Surface mine low-carbon energy planning method and system and computer equipment

Abstract

The invention discloses a surface mine low-carbon energy planning method and system and computer equipment, and the method comprises the steps: calculating the historical total energy consumption and historical total carbon emission of a surface mine; inputting the historical total energy consumption and the historical total carbon emission into a time sequence prediction model to obtain a time sequence prediction result of the total energy consumption and the total carbon emission under the reference scene; calculating a total energy consumption prediction value and a carbon emission prediction value under the reference scene based on the total energy consumption and total carbon emission time sequence prediction result and a preset production plan coefficient; and based on the carbon emission reduction value, the total energy consumption prediction value and the carbon emission prediction value of the green low-carbon scene, calculating the total carbon emission of the green low-carbon scene, and performing low-carbon energy planning according to the total carbon emission of the green low-carbon scene to obtain a low-carbon energy planning path. According to the invention, combined application of various low-carbon, zero-carbon and negative-carbon technologies can be automatically planned, energy and carbon emission low-carbon transformation paths and development trends of enterprises can be simulated, and low-carbon transformation decision making of strip mine enterprises can be assisted.

Description

Technical Field

[0001] The present invention relates to the technical field of energy planning, and in particular to a method, system and computer equipment for low-carbon energy planning in an open-pit mine. Background Art

[0002] Under the low-carbon goal, in order to promote the clean and low-carbon development of open-pit mines, we will promote the green, low-carbon and sustainable development of open-pit mines from the aspects of optimizing the energy consumption structure and promoting the application of low-carbon technologies. Through digital means to assist enterprises in the supervision of energy consumption data, automatically verify the carbon emissions of enterprises, and use low-carbon technical means such as heavy-duty truck electric energy replacement, zero-carbon technical means of photovoltaic and wind power, and negative carbon technical means of forest carbon sinks in spoil fields as the basis to reduce the huge energy consumption and carbon emissions caused by fossil energy consumption, promote the sustainable development of clean energy in open-pit mine production, and promote the low-carbon transformation of open-pit mines from the perspective of energy consumption structure and low-carbon technical means. Under the low-carbon goal, it is of great significance.

[0003] Prior art patent number CN114971048A A zero-carbon park comprehensive energy planning simulation method, system and computer equipment, the invention performs comprehensive energy planning simulation for zero-carbon parks, through comprehensive carbon accounting of the park, characteristic analysis of wind and light natural resources and load characteristic data analysis, with carbon emissions, investment costs, and new energy consumption rate as optimization targets, capacity planning and configuration of cold energy, heat energy, and electric energy energy systems to form the optimal capacity configuration and operation plan. Prior art solution 2: Prior art patent number CN 106650995A, the invention includes an energy demand prediction module, an energy optimization module and a scenario analysis module. The energy demand prediction module predicts the terminal energy demand of various departments by scientifically setting future social and economic development parameters in a variety of ways; the energy optimization module takes the TIMES energy optimization model as the core, inputs data such as energy efficiency, pollutant emission factors, and technical costs, and optimizes the system according to the principle of minimizing total cost; the scenario analysis module presets a goal, drives the energy optimization module to iterate cyclically, selects the optimal fuel and technology combination under the scenario, and outputs results such as energy supply structure, energy consumption structure, and pollutant emission structure. The present invention can scientifically predict the evolution trend of regional medium- and long-term energy consumption and pollutant emissions, thereby proposing feasible goals and implementation paths for energy transformation under the goal of energy conservation and emission reduction. Prior art solution three: Prior art patent number CN113420958A: Regional demand-side low-carbon energy planning method and system considering electric energy substitution, the invention includes: conducting planning area resource analysis: according to the utilization of clean energy in the region, analyzing low-grade energy that can be used to improve energy quality; conducting load and demand forecasting: obtaining hourly load curves, and making more accurate predictions of regional loads through simulation and expansion methods; analyzing the influencing factors of energy planning considering electric energy substitution: analyzing the main factors affecting energy planning in each region based on the applicability of electric energy substitution in each region; conducting resource allocation and optimization: using the regional demand-side low-carbon energy planning model under electric energy substitution technology to allocate and optimize resources; conducting comprehensive evaluation of economic energy conservation and environmental protection benefits: evaluating regional carbon emissions and pollutant emissions after electric energy substitution technology is configured.

[0004] Disadvantages of the first existing technical solution: In the invention patent CN 114971048 A, only photovoltaic and wind power are used for comprehensive energy planning. However, unlike the industrial park, the consumption of diesel and electricity in the production process of the open-pit mine is huge, which is the main source of energy consumption and carbon emissions. The planning method of this invention cannot meet the low-carbon needs of the open-pit mine, and the application of low-carbon and negative carbon technologies needs to be further supplemented. Disadvantages of the second existing technical solution: In the invention patent CN 106650995 A, the planning is only carried out from the perspective of energy structure adjustment based on the pre-set social and economic development parameters. It is impossible to combine this method with the actual production plan, energy consumption, battery replacement heavy trucks, carbon sinks in the spoil field and other characteristics unique to the open-pit mine. It does not consider the carbon emission calculation method in the production and operation of the mine, the carbon emission reduction calculation method of the battery replacement heavy truck, etc., and it is impossible to simulate the energy planning and carbon emission path under the established low-carbon target. Disadvantages of the existing technical solution three: Invention patent CN113420958 A mainly considers the optimization of horizontal energy resource allocation in the region, and cannot simulate the future medium- and long-term energy planning and carbon emission path. It is not suitable for the medium- and long-term energy planning of open-pit mines under the established low-carbon goals. Summary of the invention

[0005] The present invention aims to solve one of the technical problems in the related art at least to a certain extent.

[0006] To this end, the present invention proposes a low-carbon energy planning method for open-pit mines, which can monitor the diesel, gasoline, electricity, and thermal energy consumption in the production process of open-pit mines, analyze the energy structure of enterprises, and check the carbon emissions of enterprises to carry out low-carbon energy planning. Through the low-carbon energy planning method of the present invention, medium- and long-term planning can be carried out after the low-carbon target year set by the open-pit mining enterprise, and the combined application of various low-carbon, zero-carbon, and negative-carbon technologies can be automatically planned, and the energy and carbon emission low-carbon transformation path and development trend of the enterprise can be simulated to assist the low-carbon transformation decision of the open-pit mining enterprise.

[0007] Another object of the present invention is to provide a low-carbon energy planning system for open-pit mines.

[0008] A third object of the present invention is to provide a computer device.

[0009] To achieve the above-mentioned object, the present invention proposes a low-carbon energy planning method for an open-pit mine, comprising:

[0010] Calculate the total historical energy consumption and carbon emissions of open-pit mines;

[0011] Inputting the historical total energy consumption and the historical total carbon emissions into the time series prediction model to obtain the time series prediction results of the total energy consumption and the total carbon emissions under the baseline scenario;

[0012] Calculate the total energy consumption forecast value and the total carbon emission forecast value under the baseline scenario based on the total energy consumption and total carbon emission time series forecast results and the preset production plan coefficient;

[0013] The total carbon emissions of the green low-carbon scenario are calculated based on the carbon emission reduction value of the green low-carbon scenario, the total energy consumption forecast value and the carbon emission forecast value, so as to carry out low-carbon energy planning according to the total carbon emissions of the green low-carbon scenario and obtain a low-carbon energy planning path.

[0014] The open-pit mine low-carbon energy planning method of the embodiment of the present invention may also have the following additional technical features:

[0015] In one embodiment of the present invention, the total historical energy consumption is calculated by the following formula:

[0016] Total historical energy consumption = total electricity consumption * C 电 +Total diesel consumption*C 柴 +Total gasoline consumption*C 汽 + Total heat consumption*C 热 ;

[0017] Among them, the total electricity consumption, including purchased electricity and self-generated electricity from clean energy, C 电 is the electricity conversion coefficient of standard coal, C 柴 C is the diesel fuel conversion coefficient to standard coal, 汽 is the gasoline to standard coal coefficient, C 热 It is the thermal coefficient of standard coal.

[0018] In one embodiment of the present invention, the total historical carbon emissions are calculated by the following formula:

[0019] Total historical carbon emissions = total carbon emissions from net purchased electricity + total carbon emissions from diesel + total carbon emissions from gasoline + total carbon emissions from net purchased heat;

[0020] in,

[0021] Total carbon emissions from net purchased electricity = AD co2净电 *EF 电力 ;

[0022] Total net purchased thermal carbon emissions = AD co2净热 *EF 热力 ;

[0023]

[0024]

[0025] CC 柴 =NCV 柴 *EF 柴;

[0026] CC 汽 =NCV 汽 *EF 汽 ;

[0027] Among them, the total carbon emissions from net purchased electricity are the CO2 emissions implied by the net electricity purchased by the enterprise; the total carbon emissions from net purchased heat are the CO2 emissions implied by the net heat purchased by the enterprise; AD co2净电 The net electricity consumption purchased by the enterprise; AD co2净热 EF is the net purchase of heat consumption by the enterprise; 电力 is the CO2 emission factor for electricity supply, EF 热力 CO2 emission factor for heat supply; AD 柴 is diesel consumption, CC 柴 is the carbon content of diesel, OF 柴 is the diesel carbon oxidation rate, AD 汽 is gasoline consumption, CC 汽 is the carbon content of gasoline, OF 汽 NCV is the gasoline carbon oxidation rate; 柴 The low calorific value of diesel, EF 柴 NCV is the carbon content per unit calorific value of diesel; 汽 is the low calorific value of gasoline, EF 汽 It is the carbon content per unit calorific value of gasoline.

[0028] In one embodiment of the present invention, the total energy consumption prediction value is calculated by the following formula:

[0029] Total carbon emissions in the baseline scenario i =Total carbon emissions S i *Production planning coefficient i ;

[0030]

[0031] Among them, the total carbon emissions in the baseline scenario i is the predicted total carbon emissions in the future i-th year under the baseline scenario, and the total carbon emissions S i is the time series forecast result of the total carbon emissions in the future i-th year under the baseline scenario, and the production planning coefficient i The planned output of raw coal during the planning period i Coal production in the base year p ratio; i = p+1, p+2, p+3,…, q.

[0032] In one embodiment of the present invention, the carbon emission reduction value of the green and low-carbon scenario, including the carbon emission reduction value of the battery-swapped heavy truck with low-carbon technology, is calculated by the following formula:

[0033]

[0034] CC 柴 =NCV 柴 *EF 柴 ;

[0035]

[0036]

[0037]

[0038] The total annual carbon emissions of a battery-swap heavy-duty truck = the total annual carbon emissions of a fuel heavy-duty truck * (1-carbon reduction rate of battery-swap heavy-duty truck);

[0039] Carbon emission reduction value of battery-swap heavy trucks i = Change in the number of fuel heavy trucks i *Total annual carbon emissions of a fuel heavy truck*Production planning coefficient i +Changes in the number of battery-swap heavy trucks i *Total annual carbon emissions of a battery-swap heavy truck*Production plan coefficient i ;

[0040] Changes in the number of fuel heavy trucks i = Number of fuel heavy trucks i -Number of fuel heavy trucks in the base year;

[0041] Changes in the number of battery-swap heavy trucks i =Number of battery-swapped heavy trucks i -Number of heavy trucks with battery replacement in the base year;

[0042] Among them, CC 柴 is the carbon content of diesel, NCV 柴 The low calorific value of diesel, EF 柴 is the carbon content per unit calorific value of diesel, OF 柴 is the diesel carbon oxidation rate; EF 电力 CO2 emission factor for electricity supply; carbon emission reduction value for battery-swapped heavy trucks i is the carbon emission reduction value of battery-swapped heavy-duty trucks in year i, and the number of fuel heavy-duty trucks changes i is the change in the number of fuel heavy trucks and battery heavy trucks in year i i is the change in the number of battery-powered heavy trucks in year i, and the number of fuel heavy trucks i is the number of fuel heavy trucks and battery heavy trucks in year i i is the number of battery-swap heavy-duty trucks in the i-th year, the number of fuel heavy-duty trucks in the base year is the number of fuel heavy-duty trucks in the base year, and the number of battery-swap heavy-duty trucks in the base year is the number of battery-swap heavy-duty trucks in the base year.

[0043] In one embodiment of the present invention, the carbon emission reduction value of the green and low-carbon scenario also includes the carbon emission reduction value of the battery-swapped heavy truck with low-carbon technology, which is calculated by the following formula:

[0044] Calculate the photovoltaic installed capacity in year i i , Annual theoretical photovoltaic power generation i and annual carbon emission reduction of photovoltaic i :

[0045]

[0046] Constraints:

[0047]

[0048] Theoretical annual photovoltaic power generation i = Photovoltaic installed capacity i * Annual full pay hours;

[0049] Annual carbon emission reduction from photovoltaic power generation i = Annual carbon emission reduction from photovoltaic power generation*EF 电力 ;

[0050] Among them, photovoltaic installed capacity i is the photovoltaic developable area in year i i Estimated installed capacity of all photovoltaic power generation used for photovoltaic construction, and the area that can be developed for photovoltaic power generation i is the total area used for photovoltaic development as of the i-th year. The total area that can be developed for photovoltaic development is the total land area that can be developed for photovoltaic development. The annual theoretical power generation of photovoltaic i is the theoretical annual power generation of photovoltaic power plants built in the i-th year; the annual carbon emission reduction of photovoltaic power plants i is the annual carbon emission reduction of the photovoltaic power plants that have been built in the i-th year;

[0051] Calculate the installed capacity of wind power in year i i , Annual theoretical power generation of wind power i , Annual carbon emission reduction of wind power i :

[0052] Wind power installed capacity i = Area that can be developed for wind power i * Wind power installed capacity per unit area

[0053] Constraints:

[0054]

[0055] Annual theoretical wind power generation i = Wind power installed capacity i *Equivalent utilization hours;

[0056] Annual carbon emission reduction from wind power i= Annual theoretical wind power generation i *EF 电力 ;

[0057] The total area that can be developed for wind power is the total area that can be used for wind power development. i is the total area used for wind power development as of year i, and the installed capacity of wind power i is the area that can be developed for wind power in year i i Wind power installed capacity used for wind power construction; wind power annual theoretical power generation i is the theoretical annual power generation of wind power that has been built in the i-th year; the annual carbon emission reduction of wind power i is the annual carbon emission reduction of photovoltaic power plants that have been built in the i-th year.

[0058] In one embodiment of the present invention, the carbon emission reduction value of the green and low-carbon scenario also includes the carbon emission reduction value of the spoil dump forestry carbon sink of the negative carbon technology, which is calculated by the following formula:

[0059] Carbon sink in spoil dump i = Area of ​​spoil dump management i *4.42;

[0060] Constraints:

[0061]

[0062] Among them, the carbon sink of the dump i is the carbon sink amount generated by the developed spoil dump forestry carbon sink project in year i, and the spoil dump management area i is the total area used for wind power development by the i-th year, and 4.42 is the carbon sequestration capacity of new afforestation.

[0063] In one embodiment of the present invention, the total carbon emissions of the green low-carbon scenario are calculated based on the carbon emission reduction value of the green low-carbon scenario, the total energy consumption forecast value and the carbon emissions forecast value, including:

[0064] Total carbon emissions in green and low-carbon scenarios i = Total carbon emissions in the baseline scenario i +Carbon emission reduction value of battery-swap heavy trucks i -Annual carbon emission reduction from photovoltaic power generation i - Annual carbon emission reduction from wind power i - Carbon sink in spoil dump i -Carbon sink trading volume i ;

[0065] Constraints:

[0066]

[0067] Among them, the total carbon emissions in the green and low-carbon scenario iis the total carbon emissions in the i-th year under the green and low-carbon scenario, and the carbon sink trading volume i It is the amount of carbon sinks purchased by open-pit coal mining enterprises participating in carbon sink trading in year i.

[0068] To achieve the above object, the present invention provides a low-carbon energy planning system for open-pit mines, comprising:

[0069] The historical data calculation module is used to calculate the total historical energy consumption and carbon emissions of the open-pit mine;

[0070] A model result output module is used to input the historical total energy consumption and the historical total carbon emissions into the time series prediction model to obtain the total energy consumption and total carbon emissions time series prediction results under the baseline scenario;

[0071] A baseline data prediction module, used to calculate the total energy consumption prediction value and the carbon emission prediction value under the baseline scenario based on the total energy consumption and total carbon emission time series prediction results and the preset production plan coefficient;

[0072] The low-carbon energy planning module is used to calculate the total carbon emissions of the green low-carbon scenario based on the carbon emission reduction value of the green low-carbon scenario, the total energy consumption forecast value and the carbon emission forecast value, so as to carry out low-carbon energy planning according to the total carbon emissions of the green low-carbon scenario to obtain a low-carbon energy planning path.

[0073] The open-pit mine low-carbon energy planning method and system of the embodiments of the present invention can carry out medium- and long-term planning after the low-carbon target year set by the open-pit mining enterprise, automatically plan the combined application of various low-carbon, zero-carbon, and negative-carbon technologies, simulate the enterprise's energy and carbon emissions low-carbon transformation path and development trend, and assist the open-pit mining enterprise in making low-carbon transformation decisions.

[0074] To achieve the above-mentioned purpose, the third aspect embodiment of the present application proposes a computer device, comprising: a processor and a memory; wherein the processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to implement the open-pit mine low-carbon energy planning method as described in the first aspect embodiment.

[0075] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0077] Figure 1 is an architecture diagram of a low-carbon energy planning method for an open-pit mine according to an embodiment of the present invention;

[0078] Figure 2 is a flow chart of a low-carbon energy planning method for an open-pit mine according to an embodiment of the present invention;

[0079] Figure 3 is a schematic diagram of the structure of a low-carbon energy planning system for an open-pit mine according to an embodiment of the present invention;

[0080] Figure 4 is a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0081] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0082] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0083] The following describes a method and system for low-carbon energy planning for an open-pit mine according to an embodiment of the present invention with reference to the accompanying drawings.

[0084] It is understandable that smart, unmanned, green and zero carbon is the overall goal of open-pit mine planning. Realize the application of automated, intelligent and clean equipment and systems in production, realize the integration of information data chains, data processing and auxiliary decision-making, realize the integrated management and control of intelligent mining design and production organization, and finally realize green production, low-carbon emissions, smart and efficient, and less-manned modern open-pit coal mines. Carry out ecological restoration and governance work step by step and in stages, and achieve 100% governance rate from the spoil dump to the boundary area. Through the construction of photovoltaic, wind farms and forestry carbon sinks in the spoil dump, the ecological environment of the mine is effectively protected and the level of ecological restoration and governance in the mining area is comprehensively improved. Expand the promotion and use of battery-swap heavy trucks in open-pit coal mines, improve the utilization rate of renewable energy, and realize the replacement of wide-body vehicles, 100-ton dump trucks, and engineering equipment.

[0085] When open-pit mines are being audited for carbon emissions today, they are mainly calculated for diesel, gasoline, electricity, and thermal energy used in production and operations. The combustion of fossil fuels and the consumption of electricity are the main energy consumption in open-pit mine production, and are also the main sources of carbon emissions. From the perspective of energy consumption, large electric shovels and conveyor belts consume a lot of electricity during coal mining, and various types of mining trucks consume a lot of diesel during coal transportation. The consumption of diesel and electricity constitutes the main energy consumption and carbon emission sources of open-pit mines. Therefore, when conducting mid- and long-term energy planning for open-pit mines, the clean and low-carbon development of these two types of energy should be considered. Based on the above analysis, the framework of the present invention is as follows: Figure 1 As shown, the diesel, electricity, gasoline and heat consumption data of open-pit mines in recent years are checked and counted, and the energy consumption and carbon emissions of previous years are calculated; the year for the open-pit mine to achieve low carbon is set; combined with the future production plan of the open-pit coal mine, the future energy consumption and carbon emissions under the baseline scenario are predicted; low-carbon technologies, zero-carbon technologies and negative-carbon technologies are set to achieve low carbon; based on the energy consumption and carbon emissions under the baseline scenario, combined with the low-carbon target year and low-carbon technologies, zero-carbon technologies and negative-carbon technologies, energy planning is automatically carried out to achieve low-carbon path simulation.

[0086] Figure 2 It is a flow chart of a low-carbon energy planning method for an open-pit mine according to an embodiment of the present invention.

[0087] like Figure 2 As shown, the method includes but is not limited to the following steps:

[0088] S1, calculate the total historical energy consumption and total historical carbon emissions of open-pit mines.

[0089] Under the low-carbon accounting system, the carbon emissions of open-pit mines mainly come from the use of four types of energy: electricity, diesel, gasoline, and heat. Therefore, in order to calculate the historical time series data of energy consumption and carbon emissions of open-pit mines, it is necessary to obtain the total annual consumption data of electricity, diesel, gasoline, and heat in the production and operation of open-pit mines, and calculate the total energy consumption over the years through formula (1):

[0090] Total energy consumption = total electricity consumption × C 电 +Total diesel consumption×C 柴 + Total gasoline consumption × C 汽 + Total heat consumption × C 热 (1)

[0091] Among them, total energy consumption - unit: tons of standard coal; total electricity consumption - including purchased electricity and self-generated electricity from clean energy, unit: kWh; C 电 -Electricity conversion coefficient of standard coal, C 电 =0.1229×10 -3t / kWh; Total diesel consumption - unit: ton (t); C 柴 - Diesel fuel to standard coal coefficient, C 柴 =1.4571t / t; Total gasoline consumption - unit: tons (t); C 汽 -Gasoline to standard coal coefficient, C 汽 =1.4714t / t; Total heat consumption - unit: GJ; C 热 -Thermal coefficient of standard coal, C 热 =0.03412t / GJ.

[0092] The total carbon emissions over the years are calculated using formula (2):

[0093] Total carbon emissions = total carbon emissions from net purchased electricity + total carbon emissions from diesel + total carbon emissions from gasoline + total carbon emissions from net purchased heat (2)

[0094] In the formula, each total amount unit is tons of CO2;

[0095] Total carbon emissions from net purchased electricity = AD co2净电 ×EF 电力 ;

[0096] Total net purchased thermal carbon emissions = AD co2净热 ×EF 热力 ;

[0097] Among them: Total carbon emissions from net purchased electricity - refers to the CO2 emissions implied by the net purchased electricity of the enterprise, in tons of CO2; Total carbon emissions from net purchased heat - refers to the CO2 emissions implied by the net purchased heat of the enterprise, in tons of CO2; AD co2净电 The net electricity consumption purchased by the enterprise is expressed in megawatt hours (MWh); AD co2净热 The net purchased heat consumption of the enterprise, in GJ; EF 电力 EF is the CO2 emission factor of electricity supply, in tCO2 / MWh. The CO2 emission factor of electricity supply should be the average CO2 emission factor of the regional power grid to which the enterprise's production site belongs. The value should be determined based on the latest data released by the competent authority. If it cannot be provided, it should be 0.7769t CO2 / MWh. 热力 It is the CO2 emission factor of heat supply, and its unit is tCO2 / GJ. The CO2 emission factor of heat supply should give priority to the CO2 emission factor provided by the heating unit. If it cannot be provided, it shall be calculated as 0.11 tons CO2 / GJ.

[0098]

[0099]

[0100] In the formula: total carbon emissions from diesel and gasoline Unit: tons of CO2; AD 柴 is diesel consumption, in tons; CC 柴 is the carbon content of diesel, in tons of carbon / ton of fuel; OF 柴 is the diesel carbon oxidation rate, dimensionless, 98%; AD 汽 is gasoline consumption, in tons; CC 汽 is the carbon content of gasoline, in tons of carbon / ton of fuel; OF 汽 is the gasoline carbon oxidation rate, dimensionless, 98%;

[0101] CC 柴 =NCV 柴 ×EF 柴 ;

[0102] NCV 柴 It is the lower calorific value of diesel, unit is million kilojoules (GJ) / ton, and the value is 43.330 (GJ) / ton; EF 柴 is the carbon content of diesel per unit calorific value, unit: ton carbon / GJ, value is 20.20×10 -3 Tons of carbon / GJ.

[0103] CC 汽 =NCV 汽 ×EF 汽 ;

[0104] NCV 汽 The lower calorific value of gasoline, in units of million kilojoules (GJ) / ton, is 44.800 (GJ) / ton; EF 汽 is the carbon content of gasoline per unit calorific value, unit: tons of carbon / GJ, value is 18.9×10 -3 Tons of carbon / GJ.

[0105] The total energy consumption of each year (referred to as total energy consumption) is calculated by formula (1) and formula (2) respectively. t ) and the total carbon emissions over the years (recorded as total carbon emissions t ).

[0106] S2, input the historical total energy consumption and the historical total carbon emissions into the time series prediction model to obtain the time series prediction results of the total energy consumption and the total carbon emissions under the baseline scenario.

[0107] S3, based on the time series forecast results of total energy consumption and total carbon emissions and the preset production plan coefficient, calculate the total energy consumption forecast value and carbon emissions forecast value under the baseline scenario.

[0108] First, set the base year and planning year; p: base year, indicating the reference year of the baseline scenario; q: planning year, indicating the last year of the planning period; i is the complete number of years in the planning period, i = p+1, p+2, p+3, ..., q.

[0109] The baseline scenario is a scenario in which the current energy structure and production technology are maintained, without adding other low-carbon, zero-carbon, and negative-carbon technologies, and energy consumption and carbon emissions are only related to the raw coal production capacity of the production plan.

[0110] The energy structure and comprehensive energy efficiency of electricity, diesel, gasoline, and thermal power in open-pit mines are relatively stable within a certain range. Therefore, it can be considered that the consumption of these four types of energy shows a positive linear correlation with the raw coal production capacity value, that is, energy consumption will increase linearly with the increase in raw coal production capacity value.

[0111] SARIMA is a time series forecasting model that is an extension of the ARIMA model. ARIMA is an autoregressive moving average model used to analyze and forecast time series data. SARIMA includes seasonal factors and can handle time series data with obvious seasonal changes. The SARIMA model consists of four parts: seasonal autoregression (p), seasonal difference (d), seasonal moving average (q), and non-seasonal autoregressive moving average (P, D, Q). The SARIMA model can be used to predict and analyze time series data based on the seasonality of time series data. It can help us understand the trend, seasonality, and periodicity of time series data, thereby providing accurate forecasts and decision support.

[0112] In one embodiment of the present invention, the future energy consumption of the baseline scenario is calculated based on the results of the time series prediction model combined with the production plan coefficient, and the calculation formulas are as shown in Formula (3) and Formula (4).

[0113] Total energy consumption in the baseline scenario i = Total energy consumption S i *Production planning coefficient i (3)

[0114]

[0115] Including: Total energy consumption in the baseline scenario i is the predicted total energy consumption in the future i-th year under the baseline scenario; the total energy consumption S i is the time series forecast result of total energy consumption in the future i-th year under the baseline scenario; production planning coefficient i The planned output of raw coal during the planning period i Coal production in the base year p ratio; i = p+1, p+2, p+3,…, q.

[0116] In one embodiment of the present invention, the total future carbon emissions of the baseline scenario are calculated based on the results of the time series prediction model combined with the production plan coefficient, and the calculation formulas are as shown in Formula (5) and Formula (6).

[0117] Total carbon emissions in the baseline scenario i =Total carbon emissions Si*production planning coefficient i (5)

[0118]

[0119] Including: Total carbon emissions in the baseline scenario i is the predicted value of total carbon emissions in the future i-th year under the baseline scenario; total carbon emissions S i is the time series forecast result of the total carbon emissions in the future i-th year under the baseline scenario; the production planning coefficient i The planned output of raw coal during the planning period i Coal production in the base year p ratio; i = p+1, p+2, p+3,…, q.

[0120] The above calculations give the total energy consumption of the baseline scenario during the baseline scenario planning period. i and the total carbon emissions in the baseline scenario i Predicted value.

[0121] S4, based on the carbon emission reduction value, total energy consumption forecast value and carbon emission forecast value of the green low-carbon scenario, the total carbon emission of the green low-carbon scenario is calculated, so as to carry out low-carbon energy planning according to the total carbon emission of the green low-carbon scenario and obtain a low-carbon energy planning path.

[0122] It is understandable that the green and low-carbon scenario is compared with the baseline scenario. It means that on the basis of the baseline scenario, by increasing the use of low-carbon technology, zero-carbon technology, and negative carbon technology, open-pit mines will enter a green and low-carbon development mode, and through clean energy substitution and optimization of energy structure, it will help open-pit mines achieve low-carbon goals.

[0123] It is understandable that for open-pit mines, in order to reduce diesel consumption in the production and transportation links, the energy structure can be optimized by replacing diesel dump trucks with energy-saving and low-carbon technologies such as battery-swap dump trucks, reducing the proportion of diesel in total energy consumption and increasing the proportion of electricity. At the same time, by building photovoltaic power stations, wind power stations and other zero-carbon technologies in the spoil field, optimizing the source of power supply, reducing the proportion of thermal power consumption, and increasing the proportion of clean energy consumption, carbon emissions can be further reduced. Ultimately, the low-carbon process of open-pit coal mines can be achieved through the carbon sinks generated by the spoil field forest carbon sink project or participating in carbon trading in the carbon sink market.

[0124] In one embodiment of the present invention, the carbon emission reduction value of low-carbon technology-battery replacement heavy truck is calculated as follows:

[0125] First, the carbon emission levels of fuel heavy trucks and battery heavy trucks are calculated using formula (7) and formula (8) respectively. The calculation process is as follows:

[0126]

[0127] In the formula: Carbon emission level of fuel heavy trucks: t CO2 / m3*km; Energy consumption level of fuel heavy trucks: ton diesel / m3*km; CC 柴 is the carbon content of diesel, in tons of carbon per ton of fuel;

[0128] CC 柴 =NCV 柴 ×EF 柴 ;

[0129] NCV 柴 It is the lower calorific value of diesel, unit is million kilojoules (GJ) / ton, and the value is 43.330 (GJ) / ton; EF 柴 is the carbon content of diesel per unit calorific value, unit: ton carbon / GJ, value is 20.20×10 -3 Tons of carbon / GJ. OF 柴 is the diesel carbon oxidation rate, dimensionless, 98%;

[0130]

[0131] In the formula: Carbon emission level of battery-swap heavy trucks, unit: t CO2 / m3*km; Energy consumption level of battery-swap heavy trucks, unit: kWh / m3*km; EF 电力 It is the CO2 emission factor of electricity supply, and its unit is tCO2 / MWh. The CO2 emission factor of electricity supply should be the average CO2 emission factor of the regional power grid to which the enterprise's production site is located. It should be determined based on the latest data released by the competent authority. If the data is not available, it shall be 0.7769tCO2 / MWh.

[0132] The carbon reduction rate of battery-swap heavy trucks is calculated using formula (9):

[0133]

[0134] Therefore, the total annual carbon emissions of a single fuel heavy truck and battery heavy truck can be calculated by formula (10) and formula (11):

[0135]

[0136] Total annual diesel consumption of fuel heavy trucks in the base year, in tons; CC 柴 is the carbon content of diesel, in tons of carbon per ton of fuel;

[0137] CC 柴 =NCV 柴 ×EF 柴 ;

[0138] NCV 柴 It is the lower calorific value of diesel, unit is million kilojoules (GJ) / ton, and the value is 43.330 (GJ) / ton; EF 柴 is the carbon content of diesel per unit calorific value, unit: ton carbon / GJ, value is 20.20×10 -3 Tons of carbon / GJ. OF 柴 is the diesel carbon oxidation rate, dimensionless, 98%.

[0139] The total annual carbon emissions of a battery-swap heavy-duty truck = the total annual carbon emissions of a fuel heavy-duty truck × (1-carbon reduction rate of battery-swap heavy-duty truck) (11)

[0140] Finally, the carbon emission reduction value of battery-swapped heavy trucks in year i can be calculated by formula (12):

[0141] Carbon emission reduction value of battery-swap heavy trucks i = Change in the number of fuel heavy trucks i × Total annual carbon emissions of a fuel heavy truck × Production planning coefficient i +Changes in the number of battery-swap heavy trucks i × Total annual carbon emissions of a battery-swap heavy truck × Production plan coefficient i (12)

[0142] Changes in the number of fuel heavy trucks i = Number of fuel heavy trucks i -Number of fuel heavy trucks in the base year;

[0143] Changes in the number of battery-swap heavy trucks i = Number of heavy trucks with battery replacement i -Number of heavy trucks with battery replacement in the base year;

[0144] Including: Carbon emission reduction value of battery-swap heavy trucks i : is the carbon emission reduction value of battery-swapped heavy-duty trucks in year i; the change in the number of fuel heavy-duty trucks i : Change in the number of fuel heavy trucks in year i, with new additions as positive values ​​and reductions as negative values; Change in the number of battery-swap heavy trucks i : Change in the number of battery-swapped heavy trucks in year i, with new additions as positive values ​​and decreases as negative values; Number of fuel heavy trucks i : The number of fuel heavy trucks in the i-th year; the number of battery heavy trucks i : Number of battery-swap heavy-duty trucks in the i-th year; Number of fuel-powered heavy-duty trucks in the base year: Number of fuel-powered heavy-duty trucks in the base year; Number of battery-swap heavy-duty trucks in the base year: Number of battery-swap heavy-duty trucks in the base year; i=p+1, p+2, p+3,…,q.

[0145] In one embodiment of the present invention, the carbon emission reduction value of zero-carbon technology-photovoltaic and wind power is calculated as follows:

[0146] By using formulas (13)-(16), the photovoltaic installed capacity in year i can be calculated as i , Annual theoretical photovoltaic power generation i , Annual carbon emission reduction of photovoltaic i , the specific calculation is as follows:

[0147]

[0148] Constraints:

[0149]

[0150] in:

[0151] Photovoltaic installed capacity i : In the i-th year, the photovoltaic developable area i Estimated value of all photovoltaic installed capacity used for photovoltaic construction, in MWp; photovoltaic developable area i : The total area used for photovoltaic development as of the i-th year, mu; The total developable photovoltaic area: the total land area that can be developed for photovoltaics.

[0152] Theoretical annual photovoltaic power generation i = Photovoltaic installed capacity i × Annual full pay hours (15)

[0153] Including: Annual theoretical photovoltaic power generation i : The theoretical annual power generation of the constructed photovoltaic power plants in the i-th year, MWh;

[0154] Annual carbon emission reduction from photovoltaic power generation i = Annual carbon emission reduction of photovoltaic power generation × EF 电力 (16)

[0155] Including: Annual carbon emission reduction of photovoltaic i : The annual carbon emission reduction of the constructed photovoltaic power plants in the i-th year, in tCO2; EF 电力 It is the CO2 emission factor of electricity supply, with the unit of tCO2 / MWh. The CO2 emission factor of electricity supply should be the average CO2 emission factor of the regional power grid to which the enterprise's production site belongs. It should be determined based on the latest data released by the competent authority. If the data is not available, it shall be 0.7769t CO2 / MWh.

[0156] By using formulas (17)-(20), the wind power installed capacity in year i can be calculated as i , Annual theoretical power generation of wind power i , Annual carbon emission reduction of wind power i , the specific calculation is as follows:

[0157] Wind power installed capacity i = Area that can be developed for wind power i × Wind power installed capacity per unit area (17)

[0158] Constraints:

[0159]

[0160] Including: Total area that can be developed for wind power: Total area that can be used for wind power development, m 2 ; Developable area for wind power i : The total area used for wind power development as of year i, m 2 ; The default value of installed capacity per unit area is 40kW / m 2 or 40×10 -3 MW / m 2 Wind power installed capacity i : In the i-th year, the area that can be developed for wind power i Total installed capacity of wind power used for wind power construction, in MWp;

[0161] Annual theoretical wind power generation i = Wind power installed capacity i × Equivalent Utilization Hours (19)

[0162] Including: Annual theoretical power generation of wind power i : Theoretical annual power generation of wind power that has been built in the i-th year, MWh

[0163] Annual carbon emission reduction from wind power i = Annual theoretical wind power generation i ×EF 电力 (20)

[0164] Including: Annual carbon emission reduction of wind power i : The annual carbon emission reduction of the constructed photovoltaic power plants in the i-th year, in tCO2; EF 电力 It is the CO2 emission factor of electricity supply, with the unit of tCO2 / MWh. The CO2 emission factor of electricity supply should be the average CO2 emission factor of the regional power grid to which the enterprise's production site belongs. It should be determined based on the latest data released by the competent authority. If the data is not available, it shall be 0.7769t CO2 / MWh.

[0165] In one embodiment of the present invention, negative carbon technology: calculation of carbon emission reduction value of carbon sink in spoil field forestry:

[0166] Taking the new afforestation carbon sink project as an example, each hectare of new afforestation can generate 4.42tCO2 net carbon sink per year. Therefore, the annual carbon sink amount will be estimated based on the above carbon sink capacity. The calculation formula is formula (21). The calculation process is as follows:

[0167] Carbon sink in spoil dump i = Area of ​​spoil dump management i ×4.42 (21)

[0168] Constraints:

[0169]

[0170] Including: Carbon sink in dumping ground i : Carbon sink amount generated by the developed spoil dump forestry carbon sink project in year i, tCO2; spoil dump management area i : As of the i-th year, the total area used for wind power development is 4.42 hectares. The carbon sequestration capacity of newly planted forests is 4.42tCO2 / hectare.

[0171] Furthermore, based on the energy consumption and carbon emissions under the baseline scenario, combined with the low-carbon target year and low-carbon technology, zero-carbon technology, and negative carbon technology, energy planning is automatically carried out to achieve low-carbon path simulation.

[0172] Based on the above scheme, we have obtained the historical values ​​of total energy consumption and total carbon emissions in the baseline scenario, the predicted values ​​combined with the production plan, and the carbon emission reduction values ​​of battery-swapped heavy trucks, photovoltaics, wind power, and carbon sinks in the spoil field included in the green and low-carbon scenario. Next, we will carry out low-carbon energy planning based on the above formulas and calculation results to predict the future development of carbon emission paths.

[0173] Through the low-carbon technology of battery-swapped heavy trucks, the zero-carbon technology of wind power and photovoltaics, and the negative carbon technology of carbon sinks in spoil fields, open-pit mines can achieve low-carbon development, or even near-zero-carbon development. However, the ultimate realization of low-carbon goals still requires the huge role of carbon trading in the carbon sink market. Open-pit mines can purchase carbon sinks through carbon trading as a means for enterprises to achieve their own low-carbon. Therefore, when conducting low-carbon energy planning for open-pit mines, low-carbon planning needs to be achieved through carbon trading. The specific planning methods are as follows:

[0174] Total carbon emissions in green and low-carbon scenarios i = Total carbon emissions in the baseline scenario i +Carbon emission reduction value of battery-swap heavy trucks i -Annual carbon emission reduction from photovoltaic power generation i - Annual carbon emission reduction from wind power i - Carbon sink in spoil dump i -Carbon sink trading volume i (twenty two)

[0176] i=p, p+1, p+2,…, q

[0177] Constraints:

[0178]

[0179] Including: Total carbon emissions in green and low-carbon scenarios i : is the total carbon emissions in the i-th year under the green and low-carbon scenario, tCO2; carbon sink trading volume i : The amount of carbon sinks purchased by open-pit coal mining enterprises participating in carbon sink trading in year i, tCO2;

[0180] Finally, the above-mentioned technical solution was used to calculate the carbon emission development path of open-pit mines under the green and low-carbon scenario, thus realizing the low-carbon energy development plan for open-pit mining enterprises.

[0181] The open-pit mine low-carbon energy planning method of the embodiment of the present invention establishes a carbon emission baseline development scenario and a green low-carbon development scenario based on the production and operation energy consumption data of the open-pit mine enterprise, and predicts and simulates the low-carbon development carbon emission path of the future open-pit mine through low-carbon technology, zero-carbon technology, and negative carbon technology, and optimizes the energy structure of the open-pit mine. The present invention can assist enterprise decision makers in making medium- and long-term plans for energy and carbon emissions through low-carbon technical means that are fully applicable to open-pit mine enterprises, and help achieve low-carbon goals.

[0182] In order to implement the above embodiment, Figure 3 As shown, this embodiment also provides an open-pit mine low-carbon energy planning system 10, which includes a historical data calculation module 100, a model result output module 200, a benchmark data prediction module 300 and a low-carbon energy planning module 400;

[0183] A historical data calculation module 100 is used to calculate the total historical energy consumption and total historical carbon emissions of the open-pit mine;

[0184] The model result output module 200 is used to input the historical total energy consumption and the historical total carbon emission into the time series prediction model to obtain the total energy consumption and the total carbon emission time series prediction results under the baseline scenario;

[0185] A benchmark data prediction module 300 is used to calculate the total energy consumption prediction value and the carbon emission prediction value under the benchmark scenario based on the total energy consumption and total carbon emission time series prediction results and the preset production plan coefficient;

[0186] The low-carbon energy planning module 400 is used to calculate the total carbon emissions of the green low-carbon scenario based on the carbon emission reduction value, total energy consumption forecast value and carbon emission forecast value of the green low-carbon scenario, so as to carry out low-carbon energy planning according to the total carbon emissions of the green low-carbon scenario to obtain a low-carbon energy planning path.

[0187] The open-pit mine low-carbon energy planning system of the embodiment of the present invention establishes a carbon emission baseline development scenario and a green low-carbon development scenario based on the production and operation energy consumption data of the open-pit mine enterprise, and predicts and simulates the low-carbon development carbon emission path of the future open-pit mine through low-carbon technology, zero-carbon technology, and negative carbon technology, and optimizes the energy structure of the open-pit mine. The present invention can assist enterprise decision makers in making medium- and long-term plans for energy and carbon emissions through low-carbon technical means that are fully applicable to open-pit mine enterprises, and help achieve low-carbon goals.

[0188] In order to implement the method of the above embodiment, the present invention also provides a computer device, such as Figure 4 As shown, the computer device 600 includes a memory 601 and a processor 602; wherein the processor 602 runs a program corresponding to the executable program code by reading the executable program code stored in the memory 601, so as to implement each step of the method described above.

[0189] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0190] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

Claims

1. A low-carbon energy planning method for an open-pit mine, characterized in that: The method comprises the following steps: Calculate the total historical energy consumption and carbon emissions of open-pit mines; Inputting the historical total energy consumption and the historical total carbon emissions into the time series prediction model to obtain the time series prediction results of the total energy consumption and the total carbon emissions under the baseline scenario; Calculate the total energy consumption forecast value and the total carbon emission forecast value under the baseline scenario based on the total energy consumption and total carbon emission time series forecast results and the preset production plan coefficient; The total carbon emissions of the green low-carbon scenario are calculated based on the carbon emission reduction value of the green low-carbon scenario, the total energy consumption forecast value and the carbon emission forecast value, so as to carry out low-carbon energy planning according to the total carbon emissions of the green low-carbon scenario and obtain a low-carbon energy planning path.

2. The method according to claim 1, characterized in that The total historical energy consumption is calculated by the following formula: Total historical energy consumption = total electricity consumption * C 电 +Total diesel consumption*C 柴 +Total gasoline consumption* C 汽 + Total heat consumption*C 热 ; Among them, the total electricity consumption, including purchased electricity and self-generated electricity from clean energy, C 电 is the electricity conversion coefficient of standard coal, C 柴 C is the diesel fuel conversion coefficient to standard coal, 汽 is the gasoline to standard coal coefficient, C 热 It is the thermal coefficient of standard coal.

3. The method according to claim 2, characterized in that The total historical carbon emissions are calculated by the following formula: Total historical carbon emissions = total carbon emissions from net purchased electricity + total carbon emissions from diesel + total carbon emissions from gasoline + total carbon emissions from net purchased heat; in, Total carbon emissions from net purchased electricity = AD co2净电 *EF 电力 ; Total net purchased thermal carbon emissions = AD co2净热 *EF 热力 ; CC 柴 =NCV 柴 *EF 柴 ; CC 汽 =NCV 汽 *EF 汽 ; Among them, the total carbon emissions from net purchased electricity are the CO2 emissions implied by the net electricity purchased by the enterprise; the total carbon emissions from net purchased heat are the CO2 emissions implied by the net heat purchased by the enterprise; AD co2净电 The net electricity consumption purchased by the enterprise; AD co2净热 EF is the net purchase of heat consumption by the enterprise; 电力 is the CO2 emission factor for electricity supply, EF 热力 CO2 emission factor for heat supply; AD 柴 is diesel consumption, CC 柴 is the carbon content of diesel, OF 柴 is the diesel carbon oxidation rate, AD 汽 is gasoline consumption, CC 汽 is the carbon content of gasoline, OF 汽 NCV is the gasoline carbon oxidation rate; 柴 The low calorific value of diesel, EF 柴 NCV is the carbon content per unit calorific value of diesel; 汽 is the low calorific value of gasoline, EF 汽 It is the carbon content per unit calorific value of gasoline.

4. The method according to claim 3, characterized in that The total energy consumption forecast value is calculated by the following formula: Total carbon emissions in the baseline scenario i =Total carbon emissions S i *Production planning coefficient i ; Among them, the total carbon emissions in the baseline scenario i is the predicted total carbon emissions in the future i-th year under the baseline scenario, and the total carbon emissions S i is the time series forecast result of the total carbon emissions in the future i-th year under the baseline scenario, and the production planning coefficient i The planned output of raw coal during the planning period i Coal production in the base year p ratio; i = p+1, p+2, p+3,…, q.

5. The method according to claim 4, characterized in that The carbon emission reduction value of the green and low-carbon scenario, including the carbon emission reduction value of the battery-swapped heavy truck using low-carbon technology, is calculated by the following formula: CC 柴 =NCV 柴 *EF 柴 ; The total annual carbon emissions of a battery-swap heavy-duty truck = the total annual carbon emissions of a fuel heavy-duty truck * (1-carbon reduction rate of battery-swap heavy-duty truck); Carbon emission reduction value of battery-swap heavy trucks i = Change in the number of fuel heavy trucks i *Total annual carbon emissions of a fuel heavy truck *Production planning coefficient i +Changes in the number of battery-swap heavy trucks i *Total annual carbon emissions of a battery-swap heavy-duty truck *Production planning coefficient i ; Changes in the number of fuel heavy trucks i = Number of fuel heavy trucks i -Number of fuel heavy trucks in the base year; Changes in the number of battery-swap heavy trucks i = Number of heavy trucks with battery replacement i -Number of heavy trucks with battery replacement in the base year; Among them, CC 柴 is the carbon content of diesel, NCV 柴 The low calorific value of diesel, EF 柴 is the carbon content per unit calorific value of diesel, OF 柴 is the diesel carbon oxidation rate; EF 电力 CO2 emission factor for electricity supply; carbon emission reduction value for battery-swapped heavy trucks i is the carbon emission reduction value of battery-swapped heavy-duty trucks in year i, and the number of fuel heavy-duty trucks changes i is the change in the number of fuel heavy trucks and battery heavy trucks in year i i is the change in the number of battery-powered heavy trucks in year i, and the number of fuel heavy trucks i is the number of fuel heavy trucks and battery heavy trucks in year i i is the number of battery-swap heavy-duty trucks in the i-th year, the number of fuel heavy-duty trucks in the base year is the number of fuel heavy-duty trucks in the base year, and the number of battery-swap heavy-duty trucks in the base year is the number of battery-swap heavy-duty trucks in the base year.

6. The method according to claim 5, characterized in that The carbon emission reduction value of the green and low-carbon scenario also includes the carbon emission reduction value of the battery-swapped heavy truck with low-carbon technology, which is calculated by the following formula: Calculate the photovoltaic installed capacity in year i i , Annual theoretical photovoltaic power generation i and annual carbon emission reduction of photovoltaic i : Constraints: Theoretical annual photovoltaic power generation i = Photovoltaic installed capacity i * Annual full pay hours; Annual carbon emission reduction from photovoltaic power generation i = Annual carbon emission reduction from photovoltaic power generation*EF 电力 ; Among them, photovoltaic installed capacity i is the photovoltaic developable area in year i i Estimated installed capacity of all photovoltaic power generation used for photovoltaic construction, and the area that can be developed for photovoltaic power generation i is the total area used for photovoltaic development as of the i-th year. The total area that can be developed for photovoltaic development is the total land area that can be developed for photovoltaic development. The annual theoretical power generation of photovoltaic i is the theoretical annual power generation of photovoltaic power plants built in the i-th year; the annual carbon emission reduction of photovoltaic power plants i is the annual carbon emission reduction of the photovoltaic power plants that have been built in the i-th year; Calculate the installed capacity of wind power in year i i , Annual theoretical power generation of wind power i , Annual carbon emission reduction of wind power i : Wind power installed capacity i = Area that can be developed for wind power i *Constraints on wind power installed capacity per unit area: Annual theoretical wind power generation i = Wind power installed capacity i *Equivalent utilization hours; Annual carbon emission reduction from wind power i = Annual theoretical wind power generation i *EF 电力 ; The total area that can be developed for wind power is the total area that can be used for wind power development. i is the total area used for wind power development as of year i, and the installed capacity of wind power i is the area that can be developed for wind power in year i i Wind power installed capacity used for wind power construction; wind power annual theoretical power generation i is the theoretical annual power generation of wind power that has been built in the i-th year; the annual carbon emission reduction of wind power i is the annual carbon emission reduction of photovoltaic power plants that have been built in the i-th year.

7. The method according to claim 6, characterized in that The carbon emission reduction value of the green and low-carbon scenario also includes the carbon emission reduction value of the forestry carbon sink in the spoil dump of negative carbon technology, which is calculated by the following formula: Carbon sink in spoil dump i = Area of ​​spoil dump management i *4.42; Constraints: Among them, the carbon sink of the dump i is the carbon sink amount generated by the developed spoil dump forestry carbon sink project in year i, and the spoil dump management area i is the total area used for wind power development by the i-th year, and 4.42 is the carbon sequestration capacity of new afforestation.

8. The method according to claim 7, characterized in that The total carbon emissions of the green low-carbon scenario are calculated based on the carbon emission reduction value of the green low-carbon scenario, the total energy consumption forecast value and the carbon emission forecast value, including: Total carbon emissions in green and low-carbon scenarios i = Total carbon emissions in the baseline scenario i +Carbon emission reduction value of battery-swap heavy trucks i -Annual carbon emission reduction from photovoltaic power generation i - Annual carbon emission reduction from wind power i - Carbon sink in spoil dump i -Carbon sink trading volume i ; Constraints: Among them, the total carbon emissions in the green and low-carbon scenario i is the total carbon emissions in the i-th year under the green and low-carbon scenario, and the carbon sink trading volume i It is the amount of carbon sinks purchased by open-pit coal mining enterprises participating in carbon sink trading in year i.

9. A low-carbon energy planning system for open-pit mines, characterized in that: include: The historical data calculation module is used to calculate the total historical energy consumption and carbon emissions of the open-pit mine; A model result output module is used to input the historical total energy consumption and the historical total carbon emissions into the time series prediction model to obtain the total energy consumption and total carbon emissions time series prediction results under the baseline scenario; A baseline data prediction module, used to calculate the total energy consumption prediction value and the carbon emission prediction value under the baseline scenario based on the total energy consumption and total carbon emission time series prediction results and the preset production plan coefficient; The low-carbon energy planning module is used to calculate the total carbon emissions of the green low-carbon scenario based on the carbon emission reduction value of the green low-carbon scenario, the total energy consumption forecast value and the carbon emission forecast value, so as to carry out low-carbon energy planning according to the total carbon emissions of the green low-carbon scenario to obtain a low-carbon energy planning path.

10. A computer device, characterized in that: including a processor and a memory; The processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to implement the open-pit mine low-carbon energy planning method as described in any one of claims 1-8.

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