A mine energy equivalent virtual energy storage modeling method considering equipment and process flexible adjustment

Abstract

A method for modeling equivalent virtual energy storage in mines, considering flexible adjustments to equipment and processes, comprises the following steps: constructing a mine energy system architecture incorporating virtual energy storage; establishing virtual energy storage models for mine transportation, drainage, and compressed air processes; establishing equivalent electrical energy storage models; and establishing maintenance virtual energy storage models based on equipment maintenance needs; integrating power flow constraints, power balance constraints, power supply upper and lower limit constraints, and production safety constraints to establish a comprehensive mine energy system operation model; and using the GUROBI solver to solve the model and obtain the optimal scheduling scheme. This invention fully leverages the flexible adjustment potential of mine production processes, achieving economically optimized scheduling and efficient renewable energy consumption while meeting strict safety constraints and production continuity requirements. It reduces energy costs for mining enterprises while increasing the proportion of green electricity in the overall electricity mix, reducing carbon emissions, and improving energy efficiency, thus aligning with the low-carbon transformation needs of mines.

Description

Technical Field

[0001] This invention relates to a method for modeling equivalent virtual energy storage in mines that takes into account flexible adjustments to equipment and processes, and belongs to the field of mine energy management technology. Background Technology

[0002] Currently, coal mining enterprises face multiple challenges, including excessively high energy costs, insufficient capacity for renewable energy absorption, significant peak-to-valley differences in production load, and limited regulation methods. In the field of flexible power system regulation, traditional energy storage units face economic factors such as high initial investment costs, high operation and maintenance costs, and long investment payback periods; while pumped storage in abandoned mines cannot be deployed on a large scale due to high site selection requirements, difficulty in underground space modification, and high safety risks during operation.

[0003] Virtual energy storage technology, through non-physical resource aggregation and collaborative regulation mechanisms, breaks through the spatiotemporal constraints of traditional energy storage, providing a solution for improving the efficiency of new energy consumption and enhancing the flexible scheduling capabilities of the system. Existing research mainly focuses on constructing virtual energy storage models for civilian loads such as electric vehicle clusters and air conditioning load clusters. Although research on the optimization of integrated energy operation in mines considers the integration of associated multi-energy sources and flexible load resources in mines, it does not fully incorporate the scheduling of core flexible loads in the production process, and the potential for core load regulation in industrial scenarios is not fully explored. At the same time, existing research has failed to fully explore the potential of production processes to absorb intermittent renewable energy, nor has it considered the impact of equipment maintenance periods on energy system operation, making it difficult to meet the requirements of reducing carbon emission intensity and improving energy utilization efficiency in the coal production process. Summary of the Invention

[0004] The purpose of this invention is to provide a modeling method for equivalent virtual energy storage in mines that takes into account the flexible adjustment of equipment and processes. This method can fully tap the potential for flexible adjustment in the mine production process, achieve economic optimization scheduling and efficient consumption of renewable energy under the premise of meeting strict safety constraints and production continuity requirements, reduce the energy costs of mining enterprises, increase the proportion of green electricity in the power composition, reduce carbon emissions, and improve energy utilization efficiency.

[0005] To achieve the above objectives, the present invention provides a method for modeling equivalent virtual energy storage in mines that considers flexible adjustments to equipment and processes, comprising the following steps:

[0006] S1. Construct a mine energy system architecture that includes virtual energy storage;

[0007] S2. Establish virtual energy storage models for mine transportation, drainage, and compressed air processes, establish equivalent electrical energy storage models, and establish virtual energy storage models for maintenance based on equipment maintenance requirements.

[0008] S3. Integrate power flow constraints, power balance constraints, power supply upper and lower limit constraints, and production safety constraints to establish an operation model of the mine's integrated energy system. Then, call the GUROBI solver to solve the model and obtain the optimal scheduling scheme.

[0009] Furthermore, the mine energy system architecture constructed by S1, which includes virtual energy storage, includes a transportation virtual energy storage link consisting of a coal mining machine, a conveyor and a coal storage silo; a drainage virtual energy storage link consisting of a three-stage drainage pump and an underground water tank; a compressed air virtual energy storage link consisting of an air compressor and a compressed air tank; and a maintenance virtual energy storage link consisting of a plant-wide maintenance window and a flexible maintenance strategy.

[0010] Furthermore, the virtual energy storage models in S2 are as follows:

[0011] S2-1, The virtual energy storage model for transportation includes:

[0012] S2-1.1 The mathematical model of the coal mining machine is as follows:

[0013] (1);

[0014] (2);

[0015] in, For coal mining units in t Power consumed at any given moment; For traction speed; This refers to the drum rotation speed; It is a time-varying nonlinear function related to coal seam characteristics; All of these are coefficients related to the production of coal mining units; For coal mining units in t Coal mining volume at any given time; This refers to the power-coal quantity conversion coefficient of the coal mining unit. The unit time interval; It is the coal mine operating condition coefficient, which is related to factors such as coal seam geology, underground environment, and equipment operating conditions;

[0016] S2-1.2, The mathematical model of the transport aircraft is:

[0017] (3);

[0018] in, For transport aircraft t Power consumed at any given moment; For transport aircraft t Transportation volume at any given time; This refers to the speed of the transport belt; These are the efficiencies of the electric motor and the drive system, respectively. These are all parameters related to transport aircraft design;

[0019] S2-1.3, The coal storage silo model is as follows:

[0020] (4);

[0021] (5);

[0022] (6);

[0023] in, For coal bunkers t Coal reserves at any given time; They are respectively t The amount of coal constantly being transported in and out of the coal bunker; This represents the maximum capacity of the coal bunker. T This constitutes a scheduling cycle; to facilitate scheduling management, the input and output coal quantities of the coal bunker are kept in balance within a single scheduling cycle.

[0024] S2-2, The drainage virtual energy storage model includes:

[0025] S2-2.1 The mathematical model of the three-stage drainage pump is as follows:

[0026] (7);

[0027] (8);

[0028] (9);

[0029] (10);

[0030] (11)

[0031] in, Indicates the first i Seed pump in t Operating power at any given time ; The density of the gushing water; It is the acceleration due to gravity; For Yang Cheng; For the i-th type of water pump in t The flow rate at any given moment; For operational efficiency; Indicates the first i Maximum flow rate of the seed water pump; They represent the first i The upper and lower limits of the slope climbing power of the water pump; To indicate the first iA binary variable representing the operating status of a water pump, with a value of 1 indicating operation and 0 indicating non-operation;

[0032] Formulas (10) and (11) specify the start-up and shutdown sequence of the three pumps as follows: the working pump is always on, the standby pump is started when the working pump is fully loaded, and the maintenance pump is started when both the working and standby pumps are fully loaded.

[0033] S2-2.2, The underground water tank model is as follows:

[0034] (12);

[0035] (13);

[0036] (14);

[0037] in, for t The water level in the reservoir at any given time; for t Inflow rate at any given time; for t The total flow rate of the three types of water pumps: those in operation, those on standby, and those under maintenance. This represents the maximum capacity of the water tank. The average inflow rate is determined based on historical data;

[0038] S2-3, The compressed air virtual energy storage model includes:

[0039] S2-3.1 The mathematical model of the air compressor is:

[0040] (15);

[0041] in, For air compressors t Power at any given moment; for t Airflow rate at any given time; The gas adiabatic index; These are the absolute pressures of the intake and exhaust systems, respectively. For compressor efficiency;

[0042] S2-3.2, The compressed air tank model is as follows:

[0043] (16);

[0044] (17);

[0045] (18);

[0046] in, This refers to the air storage capacity of the compressed air tank. These represent the filling and releasing volumes of the compressed air tank, respectively.

[0047] S2-4. Integrate the virtual energy storage links for transportation, drainage, and compressed air into a generalized virtual energy storage model, and establish an equivalent electrical energy storage model as follows:

[0048] (19);

[0049] (20);

[0050] in, These respectively represent the coal mining machine, conveyor, three-stage drainage pump, and air compressor; This refers to the coupling relationship between equipment power and materials. Virtual energy storage SOC for transportation, drainage, and compressed air processes; These refer to the amounts of substances transported into and out of the buffer zone, respectively. These are the upper and lower limits of the virtual energy storage capacity, respectively. These are the upper and lower limits for material processing capacity, respectively. These are the equivalent charging and discharging power of virtual energy storage, respectively. For the equivalent energy storage SOC, The upper limit of the SOC (State of Charge) for equivalent electrical energy storage; This represents the maximum charging and discharging power. The electrical power required to keep the system state unchanged; Equation (19) is the generalized virtual energy storage model, and Equation (20) is the electrical energy storage model equivalent to virtual energy storage;

[0051] S2-5, The virtual energy storage process model for maintenance is as follows:

[0052] S2-5.1, Define the plant-wide maintenance window:

[0053] (twenty one);

[0054] (twenty two);

[0055] (twenty three);

[0056] in, This is a binary variable representing the maintenance window; a value of 1 indicates that the window is currently in the maintenance window. Indicates the duration of the maintenance window in hours; The number of days contained in a scheduling cycle; These are the start and end times of the maintenance window, respectively; Equation (21) defines the maintenance window for each day within a scheduling cycle, and Equation (22) indicates that the maintenance window is continuous. Hour, It changes twice a day; Equation (23) indicates that the maintenance window is set at the same time every day;

[0057] S2-5.2 Equipment maintenance window matching:

[0058] (twenty four);

[0059] (25);

[0060] (26);

[0061] (27);

[0062] in, For the first The device in the d The day's maintenance sign, A value of 1 indicates that the equipment is under maintenance on that day, while a value of 0 indicates that the equipment is not under maintenance on that day; the air compressor is... M The water pump is inspected once a day, and every [time / day / month]... N The equipment is inspected once a day. Equations (26) and (27) stipulate that the maintenance intervals of the equipment are the same to avoid the phenomenon of multiple consecutive maintenance.

[0063] Furthermore, the integrated energy system operation model for the mine established in S3 aims to minimize the system's energy cost and maximize the photovoltaic absorption rate. The objective function is:

[0064] (28);

[0065] (29);

[0066] (30);

[0067] in, These are the energy costs of the mine and the penalty for curtailment of solar power; Supply power to the mains; The price is the municipal electricity price; Demand-based electricity pricing; This refers to the number of distributed photovoltaic (PV) systems. As a penalty factor for abandoning light, For the first i Distributed photovoltaic in t The amount of light discarded at any given moment.

[0068] Furthermore, the power flow constraints, power balance constraints, power supply upper and lower limit constraints, and production safety constraints in S3 are as follows:

[0069] S3.1 Power flow constraints:

[0070] (31);

[0071] (32);

[0072] (33);

[0073] (34);

[0074] in, They are respectively j Node at t The active and reactive power injected at all times; For the line ij exist t Power that is constantly flowing; For the line ij Impedance and reactance; For nodes j exist t The square of the voltage at time; For the line ij exist t The square of the current flowing through at any given moment;

[0075] S3.2 Power balance constraint conditions:

[0076] (35);

[0077] (36);

[0078] in, This constitutes the basic electrical load for each node of the mine's power distribution network. The gas load for underground ventilation and gas-using equipment is dynamically adjusted according to fluctuations in coal mining volume and maintenance plans.

[0079] S3.3, Power supply upper and lower limit constraints:

[0080] (37);

[0081] (38);

[0082] in, This is the upper limit of the mains power supply. For nodes i The reactive power compensation device in t Reactive power that is constantly compensated; These are the upper and lower limits of the output of the reactive power compensation device, respectively.

[0083] S3.4 Production safety constraints are divided into electrical constraints and non-electrical constraints. Electrical constraints are as follows:

[0084] (39);

[0085] (40);

[0086] in, For nodes j The upper and lower limits of the voltage, For the line ij The upper and lower limits of the current;

[0087] Non-electric safety constraints include Equation (5) for coal material limitation in coal storage silos, Equation (14) for empty silo rate limitation in underground water silos, and Equation (17) for compressed air volume limitation.

[0088] This invention constructs a mine energy system architecture incorporating virtual energy storage and establishes virtual energy storage models for mine transportation, drainage, and compressed air processes. It also establishes an equivalent electrical energy storage model and a maintenance virtual energy storage model based on equipment maintenance needs. By integrating power flow constraints, power balance constraints, power supply upper and lower limit constraints, and production safety constraints, a comprehensive mine energy system operation model is established. The model is then solved using the GUROBI solver to obtain the optimal scheduling scheme. This invention fully leverages the flexible adjustment potential of mine production processes, achieving economically optimized scheduling and efficient renewable energy consumption while meeting strict safety constraints and production continuity requirements. This reduces energy costs for mining enterprises while increasing the proportion of green electricity in the overall electricity mix, lowering carbon emissions, reducing dependence on expensive conventional electricity, and improving energy efficiency, thus aligning with the low-carbon transformation needs of mines. Furthermore, the scheduling scheme obtained through this invention fully integrates actual energy-consuming processes in mines, providing a reference for enterprises to formulate monthly and quarterly energy consumption plans. Attached Figure Description

[0089] Figure 1 This is a flowchart of the process of the method of the present invention;

[0090] Figure 2 This is a schematic diagram of the architecture of a mining energy system incorporating virtual energy storage constructed according to the present invention;

[0091] Figure 3 This is a schematic diagram of the scheduling results of the virtual energy storage transportation link in an embodiment of the present invention;

[0092] Figure 4 This is a schematic diagram of the scheduling results of the drainage virtual energy storage link in an embodiment of the present invention;

[0093] Figure 5This is a schematic diagram of the scheduling results of the compressed air virtual energy storage link in an embodiment of the present invention. Detailed Implementation

[0094] The invention will now be further described with reference to the accompanying drawings.

[0095] like Figure 1 As shown, a method for modeling equivalent virtual energy storage in mines that considers flexible adjustments to equipment and processes includes the following steps:

[0096] S1. Construct a mine energy system architecture that includes virtual energy storage;

[0097] S2. Establish virtual energy storage models for mine transportation, drainage, and compressed air processes, establish equivalent electrical energy storage models, and establish virtual energy storage models for maintenance based on equipment maintenance requirements.

[0098] S3. Integrate power flow constraints, power balance constraints, power supply upper and lower limit constraints, and production safety constraints to establish an operation model of the mine's integrated energy system. Then, call the GUROBI solver to solve the model and obtain the optimal scheduling scheme.

[0099] like Figure 2 As shown, the mine energy system architecture including virtual energy storage includes a transportation virtual energy storage link consisting of a coal mining machine, a conveyor and a coal storage silo; a drainage virtual energy storage link consisting of a three-stage drainage pump and an underground water tank; a compressed air virtual energy storage link consisting of an air compressor and a compressed air tank; and a maintenance virtual energy storage link consisting of a plant-wide maintenance window and a flexible maintenance strategy.

[0100] As shown in Table 1, the virtual energy storage model for maintenance is as follows:

[0101] (1) Define the plant-wide maintenance window:

[0102] ;

[0103] ;

[0104] ;

[0105] in, This is a binary variable representing the maintenance window; a value of 1 indicates that the window is currently in the maintenance window. Indicates the duration of the maintenance window in hours; or the number of days contained in a scheduling cycle. These are the start and end times of the maintenance window, respectively. A daily maintenance window is defined within a scheduling cycle. This indicates that the maintenance windows are continuous. Hour, It changes twice in one day; This indicates that the maintenance window is set at the same time every day;

[0106] (2) Equipment maintenance window matching:

[0107] ;

[0108] ;

[0109] ;

[0110] ;

[0111] in, For the first j The device in the d The day's maintenance sign, A value of 1 indicates that the equipment is under maintenance on that day, while a value of 0 indicates that the equipment is not under maintenance on that day; the air compressor is... M The water pump is inspected once a day, and every [time / day / month]... N The system requires maintenance once a day. This model specifies that the maintenance intervals for the equipment are the same, thus avoiding the occurrence of multiple consecutive maintenance checks.

[0112] Table 1: Model parameters for virtual energy storage during maintenance:

[0113] The example is based on real data from a mining company in western China. The scheduling cycle is set at 4 days. Through simulation analysis, the optimized plant-wide maintenance window was shifted from the period of 11:00-16:00 when photovoltaic output is high and electricity prices are low to the nighttime period of 21:00-2:00 the next day when electricity prices are relatively high. Based on the maintenance cycle requirements of each piece of equipment and actual operating conditions, the coal mining machine and conveyor are maintained daily within the scheduling cycle, the air compressor is maintained on the first and third days of the scheduling cycle, and the drainage pump is maintained on the third day. This shift in equipment maintenance periods improves the utilization rate of low-priced electricity and leaves room for photovoltaic power consumption. The scheduling results for each link within a day are as follows: Figure 3 (a) and (b) to Figure 5As shown in (a) and (b), the transportation, drainage, and compressed air equipment operate at full power during the peak solar PV activity at midday. Materials in buffer containers such as coal storage silos, underground water tanks, and compressed air tanks decrease, achieving a virtual energy storage discharge process. During periods of high electricity prices, the power of each device decreases to varying degrees, while materials in the buffer containers rise, achieving a virtual energy storage charging process. This method reduces the system's energy cost by 4240 yuan / day, reduces curtailment of solar power by 4264 kWh / day, and increases the photovoltaic absorption rate to over 90%, equivalent to configuring an electrical energy storage capacity of 5330 kWh. The resulting scheduling scheme fully integrates the actual energy consumption links in the mine, providing a reference for enterprises to formulate monthly and quarterly energy consumption plans, and truly possesses practical value and engineering significance.

Claims

1. A method for modeling equivalent virtual energy storage in mines, considering flexible adjustments to equipment and processes, characterized in that, Includes the following steps: S1. Construct a mine energy system architecture that includes virtual energy storage; S2. Establish virtual energy storage models for mine transportation, drainage, and compressed air processes, establish equivalent electrical energy storage models, and establish virtual energy storage models for maintenance based on equipment maintenance requirements. S3. Integrate power flow constraints, power balance constraints, power supply upper and lower limit constraints, and production safety constraints to establish an operation model of the integrated energy system of the mine, and call the GUROBI solver to solve the model and obtain the optimal scheduling scheme. The maintenance virtual energy storage model is as follows: S2-5.1, Define the plant-wide maintenance window: ； ； ； in, This is a binary variable representing the maintenance window; a value of 1 indicates that the window is currently in the maintenance window. Indicates the duration of the maintenance window in hours; The number of days contained in a scheduling cycle; These are the start and end times of the maintenance window, respectively; Equation (21) defines the maintenance window for each day within a scheduling cycle, and Equation (22) indicates that the maintenance window is continuous. Hour, It changes twice a day; Equation (23) indicates that the maintenance window is set at the same time every day; S2-5.2 Equipment maintenance window matching: ； ； ； ； in, For the first j The device in the d The day's maintenance sign, , These represent the coal mining machine, air compressor, and three-stage drainage pump, respectively. A value of 1 indicates that the equipment is under maintenance on that day, while a value of 0 indicates that the equipment is not under maintenance on that day. The air compressor... M The water pump is inspected once a day, and every [time / day / month]... N It is inspected once a day.

2. The mine energy equivalent virtual energy storage modeling method considering flexible adjustment of equipment and processes according to claim 1, characterized in that, The mine energy system architecture constructed by S1, which includes virtual energy storage, includes a transportation virtual energy storage link consisting of a coal mining machine, a conveyor and a coal storage silo; a drainage virtual energy storage link consisting of a three-stage drainage pump and an underground water tank; a compressed air virtual energy storage link consisting of an air compressor and a compressed air tank; and a maintenance virtual energy storage link consisting of a plant-wide maintenance window and a flexible maintenance strategy.

3. The mine energy equivalent virtual energy storage modeling method considering flexible adjustment of equipment and processes according to claim 1 or 2, characterized in that, The virtual energy storage models in S2 are as follows: S2-1, The virtual energy storage model for transportation includes: S2-1.1 The mathematical model of the coal mining machine is as follows: ； ； in, For coal mining units in t Power consumed at any given moment; For traction speed; This refers to the drum rotation speed; It is a time-varying nonlinear function related to coal seam characteristics; All of these are coefficients related to the production of coal mining units; For coal mining units in t Coal mining volume at any given time; This refers to the power-coal quantity conversion coefficient of the coal mining unit. The unit time interval; This refers to the working condition coefficient of a coal mine. S2-1.2, The mathematical model of the transport aircraft is: ； in, For transport aircraft t Power consumed at any given moment; For transport aircraft t Transportation volume at any given time; This refers to the speed of the transport belt; These are the efficiencies of the electric motor and the drive system, respectively. These are all parameters related to transport aircraft design; S2-1.3, The coal storage silo model is as follows: ； ； ； in, For coal bunkers t Coal reserves at any given time; They are respectively t The amount of coal constantly being transported in and out of the coal bunker; This represents the maximum capacity of the coal bunker. T One scheduling cycle; S2-2, The drainage virtual energy storage model includes: S2-2.1 The mathematical model of the three-stage drainage pump is as follows: ； ； ； ； ； in, Indicates the first i Seed pump in t Operating power at any given time ; The density of the gushing water; It is the acceleration due to gravity; For Yang Cheng; For the i-th type of water pump in t The flow rate at any given moment; For operational efficiency; Indicates the first i Maximum flow rate of the seed water pump; They represent the first i The upper and lower limits of the slope climbing power of the water pump; To indicate the first i A binary variable representing the operating status of a water pump, with a value of 1 indicating operation and 0 indicating non-operation; Formulas (10) and (11) specify the start-up and shutdown sequence of the three pumps as follows: the working pump is always on, the standby pump is started when the working pump is fully loaded, and the maintenance pump is started when both the working and standby pumps are fully loaded. S2-2.2, The underground water tank model is as follows: ； ； ； in, for t The water level in the reservoir at any given time; for t Inflow rate at any given time; for t The total flow rate of the three types of water pumps: those in operation, those on standby, and those under maintenance. This represents the maximum capacity of the water tank. The average inflow rate is determined based on historical data; S2-3, The compressed air virtual energy storage model includes: S2-3.1 The mathematical model of the air compressor is: ； in, For air compressors t Power at any given moment; for t Airflow rate at any given time; The gas adiabatic index; These are the absolute pressures of the intake and exhaust systems, respectively. For compressor efficiency; S2-3.2, The compressed air tank model is as follows: ； ； ； in, This refers to the air storage capacity of the compressed air tank. These represent the filling and releasing volumes of the compressed air tank, respectively. S2-4. Integrate the virtual energy storage links for transportation, drainage, and compressed air into a generalized virtual energy storage model, and establish an equivalent electrical energy storage model as follows: ； ； in, , These respectively represent the coal mining machine, conveyor, three-stage drainage pump, and air compressor; This refers to the coupling relationship between equipment power and materials. Virtual energy storage SOC for transportation, drainage, and compressed air processes; These refer to the amounts of substances transported into and out of the buffer zone, respectively. These are the upper and lower limits of the virtual energy storage capacity, respectively. These are the upper and lower limits for material processing capacity, respectively. These are the equivalent charging and discharging power of virtual energy storage, respectively. For the equivalent energy storage SOC, The upper limit of the SOC (State of Charge) for equivalent electrical energy storage; This represents the maximum charging and discharging power. The electrical power required to keep the system state unchanged; Equation (19) is the generalized virtual energy storage model, and Equation (20) is the electrical energy storage model equivalent to virtual energy storage.

4. The mine energy equivalent virtual energy storage modeling method considering flexible adjustment of equipment and processes according to claim 3, characterized in that, The integrated energy system operation model for the mine established in S3 aims to minimize the system's energy cost and maximize the photovoltaic absorption rate. The objective function is: ； ； ； in, These are the energy costs of the mine and the penalty for curtailment of solar power; Supply power to the mains; The price is the municipal electricity price; Demand-based electricity pricing; This refers to the number of distributed photovoltaic (PV) systems. As a penalty factor for abandoning light, For the first i Distributed photovoltaic in t The amount of light discarded at any given moment.

5. The mine energy equivalent virtual energy storage modeling method considering flexible adjustment of equipment and processes according to claim 4, characterized in that, The power flow constraints, power balance constraints, power supply upper and lower limit constraints, and production safety constraints in S3 are as follows: S3.1 Power flow constraints: ； ； ； ； in, They are respectively j Node at t The active and reactive power injected at all times; For the line ij exist t Power that is constantly flowing; For the line ij Impedance and reactance; For nodes j exist t The square of the voltage at time; For the line ij exist t The square of the current flowing through at any given moment; S3.2 Power balance constraint conditions: ； ； in, This constitutes the basic electrical load for each node of the mine's power distribution network. The gas load for underground ventilation and gas-using equipment is dynamically adjusted according to fluctuations in coal mining volume and maintenance plans. S3.3, Power supply upper and lower limit constraints: ； ； in, This is the upper limit of the mains power supply. For nodes i The reactive power compensation device in t Reactive power that is constantly compensated; These are the upper and lower limits of the output of the reactive power compensation device, respectively. S3.4 Production safety constraints are divided into electrical constraints and non-electrical constraints. Electrical constraints are as follows: ； ； in, For nodes j The upper and lower limits of the voltage, For the line ij The upper and lower limits of the current; Non-electric safety constraints include Equation (5) for coal material limitation in coal storage silos, Equation (14) for empty silo rate limitation in underground water silos, and Equation (17) for compressed air volume limitation.

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