Building energy conservation and emission reduction strategy optimization method based on dynamic carbon emission factors

Abstract

The invention discloses a building energy conservation and emission reduction strategy optimization method based on a dynamic carbon emission factor, and relates to the technical field of power systems, and the method comprises the steps: firstly building a power building electricity-carbon coupling cost calculation model; secondly, measuring and calculating the thermal load and the operation cost of a room based on virtual energy storage, and punishing a user to discard renewable energy power; then establishing a building energy conservation and emission reduction strategy optimization model; and finally, a Gurobi solver in MATLAB is called to solve the building energy conservation and emission reduction strategy optimization model, and carbon emission reduction is realized. According to the building energy conservation and emission reduction strategy optimization method based on the dynamic carbon emission factor, virtual energy storage and demand response of the building can be effectively coordinated, the dynamic energy carbon transaction cost is brought into the target function, the target signal of carbon emission reduction is transmitted to the user, and the user experience is improved. The dynamic carbon emission factor is enabled to consider the fluctuation of renewable energy and other random energy behaviors.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a method for optimizing building energy conservation and emission reduction strategies based on dynamic carbon emission factors. Background Art

[0002] Final energy consumption in the construction industry accounts for about 33% of total consumption, and direct and indirect carbon dioxide emissions account for about 40% of global total consumption. From the perspective of energy supply and demand, building energy consumption is the demand side of the energy system. The participation of demand-side resources in achieving source-load coordinated optimization is an important part of promoting the realization of zero-carbon goals. Therefore, in the building operation stage, the use of clean energy to achieve carbon substitution and the use of system optimization scheduling to achieve carbon emission reduction are in line with the carbon reduction path in the energy field. With the rapid development of social economy and the acceleration of urbanization, the load and electricity consumption of existing buildings have increased rapidly. Especially under different climatic conditions, the proportion of energy load that meets the cooling / heating needs of users is getting higher and higher, which brings great challenges to the economy and safe operation of the power system. It also affects the stable operation of the power market. At the same time, with the development of renewable energy building integration technology, the scale of distributed renewable energy generation related to buildings is also increasing. The renewable energy output on the demand side faces consumption problems caused by the mismatch between supply and demand.

[0003] In addition, the statistics and calculation of carbon emissions are also very important in the low-carbon development of the building and energy sectors. At present, carbon measurement is mostly calculated based on the typical emission factors of different energy sources provided by the Intergovernmental Panel on Climate Change. The carbon emission factor is a fixed parameter. However, the operating intensity of the power system where carbon emissions have not completely achieved zero carbon is time-varying. It is difficult to accurately measure carbon emissions with a steady-state carbon emission factor. The role of users in reducing carbon emissions in buildings has not been fully stimulated. If we can give full play to the regulation capabilities, build flexible resources, adjust users' low-carbon energy consumption behaviors, and respond to the carbon emission reduction needs of the power system on the basis of achieving carbon emission reduction, it will be conducive to the sustainable development of the building and energy sectors. Summary of the invention

[0004] The purpose of the present invention is to provide a building energy conservation and emission reduction strategy optimization method based on dynamic carbon emission factors to solve the problem that common building low-carbon operation strategies in the prior art rely on price incentives to guide user behavior, and there is a mismatch between supply and demand of renewable energy output on the demand side.

[0005] To achieve the above object, the present invention provides a building energy conservation and emission reduction strategy optimization method based on a dynamic carbon emission factor, comprising the following steps:

[0006] Step 1: Establish a calculation model for the electricity-carbon coupling cost of power buildings;

[0007] Step 2: Calculate the room heat load and operating cost based on virtual energy storage, and impose penalties on users who abandon renewable energy;

[0008] Step 3: Establish an optimization model for building energy conservation and emission reduction strategies;

[0009] Step 4: Call the Gurobi solver in MATLAB to solve the building energy conservation and emission reduction strategy optimization model established in step 3 to achieve carbon emission reduction.

[0010] Preferably, the specific process of step one is as follows:

[0011] S11. Calculate the dynamic carbon emission factor of low-carbon demand response. The calculation expression is as follows:

[0012]

[0013] In the formula, e C,i,t is the dynamic carbon emission factor of regional power grid i in period t; Z is the set of nodes within the coverage of regional power grid i; is the load of node j in the tth period; is the carbon potential of node j;

[0014] S12. Based on the dynamic carbon emission factor, calculate the carbon emissions of building electricity purchases. The calculation expression is as follows:

[0015]

[0016] In the formula, E k is the carbon emission of electricity purchased by building user k, in kgCO2; is the electricity purchased by building user k in period t, in kW·h;

[0017] S13. Set up photovoltaic and cogeneration as energy supply equipment on the demand side of low-carbon buildings and calculate the electricity-carbon coupling cost of power buildings. The calculation expression is as follows:

[0018]

[0019] In the formula, C carbon is the electricity-carbon coupling cost of power buildings, λ is the carbon emission trading price; e C,t is the dynamic carbon emission factor of the power grid; P t grid The power supply to the grid, in Kw; N is the carbon emission calculation coefficient of cogeneration; c The installed capacity for combined heat and power generation; is the output power of the cogeneration equipment at time t, in kW; Δt is the unit scheduling time, in h.

[0020] Preferably, the process of step 2 is as follows:

[0021] S21. According to the law of conservation of energy and the principle of thermal balance, the relationship between the change of heat storage in the room is obtained, and the expression is as follows:

[0022]

[0023] Where a is the room specific heat capacity coefficient; T a is the room temperature in °C; Φ ra is the heat entering the room, in kW; Φ release,1 is the heat dissipated from the room to the outside, in kW; Φ release,2 The amount of heat that the room naturally dissipates from the enclosing structure, in kW;

[0024] S22. According to the principle of heat conduction, considering the thermal inertia under heating conditions, a simplified general model of quasi-dynamic changes in room temperature is obtained, and the expression is as follows:

[0025]

[0026] Among them, T a,t+1 is the room temperature at the next moment, in °C, T out,t is the outdoor air temperature, in °C; Φ ra,t is the heating power in time period T, in kW; η air is the thermal conductivity of air, in kW / ℃; Δt is the scheduling time, in h; t c is the heating time, in h; T a,t is the room temperature at time t, in °C;

[0027] S23. Calculate the charging and discharging power of the room virtual energy storage. The calculation expression is as follows:

[0028]

[0029] In the formula, H room The charging and discharging power of the room's virtual energy storage system; The actual heat load of the room at time t after considering human comfort, in kW; is the daily predicted heat load of the room before time t, in kW;

[0030] S24. Calculate the heat load of the room. The calculation expression is as follows:

[0031]

[0032] In the formula, Φ ra,t Indicates the heat load of the room;

[0033] S25. Calculate the operating costs, which include the electricity / natural gas consumption costs of the building energy and the operating and maintenance costs of the equipment;

[0034] S26. Penalties are imposed on users who abandon renewable energy. The penalties are as follows:

[0035]

[0036] In the formula, C curtail Power curtailment due to renewable energy curtailment; t PV,p is the photovoltaic power generation, in kW; P t PV is the photovoltaic dispatching output, in kW; k p is the light abandonment penalty coefficient, N PV is the number of photovoltaic installations.

[0037] Preferably, the calculation expressions for the electricity / natural gas consumption cost of the building energy and the operation and maintenance cost of the equipment in S25 are as follows:

[0038] The cost of electricity / gas consumption for building energy is:

[0039]

[0040] In the formula, C market Cost of electricity / gas consumption for building energy; d gas is the natural gas price; N c is the installed capacity of combined heat and power; a c,i 、b c,i 、c c,i is the cost calculation coefficient for gas consumption in CHP; is the output power of the cogeneration equipment at time t, in kW; c p is the on-grid electricity price, in CNY; P t grid is the power supply to the grid, in kW; Δt is the unit dispatching time, in h;

[0041] The operation and maintenance cost of the equipment is:

[0042]

[0043] Among them, C maintan The operation and maintenance costs of the equipment; is the output power of the cogeneration equipment at time t, in kW; is the output power of the photovoltaic device at time t, in kW; is the electric power of the electric boiler at time t, in kW; is the power consumption of the refrigerator at time t, in kW; is the charging and discharging power of the energy storage device at time t, in kW; PV is the unit power operation and maintenance cost of cogeneration, photovoltaic, electric boiler, refrigerator, and energy storage; N eb 、N re 、N eg are the number of electric boilers, refrigerators and energy storage respectively.

[0044] Preferably, the process of establishing the building energy conservation and emission reduction strategy optimization model in step three is as follows:

[0045] S31. Construct the overall objective function of the building energy consumption system, which is expressed as follows:

[0046] f=min(C market +C maintan +C curtail +C carbon );

[0047] Among them, C market The electricity / natural gas consumption cost for building energy; C maintan is the operation and maintenance cost of the equipment; C curtail Power curtailment due to renewable energy; C carbon Carbon coupling costs for electricity buildings;

[0048] S32. Establish constraints on the overall objective function of the building energy consumption system constructed in S31, including energy balance constraints and energy interaction constraints.

[0049] Preferably, the expression of the energy balance constraint in S32 is as follows:

[0050]

[0051] Among them, P t grid P is the power supply to the grid, in kW; t load is the node power load demand, in kW; P t Inject power into the node in kW; is the node heat load demand, in kW; Φ t The thermal power injected into the node, in kW; P t CHP P is the power consumption of the node cogeneration, in kW; t re is the power consumption of the node refrigerator, in kW; P t ES is the node energy storage power consumption, in kW; Pt EB is the node boiler power consumption, in kW; Inject thermal power into the node cogeneration, in kW; Inject heat load power into the node boiler in kW.

[0052] Preferably, the energy interaction constraints in S32 include the interaction constraints between the building multi-energy system and the upper power grid, the upper limit constraints of the average gas purchase rate of each natural gas, the renewable energy output limit constraints, the equipment operation constraints and the electric energy storage operation constraints, and the specific expressions are as follows:

[0053] The interaction constraints between the building's multi-energy system and the upper power grid are:

[0054]

[0055] in, The upper limit of the power supply of the power grid, in kW;

[0056] The upper limit constraint of the average gas purchase rate of each natural gas is:

[0057]

[0058] in, is the natural gas purchase volume in period t, in units of Sm 3 / h, The upper limit of natural gas purchase volume in period t, in units of Sm 3 / h;

[0059] The renewable energy output limit constraint is:

[0060]

[0061] Among them, P t re is the renewable energy power generation in period t, in kW, is the upper limit of renewable energy power generation in period t, in kW;

[0062] The equipment operation constraints are:

[0063] The combined heat and power unit generates electricity and heat by consuming natural gas. Its mathematical model is expressed as:

[0064]

[0065] Among them, α, β, and γ are the cogeneration characteristic coefficients; is the heating power of cogeneration, in kW; P t CHP The power supply of cogeneration is in kW; is the maximum power supply of cogeneration, in kW; ΔP u , ΔP d They are the maximum ramp-up / ramp-down output of cogeneration, in kW; is the lower limit of the thermal power of cogeneration, in kW; The upper limit of the thermal power of cogeneration, in kW; The power consumed by the cogeneration at the last moment, in kW;

[0066] The mathematical model of the electric boiler is expressed as:

[0067]

[0068] Among them, Q EB,τ is the heating power of the electric boiler, in kW; η EB P is the electric-to-heat conversion efficiency of the electric boiler; EB,τ is the power consumption of the electric boiler, in kW; is the rated power of the electric boiler, in kW;

[0069] Indoor temperature T r The allowable fluctuation range is [T r,min ,T r,max ], the operating time of the refrigeration system is [α AC ,β BC ]:

[0070] T r,min ≤T r (t)≤T r,max ,t∈[α AC ,β AC ];

[0071] The electric energy storage operation constraints are:

[0072] During the renewable energy electricity surplus period [T1, T2], the ability of electric energy storage to absorb renewable energy waste is described as:

[0073]

[0074] In the formula, E al is the amount of surplus power absorbed, in kW; P t BES is the rated power of the energy storage at time t, in kW; is the rated capacity of the electric energy storage, in kW; η BES ΔSOC is the charging and discharging efficiency of the electric energy storage; BES is to show the change of the charge state of the electric energy storage system in the time period [T1, T2]; is the charge state of the energy storage at time T2; is the charge state of the energy storage at time T1; is the maximum state of charge of the electric energy storage system; It is the maximum rated power of the electric energy storage.

[0075] Therefore, the present invention adopts the above-mentioned method for optimizing building energy conservation and emission reduction strategies based on dynamic carbon emission factors. First, a calculation model for the electricity-carbon coupling cost of power buildings is established, so that users bear the carbon emission costs generated by energy consumption in a form similar to electricity bills, and the carbon emission costs of demand-side energy supply equipment are included in the energy consumption strategy of building users. Then, the virtual energy storage of the building is considered, and the room heat load measurement and operation costs are further calculated. The energy demand of the building during the peak period of electricity and carbon emissions is minimized by utilizing the conversion scheduling cycle of space and time. Finally, a building operation optimization strategy is formulated, taking into account the economic operating cost of the system and the role of energy conservation and carbon emission reduction, and the cost of purchasing electricity and gas, operation and maintenance costs, renewable energy curtailment and power restriction costs, and electricity-carbon coupling costs are all included in the objective function. The electrical energy interaction is used as a constraint condition to achieve the optimization solution of the energy conservation and emission reduction strategy of power buildings.

[0076] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 This is an overall flow chart of a method for optimizing building energy conservation and emission reduction strategies based on dynamic carbon emission factors according to the present invention. DETAILED DESCRIPTION

[0078] The following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. 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.

[0079] See also Figure 1 , a building energy conservation and emission reduction strategy optimization method based on dynamic carbon emission factors, comprising the following steps:

[0080] Step 1: Establish a calculation model for the electricity-carbon coupling cost of power buildings; the specific process is as follows:

[0081] S11. Calculate the dynamic carbon emission factor of low-carbon demand response based on the node carbon potential calculated by carbon flow. The calculation expression is as follows:

[0082]

[0083] In the formula, e C,i,tis the dynamic carbon emission factor of regional power grid i in period t; Z is the set of nodes within the coverage of regional power grid i; is the load of node j in the tth period; is the carbon potential of node j;

[0084] S12. Based on the dynamic carbon emission factor, calculate the carbon emissions of building electricity purchases. The calculation expression is as follows:

[0085]

[0086] In the formula, E k is the carbon emission of electricity purchased by building user k, in kgCO2; is the electricity purchased by building user k in period t, in kW·h;

[0087] S13. Set up photovoltaic and cogeneration as energy supply equipment on the demand side of low-carbon buildings and calculate the electricity-carbon coupling cost of power buildings. The calculation expression is as follows:

[0088]

[0089] In the formula, C carbon is the electricity-carbon coupling cost of power buildings, λ is the carbon emission trading price; e C,t is the dynamic carbon emission factor of the power grid; P t grid The power supply to the grid, in Kw; N is the carbon emission calculation coefficient of cogeneration; c The installed capacity for combined heat and power generation; is the output power of the cogeneration equipment at time t, in kW; Δt is the unit scheduling time, in h.

[0090] Step 2: Calculate the room heat load and operating cost based on virtual energy storage, and impose penalties on users for abandoning renewable energy; buildings have a certain thermal inertia. During the heating / cooling process, due to the insulation effect brought by the enclosing structure, the building can balance energy consumption at any time by changing the energy consumption strategy. This method of using the thermal delay characteristics of the building to achieve the energy storage effect is called virtual energy storage. By considering building virtual energy storage, it can further increase the flexibility of the user's energy use strategy, and at the same time, it can increase the flexibility of the user's energy use strategy while minimizing the building's energy demand during peak electricity and carbon emissions by utilizing space and time conversion scheduling cycles. The specific process is as follows:

[0091] S21. According to the law of conservation of energy and the principle of thermal balance, the relationship between the change of heat storage in the room is obtained. The change of heat storage in the room is equal to the heat entering the room minus the energy flowing out of the room during the period. The specific expression is as follows:

[0092]

[0093] Where a is the room specific heat capacity coefficient; T a is the room temperature in °C; Φ ra is the heat entering the room, in kW; Φ release,1 is the heat dissipated from the room to the outside, in kW; Φ release,2 The amount of heat that the room naturally dissipates from the enclosing structure, in kW;

[0094] S22. According to the principle of heat conduction, considering the thermal inertia under heating conditions, a simplified general model of quasi-dynamic changes in room temperature is obtained, and the expression is as follows:

[0095]

[0096] Among them, T a,t+1 is the room temperature at the next moment, in °C, T out,t is the outdoor air temperature, in °C; Φ ra,t is the heating power in time period T, in kW; η air is the thermal conductivity of air, in kW / ℃; Δt is the scheduling time, in h; t c is the heating time, in h; T a,t is the room temperature at time t, in °C;

[0097] S23. Indoor temperature can be adjusted within a certain range according to human comfort requirements. Heat load becomes an optimization variable and participates in the operation optimization of the electric heating system. The charging and discharging power of the room virtual energy storage is calculated as follows:

[0098]

[0099] In the formula, H room The charging and discharging power of the room's virtual energy storage system; The actual heat load of the room at time t after considering human comfort, in kW; is the daily predicted heat load of the room before time t, in kW;

[0100] S24. Calculate the heat load of the room. The calculation expression is as follows:

[0101]

[0102] In the formula, Φ ra,tIndicates the heat load of the room;

[0103] S25. Calculate the operating cost, which includes the electricity / natural gas consumption cost of the building energy and the operation and maintenance cost of the equipment; wherein the calculation expressions of the electricity / natural gas consumption cost of the building energy and the operation and maintenance cost of the equipment are as follows:

[0104] The cost of electricity / gas consumption for building energy is:

[0105]

[0106] In the formula, C market Cost of electricity / gas consumption for building energy; d gas is the natural gas price; N c is the installed capacity of combined heat and power; a c,i 、b c,i 、c c,i is the cost calculation coefficient for gas consumption in CHP; is the output power of the cogeneration equipment at time t, in kW; c p is the on-grid electricity price, in CNY; P t grid is the power supply to the grid, in kW; Δt is the unit dispatching time, in h;

[0107] The operation and maintenance cost of the equipment is:

[0108]

[0109] Among them, C maintan The operation and maintenance costs of the equipment; is the output power of the cogeneration equipment at time t, in kW; is the output power of the photovoltaic device at time t, in kW; is the electric power of the electric boiler at time t, in kW; is the power consumption of the refrigerator at time t, in kW; is the charging and discharging power of the energy storage device at time t, in kW; PV is the unit power operation and maintenance cost of cogeneration, photovoltaic, electric boiler, refrigerator, and energy storage; N eb 、N re 、N eg are the number of electric boilers, refrigerators and energy storage respectively.

[0110] S26. Penalties are imposed on users who abandon renewable energy. The penalties are as follows:

[0111]

[0112] In the formula, C curtail Power curtailment due to renewable energy curtailment; t PV,p is the photovoltaic power generation, in kW; P t PV is the photovoltaic dispatching output, in kW; k p is the light abandonment penalty coefficient, N PV is the number of photovoltaic installations.

[0113] Step 3: Establish a building energy conservation and emission reduction strategy optimization model; the specific process is as follows:

[0114] S31. Construct the overall objective function of the building energy consumption system, which is expressed as follows:

[0115] f=min(C market +C maintan +C curtail +C carbon );

[0116] Among them, C market The electricity / natural gas consumption cost for building energy; C maintan is the operation and maintenance cost of the equipment; C curtail Power curtailment due to renewable energy; C carbon Carbon coupling costs for electricity buildings;

[0117] S32. Establish constraints on the overall objective function of the building energy consumption system constructed in S31, including energy balance constraints and energy interaction constraints. The expression of energy balance constraints is as follows:

[0118]

[0119] Among them, P t grid P is the power supply to the grid, in kW; t load is the node power load demand, in kW; P t Inject power into the node in kW; is the node heat load demand, in kW; Φ t The thermal power injected into the node, in kW; P t CHP P is the power consumption of the node cogeneration, in kW; t re is the power consumption of the node refrigerator, in kW; P t ES Power consumption for node energy storage; P t EB is the node boiler power consumption, in kW; Inject thermal power into the node cogeneration, in kW; The thermal power injected into the node boiler, in kW.

[0120] Energy interaction constraints include the interaction constraints between the building's multi-energy system and the upper power grid, the upper limit constraints of the average gas purchase rate of each natural gas, the output limit constraints of renewable energy, the equipment operation constraints and the electric energy storage operation constraints. The specific expressions are as follows:

[0121] The interaction constraints between the building's multi-energy system and the upper power grid are:

[0122]

[0123] in, The upper limit of the power supply of the power grid, in kW;

[0124] The upper limit constraint of the average gas purchase rate of each natural gas is:

[0125]

[0126] in, is the natural gas purchase volume in period t, in units of Sm 3 / h, The upper limit of natural gas purchase volume in period t, in units of Sm 3 / h;

[0127] The renewable energy output limit constraint is:

[0128]

[0129] Among them, P t re is the renewable energy power generation in period t, in kW, is the upper limit of renewable energy power generation in period t, in kW;

[0130] The equipment operation constraints are:

[0131] The combined heat and power unit generates electricity and heat by consuming natural gas. Its mathematical model is expressed as:

[0132]

[0133] Among them, α, β, and γ are the cogeneration characteristic coefficients; is the heating power of cogeneration, in kW; P t CHP The power supply of cogeneration is in kW; is the maximum power supply of cogeneration, in kW; ΔP u , ΔP dThey are the maximum ramp-up / ramp-down output of cogeneration, in kW; is the lower limit of the thermal power of cogeneration, in kW; The upper limit of the thermal power of cogeneration, in kW; The power consumed by the cogeneration at the last moment, in kW;

[0134] The mathematical model of the electric boiler is expressed as:

[0135]

[0136] Among them, Q EB,τ is the heating power of the electric boiler, in kW; η EB P is the electric-to-heat conversion efficiency of the electric boiler; EB,τ is the power consumption of the electric boiler, in kW; is the rated power of the electric boiler, in kW;

[0137] Indoor temperature T r The allowable fluctuation range is [T r,min ,T r,max ], the operating time of the refrigeration system is [α AC ,β BC ]:

[0138] T r,min ≤T r (t)≤T r,max ,t∈[α AC ,β AC ];

[0139] The electric energy storage operation constraints are:

[0140] During the renewable energy electricity surplus period [T1, T2], the ability of electric energy storage to absorb renewable energy waste is described as:

[0141]

[0142] In the formula, E al is the amount of surplus power absorbed, in kW; P t BES is the rated power of the energy storage at time t, in kW; is the rated capacity of the electric energy storage, in kW; η BES ΔSOC is the charging and discharging efficiency of the electric energy storage; BES is to show the change of the charge state of the electric energy storage system in the time period [T1, T2]; is the charge state of the energy storage at time T2; is the charge state of the energy storage at time T1; is the maximum state of charge of the electric energy storage system; It is the maximum rated power of the electric energy storage.

[0143] Step 4: Call the Gurobi solver in MATLAB to solve the building energy conservation and emission reduction strategy optimization model established in step 3 to achieve carbon emission reduction.

[0144] Therefore, the present invention adopts the above-mentioned building energy conservation and emission reduction strategy optimization method based on dynamic carbon emission factors, calculates the cost of dynamic carbon emission factors and electric carbon coupling, and then uses virtual energy storage technology to calculate the room heat load and cost of the building. Finally, an optimization model for building energy conservation and emission reduction is established to realize the carbon emission reduction strategy.

[0145] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

Claims

1. A building energy conservation and emission reduction strategy optimization method based on dynamic carbon emission factors, characterized in that: The following steps are involved: Step 1: Establish a calculation model for the electricity-carbon coupling cost of power buildings; Step 2: Calculate the room heat load and operating cost based on virtual energy storage, and impose penalties on users who abandon renewable energy; Step 3: Establish an optimization model for building energy conservation and emission reduction strategies; Step 4: Call the Gurobi solver in MATLAB to solve the building energy conservation and emission reduction strategy optimization model established in step 3 to achieve carbon emission reduction.

2. The method for optimizing building energy conservation and emission reduction strategies based on dynamic carbon emission factors according to claim 1 is characterized in that: The specific process of step one is as follows: S11. Calculate the dynamic carbon emission factor of low-carbon demand response. The calculation expression is as follows: In the formula, e C,i,t is the dynamic carbon emission factor of regional power grid i in period t; Z is the set of nodes within the coverage of regional power grid i; is the load of node j in the tth period; is the carbon potential of node j; S12. Based on the dynamic carbon emission factor, calculate the carbon emissions of building electricity purchases. The calculation expression is as follows: In the formula, E k is the carbon emission of electricity purchased by building user k, in kgCO2; is the electricity purchased by building user k in period t, in kW·h; S13. Set up photovoltaic and cogeneration as energy supply equipment on the demand side of low-carbon buildings and calculate the electricity-carbon coupling cost of power buildings. The calculation expression is as follows: In the formula, C carbon is the electricity-carbon coupling cost of power buildings, λ is the carbon emission trading price; e C,t is the dynamic carbon emission factor of the power grid; P t grid The power supply to the grid, in Kw; N is the carbon emission calculation coefficient of cogeneration; c The installed capacity for combined heat and power generation; is the output power of the cogeneration equipment at time t, in kW; Δt is the unit scheduling time, in h.

3. The method for optimizing building energy conservation and emission reduction strategies based on dynamic carbon emission factors according to claim 2 is characterized in that: The process of step 2 is as follows: S21. According to the law of conservation of energy and the principle of thermal balance, the relationship between the change of heat storage in the room is obtained, and the expression is as follows: Where a is the room specific heat capacity coefficient; T a is the room temperature in °C; Φ ra is the heat entering the room, in kW; Φ release,1 is the heat dissipated from the room to the outside, in kW; Φ release,2 The amount of heat that the room naturally dissipates from the enclosing structure, in kW; S22. According to the principle of heat conduction, considering the thermal inertia under heating conditions, a simplified general model of quasi-dynamic changes in room temperature is obtained, and the expression is as follows: Among them, T a,t+1 is the room temperature at the next moment, in °C, T out,t is the outdoor air temperature, in °C; Φ ra,t is the heating power in time period T, in kW; η air is the thermal conductivity of air, in kW / ℃; Δt is the scheduling time, in h; t c is the heating time, in h; T a,t is the room temperature at time t, in °C; S23. Calculate the charging and discharging power of the room virtual energy storage. The calculation expression is as follows: In the formula, H room The charging and discharging power of the room's virtual energy storage system; The actual heat load of the room at time t after considering human comfort, in kW; is the daily predicted heat load of the room before time t, in kW; S24. Calculate the heat load of the room. The calculation expression is as follows: In the formula, Φ ra,t Indicates the heat load of the room; S25. Calculate the operating costs, which include the electricity / natural gas consumption costs of the building energy and the operating and maintenance costs of the equipment; S26. Penalties are imposed on users who abandon renewable energy. The penalties are as follows: In the formula, C curtail Power curtailment due to renewable energy curtailment; t PV,p is the photovoltaic power generation, in kW; P t PV is the photovoltaic dispatching output, in kW; k p is the light abandonment penalty coefficient, N PV is the number of photovoltaic installations.

4. The method for optimizing building energy conservation and emission reduction strategies based on dynamic carbon emission factors according to claim 3 is characterized in that: The calculation expressions for the electricity / natural gas consumption cost and equipment operation and maintenance cost of building energy in S25 are as follows: The cost of electricity / gas consumption for building energy is: In the formula, C market Cost of electricity / gas consumption for building energy; d gas is the natural gas price; N c is the installed capacity of combined heat and power; a c,i , b c,i 、c c,i is the cost calculation coefficient for gas consumption in CHP; is the output power of the cogeneration equipment at time t, in kW; c p is the on-grid electricity price, in CNY; P t grid is the power supply to the grid, in kW; Δt is the unit dispatching time, in h; The operation and maintenance cost of the equipment is: Among them, C maintan The operation and maintenance costs of the equipment; is the output power of the cogeneration equipment at time t, in kW; is the output power of the photovoltaic device at time t, in kW; is the electric power of the electric boiler at time t, in kW; is the power consumption of the refrigerator at time t, in kW; is the charging and discharging power of the energy storage device at time t, in kW; PV is the unit power operation and maintenance cost of cogeneration, photovoltaic, electric boiler, refrigerator, and energy storage; N eb 、N re 、N eg are the number of electric boilers, refrigerators and energy storage respectively.

5. The method for optimizing building energy conservation and emission reduction strategies based on dynamic carbon emission factors according to claim 4 is characterized in that: The process of establishing the building energy conservation and emission reduction strategy optimization model in step three is as follows: S31. Construct the overall objective function of the building energy consumption system, which is expressed as follows: f=min(C market +C maintan +C curtail +C carbon ); Among them, C market The electricity / natural gas consumption cost for building energy; C maintan is the operation and maintenance cost of the equipment; C curtail Power curtailment due to renewable energy; C carbon Electricity-carbon coupling costs for electric buildings; S32. Establish constraints on the overall objective function of the building energy consumption system constructed in S31, including energy balance constraints and energy interaction constraints.

6. The method for optimizing building energy conservation and emission reduction strategies based on dynamic carbon emission factors according to claim 5 is characterized in that: The expression of energy balance constraint in S32 is as follows: Among them, P t grid P is the power supply to the grid, in kW; t load is the node power load demand, in kW; P t Inject power into the node in kW; is the node heat load demand, in kW; Φ t The thermal power injected into the node, in kW; P t CHP P is the power consumption of the node cogeneration, in kW; t re is the power consumption of the node refrigerator, in kW; P t ES is the node energy storage power consumption, in kW; P t EB is the node boiler power consumption, in kW; Inject thermal power into the node cogeneration, in kW; Inject heat load power into the node boiler in kW.

7. The method for optimizing building energy conservation and emission reduction strategies based on dynamic carbon emission factors according to claim 6 is characterized in that: The energy interaction constraints in S32 include the interaction constraints between the building's multi-energy system and the upper power grid, the upper limit constraints of the average gas purchase rate of each natural gas, the output limit constraints of renewable energy, the equipment operation constraints and the electric energy storage operation constraints. The specific expressions are as follows: The interaction constraints between the building's multi-energy system and the upper power grid are: in, The upper limit of the power supply of the power grid, in kW; The upper limit constraint of the average gas purchase rate of each natural gas is: in, is the natural gas purchase volume in period t, in units of Sm 3 / h, The upper limit of natural gas purchase volume in period t, in units of Sm 3 / h; The renewable energy output limit constraint is: Among them, P t re is the renewable energy power generation in period t, in kW, is the upper limit of renewable energy generation in period t, in kW; The equipment operation constraints are: The combined heat and power unit generates electricity and heat by consuming natural gas. Its mathematical model is expressed as: Among them, α, β, and γ are the cogeneration characteristic coefficients; is the heating power of cogeneration, in kW; P t CHP The power supply of cogeneration is in kW; is the maximum power supply of cogeneration, in kW; ΔP u , ΔP d They are the maximum ramp-up / ramp-down output of cogeneration, in kW; is the lower limit of the thermal power of cogeneration, in kW; The upper limit of the thermal power of cogeneration, in kW; The power consumed by the cogeneration at the last moment, in kW; The mathematical model of the electric boiler is expressed as: Among them, Q EB,τ is the heating power of the electric boiler, in kW; η EB P is the electric-to-heat conversion efficiency of the electric boiler; EB,τ is the power consumption of the electric boiler, in kW; is the rated power of the electric boiler, in kW; Indoor temperature T r The allowable fluctuation range is [T r,min ,T r,max ], the operating time of the refrigeration system is [α AC ,β BC ]: T r,min ≤T r (t)≤T r,max ,t∈[α AC ,b AC ]; The operating constraints of electric energy storage are: During the renewable energy electricity surplus period [T1, T2], the ability of electric energy storage to absorb renewable energy waste is described as: In the formula, E al is the amount of surplus power absorbed, in kW; P t BES is the rated power of the energy storage at time t, in kW; is the rated capacity of the electric energy storage, in kW; η BES ΔSOC is the charging and discharging efficiency of the electric energy storage; BES is to show the change of the charge state of the electric energy storage system in the time period [T1, T2]; is the charge state of the energy storage at time T2; is the charge state of the energy storage at time T1; is the maximum state of charge of the electric energy storage system; It is the maximum rated power of the electric energy storage.

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