Regional integrated energy system optimization scheduling method considering immediate-long-term carbon emission financial market

Abstract

The invention discloses a regional integrated energy system optimization scheduling method considering an instant-long-term carbon emission financial market, and the method comprises the steps: building an actual carbon emission life cycle evaluation model based on life cycle evaluation, and obtaining the actual carbon emission of an integrated energy system; on the basis of a B-S pricing model, according to the actual carbon emission of the integrated energy system, a carbon emission permit instant transaction model and a carbon emission permit long-term transaction model are respectively established; establishing an optimal scheduling model of the integrated energy system in the immediate-long-term carbon emission permit trading market; and solving the optimal scheduling model of the integrated energy system in the immediate-long-term carbon emission permit trading market. According to the method, by considering the demand response of the energy consumption user, the electric load and gas load fluctuation of the energy consumption user can be effectively slowed down, the peak load shifting effect is achieved, the operation cost of the IES and the energy purchasing cost of the energy consumption user are reduced, and the win-win situation between the IES and the energy consumption user is achieved; a price signal in the instant carbon emission permit trading market guides reasonable distribution of carbon emission resources, and carbon emission reduction is promoted; carbon emission permissions are accumulated and sold in the long-term carbon emission permit trading market, additional financial benefits are brought, and enterprises are actively guided to achieve energy conservation and emission reduction.

Description

Technical Field

[0001] The invention relates to a method for optimizing and dispatching a regional integrated energy system taking into account an immediate and long-term carbon emission financial market, and belongs to the field of integrated energy system dispatching. Background Art

[0002] As the carbon trading market mechanism gradually improves, how to adapt to the diversity of future carbon trading models needs to be solved urgently. The integrated energy system fully utilizes the complementary characteristics of different energy sources, organically coordinates and optimizes the energy generation, transmission and distribution, conversion, storage, consumption and other links, and enables the coupling and transformation of multiple types of heterogeneous energy flows, thus realizing an integrated energy system of production, supply and marketing with cascade utilization and reasonable distribution of energy.

[0003] The optimal dispatch of regional integrated energy systems considering the immediate-forward carbon emission financial market can provide a reference for the construction of the carbon financial market while improving the economic benefits of the system by coordinating the complementarity of multiple energies. How to achieve the optimal dispatch of regional integrated energy systems considering the immediate-forward carbon emission financial market is a problem that needs to be solved. Summary of the invention

[0004] The present invention provides a method for optimizing the scheduling of a regional comprehensive energy system taking into account the immediate-forward carbon emission financial market, which is used to establish an optimal scheduling model for a regional comprehensive energy system taking into account the immediate-forward carbon emission financial market, and to solve the model to obtain an optimal operation plan for the regional comprehensive energy system taking into account the immediate-forward carbon emission financial market.

[0005] The technical solution of the present invention is:

[0006] A method for optimizing the dispatch of a regional integrated energy system considering the spot-forward carbon emission financial market, comprising:

[0007] Step 1: Establish a life cycle assessment model for actual carbon emissions based on life cycle assessment to obtain the actual carbon emissions of the integrated energy system;

[0008] Step 2: Based on the BS pricing model and the actual carbon emissions of the integrated energy system, establish a carbon emission rights spot trading model and a carbon emission rights forward trading model respectively;

[0009] Step 3: Establish an optimal dispatch model for the integrated energy system under the spot-forward carbon emission rights trading market;

[0010] Step 4: Solve the optimal scheduling model of the integrated energy system under the spot-forward carbon emission rights trading market.

[0011] The actual carbon emissions of the comprehensive energy system are expressed as:

[0012] D L=D e +D g +D WT +D PV -D c

[0013] Where: D L is the actual carbon emissions of IES; D e , D g , D WT With D PV are the carbon emissions of coal-fired units, gas-fired units, wind turbines and photovoltaic units respectively; D c is the total amount of CO2 captured;

[0014] The D e , D g , D WT , D PV With D c , the expression is:

[0015]

[0016] Where: T represents the total number of time periods; δ e is the actual total carbon emission coefficient per unit of coal-fired unit power generation; P G,t is the output power of the generator at time t; δ g is the actual total carbon emission coefficient of each unit of gas-fired power generation; P CHP,t , P GB,t is the operating power of the cogeneration unit and gas boiler during period t; WT is the actual total carbon emission coefficient per unit of electricity generated by the wind turbine; δ PV is the actual total carbon emission coefficient per unit of electricity generated by the photovoltaic unit; P WT,t , P PV,t They represent the power supply of wind power and photovoltaic units in period t respectively; D c,t is the total amount of CO2 captured during period t.

[0017] The actual total carbon emission coefficient δ per unit of coal-fired unit power generation e , the expression is:

[0018] δ e =δ pe +δ te +δ ue

[0019] δ pe =I cp η cp Q ce (1+α+β)

[0020]

[0021] δ ue =I ue Q ue

[0022] Where: pe is the carbon emission coefficient per unit of electricity generated in the coal mining and washing process; δ te is the carbon emission coefficient of coal transportation per unit of electricity generation; δ ue I is the carbon emission coefficient of the unit power generation of the coal-fired power generation unit in the energy cycle; cp is the unit loss of coal production in the energy cycle; η cp is the conversion rate of coal; Q ce is the carbon emission intensity of coal production; α and β are the unit power loss rate caused by spontaneous combustion of raw coal and the unit power loss rate caused by washing, respectively; m is the type of coal transportation mode; I i is the unit loss under the i-th mode of transportation; Q i K is the carbon emission intensity of greenhouse gases generated in the energy cycle under the i-th mode of transportation; i M is the ratio of the transport distance of the i-th transport mode to the total distance of the energy cycle; i is the total amount of coal transported by the ith mode of transportation during the energy cycle; D i is the average distance of the i-th mode of transportation; ue is the unit coal consumption in the power generation stage; Q ue It is the greenhouse gas carbon emission intensity in the energy cycle of coal-fired units.

[0023] The actual total carbon emission coefficient δ of each unit of gas-fired unit power generation g , the expression is:

[0024] δ g =δ pg +δ tg +δ ug

[0025]

[0026] Where: pg is the carbon emission coefficient per unit of electricity generated in the natural gas extraction process; δ tg is the carbon emission coefficient of natural gas transportation unit power generation; δ ug is the carbon emission coefficient of unit power generation in the energy cycle when the gas generator set is running; η gas is the escape rate of natural gas during extraction; Q pg is the carbon emission intensity of natural gas in the energy cycle; η pt Q is the ratio of pipeline transportation volume to total transportation volume in the transportation process of natural gas;pt is the carbon emission intensity of natural gas in pipeline transportation; Q lt is the carbon emission intensity of natural gas in liquefied transportation; ε1 is the carbon emission intensity of natural gas per unit of power generation; ζ eh is the conversion coefficient of thermal energy and electrical energy; ε2 is the carbon emission intensity of natural gas per unit heat.

[0027] The actual total carbon emission coefficient δ of the wind turbine per unit of power generation WT , the expression is:

[0028] δ WT =δ pwt +δ twt

[0029]

[0030] Where: pwt is the carbon emission coefficient per unit of electricity generated by the wind turbine during the production process; δ twt is the carbon emission coefficient corresponding to wind power during transportation; η wt It is the conversion coefficient between unit standard electric energy and energy loss of wind power equipment in the energy cycle; The loss rate of materials used to build wind power equipment in the energy cycle; Q pwt The carbon emission intensity of materials used to build wind turbines; V pwt Q is the energy content of the materials used to build wind power equipment; twt Carbon intensity of wind turbine construction materials used in energy cycle production; V twt Value for transport losses of wind turbine construction materials used in energy production.

[0031] The actual total carbon emission coefficient δ of the photovoltaic unit per unit of power generation PV , the expression is:

[0032] δ PV =δ ppv +δ tpv

[0033]

[0034] Where: ppv is the carbon emission coefficient per unit of electricity generated by the photovoltaic generator set during the production process; δ tpv is the carbon emission coefficient corresponding to photovoltaics during transportation; η pv It is the conversion coefficient between the unit standard electric energy and energy loss of photovoltaic equipment in the energy cycle; The loss rate of materials used to build photovoltaic devices in the energy cycle; Q ppv The carbon emission intensity of materials used to build photovoltaic units; Vppv Indicates the internal energy value of the materials used to build photovoltaic equipment; Q tpv Carbon emission intensity of materials used in photovoltaic devices for energy cycle production; V tpv Represents the transport loss value of photovoltaic system construction materials used in energy cycle production.

[0035] The carbon emission rights spot trading model is expressed as:

[0036] P cem-s =[E a -(1-μ)D L ]c cea -μD L c ccer

[0037] Where: P cem,t The current carbon emission trading income of the integrated energy system; cea is the predicted closing price of carbon emission rights trading; c ccer E is the closing price of the country's certified voluntary emission reductions; a is the quota applied for according to the scheduling plan on the previous day; μ is the proportion of the buyer's deposit to purchase its own quota from the seller; D L is the actual carbon emissions of the comprehensive energy system.

[0038] The carbon emission rights forward trading model is expressed as follows:

[0039]

[0040] Where: P cem-f E is the income from the forward carbon emissions trading of the integrated energy system; a is the quota applied for according to the scheduling plan the day before; μ is the proportion of the buyer's deposit to purchase its own quota from the seller; To predict the highest price of carbon trading; M ccer，t is the number of contracts at time t; K is the highest closing price of the predicted national certified emission reductions; ave is the average price; c ccer The closing price of the national certified voluntary emission reductions; D L is the actual carbon emissions of the comprehensive energy system.

[0041] The Step 3 includes: establishing an optimization model for upper-level operators of the integrated energy system under the spot and forward carbon emission rights trading markets; and establishing an optimization model for lower-level users of the integrated energy system under the spot and forward carbon emission rights trading markets.

[0042] The above-mentioned establishment of an optimization model for the upper-level operators of the integrated energy system under the spot and forward carbon emission rights trading markets includes: the optimization objective function of the upper-level operators of the integrated energy system under the spot carbon emission rights trading market, the optimization objective function and constraints of the upper-level operators of the integrated energy system under the forward spot carbon emission rights trading market: wherein, the constraints include: cogeneration unit constraints, gas boiler model, electric boiler model, energy storage constraints, new energy constraints, interconnection line and pipeline constraints, carbon capture operation model, power-to-gas two-stage operation model, and power balance constraints.

[0043] The beneficial effects of the present invention are:

[0044] (1) The life cycle assessment method is used to consider carbon emissions in all aspects of energy conversion, which solves the problem that the traditional accounting method only considers carbon emissions in the operation phase and obtains carbon emissions in the system more accurately.

[0045] (2) After considering the demand response of energy-consuming users, it can effectively slow down the fluctuation of electricity load and gas load of energy-consuming users, play the role of peak shaving and valley filling, reduce the operating cost of the integrated energy system and the energy purchase cost of energy-consuming users, and achieve a win-win situation between the integrated energy system and energy-consuming users.

[0046] (3) Price signals in the spot carbon emission rights trading market guide the rational allocation of carbon emission resources and promote carbon emission reduction; the accumulation and sale of carbon emission rights in the forward carbon emission rights trading market brings additional financial benefits and actively guides enterprises to achieve energy conservation and emission reduction. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 is a flow chart of the present invention;

[0048] Figure 2 This is the structural diagram of the regional integrated energy system;

[0049] Figure 3 Optimize the structure diagram for the double layer;

[0050] Figure 4 This is the result diagram of the electricity load dispatch in scenario 1 on a typical day in the first quarter;

[0051] Figure 5 This is the result diagram of the electricity load dispatch in scenario 4 on a typical day in the first quarter;

[0052] Figure 6 This is the heat load dispatch result diagram for scenario 1 on a typical day in the first quarter;

[0053] Figure 7 This is the heat load dispatch result diagram for scenario 4 on a typical day in the first quarter. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical scheme and advantages of the embodiments of the present invention clearer, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. It should be noted that the embodiments in this application and the features in the embodiments can be combined with each other arbitrarily without conflict.

[0055] Example 1: Figure 1-Figure 7 As shown, according to the first aspect of an embodiment of the present invention, a method for optimizing the scheduling of a regional integrated energy system considering the spot-forward carbon emission financial market is provided, including: Step 1, establishing a life cycle assessment model of actual carbon emissions based on life cycle assessment to obtain the actual carbon emissions of the integrated energy system; Step 2, based on the BS pricing model, according to the actual carbon emissions of the integrated energy system, establishing a carbon emission rights spot trading model and a carbon emission rights forward trading model respectively; Step 3, establishing an optimal scheduling model for the integrated energy system under the spot-forward carbon emission rights trading market; Step 4, using the KKT theory to solve the optimal scheduling model for the integrated energy system under the spot-forward carbon emission rights trading market, and obtaining the optimal operation plan for the integrated energy system under the spot and forward carbon emission rights trading markets.

[0056] Furthermore, the actual carbon emissions of the comprehensive energy system are expressed as:

[0057] D L =D e +D g +D WT +D PV -D c

[0058] Where: D L is the actual carbon emissions of IES; D e , D g , D WT With D PV are the carbon emissions of coal-fired units, gas-fired units, wind turbines and photovoltaic units respectively; D c is the total amount of CO2 captured;

[0059] The D e , D g , D WT , D PV With D c , the expression is:

[0060]

[0061] Where: T represents the total number of time periods; δ eis the actual total carbon emission coefficient per unit of coal-fired unit power generation; P G,t is the output power of the generator at time t; δ g is the actual total carbon emission coefficient of each unit of gas-fired power generation; P CHP,t , P GB,t is the operating power of the cogeneration unit and gas boiler during period t; WT is the actual total carbon emission coefficient per unit of electricity generated by the wind turbine; δ PV is the actual total carbon emission coefficient per unit of electricity generated by the photovoltaic unit; P WT,t , P PV,t They represent the power supply of wind power and photovoltaic units in period t respectively; D c,t is the total amount of CO2 captured during period t.

[0062] Furthermore, the actual total carbon emission coefficient δ per unit of coal-fired unit power generation e , the expression is:

[0063] δ e =δ pe +δ te +δ ue

[0064] δ pe =I cp η cp Q ce (1+α+β)

[0065]

[0066] δ ue =I ue Q ue

[0067] Where: pe is the carbon emission coefficient per unit of electricity generated in the coal mining and washing process; δ te is the carbon emission coefficient of coal transportation per unit of electricity generation; δ ue I is the carbon emission coefficient of the unit power generation of the coal-fired power generation unit in the energy cycle; cp is the unit loss of coal production in the energy cycle; η cp is the conversion rate of coal; Q ce is the carbon emission intensity of coal production; α and β are the unit power loss rate caused by spontaneous combustion of raw coal and the unit power loss rate caused by washing, respectively; m is the type of coal transportation mode; I i is the unit loss under the i-th mode of transportation; Q i K is the carbon emission intensity of greenhouse gases generated in the energy cycle under the i-th mode of transportation; iM is the ratio of the transport distance of the i-th transport mode to the total distance of the energy cycle; i is the total amount of coal transported by the ith mode of transportation during the energy cycle; D i is the average distance of the i-th mode of transportation; ue is the unit coal consumption in the power generation stage; Q ue It is the greenhouse gas carbon emission intensity in the energy cycle of coal-fired units.

[0068] Furthermore, the actual total carbon emission coefficient δ of each unit of gas-fired unit power generation is g , the expression is:

[0069] δ g =δ pg +δ tg +δ ug

[0070]

[0071] Where: pg is the carbon emission coefficient per unit of electricity generated in the natural gas extraction process; δ tg is the carbon emission coefficient of natural gas transportation unit power generation; δ ug is the carbon emission coefficient of unit power generation in the energy cycle when the gas generator set is running; η gas is the escape rate of natural gas during extraction; Q pg is the carbon emission intensity of natural gas in the energy cycle; η pt Q is the ratio of pipeline transportation volume to total transportation volume in the transportation process of natural gas; pt is the carbon emission intensity of natural gas in pipeline transportation; Q lt is the carbon emission intensity of natural gas in liquefied transportation; ε1 is the carbon emission intensity of natural gas per unit of power generation; ζ eh is the conversion coefficient of thermal energy and electrical energy; ε2 is the carbon emission intensity of natural gas per unit heat.

[0072] Furthermore, the actual total carbon emission coefficient δ of the wind turbine per unit of power generation is WT , the expression is:

[0073] δ WT =δ pwt +δ twt

[0074]

[0075] Where: pwt is the carbon emission coefficient per unit of electricity generated by the wind turbine during the production process; δ twt is the carbon emission coefficient corresponding to wind power during transportation; ηwt It is the conversion coefficient between unit standard electric energy and energy loss of wind power equipment in the energy cycle; The loss rate of materials used to build wind power equipment in the energy cycle; Q pwt The carbon emission intensity of materials used to build wind turbines; V pwt Q is the energy content of the materials used to build wind power equipment; twt Carbon intensity of wind turbine construction materials used in energy cycle production; V twt Value for transport losses of wind turbine construction materials used in energy production.

[0076] Furthermore, the actual total carbon emission coefficient per unit of power generation of the photovoltaic unit is PV , the expression is:

[0077] δ PV =δ ppv +δ tpv

[0078]

[0079] Where: ppv is the carbon emission coefficient per unit of electricity generated by the photovoltaic generator set during the production process; δ tpv is the carbon emission coefficient corresponding to photovoltaics during transportation; η pv It is the conversion coefficient between the unit standard electric energy and energy loss of photovoltaic equipment in the energy cycle; The loss rate of materials used to build photovoltaic devices in the energy cycle; Q ppv The carbon emission intensity of materials used to build photovoltaic units; V ppv Indicates the internal energy value of the materials used to build photovoltaic equipment; Q tpv Carbon emission intensity of materials used in photovoltaic devices for energy cycle production; V tpv Represents the transport loss value of photovoltaic system construction materials used in energy cycle production.

[0080] Furthermore, the carbon emission rights spot trading model is expressed as:

[0081] P cem-s =[E a -(1-μ)D L ]c cea -μD L c ccer

[0082] Where: P cem,t The current carbon emission trading income of the integrated energy system; cea is the predicted closing price of carbon emission rights trading; c ccer E is the closing price of the country's certified voluntary emission reductions;a is the quota applied for according to the scheduling plan on the previous day; μ is the proportion of the buyer's deposit to purchase its own quota from the seller; D L is the actual carbon emissions of the comprehensive energy system.

[0083] Furthermore, the carbon emission rights forward trading model is expressed as follows:

[0084]

[0085] Where: P cem-f E is the income from the forward carbon emissions trading of the integrated energy system; a is the quota applied for according to the scheduling plan the day before; μ is the proportion of the buyer's deposit to purchase its own quota from the seller; To predict the highest price of carbon trading; M ccer，t is the number of contracts at time t; K is the highest closing price of the predicted national certified emission reductions; ave is the average price; c ccer The closing price of the national certified voluntary emission reductions; D L is the actual carbon emissions of the comprehensive energy system.

[0086] Furthermore, the Step 3 includes: establishing an optimization model for upper-level operators of the integrated energy system under the spot and forward carbon emission rights trading markets; and establishing an optimization model for lower-level users of the integrated energy system under the spot and forward carbon emission rights trading markets.

[0087] Furthermore, the establishment of an optimization model for the upper-level operator of the integrated energy system under the spot and forward carbon emission rights trading markets includes: the optimization objective function of the upper-level operator of the integrated energy system under the spot carbon emission rights trading market, the optimization objective function and constraints of the upper-level operator of the integrated energy system under the forward spot carbon emission rights trading market: wherein the constraints include: cogeneration unit constraints, gas boiler model, electric boiler model, energy storage constraints, new energy constraints, interconnection line and pipeline constraints, carbon capture operation model, power-to-gas two-stage operation model, and power balance constraints;

[0088] The optimization objective function of the upper-level operator of the integrated energy system under the spot carbon emission rights trading market is:

[0089] minC IES1 =C p +C buy +C P,DR +C H,DR +P cem-s

[0090] Where: C IES1 To consider the comprehensive energy system operating cost in the spot market; C pis the cost of thermal power; C buy is the cost of purchasing energy from the upper energy grid; C P,DR is the electricity load demand response cost; C H,DR is the heat load demand response cost; P cem,t IES spot carbon emissions trading income;

[0091] The optimization objective function of the upper-level operator of the integrated energy system under the forward carbon emission rights trading market is:

[0092] minC IES2 =C p +C buy +C P,DR +C H,DR +P cem-f

[0093] Where: C IES2 To consider the comprehensive energy system operating costs in the forward market; C p is the thermal power cost; C buy is the cost of purchasing energy from the upper energy grid; C P,DR is the electricity load demand response cost; C H,DR is the heat load demand response cost; P cem-f It is the income from IES forward carbon emission trading.

[0094] According to the second aspect of an embodiment of the present invention, a regional integrated energy system optimization and scheduling system considering the spot-forward carbon emission financial market is provided, including: an acquisition module, used to establish an actual carbon emission life cycle assessment model based on life cycle assessment, and obtain the actual carbon emissions of the integrated energy system; a first establishment module, used to establish a carbon emission rights spot trading model and a carbon emission rights forward trading model based on the BS pricing model and the actual carbon emissions of the integrated energy system; a second establishment module, used to establish an optimized scheduling model for the integrated energy system under the spot-forward carbon emission rights trading market; a solution module, used to solve the optimized scheduling model for the integrated energy system under the spot-forward carbon emission rights trading market, and obtain the optimized operation plan of the integrated energy system under the spot and forward carbon emission rights trading markets.

[0095] Further, the specific principles of the present invention are given as follows:

[0096] Furthermore, the Step 1 includes:

[0097] S1.1: Establish a life cycle assessment model for actual carbon emissions based on life cycle assessment. The life cycle assessment (LCA) energy cycle of the integrated energy system (IES) mainly includes coal, natural gas, solar energy and wind energy. The carbon emissions of the energy cycle mainly come from four parts: energy extraction, transportation, power generation and operation, and waste gas treatment. In conventional carbon emission accounting methods, the greenhouse gas emissions of new energy sources such as photovoltaics and wind power are very small during operation, so the carbon emissions are negligible; while the life cycle assessment (LCA) energy cycle takes into account the greenhouse gas emissions of new energy unit production, construction and energy transportation, and can more accurately obtain the greenhouse gas emissions of new energy units.

[0098] δ e =δ pe +δ te +δ ue

[0099] δ pe =I cp η cp Q ce (1+α+β)

[0100]

[0101] δ ue =I ue Q ue

[0102] Where: e is the actual total carbon emission coefficient per unit of coal-fired unit power generation; δ pe is the carbon emission coefficient per unit of electricity generated in the coal mining and washing process; δ te is the carbon emission coefficient of coal transportation per unit of electricity generation; δ ue I is the carbon emission coefficient of the unit power generation of the coal-fired power generation unit in the energy cycle; cp is the unit loss of coal production in the energy cycle, which is taken as 0.1; η cp is the conversion rate of coal, generally 90%; Q ce is the carbon emission intensity of coal production, which is 1.08; α and β are the unit power loss rate caused by spontaneous combustion of raw coal and the unit power loss rate caused by washing, which are 10% and 15% respectively; m is the type of coal transportation, mainly including railway, road, water transportation, etc.; I i is the unit loss under the i-th mode of transportation; Q i K is the carbon emission intensity of greenhouse gases generated in the energy cycle under the i-th mode of transportation; iM is the ratio of the transport distance of the i-th transport mode to the total distance of the energy cycle; i is the total amount of coal transported by the ith mode of transportation during the energy cycle; D i is the average distance of the i-th mode of transportation; ue is the unit coal consumption in the power generation stage, which is 0.3g / MWh; Q ue is the greenhouse gas carbon emission intensity in the energy cycle of the coal-fired unit, which is taken as 0.86.

[0103] δ g =δ pg +δ tg +δ ug

[0104]

[0105] Where: g is the actual total carbon emission coefficient of each unit of gas-fired unit power generation; δ pg is the carbon emission coefficient per unit of electricity generated in the natural gas extraction process; δ tg is the carbon emission coefficient of natural gas transportation unit power generation; δ ug is the carbon emission coefficient of unit power generation in the energy cycle when the gas generator set is running; η gas is the escape rate of natural gas during extraction, generally 10%; Q pg is the carbon emission intensity of natural gas in the energy cycle, which is 0.101; η pt It is the ratio of pipeline transportation volume to total transportation volume in the transportation process of natural gas, which is generally taken as 75%; Q pt is the carbon emission intensity of natural gas in pipeline transportation, which is 0.00575; Q lt is the carbon emission intensity of natural gas in liquefied transportation, which is 0.06; ε1 is the carbon emission intensity of natural gas per unit of power generation, which is 0.371; ζ eh is the conversion coefficient of heat energy and electricity, which is generally taken as 0.75; ε2 is the carbon emission intensity per unit heat of natural gas, which is generally taken as 0.39.

[0106] δ WT =δ pwt +δ twt

[0107]

[0108] Where: WT is the actual total carbon emission coefficient per unit of electricity generated by the wind turbine; δ pwt is the carbon emission coefficient per unit of electricity generated by the wind turbine during the production process; δ twt is the carbon emission coefficient corresponding to wind power during transportation; ηwt It is the conversion coefficient between the unit standard electric energy and energy loss of wind power equipment in the energy cycle, which is generally taken as 0.35; is the loss rate of wind power equipment construction materials in the energy cycle, which is 0.1; Q pwt is the carbon emission intensity of materials used in the construction of wind turbines, which is taken as 0.007; V pwt is the internal energy value of the material; Q twt is the carbon emission intensity of construction materials used in energy cycle production, which is 0.01; V twt This is the transport loss value of the material used in energy cycle production, which is taken as 0.1.

[0109] δ PV =δ ppv +δ tpv

[0110]

[0111] Where: PV is the actual total carbon emission coefficient per unit of power generation of the photovoltaic unit; δ ppv is the carbon emission coefficient per unit of electricity generated by the photovoltaic generator set during the production process; δ tpv is the carbon emission coefficient corresponding to photovoltaics during transportation; η pv It is the conversion coefficient between the unit standard electric energy and energy loss of photovoltaic equipment in the energy cycle, which is generally taken as 0.35; is the loss rate of photovoltaic equipment construction materials in the energy cycle, which is taken as 0.1; Q ppv The carbon emission intensity of materials used in the construction of photovoltaic units is taken as 0.03; V ppv Indicates the internal energy value of the material; Q tpv V is the carbon emission intensity of construction materials used in energy cycle production, which is 0.03; tpv It represents the transport loss value of the material used in energy cycle production, which is taken as 0.1.

[0112] D L =D e +D g +D WT +D PV -D c

[0113]

[0114] Where: D L is the actual carbon emissions of IES; D e , D g , D WT With D PVare the carbon emissions of coal-fired units, gas-fired units, wind turbines and photovoltaic units respectively; D c is the total amount of CO2 captured; T represents 24 hours a day; P G ,t is the output power of the generator at time t; P CHP ,t、P GB , t is the operating power of the cogeneration unit and gas boiler during period t; P WT ,t、P PV , t represent the power supply of wind power and photovoltaic units in period t respectively; D c , t is the total amount of CO2 captured during period t.

[0115] Furthermore, the Step 2 includes:

[0116] S2.1: Establish a BS pricing model. Carbon options are mostly European options, and their pricing method generally adopts the BS model based on a complete market. The BS model is a very mature option pricing model, and the assumptions it meets have been verified in the literature. The call option pricing model is:

[0117]

[0118]

[0119]

[0120] Where: C ccer,t is the CCER call option price signed at time t; a t is the CCER market price at time t; is the exercise price of the carbon emission option, and K ave 110%; t is the implied volatility of CCER price at time t, usually a constant, taken as 0.2; N(d1) and N(d2) are the cumulative probability distribution functions of standard normal distribution variables d1 and d2 respectively; r is the annual risk-free compound interest rate, usually the bank demand deposit rate, taken as 20%.

[0121] S2.2: Establish a spot trading model for carbon emission rights. Participants can choose to participate in spot or option trading according to their own trading strategies. The spot market is composed of daily quota spot transactions, and the forward market completes option transactions with reference to the price of the spot market. There are a large number of high-carbon emission manufacturing industries in the market that need to purchase a large number of quotas to avoid fines. In this open market, the price reflects the demand for national certified voluntary emission reductions and carbon quotas. Considering the development progress of carbon emission exchanges and the "dual carbon" goals, refer to the market rules of the European Energy Exchange, and plan quotas on a daily basis according to the daily power generation plan. Before the exchange closes, the national certified voluntary emission reductions and carbon quotas are settled based on the closing price of carbon emission rights on that day and the grid-connected electricity of various market entities.

[0122] P cem-s =[E a -(1-μ)D L ]c cea -μD L c ccer

[0123]

[0124] Where: P cem,t is the IES spot carbon emissions trading income; c cea is the predicted closing price of carbon emission rights trading, which is 90.63 yuan / t; is the quota applied for according to the dispatch plan on the previous day, and each power plant allocates it to each dispatch cycle according to the power generation plan; c ccer E is the closing price of the country's certified voluntary emission reductions; a is the quota applied for according to the scheduling plan the day before; μ is the proportion of the buyer's deposit to purchase its own quota from the seller, which is 0.1.

[0125] S2.3: Establish a carbon emission rights forward trading model. Refer to the market rules of the European Energy Exchange, which stipulates that every three months is a settlement cycle. The buyer pays a deposit to buy a European call option on the certified voluntary emission reduction of the country with a percentage of μ of its own quota from the seller, and obtains the average price K after three months. ave The right to purchase 110% of the contracted quantity of national certified voluntary emission reductions, if the market price of national certified voluntary emission reductions on the day of exercise is greater than or equal to 1.1K ave If the market price of the national certified voluntary emission reductions is less than 1.1K on the day of exercise, ave For integrated energy system operators, when purchasing national certified voluntary emission reduction options, the deposit they need to pay or receive is the option price c ccer and the contract quantity M ccer The product of is the carbon emission trading income of the comprehensive energy system after signing the forward trading contract.

[0126]

[0127] Where: P cem-f IES forward carbon emissions trading income; To predict the highest price of carbon trading; the calculation cycle in the forward carbon emission rights trading market model changes from every hour to every settlement cycle T; M ccer，t is the number of contracts at time t; The highest price of the predicted closing price of national certified voluntary emission reductions. Unlike the spot market which is cleared daily, carbon trading and national certified voluntary emission reductions are stored during the settlement period and sold at the highest price to obtain the maximum profit.

[0128] Furthermore, the Step 3 includes:

[0129] S3.1: Establish an optimization model for the upper-level operators of the integrated energy system under the immediate and forward carbon emission rights trading market. The optimization model for the upper-level operators is as follows, including: the objective function and constraints of minimizing the sum of the thermal power cost, the cost of purchasing energy from the upper energy network, the electric load demand response cost, the thermal load demand response cost, and the immediate / forward carbon emission trading income; among which, the constraints include cogeneration unit constraints, gas boiler model, electric boiler model, energy storage constraints, new energy constraints, interconnection line and pipeline constraints, carbon capture operation model, power-to-gas two-stage operation model, and power balance constraints.

[0130] The upper model needs to optimize the output of the equipment in the system and formulate the time-of-use energy price of each energy source to be passed on to energy-consuming users. Its objective function can be described as: the carbon emission trading in the spot carbon emission trading market is settled daily, which is consistent with the day-ahead dispatching rules of the power system. Therefore, 24 hours is a dispatching cycle. Carbon emission trading participates in power dispatching in the form of carbon emission costs, and the quota price is the daily settlement price predicted based on the data. In the forward carbon emission trading market, carbon emission trading is based on the period T Q Settlement is carried out. At this time, the production and consumption process of CEA and CCER in the spot market determines the market price and no longer affects power dispatch. In the forward carbon emission rights trading market, carbon finance and power system dispatch are naturally separated into two systems. The option price and final settlement still refer to the price of the spot carbon emission rights trading market. The spot and forward carbon emission rights trading market systems are exactly the same. The only difference is that the spot carbon emission rights trading market has carbon emission constraints, and the other constraints are the same.

[0131] The optimization objective function of the upper-level operator of the integrated energy system under the spot carbon emission rights trading market is:

[0132] minC IES =C p +C buy +C P,DR +CH,DR +P cem-s

[0133] The optimization objective function of the upper-level operator of the integrated energy system under the forward carbon emission rights trading market is:

[0134] min C IES =C p +C buy +C P,DR +C H,DR +P cem-f

[0135] Where: C IES To consider the comprehensive energy system operating costs in the spot / forward markets; C p is the thermal power cost; C buy is the cost of purchasing energy from the upper energy grid; C P,DR is the electricity load demand response cost; C H,DR is the heat load demand response cost; P cem,t is the IES spot carbon emissions trading income; P cem-f It is the income from IES forward carbon emission trading.

[0136] The specific calculation model is as follows:

[0137]

[0138] Where: P G,t is the output power of the generator at time t; a, b, c are the cost coefficients of the generator set, which are 36, 0.38, and 0.0034 respectively.

[0139]

[0140] Where: P e,buy,t Q is the amount of electricity purchased during period t; g,buy,t is the gas purchase volume during period t; p e,t and p g,t are the electricity and gas selling prices of the superior system during period t respectively;

[0141] C P,DR =C P,tran +C P,cut

[0142] Where: C P,tran is the compensation cost of the transferable electric load; C P,cut Compensate for electrical load reduction costs.

[0143] C H,DR =C H,tran +C H,cut

[0144] Where: CH,tran is the compensation cost of the transferable heat load; C H,cut Compensate for heat load reduction costs.

[0145]

[0146] Where: C sell The income from IES selling energy to users; e,t and c h,t The prices of electricity and heat energy are set by the integrated energy system for users in period t respectively; P DR,t represents the electric load in period t after demand response; H DR,t represents the heat load during period t after demand response.

[0147] Constraints:

[0148] (1) Constraints on cogeneration units

[0149] P CHP,t =Q CHP,t η CHP,e

[0150] H CHP,t =Q CHP,t η CHP,h

[0151] P CHP,min ≤P CHP,t ≤P CHP,max

[0152] ΔP CHP,min ≤P CHP,t -P CHP,t-1 ≤ΔP CHP,max

[0153] Where: P CHP,t is the operating power of the cogeneration unit during period t; H CHP,t is the heating power of the cogeneration unit during period t; Q CHP,t The natural gas is input to the cogeneration unit during period t; η CHP,e , η CHP,h P is the power generation efficiency and heating efficiency of the cogeneration unit; CHP,min and P CHP,max are the upper and lower limits of the power generation capacity of the cogeneration unit; ΔP CHP,min , ΔP CHP,max are the lower and upper limits of the climbing capability of the cogeneration unit, which are 0.2P CHP,min , 0.2P CHP,max .

[0154] (2) Gas boiler model

[0155] H GB,t=Q GB,t η GB

[0156] H GB,min ≤H GB,t ≤H GB,max

[0157] Where: H GB,t and Q GB,t are the heating power and gas consumption of the gas boiler during period t; η GB is the heating efficiency of the gas boiler; H GB,max and H GB,min They are the upper and lower limits of the heating power of the gas boiler respectively.

[0158] (3) Electric boiler model

[0159] H HP,t =η HP P HP,t

[0160] P HP,min ≤P HP,t ≤P HP,max

[0161] Where: H HP,t and P HP,t are the heating power of the electric boiler and the input power in period t respectively; η HP is the heating efficiency of the electric boiler, which is 0.5; P HP,min , P HP,max They are respectively the lower limit and upper limit of the input electric power of the electric boiler.

[0162] (4) Energy storage constraints

[0163] E x,t+1 =E x,t +P x,ch,t η x,ch Δt-P x,dis,t Δt / η x,dis

[0164] E x,min ≤E x,t ≤E x,max

[0165] 0≤S x,ch,t P x,ch,t ≤P x,ch,max

[0166] 0≤S x,dis,t P x,dis,t ≤P x,dis,max

[0167] E x,0 =E x,24

[0168] S x,ch,t +S x,dis,t =1

[0169] Where: subscript x represents the energy storage type, which are electric energy storage (ESS), thermal energy storage (TES), hydrogen energy storage (HS), and gas storage tank (GSD); P x,ch,t and P x.dis,t They represent the energy storage and release power of the energy storage device at time t respectively; P x,ch,max and P x.dis,max is the maximum energy storage and release power of the energy storage device; S x,ch,t and S x,dis,t It indicates the energy storage and release state of the energy storage device; E x,t is the state of the energy storage device at time t; η x,ch and η x,dis They represent the energy storage and release efficiency of the energy storage device, both of which are taken as 0.9; E x,max and E x,min is the maximum and minimum energy storage state of the energy storage device; E x,0 and E x,24 are the states of the energy storage device at the initial and final moments respectively; Δt represents the time interval of 1h.

[0170] (5) New energy constraints

[0171] P WT,t ≤P WT,pre,t

[0172] P PV,t ≤P PV,pre,t

[0173] Where: P WT,pre,t and P PV,pre,t are the predicted output values ​​of wind power and photovoltaic power at time t respectively.

[0174] (6) Tie lines and pipeline constraints

[0175] 0≤P e,buy,t ≤P e,buy,max

[0176] 0≤Q g,buy,t ≤Q g,buy,max

[0177] Where: P e,buy,max , Q g,buy,max They are the upper limit of electricity purchased from the power grid and the upper limit of gas purchased from the gas grid.

[0178] (7) Carbon capture operation model

[0179]

[0180] Where: P CCS,t is the operating power of the carbon capture device during period t; P CCSF,t , P CCSO,t are the fixed energy consumption and operating energy consumption of the carbon capture device during period t; c D is the power consumption per unit CO2 captured, which is 0.3; c,t is the total amount of CO2 captured during period t; η c is the CO2 capture rate, which is 0.8; Q P2G,c,t Q is the amount of CO2 consumed by the P2G device during methanogenesis during period t; c,t is the amount of CO2 captured by the carbon capture device during period t. e is the carbon emission intensity of the generator, which is taken as 1.08.

[0181] (8) Power-to-gas two-stage operation model

[0182]

[0183] Where: Q P2G,g,t is the amount of methane synthesized by the P2G device during period t; P P2G,t is the operating power of the P2G device during period t; Q MR,hy,t is the amount of hydrogen consumed in the methanogenic stage during period t; υ is the coefficient of CO2 consumption during the methanogenic reaction, which is taken as 0.25; is the efficiency of hydrogen production by electrolysis, which is taken as 50%; is the methanogenation efficiency, which is 85%; Q P2G,hy,t The amount of hydrogen produced by the P2G device in period t.

[0184] (9) Power balance constraints

[0185] P DR,t =P CHP,t +P WT,t +P PV,t +P ESS,dis,t -P HP,t -P ESS,ch,t +P e,buy,t -P P2G,t -P CSS,t

[0186] H DR,t =H CHP,t +H GB,t +H HP,t -P TES,dis,t +P TES,ch,t

[0187] Q g,buy,t =Q CHP,t +Q GB,t +P GSD,ch,t -QP2G,g,t -P GSD,dis,t

[0188] q P2G,hy,t =Q MR,hy,t +P HS,ch,t -P HS,dis,t

[0189] S3.2: Establish an optimization model for lower-level users of the integrated energy system under the spot and forward carbon emission rights trading market. The optimization model for lower-level users is as follows, including: users adjust flexible loads according to the energy selling price of electric and thermal energy, with the objective function and constraints of minimizing the sum of energy costs; wherein the constraints include electric load demand response constraints and thermal load demand response constraints.

[0190] After the upper-level integrated energy system operator determines the energy sales strategy, the lower-level users need to adjust the flexible load according to the energy sales price of electric and thermal energy in order to minimize the energy cost. The objective function can be expressed as follows:

[0191] minC load =C sell -C DR

[0192] C DR =C P,DR +C H,DR

[0193] Where: C load Energy cost for users; C DR is the demand response cost.

[0194] Electric load is divided into basic electric load, transferable electric load and curtailable electric load. The specific electric load demand response constraints can be expressed as follows:

[0195] P DR,t =P load,t +P tran,t -P cut,t

[0196] Where: P load,t Represents the basic electric load during period t; P tran,t represents the transferable electric load in period t; P cut,t Indicates the amount of electrical load that can be reduced during period t.

[0197] Transferable loads are more flexible in scheduling. When adjusting, it is only necessary to ensure that the total load remains unchanged within the scheduling cycle. The load transfer amount in each time period can be flexibly adjusted. Therefore, the electric load is divided into basic electric load, transferable electric load and reducible electric load.

[0198]

[0199] 0≤P tran,t ≤P tran,max

[0200]

[0201] Where: P tran,sum represents the sum of loads that can be transferred within the total dispatch time T; P tran,max Indicates the upper limit of the transferable load; c tran The unit price of compensation for unit electric power transfer is taken as 0.4.

[0202] 0≤P cut,t ≤P cut,max

[0203]

[0204] Where: P cut,max Indicates the upper limit of load reduction; c cut They are the unit price of compensation for unit electric power reduction, which is 0.08.

[0205] Adjusting the heat load within a certain range will not have an adverse impact on production and operation activities, so the heat load is divided into basic heat load, transferable heat load and reducible heat load.

[0206] H DR,t =H load,t +H tran,t -H cut,t

[0207] Where: H load,t Represents the basic heat load during period t; H tran,t represents the transferable heat load in period t; H cut,t Indicates the amount of heat load that can be reduced during period t.

[0208]

[0209] 0≤H tran,t ≤H tran,max

[0210]

[0211] Where: H tran,t represents the transferable load in period t; H tran,sum represents the sum of loads that can be transferred within the total dispatch time T; H tran,max Indicates the upper limit of the transferable load; c H,tran The unit price of compensation for unit thermal power transfer is 0.2.

[0212] 0≤H cut,t ≤H cut,max

[0213]

[0214] Where: H cut,max Indicates the upper limit of load reduction; c H,cut The unit price of compensation for unit thermal power reduction is 0.09.

[0215] Furthermore, in order to analyze the impact of the proposed model on the carbon emissions and economic benefits of the integrated energy system under the spot and forward carbon emission rights trading markets, this paper sets up four scenarios for comparative analysis, namely:

[0216] Scenario 1: The integrated energy system does not consider demand response, traditional carbon trading, spot carbon trading, and forward carbon trading;

[0217] Scenario 2: Integrated energy system taking into account demand response;

[0218] Scenario 3: Integrated energy system considering demand response and traditional carbon trading;

[0219] Scenario 4: Integrated energy system taking into account demand response and spot carbon trading.

[0220] According to the above four scenarios, the dispatch results of the integrated energy system are analyzed.

[0221] In order to verify the effectiveness and applicability of the proposed model, the present invention uses 24 hours as a cycle and 1 hour as a step size to solve it using KKT theory. The equipment parameters are shown in Table 1.

[0222] Table 1 Unit operating parameters

[0223] parameter Numeric <![CDATA[η CHP,e ]]> 0.38 <![CDATA[η CHP,h ]]> 0.67 <![CDATA[η GB ]]> 0.45 <![CDATA[η c ]]> 0.9

[0224] The operating costs and carbon emissions of the comprehensive energy system are shown in Table 2. From the operating results in Table 2, it can be seen that compared with Scenario 1 without considering demand response, the operating cost of Scenario 2 is reduced by 16,400 yuan. In terms of the total carbon emissions of the system, since demand response is not considered in Scenario 1, the carbon emissions in Scenario 2 are reduced by 10.35 tons compared with Scenario 1. Although the cost of Scenario 3 increased by 17,100 yuan compared with Scenario 2, the introduction of the carbon trading mechanism further tapped the low-carbon potential of the units and loads, reduced the carbon emissions of the system, and reduced the total carbon emissions by 160.78 tons. Compared with Scenario 2, Scenario 4 can significantly reduce the carbon trading cost by earning the difference by buying the same amount of CCER under the rules of the spot carbon trading market, reducing the carbon trading compliance cost of IES.

[0225] The load dispatch results for scenario 1 on a typical day in the first quarter are as follows: Figure 4 As shown in the figure, the load dispatch results under scenario 4 on a typical day in the first quarter are as follows: Figure 5 As shown in the figure, compared with scenario 1, the energy supply mode of the system in scenario 4 is more flexible. After the introduction of the demand response mechanism, the load curve changes more significantly with the output of new energy. When the electricity price is low, the operation of the carbon capture device reduces the carbon emissions of the thermal power units, and the power-to-gas device generates natural gas to supply the gas units, reducing the energy purchase cost of the system.

[0226] The heat load dispatch results under scenario 1 on a typical day in the first quarter are as follows: Figure 6 As shown in the figure, the heat load dispatch results under scenario 4 on a typical day in the first quarter are as follows: Figure 7 As shown in the figure, in scenario 4, heat energy is mainly produced and supplied by cogeneration units and gas boilers, and the heat storage device participates in the regulation of heat energy supply. When the electricity price is low, the output of the electric heat pump increases; when the electricity price is high during the day, the main cogeneration unit has a high operating efficiency, and heat energy is mainly provided by gas turbines and gas boilers. Due to the coupling relationship between electric and thermal energy, the system transfers part of the load during the 09:00-18:00 period, reducing the system's energy purchase cost.

[0227] According to the operating rules of the forward carbon emission rights trading market, the results are shown in Table 3. As can be seen from Table 3, only in the fourth quarter did the thermal power plant choose to exercise the right, and the contract price in the first three quarters was higher than the exercise date price. Assuming that IES does not participate in option trading, it sells the contract quantity of CEA at the highest point of the predicted price, and completes the quota settlement according to the production situation on the settlement day at the end of each quarter to obtain carbon emission income. In the four quarters, the carbon emission income of IES is 1.0039 million (contract quantity × CEA highest price). Although the margin of the first three quarters was recovered, more costs were paid in the purchase of CEA in the last quarter. In the end, compared with fully participating in the forward carbon contract, it lost 348,300 yuan (overall income - 1.0039 million yuan).

[0228] Table 2 Operating costs and carbon emissions of the integrated energy system under scenarios 1-4

[0229]

[0230] Table 3 Option trading results

[0231]

[0232] In Table 3, the contract quantity M ccer , Execution Price Option price on agreed date C ccer , CCER option price on expiration date Margin C ccer ×M ccer , CEA price c on the exercise date cea , CEA income on the exercise date CEA Maximum Price Proceeds from sale of CEA Overall benefit P cem-f .

[0233] By applying the above technical solution, it can be seen that the method proposed in the present invention can effectively slow down the fluctuation of the electric load and gas load of energy-consuming users after considering the demand response of energy-consuming users in comparison with scenarios 1 and 2, play the role of peak shaving and valley filling, reduce the operating cost of IES and the energy purchase cost of energy-consuming users, and achieve a win-win situation between IES and energy-consuming users. Compared with scenarios 3 and 4, the price signal in the spot carbon emission rights trading market guides the reasonable allocation of carbon emission resources and promotes carbon emission reduction; the accumulation and sale of carbon emission rights in the forward carbon emission rights trading market brings additional financial benefits and actively guides enterprises to achieve energy conservation and emission reduction.

[0234] The specific implementation modes of the present invention are described in detail above in conjunction with the accompanying drawings, but the present invention is not limited to the above implementation modes, and various changes can be made within the knowledge scope of ordinary technicians in this field without departing from the purpose of the present invention.

Claims

1. A method for optimizing the dispatch of regional integrated energy systems considering the immediate-forward carbon emission financial market, characterized in that: include: Step 1: Establish a life cycle assessment model for actual carbon emissions based on life cycle assessment to obtain the actual carbon emissions of the integrated energy system; Step 2: Based on the BS pricing model and the actual carbon emissions of the integrated energy system, establish a carbon emission rights spot trading model and a carbon emission rights forward trading model respectively; Step 3: Establish an optimal dispatch model for the integrated energy system under the spot-forward carbon emission rights trading market; Step 4: Solve the optimal scheduling model of the integrated energy system under the spot-forward carbon emission rights trading market.

2. The method for optimizing the dispatch of regional integrated energy systems considering the immediate and long-term carbon emission financial markets according to claim 1 is characterized in that: The actual carbon emissions of the comprehensive energy system are expressed as: D L =D e +D g +D WT +D PV -D c Where: D L is the actual carbon emissions of IES; D e , D g , D WT With D PV are the carbon emissions of coal-fired units, gas-fired units, wind turbines and photovoltaic units respectively; D c is the total amount of CO2 captured; The D e , D g , D WT , D PV With D c , the expression is: Where: T represents the total number of time periods; δ e is the actual total carbon emission coefficient per unit of coal-fired unit power generation; P G,t is the output power of the generator at time t; g is the actual total carbon emission coefficient of each unit of gas-fired power generation; P CHP,t , P GB,t is the operating power of the cogeneration unit and gas boiler during period t; WT is the actual total carbon emission coefficient per unit of electricity generated by the wind turbine; δ PV is the actual total carbon emission coefficient per unit of electricity generated by the photovoltaic unit; P WT,t , P PV,t Respectively represent the power supply of wind power and photovoltaic units during period t; D c,t is the total amount of CO2 captured during period t.

3. The method for optimizing the dispatching of regional integrated energy systems considering the immediate and long-term carbon emission financial markets according to claim 2 is characterized in that: The actual total carbon emission coefficient δ per unit of coal-fired unit power generation e , the expression is: d e =d pe +d te +d ue d pe =I cp or cp Q ce (1+a+b) δ ue =I ue Q ue Where: pe is the carbon emission coefficient per unit of electricity generated in the coal mining and washing process; δ te is the carbon emission coefficient of coal transportation per unit of electricity generation; δ ue I is the carbon emission coefficient of the unit power generation of the coal-fired power generation unit in the energy cycle; cp is the unit loss of coal production in the energy cycle; η cp is the conversion rate of coal; Q ce is the carbon emission intensity of coal production; α and β are the unit power loss rate caused by spontaneous combustion of raw coal and the unit power loss rate caused by washing, respectively; m is the type of coal transportation mode; I i is the unit loss under the i-th mode of transportation; Q i K is the carbon emission intensity of greenhouse gases generated in the energy cycle under the i-th mode of transportation; i M is the ratio of the transport distance of the i-th transport mode to the total distance of the energy cycle; i is the total amount of coal transported by the ith mode of transportation during the energy cycle; D i is the average distance of the i-th mode of transportation; ue is the unit coal consumption in the power generation stage; Q ue It is the greenhouse gas carbon emission intensity in the energy cycle of coal-fired units.

4. The method for optimizing the dispatch of regional integrated energy systems considering the immediate and long-term carbon emission financial markets according to claim 2 is characterized in that: The actual total carbon emission coefficient δ of each unit of gas-fired unit power generation g , the expression is: d g =d pg +d tg +d ug Where: pg is the carbon emission coefficient per unit of electricity generated in the natural gas extraction process; δ tg is the carbon emission coefficient of natural gas transportation unit power generation; δ ug It is the carbon emission coefficient of unit power generation in the energy cycle when the gas generator set is in operation; η gas is the escape rate of natural gas during extraction; Q pg is the carbon emission intensity of natural gas in the energy cycle; η pt Q is the ratio of pipeline transportation volume to total transportation volume in the transportation process of natural gas; pt is the carbon emission intensity of natural gas in pipeline transportation; Q lt is the carbon emission intensity of natural gas in liquefied transportation; ε1 is the carbon emission intensity of natural gas per unit of power generation; ζ eh is the conversion coefficient of thermal energy and electrical energy; ε2 is the carbon emission intensity of natural gas per unit heat.

5. The method for optimizing the dispatch of regional integrated energy systems considering the immediate and long-term carbon emission financial markets according to claim 2 is characterized in that: The actual total carbon emission coefficient δ of the wind turbine per unit of power generation WT , the expression is: d WT =d pwt +d twt Where: pwt is the carbon emission coefficient per unit of electricity generated by the wind turbine during the production process; δ twt is the carbon emission coefficient corresponding to the wind power during the transportation process; η wt It is the conversion coefficient between unit standard electric energy and energy loss of wind power equipment in the energy cycle; The loss rate of materials used to build wind power equipment in the energy cycle; Q pwt The carbon emission intensity of materials used to build wind turbines; V pwt Q is the energy content of the materials used to build wind power equipment; twt Carbon intensity of wind turbine construction materials used in energy cycle production; V twt Value for transport losses of wind turbine construction materials used in energy production.

6. The method for optimizing the dispatch of regional integrated energy systems considering the immediate and long-term carbon emission financial markets according to claim 2 is characterized in that: The actual total carbon emission coefficient δ of the photovoltaic unit per unit of power generation PV , the expression is: d PV =d ppv +d tpv Where: ppv is the carbon emission coefficient per unit of electricity generated by the photovoltaic generator set during the production process; δ tpv is the carbon emission coefficient corresponding to photovoltaics during transportation; η pv It is the conversion coefficient between the unit standard electric energy and energy loss of photovoltaic equipment in the energy cycle; The loss rate of materials used to build photovoltaic devices in the energy cycle; Q ppv The carbon emission intensity of materials used to build photovoltaic units; V ppv Indicates the internal energy value of the materials used to build photovoltaic equipment; Q tpv Carbon emission intensity of materials used in the construction of photovoltaic devices for energy cycle production; V tpv Represents the transport loss value of photovoltaic system construction materials used in energy cycle production.

7. The method for optimizing the dispatch of regional integrated energy systems considering the immediate and long-term carbon emission financial markets according to claim 1 is characterized in that: The carbon emission rights spot trading model is expressed as: P cem-s =[And a -(1-μ)D L ]c cea -μD L c ccer Where: P cem,t The current carbon emission trading income of the integrated energy system; cea is the predicted closing price of carbon emission rights trading; c ccer E is the closing price of the national certified voluntary emission reductions; a is the quota applied for according to the scheduling plan on the previous day; μ is the proportion of the buyer's deposit to purchase its own quota from the seller; D L is the actual carbon emissions of the comprehensive energy system.

8. The method for optimizing the dispatch of regional integrated energy systems considering the immediate and long-term carbon emission financial markets according to claim 1 is characterized in that: The carbon emission rights forward trading model is expressed as follows: Where: P cem-f E is the income from the forward carbon emissions trading of the integrated energy system; a is the quota applied for according to the scheduling plan the day before; μ is the proportion of the buyer's deposit to purchase its own quota from the seller; To predict the highest price of carbon trading; M ccer,t is the number of contracts at time t; K is the highest closing price of the predicted national certified emission reductions; ave is the average price; c ccer The closing price of the national certified voluntary emission reductions; D L is the actual carbon emissions of the comprehensive energy system.

9. The method for optimizing and dispatching a regional integrated energy system considering the immediate and long-term carbon emission financial market according to claim 1 is characterized in that: The Step 3 includes: establishing an optimization model for upper-level operators of the integrated energy system under the spot and forward carbon emission rights trading markets; and establishing an optimization model for lower-level users of the integrated energy system under the spot and forward carbon emission rights trading markets.

10. The method for optimizing and dispatching a regional integrated energy system considering the immediate and long-term carbon emission financial market according to claim 9 is characterized in that: The above-mentioned establishment of an optimization model for the upper-level operators of the integrated energy system under the spot and forward carbon emission rights trading markets includes: the optimization objective function of the upper-level operators of the integrated energy system under the spot carbon emission rights trading market, the optimization objective function and constraints of the upper-level operators of the integrated energy system under the forward spot carbon emission rights trading market: wherein, the constraints include: cogeneration unit constraints, gas boiler model, electric boiler model, energy storage constraints, new energy constraints, interconnection line and pipeline constraints, carbon capture operation model, power-to-gas two-stage operation model, and power balance constraints.

Images