the natural gas company, with the goal of maximizing the revenue of the natural gas company and the retail price of the gas-to-electricity service of the natural gas company as the decision variable; A first solving module is used to solve the first optimization target model and the second optimization target model by using an iterative algorithm to obtain a superior game equilibrium solution; the superior game equilibrium solution includes the payment scheme of each power company in the first optimization target model and the transmission power ratio allocated to the relay service by the telecom operator in the second optimization target model; The second solving module is used to substitute the upper-level game equilibrium solution into the third and fourth optimization target models, and solve the third and fourth optimization target models by an iterative algorithm to obtain a lower-level game equilibrium solution; the lower-level game equilibrium solution includes the demand ratio of the gas-to-electricity service of the power company in the third optimization target model and the retail price of the gas-to-electricity service of the natural gas company in the fourth optimization target model; The third solving module is used to substitute the lower-level game equilibrium solution into the first and second optimization target models, and solve the first optimization target model and the second optimization target model by an iterative algorithm to obtain a new upper-level game equilibrium solution, and use the new upper-level game equilibrium solution to obtain a new lower-level game equilibrium solution by the method described in the second solving module, and judge whether the obtained overall game equilibrium solution is consistent with the result of the previous overall game equilibrium solution. If they are consistent, it is the global optimal solution, and if they are inconsistent, the loop iteration of this step is performed; An optimization result determination module, used to determine a global optimal optimization result, wherein the global optimal optimization result is composed of a constant upper-level game equilibrium solution and a constant lower-level game equilibrium solution; The steps of constructing the first optimization target model are as follows: Through the statistical analysis method of direct load control error, the power cost model of power company i (i∈N={1,2,......,N}) is established: in, is the reserved electricity cost of power company i, m i represents the payment plan of power company i, Q i represents the direct load control error that power company i needs to compensate for due to data packet loss during information transmission, ρ1 represents the retail price of gas-to-electricity service of natural gas company, ρ2 represents the retail price of AGC service, and β is the demand ratio of gas-to-electricity service of power company; According to the statistical analysis of direct load control error, the direct load control error that power company i needs to compensate due to data packet loss during information transmission can be expressed as: Q i =aP i l -b Among them, a and b are the fitting coefficients after statistical analysis of direct load control error, P i l is the packet loss rate of power company i; There is two-way communication between the power company and the user. The packet loss rate under the DF cooperative relay transmission strategy is constructed. Without loss of generality, only the packet loss during the downlink transmission process is considered. The packet loss rate of power company i is expressed as: Among them, T in is the rate at which information reaches the DAU, It is defined as the information receiving rate of gateway i under the DF cooperative relay strategy, and g is the probability of correct information transmission from the gateway to the user; From DAU i When the DF cooperative relay transmission mode is adopted to gateway i, the information receiving rate of gateway i is expressed as: Where W is DAU i The transmission bandwidth, DAU i The information transmission power, Assigned to DAU by telecom operators i The relay transmission power, DAU i Channel gain to gateway i, is the channel gain from relay to gateway i, DAU i Channel gain to the relay; Among them, m i It represents the payment plan that the power company i has made for the telecom operator. is the sum of payment schemes formulated by all power companies, N represents the set of power companies (i∈N={1,2,......,i,......,N}), α represents the proportion of transmission power allocated by the telecom operator to the relay service, and p represents the total power of the telecom operator; In summary, the first optimization target model is the cost model of power company i: The first optimization target model constraint condition is: 0＜α＜1 0＜β＜1 in, It is allocated to DAU by telecom operators i The maximum relay transmission power.

6. A storage medium, characterized in that: The storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for collaboration among power, telecommunication and natural gas companies as described in any one of claims 1 to 4.

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