Coal mine dynamic modeling and scheduling method based on flexible production and space thermal inertia

Abstract

The invention discloses a coal mine dynamic modeling and scheduling method based on flexible production and space thermal inertia. According to the method, a comprehensive model comprising a coal production subsystem and a thermal load subsystem is constructed, the coal production subsystem and a three-stage coal bunker form a material buffer chain through a speed-adjustable belt conveyor, the transportation process is modeled as a virtual energy storage unit, and the coal mining load has time scheduling flexibility; the thermal load subsystem establishes a first-order state equation of the indoor temperature and the water tank temperature based on the thermodynamic principle. On the basis, the equipment maintenance logic, the coal flow continuity, the temperature comfort interval, the multi-energy flow balance and the carbon capture energy consumption are uniformly integrated in a mixed integer linear programming framework. On the premise that hardware investment is not newly increased, the regulation potential of logistics and thermal inertia resources in a coal mine is fully excavated, the operation economy, flexibility and low-carbon level of the system are remarkably improved, and a key technical support is provided for intelligent green mine construction under the access of high-proportion renewable energy sources.

Description

Technical Field

[0001] This invention belongs to the field of energy system optimization and intelligent scheduling technology, and in particular relates to a dynamic modeling and scheduling method for coal mines based on flexible production and spatial thermal inertia. Background Technology

[0002] Coal mines are not only major energy producers but also huge energy consumers. Annual electricity consumption for coal mining, transportation, washing, ventilation, drainage, and logistical support can reach millions of kilowatt-hours. They are also highly dependent on external power grids and fossil fuel heating, resulting in high operating costs and significant carbon emissions. Meanwhile, coal mining generates a large amount of usable resources, such as coalbed methane (CSG), waste gas (VAM), mine water (GW), and coal gangue. However, for a long time, these resources have either been directly emitted (e.g., gas emissions exacerbate the greenhouse effect) or inefficiently disposed of (e.g., coal gangue accumulation occupies land), failing to form a systematic and coordinated utilization mechanism. Existing research on integrated energy systems in coal mines largely focuses on the configuration and scheduling of energy-side equipment, severely neglecting the adjustability potential of the coal production process itself. Traditional models typically treat coal mining and transportation as rigid loads with fixed timelines and uninterrupted operation, ignoring the material buffering capacity of belt conveyor systems and multi-level coal bunkers, which can actually serve as "virtual energy storage" for system optimization. Simultaneously, the handling of heat load in mining areas is also rather crude, generally employing constant power or constant temperature settings without considering the flexible scheduling space inherent in building thermal inertia and the heat storage characteristics of hot water systems. Furthermore, although some studies have introduced carbon capture, utilization, and storage (CCUS) technology to control emissions, it is often treated as an independent module, failing to dynamically couple it with production rhythms and energy scheduling. These limitations make it difficult for existing scheduling methods to effectively respond to electricity price fluctuations, uncertainties in renewable energy output, and changes in carbon costs while ensuring the rigid constraint of daily coal production. The systems suffer from insufficient flexibility, limited economic viability, and unrealized carbon reduction potential.

[0003] To address these issues, we provide a dynamic modeling and scheduling method for coal mines based on flexible production and spatial thermal inertia. Summary of the Invention

[0004] The purpose of this invention is to provide a dynamic modeling and scheduling method for coal mines based on flexible production and spatial thermal inertia. By modeling the belt conveyor and multi-level coal bunker system in the coal production process as virtual energy storage units with time adjustability, and combining the thermal inertia of the building space with the thermal dynamic characteristics of the hot water system to construct a temperature state equation, the originally rigid coal mining load and fixed heat demand are transformed into dispatchable flexible resources. Thus, while ensuring daily coal production and miners' thermal comfort, the method achieves synergistic optimization of multiple energy flows (electricity, heat, and cooling) with coal and carbon flows. This solves key technical problems in existing coal mine scheduling methods, such as insufficient flexibility in the production process, neglect of heat load response capability, insufficient coal-energy-carbon coupling, high operating costs, and difficulty in adapting to renewable energy fluctuations and carbon constraints.

[0005] To solve the above-mentioned technical problems, the present invention is achieved through the following technical solution:

[0006] This invention provides a dynamic modeling and scheduling method for coal mines based on flexible production and spatial thermal inertia. The method constructs a scheduling model according to the following logical hierarchy:

[0007] The physical system structure is constructed, including a coal production subsystem and a heat load subsystem. The coal production subsystem consists of a tunneling machine, a coal mining machine, four belt conveyors, an underground coal bunker (UCB), a surface raw coal bunker (RCS), a coal preparation plant (CPP), a clean coal silo (CCS), and a coal gangue silo (GS), connected sequentially. The electrical load of the tunneling machine and the coal mining machine is specified. Determine the amount of coal mined satisfy Four belt conveyors connect the working face to UCB, UCB to RCS, RCS to CPP, and CPP to CCS, respectively, with a running speed V. t (i) Adjustable, power consumption P t (i) Determined by a cubic polynomial function of velocity; the operating state of key downhole equipment is subject to binary maintenance variables. Control, when At that time, the corresponding equipment load is zero; the heat load subsystem includes a space heat load unit and a hot water load unit, which respectively serve the miners' indoor environment and bathing needs;

[0008] A dynamic behavior model is established, including coal flow dynamics and thermal inertia dynamics; the coal flow dynamics are reflected in the continuous updating of the storage capacity of each coal bunker with the inflow and outflow of coal, satisfying... Material conservation relationships; the aforementioned spatial thermal inertia dynamics are described by the indoor temperature state equation:

[0009]

[0010] in, The total space heat load demand; the hot water inertial dynamics are described by the water tank temperature state equation:

[0011]

[0012] An integrated and unified scheduling model is established, with coal mining volume, belt speed, equipment maintenance status, clean coal silo switch status, indoor temperature, water tank temperature, and output of each energy equipment as decision variables. The constraints are coal flow continuity, coal storage limit, temperature comfort range, balance of electricity / heat / cooling multi-energy flow, and carbon capture energy consumption. The objective function is to minimize the sum of electricity purchase cost, natural gas purchase cost, equipment operation and maintenance cost, and carbon dioxide storage cost, thus forming a mixed integer linear programming scheduling model.

[0013] The present invention is further configured such that the power consumption P of the four belt conveyors t (i) satisfy:

[0014]

[0015] And the speed is constrained:

[0016]

[0017] Where i = 1, 2, 3, 4.

[0018] The present invention is further configured such that the outlet of the clean coal silo CCS is determined by a binary variable. Control, satisfy:

[0019]

[0020] Furthermore, all refined coal loading is completed before the two preset departure times, and the total daily loading volume is equal to the daily refined coal output.

[0021] The present invention is further configured such that the total space heat load demand It consists of six heat loss / heat gain factors: heat transfer through the building envelope, wind infiltration, leakage through doors and windows, accidental opening, solar radiation, and mining activities.

[0022]

[0023] The present invention is further configured such that the hot water consumes heat power. satisfy:

[0024]

[0025] in, The volume of hot water replaced per unit time period. This refers to the temperature of the cold water.

[0026] The present invention is further configured such that the outlet coal flow of the coal gangue silo GS Directly supplied to coal-fired power units (CFUs), the CFUs' power generation capacity meets the following requirements:

[0027]

[0028] The present invention is further configured such that the objective function is expressed as:

[0029]

[0030] in, For real-time electricity pricing, c gas This refers to the unit price of natural gas. Let n be the unit operation and maintenance cost of equipment. Cost per unit of carbon dioxide storage.

[0031] The present invention is further configured such that the mass of carbon dioxide captured by the carbon capture, utilization and storage (CCUS) unit is... satisfy:

[0032]

[0033] Where, η c For capture efficiency, and These are the carbon emission coefficients for thermal equipment and power generation equipment, respectively.

[0034] The present invention is further configured such that the indoor temperature With water tank temperature satisfy:

[0035]

[0036] Furthermore, the total heat load and total hot water load during the scheduling cycle are equal to their baseline values ​​at the preset temperature.

[0037] The present invention further specifies that the binary variables in the scheduling model include equipment maintenance status variables. and the state variables of the coal silo switch Continuous variables include coal mining volume Belt speed V t (i) Coal storage capacity Temperature status and And the power of energy equipment.

[0038] The present invention has the following beneficial effects:

[0039] 1. This invention combines the speed adjustment of belt conveyors with the storage capacity of three-stage coal bunkers to give the coal transportation process "virtual energy storage" characteristics. It accelerates coal transportation and advances coal storage during periods of low electricity prices or peak wind and solar power output, and reduces power consumption or activates coal gangue power generation during periods of high electricity prices or insufficient renewable energy. This transforms the originally unadjustable coal mining load into a flexible resource with a certain time elasticity, effectively smoothing out power fluctuations in the power grid.

[0040] 2. This invention unifies the modeling of coal production, energy conversion, thermal environment management, and carbon capture units, enabling the system to comprehensively balance the costs of purchased electricity, natural gas, equipment operation and maintenance, and carbon emissions while meeting daily output and thermal comfort constraints. By directly coupling coal gangue silos with coal-fired power units, it achieves on-site consumption of low-grade solid waste energy. At the same time, the energy consumption and capture volume of the CCUS unit are accurately incorporated into the cost function, prompting the scheduling scheme to maximize carbon emission reduction benefits within the economically feasible range.

[0041] 3. This invention establishes a first-order state equation for indoor temperature and water tank temperature based on thermodynamic principles, accurately characterizing the thermal inertia characteristics of spatial heat load and hot water load. On this basis, it allows for spatiotemporal shifting and power shaping of heating and hot water supply, provided that the thermal comfort of miners is guaranteed (e.g., indoor temperature is maintained at 18–22℃ and hot water temperature is not lower than 45℃). For example, the hot water storage tank can be preheated or the room temperature raised during off-peak electricity price periods at night, and the heating intensity can be appropriately reduced during high-price periods during the day. By utilizing the heat storage capacity of buildings and water bodies to "transfer" energy demand across time periods, the cost of heat energy procurement can be significantly reduced.

[0042] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Detailed Implementation

[0043] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention.

[0044] This invention provides a dynamic modeling and scheduling method for coal mines based on flexible production and spatial thermal inertia. The method constructs a scheduling model according to the following logical hierarchy:

[0045] The physical system structure is constructed, including a coal production subsystem and a heat load subsystem. The coal production subsystem consists of a tunneling machine, a coal mining machine, four belt conveyors, an underground coal bunker (UCB), a surface raw coal bunker (RCS), a coal preparation plant (CPP), a clean coal silo (CCS), and a coal gangue silo (GS), connected sequentially. The electrical load of the tunneling machine and the coal mining machine is specified. Determine the amount of coal mined satisfy Four belt conveyors connect the working face to UCB, UCB to RCS, RCS to CPP, and CPP to CCS, respectively, with a running speed V. t (i) Adjustable, power consumption P t (i) Determined by a cubic polynomial function of velocity; the operating state of key downhole equipment is subject to binary maintenance variables. Control, when At that time, the corresponding equipment load is zero; the heat load subsystem includes a space heat load unit and a hot water load unit, which respectively serve the miners' indoor environment and bathing needs;

[0046] Among them, the power consumption P of the four belt conveyors t (i) satisfy:

[0047]

[0048] And the speed is constrained:

[0049]

[0050] Where i = 1, 2, 3, 4;

[0051] A dynamic behavior model is established, including coal flow dynamics and thermal inertia dynamics; the coal flow dynamics are reflected in the continuous updating of the storage capacity of each coal bunker with the inflow and outflow of coal, satisfying... Material conservation relationships; the aforementioned spatial thermal inertia dynamics are described by the indoor temperature state equation:

[0052]

[0053] in, The total space heat load demand, the total space heat load demand It consists of six heat loss / heat gain factors: heat transfer through the building envelope, wind infiltration, leakage through doors and windows, accidental opening, solar radiation, and mining activities.

[0054]

[0055] The inertial dynamics of the hot water are described by the temperature state equation of the water tank:

[0056]

[0057] An integrated and unified scheduling model is established, with coal mining volume, belt speed, equipment maintenance status, clean coal silo switch status, indoor temperature, water tank temperature, and output of each energy equipment as decision variables. The constraints are coal flow continuity, coal storage limit, temperature comfort range, balance of electricity / heat / cooling multi-energy flow, and carbon capture energy consumption. The objective function is to minimize the sum of electricity purchase cost, natural gas purchase cost, equipment operation and maintenance cost, and carbon dioxide storage cost, thus forming a mixed integer linear programming scheduling model.

[0058] This invention aligns and couples the inherent coal flow, energy flow (electricity / heat / cold), and information flow (scheduling instructions) of coal mines through spatiotemporal modeling using state variables (coal storage capacity, temperature) and controllable variables (equipment start / stop, speed, output). This transforms traditional high-energy-consuming and low-flexibility coal mines into comprehensive energy systems with endogenous regulatory capabilities. The overall design is based on the deep coupling of the coal mine production system and the energy-thermal environment system. Through a three-pronged architecture design of "layered physical entity modeling—precise dynamic behavior characterization—multi-objective collaborative scheduling," it achieves unified description and optimized control of the multi-dimensional coupling process of coal-energy-carbon-heat. Specifically, at the physical structure level, the coal mine is divided into two core modules: the coal production subsystem and the heat load subsystem. The former starts with the tunneling machine and the coal mining machine, and is connected to the underground coal bunker (UCB), the surface raw coal bunker (RCS), the coal preparation plant (CPP), the clean coal silo (CCS), and the coal gangue silo (GS) through a transportation network composed of four adjustable speed belt conveyors, forming a closed-loop coal flow path. The latter includes the spatial heat load unit (corresponding to indoor heating for miners) and the hot water load unit (corresponding to bathing heat), both of which have significant thermal inertia characteristics. Secondly, at the dynamic behavior level, a virtual energy storage mechanism is introduced for coal production. By adjusting the speed of the belt conveyor to change its power consumption and coal flow rate, the storage capacity of the three-level coal bunker becomes a dispatchable state variable, thereby transforming the highly rigid coal mining process into an energy response unit with a certain degree of time flexibility. Simultaneously, a first-order thermal inertia state model is established for the thermal environment, using indoor temperature and water tank temperature as state variables. Their rate of change is driven by the net difference between the output power of heating / cooling equipment and heat loss / consumption. The thermal response hysteresis characteristic provides scheduling freedom for shifting and peak shaving of the heat load. Thirdly, at the integrated scheduling level, constraints such as equipment maintenance status (represented by binary variables), silo switching logic, coal flow continuity, temperature comfort range, balance of electricity / heat / cooling multi-energy flow, and carbon capture energy consumption are uniformly embedded into a mixed-integer linear programming framework. With the goal of minimizing both operating costs and carbon emissions, the previously isolated coal mining operations, energy conversion, and thermal environment management are collaboratively optimized under a unified mathematical model.

[0059] Specifically, the outlet of the refined coal silo CCS is determined by a binary variable. Control, satisfy:

[0060]

[0061] Furthermore, all refined coal loading is completed before the two preset departure times, and the total daily loading volume is equal to the daily refined coal output.

[0062] The hot water consumes heat power satisfy:

[0063]

[0064] in, The volume of hot water replaced per unit time period. This refers to the temperature of the cold water.

[0065] The coal flow at the outlet of the coal gangue silo GS Directly supplied to coal-fired power units (CFUs), the CFUs' power generation capacity meets the following requirements:

[0066]

[0067] The objective function is expressed as:

[0068]

[0069] in, For real-time electricity pricing, c gas This refers to the unit price of natural gas. Let n be the unit operation and maintenance cost of equipment. Cost per unit of carbon dioxide storage.

[0070] The carbon dioxide capture mass of the CCUS unit satisfy:

[0071]

[0072] Where, η c For capture efficiency, and These are the carbon emission coefficients for thermal equipment and power generation equipment, respectively.

[0073] The indoor temperature With water tank temperature satisfy:

[0074]

[0075] Furthermore, the total heat load and total hot water load during the scheduling cycle are equal to their baseline values ​​at the preset temperature.

[0076] Furthermore, the binary variables in the scheduling model include equipment maintenance status variables. and the state variables of the coal silo switch Continuous variables include coal mining volume Belt speed V t (i) Coal storage capacity Temperature status and And the power of energy equipment.

[0077] The operation process in this embodiment is as follows: First, collect the system parameters and operating data of the target coal mine, including the load-output coefficients of the tunneling machine and the coal mining machine, and the structural parameters of the four belt conveyors (such as load per unit length and empirical coefficients). The model includes parameters such as motor efficiency, capacity of coal bunkers at all levels, gangue discharge rate of coal preparation plants, building thermal parameters (heat transfer coefficient, room volume, solar radiation absorptivity, etc.), hot water usage patterns, energy equipment efficiency (such as gas boilers, micro gas turbines, coal-fired units, water source heat pumps, etc.), carbon emission coefficients, and carbon capture energy consumption parameters. It also obtains the electricity / heat / cooling load curves, renewable energy predicted output, time-of-use electricity prices, and natural gas prices within the scheduling cycle (usually 24 hours). Secondly, based on these parameters, a three-layer structural model is constructed: In the physical layer, the complete material path of coal from the working face through UCB, RCS, CPP to CCS / GS is defined, and the thermal environment and hot water system heat ports are defined. In the dynamic layer, the linear relationship between coal mining volume and working face load, the cubic polynomial function of belt power consumption and speed, the material conservation equation for coal bunker storage at all levels, and the first-order difference state equation for indoor temperature and water tank temperature are established. Binary variables are introduced to characterize equipment maintenance windows and the loading logic of clean coal silos. In the integration layer, all variables (including continuous variables such as...) are integrated. V t (i) , Power of each device and binary variables, such as and The system incorporates a unified framework and sets constraints covering: coal flow continuity, coal storage limits, belt speed and ramp limits, temperature comfort range, daily loading of all clean coal, unique maintenance periods, balance equations for electricity / heat / cold energy flows, and the carbon capture energy consumption model for CCUS units. Subsequently, an objective function is constructed to minimize total operating costs, including purchased electricity costs, natural gas procurement costs, equipment operation and maintenance costs, and carbon dioxide storage costs. Next, the above model is encoded as a mixed-integer linear programming problem and input into a commercial optimization solver for solving. Finally, based on the solution results, optimal scheduling instructions for each time period are generated, including the operating power of the coal mining machine and tunneling machine, the speed setpoints of the four belt conveyors, maintenance arrangements for key equipment, the opening and closing times of the clean coal silos, the output plans of each energy device, the charging and discharging strategies of the thermal / electrical storage devices, and the temperature control schemes for the indoor heating and hot water systems. These instructions are then transmitted in real-time to the corresponding execution units via the coal mine's internal fiber optic communication network, completing closed-loop scheduling.

[0078] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

Claims

1. A dynamic modeling and scheduling method for coal mines based on flexible production and spatial thermal inertia, characterized in that, The method constructs a scheduling model according to the following logical hierarchy: The physical system structure is constructed, including a coal production subsystem and a heat load subsystem. The coal production subsystem consists of a tunneling machine, a coal mining machine, four belt conveyors, an underground coal bunker (UCB), a surface raw coal bunker (RCS), a coal preparation plant (CPP), a clean coal silo (CCS), and a coal gangue silo (GS), connected sequentially. The electrical load of the tunneling machine and the coal mining machine is specified. Determine the amount of coal mined satisfy Four belt conveyors connect the working face to UCB, UCB to RCS, RCS to CPP, and CPP to CCS, respectively, with a running speed V. t (i) Adjustable, power consumption Determined by a cubic polynomial function of velocity; the operating state of key downhole equipment is subject to binary maintenance variables. Control, when At that time, the corresponding equipment load is zero; the heat load subsystem includes a space heat load unit and a hot water load unit, which respectively serve the miners' indoor environment and bathing needs; A dynamic behavior model is established, including coal flow dynamics and thermal inertia dynamics; the coal flow dynamics are reflected in the continuous updating of the storage capacity of each coal bunker with the inflow and outflow of coal, satisfying... Material conservation relationships; the aforementioned spatial thermal inertia dynamics are described by the indoor temperature state equation: in, The total space heat load demand; the hot water inertial dynamics are described by the water tank temperature state equation: An integrated and unified scheduling model is established, with coal mining volume, belt speed, equipment maintenance status, clean coal silo switch status, indoor temperature, water tank temperature, and output of each energy equipment as decision variables. The constraints are coal flow continuity, coal storage limit, temperature comfort range, balance of electricity / heat / cooling multi-energy flow, and carbon capture energy consumption. The objective function is to minimize the sum of electricity purchase cost, natural gas purchase cost, equipment operation and maintenance cost, and carbon dioxide storage cost, thus forming a mixed integer linear programming scheduling model.

2. The coal mine dynamic modeling and scheduling method based on flexible production and spatial thermal inertia according to claim 1, characterized in that, The power consumption of the four belt conveyors satisfy: And the speed is constrained: Where i = 1, 2, 3, 4.

3. The coal mine dynamic modeling and scheduling method based on flexible production and spatial thermal inertia according to claim 1, characterized in that, The outlet of the refined coal silo CCS is determined by a binary variable. Control, satisfy: Furthermore, all refined coal loading is completed before the two preset departure times, and the total daily loading volume is equal to the daily refined coal production.

4. The coal mine dynamic modeling and scheduling method based on flexible production and spatial thermal inertia according to claim 1, characterized in that, The total space heat load demand It consists of six heat loss / heat gain factors: heat transfer through the building envelope, wind infiltration, leakage through doors and windows, accidental opening, solar radiation, and mining activities.

5. The coal mine dynamic modeling and scheduling method based on flexible production and spatial thermal inertia according to claim 1, characterized in that, The hot water consumes heat power satisfy: in, The volume of hot water replaced per unit time period. This refers to the temperature of the cold water.

6. The coal mine dynamic modeling and scheduling method based on flexible production and spatial thermal inertia according to claim 1, characterized in that, The coal flow at the outlet of the coal gangue silo GS Directly supplied to coal-fired power units (CFUs), the CFUs' power generation capacity meets the following requirements:

7. The coal mine dynamic modeling and scheduling method based on flexible production and spatial thermal inertia according to claim 1, characterized in that, The objective function is expressed as: in, For real-time electricity pricing, c gas This refers to the unit price of natural gas. Let n be the unit operation and maintenance cost of equipment. Cost per unit of carbon dioxide storage.

8. The coal mine dynamic modeling and scheduling method based on flexible production and spatial thermal inertia according to claim 7, characterized in that, The carbon dioxide capture mass of the CCUS unit satisfy: Where, η c For capture efficiency, and These are the carbon emission coefficients for thermal equipment and power generation equipment, respectively.

9. The coal mine dynamic modeling and scheduling method based on flexible production and spatial thermal inertia according to claim 1, characterized in that, The indoor temperature With water tank temperature satisfy: Furthermore, the total heat load and total hot water load during the scheduling cycle are equal to their baseline values ​​at the preset temperature.

10. The coal mine dynamic modeling and scheduling method based on flexible production and spatial thermal inertia according to claim 1, characterized in that, The binary variables in the scheduling model include equipment maintenance status variables. and the state variables of the coal silo switch Continuous variables include coal mining volume Belt speed V t (i) Coal storage capacity Temperature status and And the power of energy equipment.

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