CN115310651A - Low-carbon operation method of coal mine energy system based on material flow-energy flow coordination - Google Patents

Abstract

The invention discloses a coal mine energy system low-carbon operation method based on material flow-energy flow cooperation, which is used for simplifying and abstracting a coal mine energy supply network and a coal mine material flow-coal flow to obtain node-branch topology and topology parameters and establishing a coupling relation between the energy flow and the material flow through node physical quantity; based on the accurate carbon metering method of the coal mine energy supply side, an optimized scheduling model aiming at the minimum running cost and carbon emission of a coal mine energy system is constructed, the material flow of the coal mine is guided to realize the flexible adjustment of multiple production links, the flexible elastic characteristics of the belt speed and the transportation quantity of a silo and a belt conveyor in the coal flow transportation link are exerted, and the material flow and the energy flow are subjected to economic and low-carbon running scheduling along with the electricity price and the comprehensive carbon emission factor. The invention has the advantages that: the coal mine energy system low-carbon operation scheduling method based on cooperation of material flow and energy flow can improve the system operation level, and has obvious effects on improving the system economy and reducing the carbon benefits.

Description

Low-carbon operation method of coal mine energy system based on material flow-energy flow coordination

technical field

The invention belongs to the technical field of energy scheduling, and in particular relates to a low-carbon operation method of a coal mine energy system based on material flow-energy flow coordination.

Background technique

Coal is an important primary energy source in my country. According to statistics, coal power will account for 61% of my country's power generation in 2020. However, coal mines with a production capacity of more than 70% are still in the stage of extensive production in the 1970s. Compared with developed countries, my country's energy consumption per ton of coal is still at a relatively high level, and the average energy consumption of coal mining is nearly four times that of developed countries. Coal mines consume a lot of electricity in the production process, and the energy consumption management method is extensive, so there is room for improvement in helping the realization of the dual carbon goals. Therefore, mining the reasons for the low level of energy efficiency in the coal mine production process and improving the relationship between energy supply and demand in the coal mine production process is one of the effective ways for the coal mine production system to help achieve the double carbon goal. As the intermediate link of coal mining and washing, the mine transportation system often accounts for more than 10% of the overall energy consumption of the mine. At the same time, the silo in the coal mine transportation system endows the transportation equipment with flexible and elastic characteristics in response to the material flow scheduling requirements, and the material flow transportation equipment is flexible and controllable. Therefore, the coordinated optimization of coal mine energy flow and coal transportation material flow has great potential in reducing energy costs and low-carbon cleanliness.

At present, the multi-type energy demand and energy supply network of coal mines are regarded as independent parts, lack of dynamic analysis of material flow and energy flow, and do not consider the coordinated operation of material flow and energy flow under the influence of time-of-use electricity price and carbon emission factors. Therefore, there is an urgent need for an energy system operation optimization method that can promote the coordination of coal mineral flow and energy flow, take advantage of the flexible and elastic characteristics of the silo and belt conveyor belt speed and volume in the coal flow transportation link, and guide coal mineral flow to achieve more production The flexible scheduling of links can promote energy consumption to follow the electricity price and comprehensive carbon emission factors to adjust the material flow, and improve the economy and carbon reduction benefits of coal mine energy system operation.

Contents of the invention

The technical problem to be solved by the present invention is, based on the time-of-use electricity price of coal mines and the carbon emission factors of power generation of different energy sources, considering the economical and low-carbon nature of coal mine energy use, and finally obtaining the optimal coal mine energy system under the coordination of material flow and energy flow Run the scenario.

The technical scheme adopted in the present invention is:

Step 1: Simplify and abstract the energy supply network of the selected coal mine, obtain the energy flow parameters of the coal mine, and define its decision variables;

Step 2: Simplify and abstract the main material flow-coal flow according to the selected coal mine, obtain the coal mineral flow parameters, and define its decision variables;

Step 3: According to the coal mine energy flow and material flow structure and parameters provided in Step 1 and Step 2, establish the coupling relationship between energy flow and material flow;

Step 4: Establish an accurate carbon measurement method for coal mine energy supply side, and calculate the comprehensive carbon emission factor of coal mine hourly electric energy;

Step 5: Based on the completed topology and parameter acquisition and accurate carbon measurement methods of Step 1, Step 2, Step 3, and Step 4, establish a coal mine energy system operation model that coordinates material flow and energy flow;

Step 6: Based on the mathematical model established in step 5, construct a method for the coordinated operation of coal mineral flow and energy flow;

Step 7: Perform convex transformation on the nonlinear terms in the constraints established in step 6 to construct a second-order cone model that is easy to solve;

Step 8: Based on the operating model established in steps 5, 6, and 7, use the Gurobi solver in the YALMIP optimization solution tool to solve the model and verify the validity of the algorithm;

Step 9: Generate a low-carbon operation scheduling scheme for the coal mine energy system that coordinates material flow and energy flow.

The advantage of the present invention is that: the low-carbon operation method of the coal mine energy system based on the coordination of material flow and energy flow proposed by the present invention is based on solving the problem of optimal operation of the coal mine energy system under the coordination of material flow and energy flow, and makes full use of the coal flow transportation link The flexible and elastic characteristics of the silo and belt conveyor belt speed and transportation volume guide the coal mineral flow to realize the flexible scheduling of multiple production links, and promote energy consumption to follow the electricity price and comprehensive carbon emission factors to adjust the decision variables such as material flow belt speed and transportation volume. , with the goal of improving the economy and carbon reduction benefits of coal mine energy system operation, a low-carbon operation scheduling model of coal mine energy system with coordinated material flow and energy flow is established, and the relevant mathematical solver is used to solve the problem, and the system's day-ahead scheduling plan is obtained.

Description of drawings

Figure 1 is a flowchart of a low-carbon operation method for coal mine energy systems based on material flow-energy flow coordination;

Figure 2 is a topological structure diagram of the coal mine energy system in which material flow and energy flow are coordinated;

Fig. 3 is a schematic diagram of a simplified coal mineral flow-coal flow model;

Figure 4 is a graph of the proportion of power generation by different types of energy sources in power purchases in mining areas;

Figure 5 is the electricity price in mining area;

Fig. 6 is the optimization result of coal mineral flow-coal flow;

Figure 7 is a diagram of the power consumption of the system before and after operation optimization based on precise carbon measurement.

Detailed ways

The low-carbon operation method of the coal mine energy system based on the material flow-energy flow coordination proposed by the present invention will be described in detail below in combination with the implementation cases and the accompanying drawings.

The low-carbon operation method of coal mine energy system based on material flow-energy flow coordination of the present invention, as shown in Figure 1, includes the following steps:

1) According to the simplified abstraction of the energy supply network of the selected coal mine, the node-branch topology of the energy flow is obtained, the nodes and branches of the topology are numbered, and the energy flow parameters are obtained and calculated, including the load value of the known nodes , the length and impedance value of the branch, the predicted value of photovoltaic power generation, and define the decision variables, including the system power purchase, the power value of the adjustable point, the serial number and capacity of the reactive power compensation node, etc. The energy flow topology described is shown in Figure 2 Show;

2) Simplify and abstract the main material flow-coal flow according to the selected coal mine, and obtain five key links of coal flow: coal mining at the working face, belt conveyor, bottom coal bunker, belt conveyor, ground coal bunker, And carry out parameter acquisition and variable definition for each link, including coal mining volume, coal transport volume, power value, belt conveyor speed, etc. The schematic diagrams of the material flow-coal flow topology and model are shown in Figure 2 and Figure 3;

3) According to the simplified topology of coal mine energy flow and material flow provided by step 1) and step 2), the coupling relationship between energy flow and material flow is established, including the change of the power value of each link of material flow to the load value of the associated node of energy flow Analysis of the influence and degree of influence of the distribution of tidal currents, and the influence and degree of influence of the power value of energy flow input material flow on material flow coal mining, coal transportation, and belt conveyor speed;

The coupling relationship between energy flow and material flow is established, which can be expressed as:

In the formula, P _t,jh is the head active power of the branch jh at time t of the energy flow; P _t,c is the average power of the coal mining face in the t hour; Ω _c is the coal mining work in the energy flow surface load node set; Ω _bc is the energy flow belt conveyor load node set; P _{bc, t} represents the power obtained by the belt conveyor of the coal flow transportation system from the node, j represents the energy flow node, and the coal mining face load node in the energy flow Including shearer, scraper conveyor, reloader and crusher load of coal mining face.

4) Establish an accurate carbon measurement method for the energy supply side of coal mines, analyze and select the hourly power components of coal mines according to the power source of the large power grid, that is, the hourly proportion of thermal power, wind power, photovoltaics, hydropower, and nuclear power purchased by coal mines, and Based on the carbon emission factors of different power components, the comprehensive carbon emission factor of coal mine hourly electric energy is calculated, and the hourly energy consumption carbon emission of coal mines is calculated according to the hourly electricity consumption;

The precise carbon measurement method on the coal mine energy supply side can be expressed as:

表示第i种类型的能源成分在第t小时为煤矿供电的功率；

为每小时从电网总购电量；

表示煤电、核电、光伏发电、风电、水电在电源成分中的占比；

代表矿区能源供给侧第t小时的综合碳排放因子，表征每小时矿区电源的碳排放强度，单位为kgCO₂/kWh；α_Gi为外购电中第i种发电类型的碳排放因子，

为外购电中第i种发电类型的发电量占比。In the formula, i represents coal power, nuclear power, photovoltaic power generation, wind power, hydropower;

Indicates the power of the i-th type of energy component supplying power to the coal mine at hour t;

is the total electricity purchased from the grid per hour;

Indicates the proportion of coal power, nuclear power, photovoltaic power generation, wind power, and hydropower in the power supply components;

Represents the comprehensive carbon emission factor of the energy supply side of the mining area at hour t, and represents the carbon emission intensity of the power supply in the mining area per hour, and the unit is kgCO ₂ /kWh; α _Gi is the carbon emission factor of the i-th power generation type in the purchased electricity,

It is the proportion of power generation of the i-th power generation type in the purchased power.

5) According to the simplified and abstract topology, parameters and coupling relationship of coal mineral flow and energy flow provided in step 1), step 2), and step 3) and the accurate carbon measurement method on the energy supply side provided in step 4), the material flow and energy flow are established. Coal mine energy system operation model based on flow coordination, with the goal of minimizing the economic cost and carbon emissions of the coal mine energy supply system, with the constraints of Distflow branch current flow, energy network security operation constraints, photovoltaic power generation operation constraints, reactive power compensation constraints, and mine production safety Constraints are constraints;

(1) The goal of minimizing the economic cost and carbon emissions of the coal mine energy supply system can be expressed as:

minF＝F ₁ +F ₂ #(5)

In the formula, F ₁ is the operating cost of the coal mine energy system, that is, the power purchase cost of the mining area, and Cp is the time-of-use electricity price of the coal mine; F ₂ is the penalty cost of carbon emissions in the coal mine energy system, and δ is the penalty cost coefficient of carbon emissions, unit is yuan/kg; T is the total number of time slots in a complete scheduling cycle, and t is the scheduling time interval.

(2) The power flow constraint of the Distflow branch is expressed as

In the formula, P _{t, ij} , Q _{t, ij} are the active and reactive power flowing from node i to node j at time t, I _{t, ij} is the current of line ij at time t, r _ij and x _ij are the currents of line ij respectively Resistance and reactance, V _t,i is the voltage at node i at time t.

(3) The security operation constraints of the energy network are expressed as

In the formula, V _min and V _max are the allowable operating upper limit and lower limit of the node voltage respectively; I _{ij, max} is the maximum current allowed by the line ij.

(4) The operating constraints of photovoltaic power generation described in (4) are expressed as

为在节点i处的分布式光伏在t时段内的实际出力；

为分布式光伏的出力最大值。In the formula,

is the actual output of the distributed photovoltaic at node i in the period t;

is the maximum output of distributed photovoltaic.

The reactive compensation constraint mentioned in (5) is expressed as

为在节点i处的SVC设备在t时段内的实际无功补偿量；

分别为SVC设备无功补偿量的最小值和最大值。In the formula, i is the access node of the reactive power compensation device,

is the actual reactive power compensation amount of the SVC equipment at node i in the period t;

They are the minimum value and maximum value of reactive power compensation amount of SVC equipment respectively.

(6) The mine production safety constraints mentioned include the power expression of the belt conveyor, the constraint on the relationship between the transport volume and the belt speed, the upper and lower limits of the transport volume per unit length of the belt conveyor, the upper and lower limits of the belt conveyor speed, the expression of the coal volume in the coal bunker and the upper and lower limits. The lower bound constraints can be expressed as

M _min ≤ M _{t ≤} M _max #(18)

0<v<v _max #(19)

C _t+1 = C _t +θ _{in, t} -θ _{out, t} #(20)

0.2C _N ≤C _t ≤0.9C _N #(21)

In the formula, P _{bc, t} is the average power of the belt conveyor at hour t; the four parameters μ ₁ , μ ₂ , μ ₃ and μ ₄ are coefficients related to the structure of the belt conveyor; η _d and η _m are the motor and Efficiency of the drive system; M _t is the unit length bearing mass of the belt conveyor in the t-th period, and the unit is kg/m; v _t is the coal transporting speed of the belt conveyor; θ _t is the transport volume of the belt conveyor in the t-th period, The unit is ton/h; v _max is the maximum belt speed of the belt conveyor; M _min and M _max are the upper and lower limits of the unit length of the belt conveyor, respectively, and the unit is kg/m; θ _{in, t} , θ _{out, t} Respectively, the amount of coal transported into and out of the coal bunker; C _N is the capacity of the coal bunker, and C _t is the coal storage capacity of the coal bunker in the tth hour.

6) Based on the mathematical model established in step 5), a collaborative operation method of coal mineral flow and energy flow is constructed. Based on the coal mine time-of-use electricity price and hourly comprehensive carbon emission factor, the silo and belt conveyor belt speed, The flexible and elastic characteristics of the transportation volume guide the coal mineral flow to realize the effective scheduling of multiple production links, promote the energy consumption to follow the electricity price and the comprehensive carbon emission factor to adjust the material flow, and improve the economy and carbon reduction benefits of the coal mine energy system operation;

7) Perform convex transformation on the nonlinear term in the model built in step 5), linearize the power expression of the belt conveyor, use auxiliary variables to transform the nonlinear term in the Distflow power flow constraint into a standard second-order cone form, and construct Easy-to-solve linear models;

(1) Linearize the power expression of the belt conveyor in the operation constraints, which can be expressed as

(2) Perform second-order cone transformation on the Distflow power flow constraint in the operational constraints, which can be expressed as

和电流平方

用

和 l_t，ij代替，则式(8)-(11)变为式(23)-(27)，对式(26)进行二阶锥松弛转换，转变为如式(28)的标准二阶锥形式。For the square of the voltage amplitude in the distribution network power flow

and current squared

use

and l _{t, ij} , then formulas (8)-(11) become formulas (23)-(27), and formula (26) is transformed into the standard second-order cone form.

||[2P _{t, ij} 2Q _{t, ij} l _{t, ij} -v _{t, i} ] ^T || ₂ ≤ l _{t, ij} +v _{t, i} #(28)

8) Based on the operating model established in step 5), step 6) and step 7), the Gurobi solver is used to solve the model in the YALMIP optimization solution tool, and the validity of the algorithm is verified;

9) Generating a low-carbon operation scheduling scheme for coal mine energy systems that coordinate material flow and energy flow: According to information such as coal mining plan, node load forecast value, photovoltaic output forecast output, comprehensive carbon emission factor, and electricity price, the two-dimensional energy system established by the above steps is carried out. Solving the step-cone programming model to obtain the low-carbon operation plan of the coal mine energy system based on the coordination of material flow-energy flow, the daily operating cost of the coal mine energy supply level, the daily carbon emissions, the coal storage status of the material flow in the coal bunker, the belt conveyor transportation amount, belt speed, reactive compensation power, etc.

Simulation:

In order to verify the effectiveness of this method, taking a coal mine in Shanxi Province as an example, first determine the key nodes and voltage levels in the energy flow topology. The energy flow topology consists of key nodes such as coal mining, transportation, ventilation, and gas drainage, including There are 5 voltage levels of 35kV, 10kV, 1.14kV, 0.69kV, and 0.4kV, with a total of 34 nodes and 33 branches, as shown in Figure 3.

Based on the low-carbon operation requirements of the mining area and considering the geographical conditions of the coal mine, a distributed photovoltaic power generation system is configured at the 3rd, 8th, and 11th nodes. Starting from the energy demand, the coal flow system is simplified into five links: "coal mining at the working face - belt conveyor - bottom coal bunker - belt conveyor - ground coal bunker". Connect the electrical equipment involved in coal mineral flow to 6 nodes respectively. Among them, nodes 7, 24, 25, and 34 are respectively connected to coal shearers, scraper conveyors, loaders, and crushers, while nodes 22 and 32 are connected to belt conveyors. Figure 4 shows the proportion of power generation of different types of energy sources in the mining area electricity purchase, and the time-hour electricity price in the mining area is shown in Figure 5, which can be divided into peak hours, valley hours, and normal hours.

In order to verify the effectiveness of the material flow-energy flow collaborative operation method and calculate the carbon emissions, the following two operation scenarios are constructed for comparison: 1) Coal mineral flow and energy flow operate independently; 2) Coal mines considering accurate carbon measurement Matter flow-energy flow works in tandem.

The software for performing the simulation of the example is MATLAB_R2018a configured with the YALMIP toolbox, and the Gurobi 9.1 solver is called to solve the problem. The emulation platform processor used is AMD Ryzen 5 5500U, the memory is 16GB, and the operating system is 64-bit Windows 10. The specific algorithm flow chart is shown in Figure 1. Through the calculation, the maximum magnitude of the relaxation error is 10e-6, and the magnitude of the error is negligible, which shows that the second-order cone relaxation algorithm is feasible to relax the model.

The material flow-coal flow optimization results are shown in Fig. 6. Compared with the constant-speed operation of the traditional coal flow system, the material flow-coal flow synergistically optimized belt speed changes with the transportation volume. When the electricity price is high, the transportation volume and belt speed are reduced, which shows that the belt speed and transportation volume can be combined. Flexible response to time-of-use electricity prices. The power consumption is reduced by 12705.6kWh, and the daily power consumption cost is reduced by 10857.84 yuan, which realizes the improvement of energy saving and economy. See Table 1 for the comparison of energy consumption per ton of coal production whether or not to consider the material flow-energy flow coordinated operation mode.

Figure 7 shows the real-time carbon emission factors of purchased electricity in mining areas and the comparison of power consumption before and after optimization. During the maintenance period of the mining area, the electricity price is flat from 11:00 to 16:00, and the real-time carbon emission factor is lower; the electricity price from 17:00 to 22:00 is the peak period, and the real-time carbon emission factor is higher. Therefore, choosing the period from 17:00 to 22:00 as the maintenance period is a more economical and low-carbon mining operation mode. The carbon emissions before and after considering accurate carbon measurement are shown in Table 2, and the carbon emissions per ton of coal production are reduced by 0.9kg.

In summary, compared with the traditional independent operation of material flow and energy flow, the coordinated control operation of coal mineral flow and energy flow considering accurate carbon measurement improves the economics of the coal mine production system; the real-time speed regulation of material transportation improves the ton of the system. Coal energy efficiency level; the coordinated operation of coal mineral flow and energy flow under accurate carbon measurement reduces system carbon emissions by 18%, providing an effective solution for coal mines to assist the "dual carbon" target task.

Table 1 Comparison of operation results of coal mine energy system with or without consideration of material flow-energy flow coordination

Note: Daily coal output (ton), electricity (kWh), energy consumption per ton of coal (kg standard coal/ton), cost (yuan), cost of electricity consumption per ton of coal (yuan/ton)

Table 2 Comparison of carbon emissions in the coal mine energy system with or without accurate carbon measurement

Note: electricity (kWh), carbon emissions (tons), carbon emissions per ton of coal production (kgCO ₂ /ton of coal)

Claims (5)

1. The low-carbon operation method of coal mine energy system based on material flow-energy flow coordination, is characterized in that, comprises the following steps: Step 1: According to the simplified abstraction of the energy supply network of the selected coal mine, obtain the node-branch topology of energy flow, number the nodes and branches of the topology, obtain and calculate the energy flow parameters, including the load of known nodes Value, branch length and impedance value, photovoltaic power generation prediction value, and define decision variables, including system purchase power, adjustable point power value, reactive power compensation node number and capacity, etc.; Step 2: Simplify and abstract the main material flow-coal flow of the selected coal mine, and obtain five key links of coal flow: coal mining at the working face, belt conveyor, bottom coal bunker, belt conveyor, and ground coal bunker , and carry out parameter acquisition and variable definition for each link, including coal mining volume, coal transport volume, power value, belt conveyor speed, etc.; Step 3: According to the simplified topology of coal mine energy flow and material flow provided in Step 1 and Step 2, the coupling relationship between energy flow and material flow is established, including the influence of the power value of each link of the material flow on the load value of the associated node of the energy flow. Analysis of the influence and degree of influence of the tidal current distribution, the influence and degree of influence of the power value of energy flow input material flow on material flow coal mining volume, coal transport volume, and belt conveyor speed; Step 4: Establish an accurate carbon measurement method on the energy supply side of coal mines, and analyze and select the power components of coal mines per hour according to the power source of the large power grid, that is, the hourly proportion of thermal power, wind power, photovoltaics, hydropower, and nuclear power purchased by coal mines. And based on the carbon emission factors of different power components, calculate the coal mine hour-level comprehensive carbon emission factor of electric energy, and calculate the hourly carbon emission of the coal mine from energy consumption according to the hourly power consumption and hour-level comprehensive carbon emission factor; Step 5: According to the simplified and abstract topology, parameters and coupling relationship of coal mineral flow and energy flow provided in Step 1, Step 2, and Step 3, and the accurate carbon measurement method on the energy supply side provided in Step 4, establish a coordination system for material flow and energy flow. The coal mine energy system operation model aims to minimize the economic cost and carbon emissions of the coal mine energy supply system, and is constrained by the flow constraints of the Distflow branch, the security operation constraints of the energy network, the photovoltaic power generation operation constraints, the reactive power compensation constraints, and the mine production safety constraints. condition; Step 6: Based on the mathematical model established in Step 5, a collaborative operation method of coal mineral flow and energy flow is proposed. Based on the time-of-use electricity price of coal mines and the comprehensive carbon emission factor per hour, the silos and belt conveyors in the coal flow transportation link are brought into play. The flexible and elastic characteristics of the quantity guide the coal mineral flow to realize the effective scheduling of multiple production links, promote the energy consumption to follow the electricity price and the comprehensive carbon emission factor to adjust the material flow, and improve the economy and carbon reduction benefits of the coal mine energy system operation; Step 7: Perform convex transformation on the non-linear terms in the constraints established in step 5 to construct a second-order cone model that is easy to solve; Step 8: Based on the operating model established in Step 5 and Step 6, use the Gurobi solver in the YALMIP optimization solution tool to solve the model and verify the validity of the algorithm; Step 9: Generate a low-carbon operation scheduling plan for the coal mine energy system that coordinates material flow and energy flow, including daily operating costs at the coal mine energy supply level, daily carbon emissions, coal storage status in coal bunkers, belt conveyor capacity, belt speed, Compensation power, etc. 2. The low-carbon operation method of coal mine energy system based on material flow-energy flow coordination according to claim 1, characterized in that the coal mine energy system constructed according to the coal mine energy supply network and coal flow characteristics described in step 1 and step 2 flow and material flow topology, including the simplification of the coal mine power supply system diagram and the abstraction of the node-branch topology. There are five parts: type conveyor and ground coal bunker, and parameter acquisition and variable definition are carried out for each link, including coal mining volume, coal transport volume, power value, belt conveyor speed, etc. 3. The low-carbon operation method of coal mine energy system based on material flow-energy flow coordination according to claim 1, characterized in that the establishment of the coupling relationship between energy flow and material flow in step 3 can be expressed as:

In the formula, P _t,jh is the head active power of the branch jh at time t of the energy flow; P _t,c is the average power of the coal mining face in the t hour; Ω _c is the coal mining work in the energy flow surface load node set; Ω _bc is the energy flow belt conveyor load node set; P _{bc, t} represents the power obtained by the belt conveyor of the coal flow transportation system from the node, j represents the energy flow node, and the coal mining face load node in the energy flow Including shearer, scraper conveyor, reloader and crusher load of coal mining face. 4. The low-carbon optimization operation method of coal mine energy system based on material flow-energy flow coordination according to claim 1, characterized in that, the precise carbon measurement method on the coal mine energy supply side described in step 4 proposes the coal mine energy supply level The hourly comprehensive carbon emission factor can be expressed as:

In the formula, i represents coal power, nuclear power, photovoltaic power generation, wind power, hydropower;

Indicates the power of the i-th type of energy component supplying power to the coal mine at hour t;

is the total electricity purchased from the grid per hour;

Indicates the proportion of coal power, nuclear power, photovoltaic power generation, wind power, and hydropower in the power supply components;

Represents the comprehensive carbon emission factor of the energy supply side of the mining area at hour t, and represents the carbon emission intensity of the power supply in the mining area per hour, and the unit is kgCO ₂ /kWh; α _Gi is the carbon emission factor of the i-th power generation type in the purchased electricity,

It is the proportion of power generation of the i-th power generation type in the purchased power. 5. The low-carbon operation method of coal mine energy system based on material flow-energy flow coordination according to claim 1, characterized in that, in step 5, the economic cost and carbon emissions of the coal mine energy supply system are minimized, which can be Expressed as: minF＝F ₁ +F ₂ #(5)

In the formula, F ₁ is the operating cost of the coal mine energy system, that is, the power purchase cost in the mining area, and Cp is the time-of-use electricity price of the coal mine; F ₂ is the penalty cost of carbon emissions in the coal mine energy system, and δ is the penalty cost coefficient of carbon emissions, unit is yuan/kg; T is the total number of time slots in a complete scheduling cycle, and t is the scheduling time interval.

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