Search

CN-115186926-B - Park energy optimization method and system based on electric-carbon sharing

CN115186926BCN 115186926 BCN115186926 BCN 115186926BCN-115186926-B

Abstract

The invention relates to a park energy optimization method and system based on electric-carbon sharing, wherein the method comprises the steps of obtaining a user side basic load model, a capacity model and a carbon emission model, constructing a user side income model, constructing a park carbon quota distribution model based on the total amount of park carbon quota and the typical daily average carbon emission of the same type of users, constructing an operator utility model according to the electric energy income and the carbon quota income of operators, constructing a Stokes master-slave game model, determining an objective function of the Stokes master-slave game model based on the user side income model and the operator utility model, optimizing the objective function, gaming the park operators and the users to reach game balance points, determining a user optimal load strategy and an operator optimal electric-carbon pricing strategy according to the game balance points, and realizing park energy optimization of electric-carbon sharing. The invention can keep balance between energy and carbon quota supply and demand in the park, promote clean energy consumption rate and reduce carbon emission in the park.

Inventors

  • LIU NIAN
  • LIU JINGYING

Assignees

  • 华北电力大学

Dates

Publication Date
20260512
Application Date
20220729

Claims (8)

  1. 1. A method of park energy optimization based on electro-carbon sharing, the method comprising: Acquiring a user side basic load model, a user side capacity model and a user side carbon emission model in a park, and constructing a user side income model based on energy flow-carbon flow coupling based on the user side basic load model, the user side capacity model and the user side carbon emission model; Establishing a park carbon quota allocation model based on the total amount of the park carbon quota and typical daily average carbon emission of the same type of users in a set time; constructing an operator utility model according to the electric energy benefits and the carbon quota benefits of operators in the park; Establishing a Starberg master-slave game model, and determining an objective function of the Starberg master-slave game model based on the user side income model and the operator utility model, wherein in the Starberg master-slave game model, a park operator influences user income by optimizing shared electricity price, carbon price and carbon quota in the park, a user influences park operator income by changing load consumption, and the park operator plays games with the user; Optimizing the objective function, and performing gaming of the park operator and the user until a gaming balance point is reached, wherein the earnings of the operator and the user at the gaming balance point reach the maximum value; Determining a user load strategy corresponding to the game balancing point as a user optimal load strategy, and determining a buying and selling electricity price and carbon price strategy corresponding to the game balancing point as an operator optimal electricity-carbon pricing strategy to realize energy optimization of an electricity-carbon shared park; the expression of the user side income model is as follows: ; Wherein, the Representing the benefits of the campus users, Indicating power consumption by users in a park The benefit of the production is that, Representing the benefit factor of the nth user, Representing the cost per unit of power produced by the self-contained power plant, Indicating the benefit to the user when there is a remaining energy source, Indicating the cost of purchasing electrical energy when the energy is not sufficient, The benefits of participating in carbon allocation sharing for the user, For the price of electricity sold in the campus, For the electricity purchase price in the campus, The carbon prices are shared for the campuses, For the remaining carbon quota for the campus subscriber t period, For the total energy produced by the nth user during period t, Total consumption load for nth user in t period; When park payload When the objective function is: When the park payload When the objective function is: ; Wherein, the Representing the benefits of the park operators at the time t; weighting the initial value of the carbon emission intensity for the period t; a selling price for electricity traded with the utility grid; an initial free carbon emission allowance allocated for historical carbon emissions; Carbon emission intensity for self-contained power plants; Generating power for the power plant of the nth user in the period t; a weighted carbon emission intensity initial value for the nth user at time t; Carbon prices for the external carbon market; Number of buyers for energy sharing in the campus; The number of sellers at the time of energy sharing for the campus; Total number of users involved in the transaction; To purchase electricity prices for trading with the utility grid.
  2. 2. The method for optimizing energy of a campus based on electricity-carbon sharing according to claim 1, wherein the obtaining a user side base load model, a user side capacity model, and a user side carbon emission model in the campus specifically comprises: the method comprises the steps of obtaining a user side basic load model for an nth user of a user side, wherein the user side basic load model represents the total consumption load of the nth user in a t period, and the total consumption load of the nth user is the sum of adjustable load, reducible load and fixed load of the nth user; The method comprises the steps of obtaining a user side productivity model, wherein the user side productivity model represents the total energy produced by an nth user in a t period, and the total energy produced by the nth user in the t period is the sum of clean energy produced by the nth user in the t period and the generated energy of a self-contained power plant in the t period; The method comprises the steps of obtaining a user side carbon emission model, wherein the user side carbon emission model represents carbon emission produced by a user in a t period, and determining the carbon emission of an nth user in the t period by obtaining the carbon emission intensity of the self-contained power plant, the self-contained power plant power generation amount of the nth user in the t period, the carbon emission intensity of an ith carbon emission source, unclean energy consumed by the carbon emission source i and a t period weighted carbon emission intensity initial value, and combining the total consumption load of any period of the nth user and the total energy produced by the nth user in any period.
  3. 3. The method for optimizing energy for a campus based on electro-carbon sharing according to claim 2, wherein the calculation formula of the initial value of the t-period weighted carbon emission intensity is: ; ; ; Wherein, the The initial value of the carbon emission intensity is weighted for the period t, Representing the carbon emission intensity obtained by tracking the carbon flow of the main network in the period t, The net purchase amount representing the initial states of all users at the current moment, The net sales power representing the initial status of all users at the current time, For the total energy produced by the nth user during period t, The initial total consumption load for the nth user during the period t.
  4. 4. The electricity-carbon sharing-based campus energy optimization method of claim 1, wherein the campus carbon quota allocation model has the expression: ; ; Wherein, the Representing the initial free carbon emission allowance of the user, As a typical daily average total carbon emission of the same type, Represents the typical daily average carbon emission of the nth user class, Representing the typical day of the nth user type The load average value of the time period, Represents the total amount of carbon quota for d-day park, Representing the quota coefficient.
  5. 5. The electricity-carbon sharing based campus energy optimization method of claim 1, wherein the operator utility model is expressed as: ; ; ; Wherein, the Indicating the return to the campus operator at time t, For the power return of the campus operator at time t, For carbon quota benefits for the campus operator at time t, Indicating the total net bid amount of the campus subscriber at time t, Indicating the total net sales volume of the campus subscribers at time t, Indicating the total payload of the campus subscribers at time t, For the price of electricity sold in the campus, For the electricity purchase price in the campus, The carbon prices are shared for the campuses, To trade the purchase price with the utility grid, For the selling price of electricity to be traded with the utility grid, For the remaining carbon quota for the campus subscriber t period, Carbon prices for the external carbon market.
  6. 6. A campus energy optimization system based on electro-carbon sharing, the system comprising: The system comprises a user side income model building unit, a user side income model generation unit and a user side income model generation unit, wherein the user side income model building unit is used for obtaining a user side basic load model, a user side capacity model and a user side carbon emission model in a park, and building the user side income model based on energy flow-carbon flow coupling based on the user side basic load model, the user side capacity model and the user side carbon emission model; a campus carbon quota allocation model building unit, the method comprises the steps of establishing a campus carbon quota allocation model based on the total amount of the campus carbon quota and typical daily average carbon emission of the same type of users in a set time; The operator utility model construction unit is used for constructing an operator utility model according to the electric energy benefits and the carbon quota benefits of operators in the park; The system comprises a starboard primary-secondary game model establishing and target function determining unit, a starboard primary-secondary game model establishing and target function determining unit and a target function determining unit, wherein the starboard primary-secondary game model establishing and target function determining unit is used for establishing a starboard primary-secondary game model and determining the target function of the starboard primary-secondary game model based on the user side income model and the operator utility model; The game balancing point determining unit is used for optimizing the objective function, and performing games of the park operator and the user until reaching a game balancing point, wherein the benefits of the operator and the user at the game balancing point reach the maximum value; The park energy optimization unit is used for determining a user load strategy corresponding to the game balancing point as a user optimal load strategy, determining a buying and selling electricity price and carbon price strategy corresponding to the game balancing point as an operator optimal electricity-carbon pricing strategy and realizing park energy optimization of electricity-carbon sharing; the expression of the user side income model is as follows: ; Wherein, the Representing the benefits of the campus users, Indicating power consumption by users in a park The benefit of the production is that, Representing the benefit factor of the nth user, Representing the cost per unit of power produced by the self-contained power plant, Indicating the benefit to the user when there is a remaining energy source, Indicating the cost of purchasing electrical energy when the energy is not sufficient, The benefits of participating in carbon allocation sharing for the user, For the price of electricity sold in the campus, For the electricity purchase price in the campus, The carbon prices are shared for the campuses, For the remaining carbon quota for the campus subscriber t period, For the total energy produced by the nth user during period t, Total consumption load for nth user in t period; When park payload When the objective function is: When the park payload When the objective function is: ; Wherein, the Representing the benefits of the park operators at the time t; weighting the initial value of the carbon emission intensity for the period t; a selling price for electricity traded with the utility grid; an initial free carbon emission allowance allocated for historical carbon emissions; Carbon emission intensity for self-contained power plants; Generating power for the power plant of the nth user in the period t; a weighted carbon emission intensity initial value for the nth user at time t; Carbon prices for the external carbon market; Number of buyers for energy sharing in the campus; The number of sellers at the time of energy sharing for the campus; Total number of users involved in the transaction; To purchase electricity prices for trading with the utility grid.
  7. 7. The system for optimizing energy of a campus based on electricity-carbon sharing of claim 6, wherein the user-side profit model building unit specifically comprises: A user side basic load model obtaining subunit, configured to obtain a user side basic load model for an nth user on a user side, where the user side basic load model represents a total consumption load of the nth user in a period t; the system comprises a user side productivity model acquisition subunit, a user side productivity model generation subunit, a power generation unit and a power generation unit, wherein the user side productivity model is used for acquiring a user side productivity model, and the user side productivity model represents total energy produced by an nth user in a t period; The system comprises a user side carbon emission model acquisition subunit, a carbon emission control subunit, a control subunit and a control subunit, wherein the user side carbon emission model is used for acquiring a user side carbon emission model and represents carbon emission produced by a user in a t period, and the carbon emission of the nth user in the t period is determined by acquiring the carbon emission intensity of the self-contained power plant, the self-contained power plant generating capacity of the nth user in the t period, the carbon emission intensity of an ith carbon emission source, unclean energy consumed by the carbon emission source i and a t period weighted carbon emission intensity initial value and combining the total consumption load of the nth user in any period and the total energy produced by the nth user in any period.
  8. 8. The electricity-carbon sharing based campus energy optimization system of claim 6 wherein the expression of the operator utility model is: ; ; ; Wherein, the Indicating the return to the campus operator at time t, For the power return of the campus operator at time t, For carbon quota benefits for the campus operator at time t, Indicating the total net bid amount of the campus subscriber at time t, Indicating the total net sales volume of the campus subscribers at time t, Indicating the total payload of the campus subscribers at time t, For the price of electricity sold in the campus, For the electricity purchase price in the campus, The carbon prices are shared for the campuses, To trade the purchase price with the utility grid, For the selling price of electricity to be traded with the utility grid, For the remaining carbon quota for the campus subscriber t period, Carbon prices for the external carbon market.

Description

Park energy optimization method and system based on electric-carbon sharing Technical Field The invention relates to the technical field of electric power systems, in particular to a park energy optimization method and system based on electric-carbon sharing. Background The electric power system is used as an important component of a hub of an energy chain and a carbon emission chain, and the installed capacity of new energy is created year by year under the promotion of solid policies and energy demands. Meanwhile, the carbon emission reduction potential of the source side of the power system is continuously excavated, the carbon emission is reduced by reducing carbon transformation and optimizing production of the thermal power generating unit, and the research on the carbon emission reduction potential of the load side user is less. And a large amount of new energy sources are connected with the grid to impact the stability of the power system, and the intermittent and fluctuating output leads to deep peak shaving of the thermal power, so that the carbon emission is increased. How to widen the emission reduction main body of the power system, dredge the carbon cost of the power generation side, and stimulate the deep emission reduction of the load side user is a key problem of improving the total carbon emission reduction upper limit of the power system. Disclosure of Invention The invention aims to provide a park energy optimization method and system based on electric-carbon sharing, which can keep balance between park energy and carbon quota supply and demand, improve clean energy consumption rate and reduce park carbon emission. In order to achieve the above object, the present invention provides the following solutions: the invention provides a park energy optimization method based on electric-carbon sharing, which comprises the following steps: Acquiring a user side basic load model, a user side capacity model and a user side carbon emission model in a park, and constructing a user side income model based on energy flow-carbon flow coupling based on the user side basic load model, the user side capacity model and the user side carbon emission model; Establishing a park carbon quota allocation model based on the total amount of the park carbon quota and typical daily average carbon emission of the same type of users in a set time; constructing an operator utility model according to the electric energy benefits and the carbon quota benefits of operators in the park; Establishing a Star primary-secondary game model, and determining an objective function of the Star primary-secondary game model based on the user side benefit model and the operator utility model, wherein in the Star primary-secondary game model, a park operator influences user benefits by optimizing shared electricity price, carbon price and carbon quota in the park, a user influences park operator benefits by changing load consumption, and the park operator plays games with the user; Optimizing the objective function, and performing gaming of the park operator and the user until a gaming balance point is reached, wherein the earnings of the operator and the user at the gaming balance point reach the maximum value; And determining a user load strategy corresponding to the game balancing point as a user optimal load strategy, and determining a buying and selling electricity price and carbon price strategy corresponding to the game balancing point as an operator optimal electricity-carbon pricing strategy to realize energy optimization of the electricity-carbon shared park. Optionally, the obtaining the user side base load model, the user side capacity model and the user side carbon emission model in the campus specifically includes: the method comprises the steps of obtaining a user side basic load model for an nth user of a user side, wherein the user side basic load model represents the total consumption load of the nth user in a t period, and the total consumption load of the nth user is the sum of adjustable load, reducible load and fixed load of the nth user; The method comprises the steps of obtaining a user side productivity model, wherein the user side productivity model represents the total energy produced by an nth user in a t period, and the total energy produced by the nth user in the t period is the sum of clean energy produced by the nth user in the t period and the generated energy of a self-contained power plant in the t period; The method comprises the steps of obtaining a user side carbon emission model, wherein the user side carbon emission model represents carbon emission produced by a user in a t period, and determining the carbon emission of an nth user in the t period by obtaining the carbon emission intensity of the self-contained power plant, the self-contained power plant power generation amount of the nth user in the t period, the carbon emission intensity of an ith carbon emission source, unclean energy consume