Carbon emission prediction and novel power system planning method and system in urban power field

Abstract

The invention discloses a carbon emission prediction and novel power system planning method and system in the urban power field. The method comprises the following steps: calculating the energy demand quantity of each department according to the urban total production value GDP, population, industrial structure and energy consumption characteristic data; calculating the total carbon emission amount of the electric power department based on the energy demand in combination with the carbon emission factor; on the basis of the total carbon emission amount of an electric power department, urban energy endowment, emission reduction tasks, emission reduction policies and power generation technology improvement are considered, and on the basis of economy, population and electricity consumption parameters of an electric power demand end, various development situations of low carbon, zero carbon and negative carbon of an electric power system are designed; predicting carbon emission and carbon emission reduction corresponding to the demand end in each scene, and obtaining an emission reduction path from the demand end; and establishing a power system multi-scene optimization planning model by taking the lowest net present value of the total cost of the system as an objective function and taking urban power related constraints as constraint conditions, and calculating a power generation installed capacity development path meeting the system cost and the related constraints.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and more specifically, to a method and system for predicting carbon emissions in the urban power sector and planning a new power system. Background Art

[0002] As the cornerstone of economic and social development, the power system is also the main source of greenhouse gas emissions. It occupies a core position in the energy chain, and its carbon emissions account for more than one-third of the national total. Based on historical data, development trends and policy orientations, taking into account a variety of factors such as power system structure, energy consumption patterns, technological progress and policy changes, accurate carbon emission forecasts are required to formulate scientific and reasonable power system planning plans, promote energy transformation and intelligent development of power systems, and accurately predict carbon emissions in the urban power sector.

[0003] At present, there may be differences between energy balance models and electricity market optimization models in terms of modeling methods, algorithm design, time scale, etc. How to achieve seamless connection and collaborative work between models is a technical challenge. Summary of the invention

[0004] According to the present invention, a method and system for predicting carbon emissions in the urban power sector and planning a new power system are provided to solve the technical problem of achieving seamless connection and collaborative work between models.

[0005] According to a first aspect of the present invention, a method for predicting carbon emissions in the urban power sector and planning a new power system is provided, comprising:

[0006] Calculate the energy demand of each department based on the city's GDP, population, industrial structure, and energy consumption characteristics;

[0007] Based on energy demand and combined with carbon emission factors, the total carbon emissions of the power sector are calculated;

[0008] Based on the total carbon emissions of the power sector in the base year, taking into account the city's energy endowment, emission reduction tasks, emission reduction policies and power generation technology improvements, and based on the economic, population and electricity consumption parameters on the power demand side, various development scenarios for the power system, including low-carbon, zero-carbon and negative-carbon, are designed;

[0009] Predict the carbon emissions and carbon reductions corresponding to the demand side under each scenario, and obtain the path for emission reduction from the demand side;

[0010] Taking the minimum net present value of the total system cost as the objective function, a multi-scenario optimization planning model of the power system is established by considering the urban power-related constraints as constraints, and the development path of the installed power capacity that meets the system cost and related constraints is calculated.

[0011] Optionally, the energy demand of each sector can be calculated based on the city's GDP, population, industrial structure, and energy consumption characteristics, including:

[0012] The energy demand of each department is calculated according to the following formula, including:

[0013] EC k =∑ i ∑ j AL i,j ×EI i,j ×S i,j,k (1)

[0014] In the formula, i = 1, 2, 3…6, corresponding to the terminal sectors in the model divided into residential life, industry, agriculture, transportation, commerce and others, j represents the sub-sector, EC k represents the demand for k types of energy, AL i,j represents the energy activity level of the jth sub-sector of the ith sector, EI i,j It represents the energy intensity per unit activity level of the i-sector and the j-sector, S i,j,k Represents the energy structure of terminal energy consumption.

[0015] Optionally, the total carbon emissions of the power sector are calculated based on the energy demand and combined with the carbon emission factor, including:

[0016] The total carbon emissions from the power sector are calculated using the following formula:

[0017] CE=∑ k EC k ×EF k (2)

[0018] Among them, CE is the total carbon emissions, EF is k Represents the carbon emission factor of k type of energy.

[0019] Optionally, taking the minimum net present value of the total system cost as the objective function, a multi-scenario optimization planning model of the power system is established by considering the constraints related to urban power as constraints, and calculating the development path of the installed power generation capacity that meets the system cost and related constraints, including:

[0020] According to the following formula, the development path of installed power generation capacity that meets system costs and related constraints is calculated:

[0021]

[0022] Where TC is the total cost, N t represents the total number of years from the baseline to the target year, p is the power generation technology, d is the discount rate, C c is the initial capital cost, C at is the capacity in year t, foct is the fixed operation and maintenance cost in year t, Voc t is the variable operation and maintenance cost in year t, P t is the output power in year t, F ct is the fuel cost in year t.

[0023] Optionally, it also includes:

[0024] Based on the long-term energy alternative planning system LEAP model, the urban power sector carbon emission pathway analysis framework adopts a bottom-up approach to calculate energy demand and pollutant emissions under different scenarios.

[0025] Optionally, it also includes:

[0026] The LEAP model of the long-term energy alternative planning system includes multiple modules such as key assumptions, demand, conversion, and resources. The key assumptions are to set the status of economic and social development and the key factors affecting the energy environment, including the city's GDP, population, industrial structure, and energy consumption characteristics; demand is to set the energy demand sectors, including residents, industry, agriculture, commerce, and transportation; conversion refers to the process of converting primary energy into secondary energy, including power generation and the transmission and distribution of electricity, among which the power generation modules include coal-fired power, oil-fired power, natural gas power, wind power, photovoltaics, and coal-fired power containing CCS technology, i.e., carbon capture and storage technology; resources include all energy involved in the model, both primary and secondary energy.

[0027] According to another aspect of the present invention, there is also provided a system for predicting carbon emissions in the urban power sector and planning a new power system, comprising:

[0028] Energy demand calculation module, used to calculate the energy demand of each department based on the city's gross domestic product GDP, population, industrial structure, and energy consumption characteristics data;

[0029] The module for calculating the total carbon emissions is used to calculate the total carbon emissions of the power sector based on energy demand and carbon emission factors;

[0030] Design a development prospect module, which is used to design low-carbon, zero-carbon and negative-carbon development scenarios for the power system based on the total carbon emissions of the power sector in the base year, taking into account the city's energy endowment, emission reduction tasks, emission reduction policies and power generation technology improvements, and based on the economic, population and electricity consumption parameters of the power demand side;

[0031] Obtain emission reduction path module, which is used to predict the carbon emissions and carbon emission reductions corresponding to the demand side under each scenario, and obtain the emission reduction path from the demand side;

[0032] The capacity development path calculation module is used to establish a multi-scenario optimization planning model for the power system with the lowest net present value of the total system cost as the objective function, considering the urban power-related constraints as constraints, and calculate the development path of the installed power capacity that meets the system cost and related constraints.

[0033] Optionally, the module for calculating energy demand comprises:

[0034] The energy demand calculation module is used to calculate the energy demand of each department according to the following formula, including:

[0035] EC k =∑ i ∑ j AL i,j ×EI i,j ×S i,j,k (1)

[0036] In the formula, i = 1, 2, 3…6, corresponding to the terminal sectors in the model divided into residential life, industry, agriculture, transportation, commerce and others, j represents the sub-sector, EC k represents the demand for k types of energy, AL i,j represents the energy activity level of the jth sub-sector of the ith sector, EI i,j It represents the energy intensity per unit activity level of the i-sector and the j-sector, S i,j,k Represents the energy structure of terminal energy consumption.

[0037] Optionally, a module for calculating total carbon emissions includes:

[0038] The carbon emission calculation submodule is used to calculate the total carbon emission of the power sector according to the following formula:

[0039] CE=∑ k EC k ×EF k (2)

[0040] Among them, CE is the total carbon emissions, EF is k Represents the carbon emission factor of k type of energy.

[0041] Optionally, the computing capacity development path module includes:

[0042] The capacity development path calculation submodule is used to calculate the installed capacity development path that meets the system cost and related constraints according to the following formula:

[0043]

[0044] Where TC is the total cost, N t represents the total number of years from the baseline to the target year, p is the power generation technology, d is the discount rate, Cc is the initial capital cost, C at is the capacity in year t, foc t is the fixed operation and maintenance cost in year t, Voc t is the variable operation and maintenance cost in year t, P t is the output power in year t, F ct is the fuel cost in year t.

[0045] Therefore, by comprehensively considering historical data of urban electricity consumption, changes in energy structure, technological progress, policy orientation and other factors, an accurate prediction of carbon emissions in the urban power sector in the future can be achieved, providing a scientific basis for government decision-making and power industry development planning. Based on the carbon emission prediction results, a new power system planning optimization method is proposed. This method aims to build a safe, clean, efficient and sustainable urban energy system by optimizing the energy structure, improving energy utilization efficiency, developing renewable energy, promoting flexible transformation of coal-fired power and low-carbon transformation. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] A more complete understanding of exemplary embodiments of the present invention may be obtained by referring to the following drawings:

[0047] Figure 1 A schematic diagram of a process for predicting carbon emissions in the urban power sector and a new power system planning method described in this implementation mode;

[0048] Figure 2 This is a schematic diagram of the carbon emission pathway analysis framework in the urban power sector based on the LEAP model described in this implementation mode;

[0049] Figure 3 A schematic diagram of carbon emission prediction for different industries according to this implementation mode;

[0050] Figure 4 A schematic diagram of the annual power generation costs of different power generation schemes described in this implementation mode;

[0051] Figure 5 This is a schematic diagram of a system for predicting carbon emissions in the urban power sector and planning a new power system according to this embodiment. DETAILED DESCRIPTION

[0052] Now, exemplary embodiments of the present invention are described with reference to the accompanying drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. These embodiments are provided to disclose the present invention in detail and completely and to fully convey the scope of the present invention to those skilled in the art. The terms used in the exemplary embodiments shown in the accompanying drawings are not intended to limit the present invention. In the accompanying drawings, the same units / elements are marked with the same reference numerals.

[0053] Unless otherwise specified, the terms (including technical terms) used herein have the commonly understood meanings to those skilled in the art. In addition, it is understood that the terms defined in commonly used dictionaries should be understood to have the same meanings as those in the context of the relevant fields, and should not be understood as idealized or overly formal meanings.

[0054] According to a first aspect of the present invention, a method 100 is provided, referring to Figure 1 As shown, the method 100 includes:

[0055] S101: Calculate the energy demand of each department based on the city’s GDP, population, industrial structure, and energy consumption characteristics;

[0056] S102: Based on energy demand and combined with carbon emission factors, calculate the total carbon emissions of the power sector;

[0057] S103: Based on the total carbon emissions of the power sector in the base year, taking into account the city's energy endowment, emission reduction tasks, emission reduction policies and power generation technology improvements, and based on the economic, population and electricity consumption parameters of the power demand side, design a variety of low-carbon, zero-carbon and negative-carbon development scenarios for the power system;

[0058] S104: predicting the carbon emissions and carbon reductions corresponding to the demand side under each scenario, and obtaining a path for emission reduction from the demand side;

[0059] S105: Taking the minimum net present value of the total system cost as the objective function, a multi-scenario optimization planning model of the power system is established by considering the urban power-related constraints as constraints, and the development path of the installed power generation capacity that meets the system cost and related constraints is calculated.

[0060] Specifically, refer to Figure 2As shown in the figure, firstly, based on the carbon emission path analysis framework of the urban power sector of the LEAP (long-range energy alternatives planning system) model, a bottom-up approach is used to accurately calculate the energy demand and pollutant emissions under different scenarios. The LEAP model includes four modules: key assumptions, demand, conversion, and resources. The key assumptions are mainly to set the status of economic and social development and the key factors affecting the energy environment, mainly including the city's GDP, population, industrial structure, and energy consumption characteristics; demand is mainly to set the energy demand sector, including residents, industry, agriculture, commerce, transportation, etc.; conversion refers to the conversion process of primary energy into secondary energy, including power generation and power transmission and distribution. The power generation module includes coal-fired power, oil-fired power, natural gas power, wind power, photovoltaics, and coal-fired power with CCS technology (carbon capture and storage technology); resources mainly include all energy involved in the model, including primary energy and secondary energy.

[0061] First, the terminal energy consumption of each department, that is, the energy demand, is calculated based on data such as the city’s gross domestic product (GDP), population, industrial structure, and energy consumption characteristics.

[0062] EC k =∑ i ∑ j AL i,j ×EI i,j ×S i,j,k (1)

[0063] In the formula, i = 1, 2, 3…6, corresponding to the terminal sectors in the model divided into residential life, industry, agriculture, transportation, commerce and others, and j represents the sub-sector. k represents the demand for k types of energy, AL i,j represents the energy activity level of the jth sub-sector of the ith sector, EI i,j It represents the energy intensity per unit activity level of the i-sector and the j-sector, S i,j,k Represents the energy structure of terminal energy consumption.

[0064] After obtaining the energy demand, we further used the power generation data, combined with the power generation structure (including the proportion of various power generation technologies such as thermal power generation, wind power generation, and solar power generation), the carbon emission factors of each power generation technology, and power generation efficiency, to accurately calculate the total carbon emissions of the power sector.

[0065] CE=∑ k EC k ×EF k (2)

[0066] EF kThe carbon emission factor of each energy type in the present invention adopts the carbon emission factor specified by IPCC and is already included in the LEAP model technology and environment database.

[0067] This invention takes 2020 as the base year and 2060 as the target year. Based on the total carbon emissions of the power sector in the base year, it considers the city's energy endowment, emission reduction tasks, emission reduction policies, and improvements in power generation technology. Based on parameters such as the economy, population, and electricity consumption on the power demand side, it designs three development scenarios for the power system: low-carbon, zero-carbon, and negative-carbon. It predicts the corresponding carbon emissions and carbon emission reductions on the demand side under each scenario, thereby obtaining the path to emission reduction from the demand side.

[0068] NEMO (Next Energy Modelling system) is a deterministic optimization tool for energy systems that aims to determine the lowest cost power generation expansion path required to meet electricity demand and seek to maximize the reserve profit margin at the lowest discounted total cost. These discounted costs cover the operation and maintenance (O&M) costs, capital / investment costs, raw material fuel costs, and externality costs of all power plants. Based on the NEMO tool, this paper takes the lowest net present value of the total system cost as the objective function, performs cost minimization for all modeling time periods at the same time, and all costs are discounted to the beginning of the simulation. Considering urban power demand constraints, unit operation constraints, unit construction capacity constraints, system reliability constraints, emission constraints, renewable energy target constraints, and resource constraints as constraints, a multi-scenario optimization planning model for the power system is established, and finally the development path of installed power capacity that meets system costs and related constraints is calculated.

[0069]

[0070] TC is the total cost, N t represents the total number of years from the baseline to the target year, p is the power generation technology, d is the discount rate, C c is the initial capital cost, Ca t is the capacity in year t, foc t is the fixed operation and maintenance cost in year t, Voc t is the variable operation and maintenance cost in year t, P t is the output power in year t, Fc t is the fuel cost in year t.

[0071] The embodiment of the present invention takes a city as the research object, takes 2020 as the base year, and sets the key assumptions. The city has a population of 3.5058 million and a GDP of 333.732 billion yuan. The forecast of the industrial structure includes commerce, transportation, industry, and residents. The forecast results are as follows: Figure 3 shown.

[0072] According to the forecast results, the city's transportation sector accounts for the largest proportion of carbon emissions, reaching a total of 20 million tons in 2060, while the commercial sector has the lowest carbon emissions, reaching a total of 3.4 million tons in 2060. Based on the total carbon emissions, the annual power generation costs of coal power, hydropower, natural gas, and wind power as single energy sources are calculated, including construction costs, operation and maintenance costs, etc., and the time value of money is considered. The net present value is calculated by discounting, such as Figure 4 shown.

[0073] Based on the NEMO tool, the objective function is to minimize the net present value of the total system cost, optimize the installed capacity of different energy sources, and obtain the optimal energy combination that meets all constraints.

[0074] Thus, by integrating the long-term energy balance capability of the LEAP model with the power market optimization capability of the NEMO model, the carbon emissions in the urban power system can be accurately and comprehensively predicted, better reflecting the actual application effect and policy effect of technical improvements. The present invention can provide scientific decision-making support to help urban planners formulate more efficient and sustainable power system planning schemes under different policy and market environments, and reduce system costs and carbon emissions. By analyzing and optimizing renewable energy resources, it can promote their integration and application in urban power systems, reduce dependence on fossil fuels, and reduce the overall carbon footprint.

[0075] Optionally, the energy demand of each sector can be calculated based on the city's GDP, population, industrial structure, and energy consumption characteristics, including:

[0076] The energy demand of each department is calculated according to the following formula, including:

[0077] EC k =Σ i Σ j AL i,j ×EI i,j ×S i,j,k (1)

[0078] In the formula, i = 1, 2, 3…6, corresponding to the terminal sectors in the model divided into residential life, industry, agriculture, transportation, commerce and others, j represents the sub-sector, EC k represents the demand for k types of energy, AL i,j represents the energy activity level of the jth sub-sector of the ith sector, EI i,j It represents the energy intensity per unit activity level of the i-sector and the j-sector, S i,j,k Represents the energy structure of terminal energy consumption.

[0079] Optionally, the total carbon emissions of the power sector are calculated based on the energy demand and combined with the carbon emission factor, including:

[0080] The total carbon emissions from the power sector are calculated using the following formula:

[0081] CE=Σ k EC k ×EF k (2)

[0082] Among them, CE is the total carbon emissions, EF is k Represents the carbon emission factor of k type of energy.

[0083] Optionally, taking the minimum net present value of the total system cost as the objective function, a multi-scenario optimization planning model of the power system is established by considering the constraints related to urban power as constraints, and calculating the development path of the installed power generation capacity that meets the system cost and related constraints, including:

[0084] According to the following formula, the development path of installed power generation capacity that meets system costs and related constraints is calculated:

[0085]

[0086] Where TC is the total cost, N t represents the total number of years from the baseline to the target year, p is the power generation technology, d is the discount rate, C c is the initial capital cost, C at is the capacity in year t, foc t is the fixed operation and maintenance cost in year t, Voc t is the variable operation and maintenance cost in year t, P t is the output power in year t, F ct is the fuel cost in year t.

[0087] Optionally, it also includes:

[0088] Based on the long-term energy alternative planning system LEAP model, the urban power sector carbon emission pathway analysis framework adopts a bottom-up approach to calculate energy demand and pollutant emissions under different scenarios.

[0089] Optionally, it also includes:

[0090] The LEAP model of the long-term energy alternative planning system includes multiple modules such as key assumptions, demand, conversion, and resources. The key assumptions are to set the status of economic and social development and the key factors affecting the energy environment, including the city's GDP, population, industrial structure, and energy consumption characteristics; demand is to set the energy demand sectors, including residents, industry, agriculture, commerce, and transportation; conversion refers to the process of converting primary energy into secondary energy, including power generation and the transmission and distribution of electricity, among which the power generation modules include coal-fired power, oil-fired power, natural gas power, wind power, photovoltaics, and coal-fired power containing CCS technology, i.e., carbon capture and storage technology; resources include all energy involved in the model, both primary and secondary energy.

[0091] Thus, by integrating the long-term energy balance capability of the LEAP model with the power market optimization capability of the NEMO model, the carbon emissions in the urban power system can be accurately and comprehensively predicted, better reflecting the actual application effect and policy effect of technical improvements. The present invention can provide scientific decision-making support to help urban planners formulate more efficient and sustainable power system planning schemes under different policy and market environments, and reduce system costs and carbon emissions. By analyzing and optimizing renewable energy resources, it can promote their integration and application in urban power systems, reduce dependence on fossil fuels, and reduce the overall carbon footprint.

[0092] According to another aspect of the present invention, a system 500 for predicting carbon emissions in the urban power sector and planning a new power system is provided. Figure 5 As shown, the system 500 includes:

[0093] The energy demand calculation module 510 is used to calculate the energy demand of each department based on the city's gross domestic product GDP, population, industrial structure, and energy consumption characteristics data;

[0094] A module 520 for calculating the total carbon emissions is used to calculate the total carbon emissions of the power sector based on the energy demand and the carbon emission factor;

[0095] Design development prospect module 530, which is used to design low-carbon, zero-carbon, and negative-carbon development scenarios for the power system based on the total carbon emissions of the power sector in the base year, taking into account the city's energy endowment, emission reduction tasks, emission reduction policies, and power generation technology improvements, and based on the economic, population, and electricity consumption parameters of the power demand side;

[0096] The emission reduction path acquisition module 540 is used to predict the carbon emissions and carbon emission reductions corresponding to the demand side under each scenario, and to acquire the emission reduction path from the demand side;

[0097] The capacity development path calculation module 550 is used to establish a multi-scenario optimization planning model for the power system with the lowest net present value of the total system cost as the objective function, considering the city power-related constraints as constraints, and calculate the power generation installed capacity development path that meets the system cost and related constraints.

[0098] Optionally, the module for calculating energy demand comprises:

[0099] The energy demand calculation module is used to calculate the energy demand of each department according to the following formula, including:

[0100] EC k =Σ i Σ j AL i,j ×EI i,j ×S i,j,k (1)

[0101] In the formula, i = 1, 2, 3…6, corresponding to the terminal sectors in the model divided into residential life, industry, agriculture, transportation, commerce and others, j represents the sub-sector, EC k represents the demand for k types of energy, AL i,j represents the energy activity level of the jth sub-sector of the ith sector, EI i,j It represents the energy intensity per unit activity level of the i-sector and the j-sector, S i,j,k Represents the energy structure of terminal energy consumption.

[0102] Optionally, a module for calculating total carbon emissions includes:

[0103] The carbon emission calculation submodule is used to calculate the total carbon emission of the power sector according to the following formula:

[0104] CE=Σ k EC k ×EF k (2)

[0105] Among them, CE is the total carbon emissions, EF is k Represents the carbon emission factor of k type of energy.

[0106] Optionally, the computing capacity development path module includes:

[0107] The capacity development path calculation submodule is used to calculate the installed capacity development path that meets the system cost and related constraints according to the following formula:

[0108]

[0109] Where TC is the total cost, N t represents the total number of years from the baseline to the target year, p is the power generation technology, d is the discount rate, Cc is the initial capital cost, C at is the capacity in year t, foc t is the fixed operation and maintenance cost in year t, Voc t is the variable operation and maintenance cost in year t, P t is the output power in year t, F ct is the fuel cost in year t.

[0110] A system 500 for predicting carbon emissions in the urban power sector and planning a new power system in an embodiment of the present invention corresponds to a method 100 for predicting carbon emissions in the urban power sector and planning a new power system in another embodiment of the present invention, which will not be repeated here.

[0111] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0112] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0113] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0114] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0115] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0116] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for predicting carbon emissions in the urban power sector and planning a new power system, characterized in that: include: Calculate the energy demand of each department based on the city's GDP, population, industrial structure, and energy consumption characteristics; Based on energy demand and combined with carbon emission factors, the total carbon emissions of the power sector are calculated; Based on the total carbon emissions of the power sector in the base year, taking into account the city's energy endowment, emission reduction tasks, emission reduction policies and power generation technology improvements, and based on the economic, population and electricity consumption parameters on the power demand side, various development scenarios for the power system, including low-carbon, zero-carbon and negative-carbon, are designed; Predict the carbon emissions and carbon reductions corresponding to the demand side under each scenario, and obtain the path for emission reduction from the demand side; Taking the minimum net present value of the total system cost as the objective function, a multi-scenario optimization planning model of the power system is established by considering the urban power-related constraints as constraints, and the development path of the installed power generation capacity that meets the system cost and related constraints is calculated.

2. The method according to claim 1, characterized in that Based on the city's GDP, population, industrial structure, and energy consumption characteristics, the energy demand of each department is calculated, including: The energy demand of each department is calculated according to the following formula, including: EC k ∑ i ∑ j IT i,j ×EI i,j ×S i,j,k (1) In the formula, i = 1, 2, 3…6, corresponding to the terminal sectors in the model divided into residential life, industry, agriculture, transportation, commerce and others, j represents the sub-sector, EC k represents the demand for k types of energy, AL i,j represents the energy activity level of the jth sub-sector of the ith sector, EI i,j It represents the energy intensity per unit activity level of the i-sector and the j-sector, S i,j,k Represents the energy structure of terminal energy consumption.

3. The method according to claim 1, characterized in that Based on energy demand and carbon emission factors, the total carbon emissions of the power sector are calculated, including: The total carbon emissions from the power sector are calculated using the following formula: CE=Σ k EC k ×EF k (2) Among them, CE is the total carbon emissions, EF is k Represents the carbon emission factor of k type of energy.

4. The method according to claim 1, characterized in that: Taking the minimum net present value of the total system cost as the objective function, the multi-scenario optimization planning model of the power system is established by considering the urban power-related constraints as constraints, and the development path of the installed power generation capacity that meets the system cost and related constraints is calculated, including: According to the following formula, the development path of installed power generation capacity that meets system costs and related constraints is calculated: Where TC is the total cost, N t represents the total number of years from the baseline to the target year, p is the power generation technology, d is the discount rate, C c is the initial capital cost, C at is the capacity in year t, foc t is the fixed operation and maintenance cost in year t, Voc t is the variable operation and maintenance cost in year t, P t is the output power in year t, F ct is the fuel cost in year t.

5. The method according to claim 1, characterized in that Also includes: Based on the long-term energy alternative planning system LEAP model, the urban power sector carbon emission pathway analysis framework adopts a bottom-up approach to calculate energy demand and pollutant emissions under different scenarios.

6. The method according to claim 5, characterized in that Also includes: The LEAP model of the long-term energy alternative planning system includes multiple modules such as key assumptions, demand, conversion, and resources. The key assumptions are to set the status of economic and social development and the key factors affecting the energy environment, including the city's GDP, population, industrial structure, and energy consumption characteristics; demand is to set the energy demand sectors, including residents, industry, agriculture, commerce, and transportation; conversion refers to the conversion process of primary energy into secondary energy, including power generation and the transmission and distribution of electricity, among which the power generation module includes coal-fired power, oil-fired power, natural gas power, wind power, photovoltaics, and coal-fired power containing CCS technology, i.e., carbon capture and storage technology; resources include all energy involved in the model, both primary and secondary energy.

7. A system for predicting carbon emissions in the urban power sector and planning new power systems, characterized in that: include: Energy demand calculation module, used to calculate the energy demand of each department based on the city's gross domestic product GDP, population, industrial structure, and energy consumption characteristics data; The module for calculating the total carbon emissions is used to calculate the total carbon emissions of the power sector based on energy demand and carbon emission factors; Design a development prospect module, which is used to design low-carbon, zero-carbon and negative-carbon development scenarios for the power system based on the total carbon emissions of the power sector in the base year, taking into account the city's energy endowment, emission reduction tasks, emission reduction policies and power generation technology improvements, and based on the economic, population and electricity consumption parameters of the power demand side; Obtain emission reduction path module, which is used to predict the carbon emissions and carbon emission reductions corresponding to the demand side under each scenario, and obtain the emission reduction path from the demand side; The capacity development path calculation module is used to establish a multi-scenario optimization planning model for the power system with the lowest net present value of the total system cost as the objective function, considering the urban power-related constraints as constraints, and calculate the development path of the installed power capacity that meets the system cost and related constraints.

8. The system according to claim 7, characterized in that Module for calculating energy demand, including: The energy demand calculation module is used to calculate the energy demand of each department according to the following formula, including: EC k ∑ i ∑ j IT i,j ×EI i,j ×S i,j,k (1) In the formula, i = 1, 2, 3…6, corresponding to the terminal sectors in the model divided into residential life, industry, agriculture, transportation, commerce and others, j represents the sub-sector, EC k represents the demand for k types of energy, AL i,j represents the energy activity level of the jth sub-sector of the ith sector, EI i,j It represents the energy intensity per unit activity level of the i-sector and the j-sector, S i,j,k Represents the energy structure of terminal energy consumption.

9. The system according to claim 7, characterized in that Module for calculating total carbon emissions, including: The carbon emission calculation submodule is used to calculate the total carbon emission of the power sector according to the following formula: WHAT=∑ k EC k ×EF k (2) Among them, CE is the total carbon emissions, EF is k Represents the carbon emission factor of k type of energy.

10. The system according to claim 7, characterized in that Compute capacity development path module, including: The capacity development path calculation submodule is used to calculate the installed capacity development path that meets the system cost and related constraints according to the following formula: Where TC is the total cost, N t represents the total number of years from the baseline to the target year, p is the power generation technology, d is the discount rate, C c is the initial capital cost, C at is the capacity in year t, foc t is the fixed operation and maintenance cost in year t, Voc t is the variable operation and maintenance cost in year t, P t is the output power in year t, F ct is the fuel cost in year t.

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