A smart control system for waste heat recovery from mine water

Abstract

This invention belongs to the field of thermal energy recovery and automation control, specifically relating to an intelligent control system for mine water waste heat recovery. The system includes a production condition sensing device, a multi-source thermal monitoring device, an energy value analysis center, a dynamic load dispatching terminal, a multi-media heat exchange actuator, and a flexible thermal energy storage system. The system collects real-time mine production conditions and multi-source thermal parameters, constructs an energy asset model using a discrete state transition probability model, and, based on a game theory bidding mechanism and electricity price fluctuation trend prediction, guides the heat exchange actuator and storage system to perform optimized allocation and predictive storage of thermal energy. This invention transforms fluctuating heat sources into predictable energy assets, achieving the lowest-cost and most energy-efficient energy configuration scheme in a multi-source coupled environment, improving resource utilization, and ensuring the stability of energy supply in the mining area.

Description

Technical Field

[0001] This invention belongs to the field of heat energy recovery and utilization and automation control, specifically relating to an intelligent control system for mine water waste heat recovery. Background Technology

[0002] Against the backdrop of green mine construction and energy structure transformation, waste heat recovery and utilization technology in mines is significant for achieving energy conservation, emission reduction, and low-carbon production in mining areas. By integrating various low-grade energy sources generated during mine production and utilizing heat pump technology and heat exchange equipment for energy enhancement and conversion, it can replace traditional high-energy-consuming heat sources and meet the heating and domestic hot water needs of mine industrial sites and living areas.

[0003] For complex waste heat systems that include multiple sources such as mine water, exhaust air, air compressors, and gas power generation, how to achieve multi-energy complementarity and coordinated scheduling is a core issue in the field of intelligent control.

[0004] These systems monitor the temperature, flow rate, and pressure parameters of various heat sources in real time through sensor networks, and adjust the operating conditions of each heat exchange branch and heat pump unit in accordance with the thermodynamic cycle principle, aiming to improve the overall heat extraction efficiency and energy supply stability of the system.

[0005] Existing technologies typically employ logic control methods based on fixed priorities, which struggle to adapt to the randomness of heat source supply caused by fluctuations in mine production loads, resulting in low dynamic matching efficiency during multi-energy flow coupling. Simultaneously, traditional scheduling schemes lack a real-time mechanism for measuring energy acquisition costs and heat output value, failing to proactively allocate resources based on electricity price fluctuations or the operational probability of production equipment, leading to temporal and spatial scheduling imbalances between thermal storage facilities and production equipment. Furthermore, due to the differences in energy quality among heat sources and their complex nonlinear relationships with the operating environment, a single linear logic approach cannot achieve globally optimal allocation under multi-objective constraints, making it difficult to simultaneously consider both overall operating costs and energy efficiency ratios in complex operating scenarios. Summary of the Invention

[0006] The purpose of this invention is to provide an intelligent control system for mine water waste heat recovery, which can solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0008] A smart control system for waste heat recovery from mine water includes a production condition sensing device, a multi-source thermal monitoring device, an energy value analysis center, a dynamic load dispatching terminal, a multi-media heat exchange actuator, and a flexible thermal energy storage system, wherein: The production condition sensing device is used to collect real-time operating status data of various production systems inside the mine. The operating status data includes the number of air compressor units in operation and instantaneous load power, instantaneous water inflow and water level change rate of the mine drainage system, flue gas emission flow of the gas power generation system, and air volume parameters of the exhaust ventilation system. The multi-source thermal monitoring device is used to acquire physical parameters of various heat sources in the mine in an all-round way. The heat sources include mine water, air compressor cooling water, exhaust air and high-temperature flue gas from gas power generation. The parameters it monitors cover the real-time temperature, fluid pressure and flow rate of each heat source medium, and convert the above physical parameters into digital thermal energy abundance signals. The energy value analysis center is used to receive data transmitted by the production condition sensing device and the multi-source thermal monitoring device. Through the built-in discrete state transition probability model and linear minimum variance state estimation model, it quantitatively predicts the heat production cost and expected energy efficiency ratio of each heat source in a predetermined time period in the future, and transforms the originally fluctuating thermal energy resources into an energy asset model with virtual value weight. The dynamic load dispatch terminal is used to construct a multi-objective dynamic optimization combination scheme based on the energy asset model generated by the energy value analysis center, and to formulate energy allocation instructions for the heating demand of mine industrial sites and the domestic hot water demand by sorting the real-time acquisition costs of each heat source. The multi-media heat exchange actuator is used to receive the allocation instructions from the dynamic load scheduling terminal and to extract and convert heat sources of different grades on demand by adjusting the opening of the flow regulating valve of each heat exchange branch, the operating frequency of the heat pump unit and the speed of the circulating pump. The flexible thermal energy storage system is used to perform advance storage or release of heat based on the electricity price fluctuation trend forecast and thermal energy supply and demand gap forecast provided by the energy value analysis center. The flexible thermal energy storage system includes a large thermal storage tank and corresponding inlet and outlet water temperature compensation logic.

[0009] Preferably, when processing production data, the energy value analysis center uses state estimation logic to denoise the raw signals collected by sensors. The linear minimum variance state estimation model tracks the continuous supply capacity of the heat source by observing the current and voltage fluctuations of the production equipment and the pulsation of the heat source flow in real time. This trend tracking does not rely on fixed physical values, but is a predicted trajectory generated based on the fluctuation patterns of historical data.

[0010] Furthermore, the Energy Value Analysis Center uses a discrete state transition probability model to simulate and analyze the random start-up behavior of air compressor units and the probability of sudden start-up of mine drainage pumps. The discrete state transition probability model divides the production process into several mutually exclusive production states and calculates the transition probability between each state within a specific time step, determining the deterministic weight of the supply of each heat source in the next few hours.

[0011] Furthermore, the energy value analysis center introduces cost-efficiency evaluation indicators, comprehensively calculating the electricity consumption, equipment depreciation costs, and water and chemical costs required to extract a unit of heat, generating a real-time price for each heat source. This real-time price is a dynamically fluctuating logical variable; as the mine's production load increases, when a certain type of waste heat resource changes from surplus to scarcity, its corresponding real-time price logical value rises accordingly.

[0012] Furthermore, the dynamic load dispatching terminal employs a game-theoretic bidding mechanism for load allocation. When heating load demand arises, the dynamic load dispatching terminal compares the instantaneous price of each available heat source with its expected energy efficiency ratio, prioritizing the combination of heat sources with the highest energy efficiency ratio and the lowest price. When it is predicted that electricity prices will be in a preset high-price period, the dynamic load dispatching terminal will reduce the output weight of the electric-driven heat pump unit and instead increase the energy storage release weight of the flexible thermal energy storage system.

[0013] Furthermore, the multi-media heat exchange actuator includes a mine water heat exchange branch, a waste air heat exchange branch, an air compressor waste heat recovery branch, and a gas flue gas waste heat utilization branch. Upon receiving a dispatch command, the multi-media heat exchange actuator precisely controls the mass flow rate of the circulating medium in each branch by adjusting the output current frequency of the variable frequency drive, thereby maintaining the outlet temperature of each heat exchanger within a preset process temperature range.

[0014] Furthermore, the flexible thermal energy storage system possesses predictive regulation capabilities. When the energy value analysis center predicts a sustained peak in low-cost waste heat or a period of low electricity prices, the flexible thermal energy storage system controls cold water to enter the bottom of the storage tank, utilizing waste heat resources to pre-raise the water temperature to a preset storage temperature. When peak production energy consumption or peak electricity price periods arrive, the flexible thermal energy storage system replenishes the heating network with high-temperature media through the top water outlet device, reducing the instantaneous load on core production equipment.

[0015] Furthermore, the production condition sensing device also includes fault self-diagnosis logic. When the current characteristics of the air compressor or drain pump fluctuate abnormally and deviate from the preset normal operating range, the production condition sensing device sends a fault load reduction signal to the energy value analysis center. The energy value analysis center immediately recalculates the supply reliability weight of the affected heat source and lowers the call priority of the heat source in the game bidding model.

[0016] Furthermore, the intelligent control system for mine water waste heat recovery also includes a remote redundant control module. This remote redundant control module monitors the operating status of the dynamic load scheduling terminal in real time via an independent data link. When an abnormality is detected in the main controller's logic operation, the remote redundant control module automatically takes over control authority and switches to a preset emergency operation plan based on safety priorities to ensure the continuity of heating in the mine area.

[0017] Furthermore, the multi-source thermal monitoring device comprehensively considers the influence of air humidity on enthalpy when measuring exhaust air heat. The device obtains the moisture content of the exhaust air through a humidity sensing component and, combined with the dry-bulb temperature signal, calculates the total enthalpy of the humid air in the exhaust air, providing a more accurate thermal energy abundance benchmark for the energy value analysis center.

[0018] Furthermore, the heat pump unit in the multi-media heat exchange actuator adopts multi-cascade control logic. Based on the total load demand calculated by the dynamic load scheduling terminal, the compressor inside the heat pump unit automatically adjusts the position of the slide valve or the speed of the frequency converter according to the pressure ratio relationship between the suction pressure and the discharge pressure, so as to ensure that the unit always operates within the optimal range of the energy efficiency ratio curve under different heat source inlet water temperatures.

[0019] Furthermore, the thermal energy flexible storage system's storage tank is equipped with a layered barrier structure. This layered barrier structure slows down the mixing rate of hot and cold water inside the tank through physical guide plates, maintaining a significant water temperature gradient. This allows the stored high-temperature water to be output to the heating network at a more stable temperature, improving heat utilization.

[0020] Furthermore, the energy asset model generated by the energy value analysis center also includes an environmental premium factor. This factor is logically converted based on the real-time monitored carbon emission reduction equivalent, and a higher weighting coefficient is assigned to low-carbon emission heat source extraction methods, guiding the system to maximize the utilization of renewable waste heat resources while meeting economic requirements.

[0021] Furthermore, the execution control mechanism includes various types of actuators, pump motors, and fan drives distributed throughout the mining area. The execution control mechanism receives digitized opening commands via a fieldbus and provides real-time feedback on the actual position or speed signals of the actuators, forming a closed-loop feedback control circuit to ensure the precise execution of scheduling commands.

[0022] Furthermore, the intelligent control system for waste heat recovery from mine water enters a self-learning mode during the initial startup phase. The energy value analysis center automatically corrects the energy efficiency response functions of each heat source under different production loads by recording operating condition fluctuations and energy consumption data within a predetermined period, gradually bringing the game-theoretic bidding scheduling algorithm closer to the optimal economic operating point of actual mine production.

[0023] Furthermore, the production condition sensing device can identify the seasonal patterns of mine production. In summer mode, the system focuses on domestic hot water supply and system cooling maintenance; in winter mode, the system focuses on mine antifreeze heating and building heating. The energy value analysis center will automatically load different asset value assessment logics according to seasonal switching signals to adapt to the energy supply and demand characteristics of different seasons.

[0024] Compared with the prior art, the present invention has the following beneficial effects: 1. The intelligent control system for waste heat recovery from mine water provided by this invention breaks away from the fixed and rigid priority control logic of traditional mine heating systems by introducing time series analysis and game-theoretic bidding mechanisms similar to those in the financial field. The system can perceive fluctuations in mine production conditions in real time, transforming the previously unpredictable heat source supply into quantifiable and predictable energy assets. In complex environments with multi-source coupling, it consistently seeks low-cost and high-efficiency energy combination solutions. Through precise tracking and trend prediction of air compressor, drainage volume, and gas power generation load, it achieves in-depth extraction and optimized allocation of low-grade energy levels from exhaust air and mine water.

[0025] 2. This invention utilizes the deep coupling of a flexible thermal energy storage system with electricity price trends to achieve energy dispatch by buying low and selling high. It stores heat during periods of low electricity prices or surplus heat and releases energy during peak energy consumption or high electricity price periods, reducing the overall operating cost of the system. Simultaneously, the system's modular architecture and redundant control logic enhance the stability of mine energy supply under extreme conditions. The introduction of a multi-objective dynamic optimization algorithm enables the system to not only consider economic efficiency but also increase the utilization ratio of renewable energy based on environmental premium factors, achieving energy conservation and emission reduction benefits as well as intelligent operation, providing a reliable system guarantee for energy management in green mines. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the overall technical solution architecture of the present invention; Figure 2 This is a schematic diagram of the core principle framework of energy asset modeling based on discrete state transition and linear minimum variance estimation in this invention; Figure 3 This is a flowchart illustrating the logical process of multi-objective dynamic load scheduling based on a game-theoretic bidding mechanism in this invention. Figure 4 This is a schematic diagram of the multi-level interaction and data flow between the production condition sensing device, the energy value analysis center, and the heat exchange actuator in this invention. Figure 5 This is a schematic diagram of the flexible regulation principle framework of the thermal energy flexible storage system combined with electricity price fluctuation prediction in this invention. Detailed Implementation

[0027] Example 1: To make the objectives, technical solutions, and advantages of the present invention clearer, the following description is provided in conjunction with the appendix. Figure 1 To be continued Figure 5 The present invention will be further described in detail with reference to specific embodiments.

[0028] A smart control system for mine water waste heat recovery includes a production condition sensing device, a multi-source thermal monitoring device, an energy value analysis center, a dynamic load scheduling terminal, a multi-media heat exchange actuator, and a flexible thermal energy storage system.

[0029] The production condition sensing device is configured to capture and analyze the original physical characteristics reflecting the mine's operating load in real time through a multi-dimensional sensor array deployed at key production nodes in the mine. Structurally, the production condition sensing device includes a data acquisition and control cabinet, a high-precision current transformer, an industrial-grade flow meter, and a bus communication adapter.

[0030] The data acquisition and control cabinet integrates a high-performance field-programmable logic array (FPGA) for preprocessing analog signals transmitted from front-end sensors. The operating status data collected by the production condition sensing device covers the number of air compressor units in operation and the real-time load power. Specifically, it determines whether the air compressor is in an unloaded, light-load, or full-load operating state by monitoring the three-phase current fluctuations and active power parameters of each air compressor motor.

[0031] The production condition sensing device is also connected to the automated control cabinet of the mine's main drainage system to obtain instantaneous water inflow data and water level change rate in the water tank, and calculates the potential increase in mine water supply in the future period of time by combining the opening frequency of the drainage pump.

[0032] The production condition sensing device also includes a flow orifice plate deployed on the flue gas pipeline of the gas power plant and a thermal anemometer at the exhaust gas outlet, used to obtain the flue gas emission flow rate and the air volume parameters of the exhaust gas system, and to establish a panoramic working condition map reflecting the energy output of the mine.

[0033] The multi-source thermal monitoring device is configured to perform precise physical quantification monitoring of various heat energy carriers generated during mine production. These heat sources include, but are not limited to, mine water inflow, air compressor cooling water, exhaust air from the return air shaft, and high-temperature flue gas generated by gas power generation. The device is equipped with armored platinum resistance temperature sensors, pressure transmitters, and ultrasonic flow meters on the extraction branches of each heat source. For mine water that is corrosive or prone to scaling, the device also employs non-contact measurement components to ensure long-term data reliability.

[0034] The processing unit inside the multi-source thermal monitoring device synchronously processes the collected real-time temperature signal, fluid pressure signal, and mass flow rate signal, and calculates the heat flux per unit time based on the specific heat capacity coefficient of different media.

[0035] For monitoring exhaust air heat, the multi-source thermal monitoring device integrates a humidity sensing component to obtain the moisture content of the exhaust air. Combined with the dry-bulb temperature signal, and based on the enthalpy-humidity diagram logic of the humid air, the above parameters are converted into a digital thermal abundance signal. The thermal abundance signal can reflect the energy density and thermal quality of each heat source at different times.

[0036] The energy value analysis center is configured as the logical decision-making brain of the entire system. It operates on a high-performance industrial computing platform and transforms the massive amounts of heterogeneous data collected into assets through deep integration of financial time series analysis algorithms.

[0037] The energy value analysis center internally stores discrete state transition probability models and linear minimum variance state estimation models.

[0038] The linear minimum variance state estimation model is configured to perform real-time denoising and smoothing on the raw physical signals from the sensor layer. By constructing a state space model, the optimal state trajectory with minimum variance is calculated using the estimated state value of the heat source at the previous moment and the observed value at the current moment.

[0039] The linear minimum variance state estimation model dynamically adjusts the Kalman gain coefficient during operation. When the noise level of sensor observations fluctuates, the model automatically increases or decreases the weight of the observations, achieving continuous trend tracking of heat source supply capacity. The discrete state transition probability model is used to handle production behaviors with randomness, such as sudden loading and unloading of air compressors or random starting of drainage pumps. This model divides the production conditions into several mutually exclusive state intervals, generates a state transition matrix by statistically analyzing the transition frequencies between states in historical operating cycles, and then calculates the deterministic weights of various heat source supplies in a predetermined future time period.

[0040] The energy value analysis center also introduces cost-efficiency evaluation indicators, comprehensively calculating the electricity consumption required to extract a unit of heat, the depreciation costs incurred by regular cleaning and maintenance of heat exchangers, and even the water resource losses caused by the operation of circulating water pumps, assigning each heat source carrier a dynamically fluctuating real-time price. This asset-based modeling approach transforms the originally complex physical heat balance problem into a valuation problem similar to that of heat source stocks in the financial market, generating an energy asset model that includes cost weights, expected rates of return, and risk volatility.

[0041] The dynamic load dispatching terminal is configured to execute precise energy allocation commands based on a game-theoretic bidding mechanism. The dynamic load dispatching terminal is connected to the mining area heating load monitoring node and domestic hot water demand terminal via an industrial Ethernet network.

[0042] When heating load demand changes, the dynamic load scheduling terminal does not follow the preset static priority, but instead constructs a multi-objective dynamic optimization combination based on the energy asset model provided by the energy value analysis center.

[0043] The multi-objective dynamic optimization combination aims to achieve the lowest overall system operating cost, the largest carbon emission reduction equivalent, and the strongest energy supply stability. In terms of allocation logic, the dynamic load dispatching terminal simulates a financial transaction process, treating each available heat source as a trading entity participating in the bidding. It compares the real-time price of each heat source with its expected energy efficiency ratio, prioritizing the use of heat source combinations that are in a price trough and have a high rate of return (i.e., generate more heat per unit of electricity consumption).

[0044] When the system detects that the mine is in a high-power drainage phase and the air compressor is operating at its peak, it will automatically determine that the cost-effectiveness of recovering waste heat at this time is far higher than turning on the high-power air source heat pump.

[0045] The dynamic load dispatching terminal also has electricity price sensitivity. When it is predicted that the peak period of time-of-use electricity price will be entered in the next few hours, the terminal will adjust the dispatching strategy in advance, prioritize locking low-cost waste heat resources and instruct the storage system to take action, so as to realize the elastic displacement of the load on the time axis.

[0046] The multi-media heat exchange actuator is configured as a physical operation layer that responds to scheduling commands, and includes heat exchange branches and core production capacity equipment distributed in various energy exchange stations in the mining area.

[0047] It includes a mine water plate heat exchanger assembly, a waste air spray heat exchange tower, an air compressor waste heat recovery device, and a gas flue gas waste heat boiler. Each branch is equipped with a variable frequency drive circulating water pump and an electric regulating valve. After receiving a digital distribution command, the multi-media heat exchange actuator's internal proportional-integral-derivative control unit automatically calculates the target opening degree or speed of the actuator. For example, by adjusting the flow regulating valves of each heat exchange branch, the flow rate of the medium entering the heat exchanger can be precisely controlled, so that the secondary side return water temperature after heat exchange accurately converges to the preset process temperature.

[0048] For heat pump units, the actuator adopts multi-level control logic, which automatically adjusts the position of the compressor slide valve or the output frequency of the inverter according to the changes in total load demand, so as to ensure that the unit always operates within the energy efficiency curve range under different heat source inlet water temperatures and ambient temperatures, avoiding energy waste and equipment damage caused by frequent start-stop.

[0049] The thermal energy flexible storage system is configured as an energy buffer and time-series temperature control device, the core of which is a large thermal storage tank group with high thermal insulation performance and a matching temperature compensation control logic.

[0050] The flexible thermal energy storage system is deeply coupled with the energy value analysis center and has predictive regulation capabilities. When the energy value analysis center predicts a sustained peak in low-cost waste heat (such as continuous full-load operation of air compressors) or a period of low electricity prices, the storage system will be instructed to enter a low-buy mode. This mode instructs the multi-media heat exchange actuator to increase the heat extraction intensity and store the excess heat in the heat storage tank through the heat storage medium.

[0051] The thermal storage tank is equipped with a special layered barrier structure. This structure uses physical baffles to slow down the mixing rate of hot and cold water inside the tank, creating a significant water temperature gradient and maintaining a balance between the hot water zone at the top and the cold water zone at the bottom. During peak heating seasons or periods of high electricity prices, the system enters a high-temperature release mode, replenishing the heating network with high-temperature media through the top outlet device. This reduces the system's immediate demand for high-priced electricity, thus playing a role in peak shaving and valley filling.

[0052] When processing production data, the energy value analysis center uses state estimation logic to perform refined noise reduction on the raw signals collected by sensors. During operation, the linear minimum variance state estimation model constructs a state transition equation reflecting the continuity of the physical system in real time.

[0053] The equations describe the correlation between heat source flow rate, temperature, and parameters from the previous moment. When the field sensors generate random pulsating signals due to electromagnetic interference in the mine, the model can filter out these interference signals based on a preset error covariance matrix, extracting the true heat source supply trend trajectory. This trend tracking does not rely on fixed instantaneous physical values, but is based on a prediction window that includes historical fluctuation patterns, enabling the system to provide stable logical support even when faced with short-term data acquisition interruptions or sudden increases in noise.

[0054] Furthermore, the energy value analysis center uses a discrete state transition probability model to predict and analyze the uncertainties of the mine production subsystem. This model divides the operating state of the air compressor into multiple discrete levels and calculates the probability distribution of a state transition at the current moment and in the next moment, based on the mine's shift schedule and historical load fluctuations. For example, during shift changes, the probability of the air compressor transitioning from full load to light load increases. Once the energy value analysis center detects this probability change, it will preemptively lower the supply reliability weight of the heat source in the asset model, prompting the dispatch terminal to proactively find alternative heat sources. This probability-based prediction mechanism enables the system to handle unpredictable and sudden operating conditions.

[0055] Furthermore, the energy asset model generated by the energy value analysis center specifically incorporates an environmental premium factor. This factor is defined as a logical variable linked to real-time carbon emission equivalents. For heat sources with environmental benefits from waste heat from gas power generation, the system assigns them additional bidding weight through the environmental premium factor. This means that, given similar economic costs, the system will prioritize the extraction paths of heat sources with low carbon emissions or greenhouse gas emission reduction effects. Through this logical setting, the system not only achieves operational economy but also guides the entire mining area's energy system towards a green and low-carbon evolution.

[0056] Furthermore, the production condition sensing device possesses advanced fault self-diagnosis logic. Internally, it stores equipment characteristic fingerprints under normal operating conditions, including the current spectrum distribution of motors and the pressure-flow correlation curve of water pumps. When abnormal fluctuations in the current characteristics of the air compressor or drainage pump are detected, and these fluctuations deviate from the preset normal distribution range, the sensing device immediately triggers a fault warning. At this time, the sensing device does not simply cut off the signal, but instead sends a fault load reduction signal with a confidence level assessment to the energy value analysis center. Upon receiving this fault load reduction signal, the analysis center quickly reconstructs the game theory bidding model, lowering the weight of the heat source supply associated with the faulty equipment to a safety protection level, ensuring that the system will not experience overall energy efficiency collapse or secondary hardware damage due to the use of abnormal heat sources.

[0057] Furthermore, the intelligent control system for mine water waste heat recovery also includes a remote redundant control module. This remote redundant control module, as a physically independent hardware redundancy unit, monitors the heartbeat signal of the dynamic load scheduling terminal via a dedicated one-to-one data link. If the main controller experiences a logic response halt due to a strong electromagnetic pulse, software infinite loop, or memory overflow fault, the redundant control module will automatically take over bus control within microseconds. After taking over, the system immediately switches from a complex game-theoretic bidding strategy to a preset emergency operation plan based on safety priorities. This preset emergency operation plan prioritizes ensuring the minimum heating temperature at the mine entrance and in key protected areas, providing the mine with an ultimate energy efficiency and safety barrier.

[0058] Furthermore, the heat pump unit in the multi-media heat exchange actuator employs deep frequency conversion control and circulation pump linkage logic. Under low-load conditions, to avoid frequent start-stop cycles of the heat pump unit, the system adjusts the circulation pump speed to change the heat exchange temperature difference, extending the unit's continuous operating time and improving the system's overall performance coefficient. Simultaneously, for the mine water heat exchange branch, the actuator is equipped with automatic backflushing logic. It automatically judges the degree of scaling based on changes in the pressure drop at the heat exchanger inlet and outlet and performs flushing operations as needed to maintain long-term stable heat exchange efficiency.

[0059] Furthermore, the thermal energy flexible storage system's storage tank is equipped with inlet and outlet water temperature compensation logic. Due to fluctuations in heat source temperature during mine production, the water temperature entering the storage tank is often inconsistent. This compensation logic, by installing a mixing and temperature regulating valve in the inlet pipeline, pre-mixes waste heat fluids from different sources, allowing them to be injected into the tank at a relatively constant temperature. This avoids violent turbulence within the tank, protects the stability of the temperature stratification structure, and enables the stored high-temperature thermal energy to be output to the user at a more stable grade.

[0060] Furthermore, the execution control mechanism includes actuators distributed throughout the mining area, such as high-performance electric butterfly valves and variable frequency pump controllers. These actuators are interconnected via industrial fieldbuses (such as CAN bus or RS485 bus) and interact with each other using standard industrial handshake protocols. The execution control mechanism not only receives opening or speed commands but also transmits real-time feedback of the valve's actual position, the motor's real-time speed signal, and winding temperature health monitoring data back to the load dispatching terminal, forming a fully closed-loop precision execution system.

[0061] Furthermore, the intelligent control system for mine water waste heat recovery will activate a self-learning mode during its initial operation. In this mode, the energy value analysis center will activate its data lake storage function to record system response data under different production cycles, weather conditions, and inflow rates. Through regression analysis and feature extraction of this historical big data, the system will automatically correct the cost function parameters and energy efficiency response curve in the game theory bidding model. This adaptive evolutionary capability allows the system to maintain its optimal control trajectory regardless of changes in mine production, equipment aging, or increasing mining depth.

[0062] Furthermore, the production condition sensing device features automatic seasonal mode switching. The system has a built-in annual weather calendar and, combined with real-time temperature data from external weather stations, divides its operating logic into summer mode, transitional season mode, and winter mode. In summer mode, the system logic automatically prioritizes maximizing domestic hot water supply and coordinating with cold water circulation for machine room cooling; in winter mode, the system switches to a high-intensity heating mode, focusing on ensuring adequate freeze protection at the wellhead. The energy value analysis center automatically loads different asset valuation logics based on seasonal signals, ensuring optimal resource allocation at every moment of the year.

[0063] Example 2: Based on Example 1, this example provides a variant of the intelligent control system for mine water waste heat recovery based on an edge computing and cloud collaborative architecture. In this scheme, the production condition sensing device and the multi-source thermal monitoring device have edge computing capabilities, enabling them to perform rapid signal processing and feature extraction directly at the data source.

[0064] In this embodiment, the production condition sensing device is constructed as an edge computing gateway. This gateway is equipped with a dedicated tensor processing unit configured to perform high-frequency sampling and Fourier transform on the acquired air compressor current signal. By analyzing the frequency domain characteristics of the current signal at the edge, the system can more sensitively capture subtle changes in the air compressor load, converting complex waveform data into simplified condition status codes for transmission to the upper layer. This edge-side preprocessing mechanism reduces the data transmission pressure on the mining area's industrial ring network and improves the system's response speed to sudden load changes.

[0065] In this embodiment, the energy value analysis center employs a distributed computing architecture. The core discrete state transition probability model runs on a highly available server cluster deployed in the central computer room of the mining area, responsible for long-term historical pattern analysis and strategic-level energy asset modeling.

[0066] The lightweight linear minimum variance state estimation model runs in the local control box of each energy exchange station, responsible for real-time tracking of the local heat source status. This cloud-edge collaborative architecture ensures that when the backbone network experiences a short-term communication interruption, each energy exchange station can still operate autonomously based on its local prediction model, maintaining the continuity of heating.

[0067] In this embodiment, the dynamic load scheduling terminal incorporates a reinforcement learning optimization engine. This engine is configured to continuously optimize the action selection logic in the game-theoretic bidding strategy by learning from tens of thousands of simulated running paths. By using the total operating cost of the system as a negative feedback signal and the energy efficiency ratio as a reward function, the reinforcement learning algorithm can gradually discover the nonlinear scheduling patterns hidden under complex operating conditions. For example, in a combined scenario of extreme cold weather and a sudden large influx of water in a mine, the scheduling terminal can select a more efficient heat storage and release path than traditional logic.

[0068] In this embodiment, the multi-media heat exchange actuator is enhanced with a module for monitoring refrigerant flow parameters within the heat pump unit. This module includes an electronic expansion valve opening feedback unit, a suction pressure transmitter, and a discharge pressure transmitter.

[0069] The actuator is configured to match the heat exchange load of the evaporator in real time by adjusting the opening of the electronic expansion valve, preventing liquid refrigerant from entering the compressor and causing liquid slugging. At the same time, it also improves the operating life of the heat pump in low-grade mine water environment by adjusting the superheat.

[0070] In this embodiment, the flexible thermal energy storage system employs a multi-tank series-parallel switching architecture. The system comprises multiple physically independent thermal storage tanks connected by a set of automated switching valves. Based on the predicted thermal storage demand from the Energy Value Analysis Center, the system can dynamically change the tank configuration. Under low-load thermal storage demand, only a single tank is activated to reduce heat loss; under high-load demand, multiple tanks are connected in parallel to expand storage capacity.

[0071] Meanwhile, the system is also equipped with a real-time thermal storage quality assessment unit, which monitors the water temperature gradient distribution in different tanks, optimizes the inlet and outlet water switching logic, and ensures the stability of the output thermal energy.

[0072] The intelligent control system for mine water waste heat recovery in this embodiment also integrates an augmented reality (AR)-based operation and maintenance assistance module. This module synchronizes with the production condition sensing device and multi-source thermal monitoring device via data links, overlaying real-time operating parameters onto the physical image of the equipment. When an alarm is triggered by the execution control mechanism, the system automatically pushes the logic diagram of the faulty part and maintenance instructions to the mobile device of the operation and maintenance personnel, shortening troubleshooting time through visualization.

[0073] The energy asset model in this embodiment enhances the responsiveness to power frequency regulation ancillary services. When the power grid to which the mining area belongs issues a frequency regulation signal, the dynamic load dispatching terminal translates the real-time power adjustment demand into action instructions for the thermal energy storage system. By briefly changing the power input of the heat pump unit and utilizing the buffering effect of the thermal storage tank to maintain stable heating, the system can participate in ancillary services in the electricity market, further improving the system's economic benefits.

[0074] Example 3: For large mining groups with complex geographical environments and multiple dispersed ventilation shafts and inclined shafts, this example provides an intelligent control system for mine water waste heat recovery with a distributed cluster control architecture.

[0075] In this embodiment, the intelligent control system for mine water waste heat recovery includes a group-level energy brain and multiple site-level control nodes. Each site-level control node contains a complete production condition sensing device, a multi-source thermal monitoring device, and a multi-media heat exchange actuator, forming an autonomous energy acquisition and conversion unit. The energy value analysis center and dynamic load scheduling terminal adopt a hierarchical design, divided into two layers: site-level real-time scheduling and group-level strategic optimization.

[0076] The site-level control node is logically granted greater autonomy. Its internal linear minimum variance state estimation model is configured to respond to local heat source fluctuations at extremely high frequencies (e.g., milliseconds). For example, when the exhaust air temperature of a ventilation shaft experiences a momentary drop due to fan speed regulation, the site-level node can immediately adjust the local heat exchange tower makeup water volume without waiting for instructions from the upper-level energy control system.

[0077] The group-level energy brain, with its integrated energy value analysis center, is configured to perform overall collaborative modeling of energy output from all sites across the entire mining area. By analyzing the complementary nature of waste heat from ventilation shafts and water wells in different geographical locations at different times, the energy brain can formulate cross-site energy transmission instructions. For example, when there is excess waste heat from the exhaust wind at the south wing ventilation shaft while the heat storage tanks in the north wing living area are not yet full, the system will instruct the cross-regional circulation network to be activated, achieving optimized energy distribution in geographical space.

[0078] In this embodiment, the dynamic load scheduling terminal employs a multi-agent negotiation game algorithm. Each site-level node is considered a player with independent economic interests, and they submit supply or demand prices to the group-level energy brain based on their local energy surplus, heat demand, and storage status. By facilitating energy transactions among the sites, the group-level brain achieves the most efficient flow of waste heat resources across the entire group, reducing the group's overall fossil energy procurement expenditure.

[0079] In this embodiment, the multi-media heat exchange actuator employs an anti-interference enhanced bus design. Due to the large physical distance between stations within the mining area, there are strong ground potential differences and electromagnetic interference. The communication interfaces of the actuators are equipped with digital isolators and surge protectors, and redundant ring industrial Ethernet is used for data transmission. If a section of fiber optic cable in the ring network is damaged, data can automatically find its way back to the other side, ensuring the real-time performance and reliability of the distributed system control in the large mining area.

[0080] In this embodiment, the flexible thermal energy storage system incorporates a phase change thermal storage module. In addition to traditional large-scale water-based thermal storage tanks, the system incorporates small thermal storage units based on phase change materials at key heating terminals. These units utilize low-cost electricity and excess waste heat for latent heat storage at night, and release heat through phase change during peak daytime heating periods to provide constant-temperature hot water. This storage scheme, combining sensible and latent heat, enhances the system's energy density in space-constrained areas and strengthens its ability to cope with extreme cold and peak loads.

[0081] In this embodiment, the production condition sensing device also integrates a mine environmental monitoring sensor. This mine environmental sensor array is used to monitor the concentration of corrosive gases and dust in the environment that may affect equipment lifespan. The Energy Value Analysis Center incorporates these environmental parameters into the asset valuation model as correction factors for equipment depreciation costs. For example, in areas with high dust concentrations, the system automatically increases the virtual depreciation price of heat exchange actuators, guiding the dispatch terminal to reduce the operating frequency of equipment in that area when unnecessary, thereby extending the overall system lifespan.

[0082] Through the above-mentioned multi-level, distributed, and intelligent architecture design, the system in this embodiment can support the energy management needs of ultra-large-scale mining areas and realize full-process and full-element digital control from a single collection point to the entire mining area.

[0083] Example 4: Based on the above examples, this example focuses on describing the implementation details of an intelligent control system for mine water waste heat recovery that integrates high-precision energy efficiency diagnosis and digital twin prediction functions.

[0084] In this embodiment, the energy value analysis center integrates a full-parameter digital twin engine. Based on thermodynamic laws, fluid dynamics equations, and electromechanical coupling characteristics, this engine constructs a virtual digital mapping model of the entire waste heat recovery system in the mining area. The digital twin engine not only displays the current operating status in real time, but more importantly, it can utilize the optimal initial state values ​​output by the linear minimum variance state estimation model to rapidly simulate the system's operation for the next 24 hours in virtual space. By simulating different combinations of control strategies, the engine can assess the potential energy efficiency risks and economic gains / losses of each strategy in the future.

[0085] The production condition sensing device, in terms of hardware configuration, adds vibration monitoring and lubrication status sensing for key moving parts of the actuators. This unstructured data undergoes feature extraction using a deep learning model at the edge and is transformed into quantitative indicators reflecting equipment health scores. The energy value analysis center uses these health scores as a risk premium coefficient when constructing the energy asset model. If the compressor vibration amplitude of a heat pump unit exceeds the warning benchmark, the priority of that heat pump in the game bidding will automatically decrease, enabling preventative maintenance through scheduling to avoid heating interruptions caused by unplanned shutdowns.

[0086] In this embodiment, the multi-source thermal monitoring device employs soft sensing technology. For extreme high-temperature or high-pressure areas where sensors cannot be directly installed, the multi-source thermal monitoring device calculates the physical parameters of these blind spots using existing ambient temperature and pressure data, combined with built-in energy balance observer logic. This virtual sensing capability expands the system's insight into energy flow, making the energy asset model more refined.

[0087] In this embodiment, the dynamic load dispatching terminal incorporates asymmetric information game logic. The system comprehensively considers the uncertainty of future weather forecasts and the probability of production plan adjustments. When a high-probability cold air intrusion is predicted, the dispatching terminal proactively increases the purchase price of the thermal storage system, inducing the actuators to enter the thermal storage state ahead of schedule. This dispatching logic with prior predictive capabilities enhances the system's robustness in energy supply under conditions of severe weather fluctuations.

[0088] In this embodiment, the multi-media heat exchange actuator employs active disturbance rejection control (ADRC). When dealing with significant disturbances in mine water flow, the actuator's controller can estimate the total external disturbance in real time using an internal extended state observer and generate corresponding compensation components to offset it. This allows the actuator's outlet temperature to quickly recover to the target setpoint within a short time after the disturbance occurs, improving control accuracy compared to traditional PID logic.

[0089] The flexible thermal energy storage system also includes a low-temperature recirculation module. This module features a two-stage heat exchange coil at the bottom of the storage tank, specifically designed to recover the low-grade heat remaining in the mine water after the first-stage heat exchange. Through this secondary heat stripping and collection, the system further widens the temperature gradient within the storage tank, increasing the energy density of a single storage volume and achieving optimal extraction of waste heat resources.

[0090] This embodiment of the system also provides an open API interface layer, allowing safety production monitoring systems in the mining area (such as gas monitoring systems and disaster prevention systems) to connect. When a safety emergency occurs in the mine, this interface can receive the highest priority forced load reduction command, and the mine water waste heat system will immediately enter a low-power maintenance mode to prioritize the load safety of the mine's main power supply system, fully demonstrating the system's collaborative safety in the mine's production environment.

[0091] The system in this embodiment not only automates the control process but also assetizes the decision-making process and visualizes risks. Through deep coupling of digital twins and game theory algorithms, the system can consistently find the optimal energy consumption balance point through precise value game theory in complex and ever-changing mine production environments.

[0092] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention. Any variations, combinations, and functional extensions based on the technical features of the present invention without departing from the concept of the present invention are within the protection scope of this patent.

[0093] In the above embodiments, all logical operations, parameter comparisons, and mathematical relationships involved in the generation of control strategies have been described in detail using textual descriptions. The instructions and data structures stored internally in each module, device, and terminal of the system are configured to implement the functions described above. In actual operation, the system does not rely on specific formulas but achieves efficient, economical, and stable management of mine waste heat resources by executing preset logical steps and data interaction processes.

Claims

1. An intelligent control system for mine water waste heat recovery, characterized in that, include: The production status sensing device is used to collect real-time operating status data of various production systems inside the mine. The operating status data includes the number of air compressor units in operation and the instantaneous load power, the instantaneous water inflow and water level change rate of the mine drainage system, the flue gas emission flow of the gas power generation system, and the air volume parameters of the exhaust air emission system. The multi-source thermal monitoring device is used to acquire physical parameters of various heat sources in the mine in an all-round way. The parameters it monitors include the real-time temperature, fluid pressure and flow rate of each heat source medium, and converts the physical parameters into digital thermal energy abundance signals. The Energy Value Analysis Center, connected to the production condition sensing device and the multi-source thermal monitoring device, is used to quantitatively predict the heat production cost and expected energy efficiency ratio of each heat source in a predetermined time period through the built-in discrete state transition probability model and linear minimum variance state estimation model, and generate an energy asset model containing virtual value weights. The energy value analysis center includes a high-performance industrial computing platform, and the linear minimum variance state estimation model is configured to perform real-time noise reduction processing on the raw physical signals from the production condition sensing device and the multi-source thermal monitoring device. The linear minimum variance state estimation model constructs a state-space model that reflects the continuity of the physical system, and uses the estimated state value of the heat source at the previous moment and the observed value at the current moment to calculate the optimal state trajectory with minimum variance. During operation, the linear minimum variance state estimation model dynamically adjusts the Kalman gain coefficient based on the noise level fluctuations of the sensor observations. When the observation noise increases, it automatically reduces the weight component of the observation, thereby achieving trend tracking of the continuous heat supply capacity. The Energy Value Analysis Center classifies the operating status of the air compressor using the discrete state transition probability model. Based on the shift schedule of the mine production shifts and the historical load fluctuation pattern, it calculates the probability distribution of the state transitioning to different load levels at the current moment and adjusts the supply reliability weight of the heat source in the energy asset model accordingly. The energy asset model also introduces an environmental premium factor, which is logically calculated based on the real-time monitored carbon emission reduction equivalent. Higher bidding weight coefficients are assigned to heat source extraction paths with greenhouse gas emission reduction effects. The dynamic load dispatch terminal adopts a game-theoretic bidding mechanism, treating each available heat source as a trading entity participating in the bidding. It compares the real-time price of each heat source with the expected energy efficiency ratio, and prioritizes the use of heat source combinations that are in a price trough and have a high energy efficiency ratio. When it is predicted that the time-of-use electricity price will enter a preset high-price period in the next few hours, the dynamic load dispatch terminal reduces the output weight of the electric-driven heat pump unit, and the thermal energy flexible storage system enters the energy release mode. The energy value analysis center is equipped with a self-learning mode and a digital twin engine; The self-learning mode records the operating condition fluctuations and energy consumption data within a predetermined period through the data lake storage function, and automatically corrects the energy efficiency response function of each heat source under different production loads through regression analysis. The digital twin engine constructs a virtual digital mapping model of the waste heat recovery system in the mining area based on the laws of thermodynamics and electromechanical coupling characteristics. It uses the optimal initial state value output by the linear minimum variance state estimation model to simulate the system operation state for a predetermined number of hours in the future in the virtual space, and evaluates the energy efficiency risk and economic gains and losses under different control strategy combinations. The production condition sensing device also has an automatic seasonal mode switching function. Based on the annual meteorological calendar and real-time meteorological data, the operating logic is divided into summer mode, transition season mode and winter mode, and the corresponding energy asset assessment weights are automatically loaded. The dynamic load dispatching terminal is used to construct a multi-objective dynamic optimization combination scheme based on the energy asset model, and to formulate energy allocation instructions by sorting the real-time acquisition costs of each heat source. A multi-media heat exchange actuator is used to receive the energy distribution command and, by adjusting the opening of the flow regulating valve of each heat exchange branch, the operating frequency of the heat pump unit, and the speed of the circulating pump, realize the on-demand extraction and conversion of heat sources of different grades. Flexible thermal energy storage systems are used to store or release heat based on forecasts of electricity price fluctuations and the supply-demand gap in thermal energy.

2. The intelligent control system for mine water waste heat recovery according to claim 1, characterized in that, The energy value analysis center is also equipped with cost-efficiency evaluation logic, which comprehensively calculates the electricity consumption required to extract a unit of heat, the equipment depreciation cost caused by the regular maintenance of the heat exchanger, and the water resource and chemical cost generated by the operation of the circulating water pump, and generates an instantaneous price logic variable that fluctuates dynamically with the mine's production load.

3. The intelligent control system for mine water waste heat recovery according to claim 2, characterized in that, The production condition sensing device includes a data acquisition and control cabinet, a high-precision current transformer, an industrial-grade flow meter, and a bus communication adapter. The data acquisition control cabinet integrates a field-programmable logic array for digital filtering and preprocessing of analog signals transmitted back from the front-end sensors. The production condition sensing device monitors the three-phase current fluctuations and active power parameters of each air compressor motor through the high-precision current transformer, and identifies whether the air compressor is in an unloaded, light-load or full-load operating state. The production condition sensing device also establishes a communication connection with the automated control cabinet of the mine's main drainage system to obtain the derivative relationship of the water level in the water tank changing with time to determine the rate of water level change, and calculates the potential increase in mine water supply within a predetermined time window by combining the opening frequency of the drainage pump. The production condition sensing device also includes a flow orifice plate deployed on the flue gas duct of the gas power plant and a thermal anemometer deployed at the exhaust gas outlet, for real-time acquisition of the mass flow rate of the heat source medium.

4. The intelligent control system for mine water waste heat recovery according to claim 3, characterized in that, The multi-source thermal monitoring device is equipped with armored platinum resistance temperature sensors, pressure transmitters and ultrasonic flow meters on the extraction branches of each heat source. For mine water media that are corrosive or prone to scaling, the multi-source thermal monitoring device uses non-contact measurement components to acquire physical signals; The processing unit inside the multi-source thermal monitoring device synchronously processes the collected real-time temperature signal, fluid pressure signal, and mass flow rate signal, and calculates the heat flux per unit time based on the specific heat capacity coefficient of different media. For monitoring exhaust air heat, the multi-source thermal monitoring device also integrates a humidity sensing component to obtain the moisture content of the exhaust air. Combined with the dry-bulb temperature signal, the device calculates the total enthalpy of the exhaust air based on the enthalpy logic of the humid air and converts the obtained physical quantity into a digital thermal energy abundance signal. The digital thermal energy abundance signal is used to characterize the energy density and thermal quality of the heat source at different times.

5. The intelligent control system for mine water waste heat recovery according to claim 1, characterized in that, The multi-media heat exchange actuator includes a mine water plate heat exchanger group, a waste air spray heat exchange tower, an air compressor waste heat recovery device, and a gas flue gas waste heat boiler. Each branch is equipped with a variable frequency drive circulating water pump and an electric regulating valve; The multi-media heat exchange actuator is equipped with an internal disturbance rejection control unit, which estimates and compensates for the impact of flow disturbance on the outlet temperature in real time through an expanded state observer, so that the secondary side return water temperature after heat exchange converges to the preset process temperature. For heat pump units, the multi-media heat exchange actuator adopts multi-cascade control logic. Based on the total load demand calculated by the dynamic load scheduling terminal, it automatically adjusts the position of the compressor slide valve or the output frequency of the frequency converter, and adjusts the speed of the circulating pump in conjunction to change the heat exchange temperature difference, so as to ensure that the heat pump unit operates within the preset optimal range of the energy efficiency curve under different heat source inlet water temperatures. The multi-media heat exchange actuator is also equipped with automatic backwashing logic, which automatically performs flushing operations based on changes in the pressure drop at the inlet and outlet of the heat exchanger.

6. The intelligent control system for mine water waste heat recovery according to claim 5, characterized in that, The flexible thermal energy storage system includes a large thermal storage tank with high thermal insulation performance and an inlet and outlet water temperature compensation logic unit. The heat storage tank is equipped with a layered barrier structure, which slows down the mixing speed of hot and cold water in the tank through physical guide plates, and maintains the water temperature gradient between the hot water zone and the cold water zone. The inlet and outlet water temperature compensation logic unit uses a mixing and temperature regulating valve in the inlet water pipeline to initially mix waste heat fluids from different sources, so that they are injected into the tank at a constant temperature. When the energy value analysis center predicts that there will be a surplus of waste heat in the future or that there will be a period of low electricity price, the flexible thermal energy storage system controls cold water to enter the bottom of the thermal storage tank and uses waste heat resources to raise the water temperature to the preset thermal storage temperature in advance. When entering peak energy consumption or peak electricity price periods, the flexible thermal energy storage system replenishes the heating network with high-temperature medium through the top water outlet device, and is equipped with a low-temperature return water cascade utilization module, which recovers the residual low-grade heat of the system by setting a two-stage heat exchange coil at the bottom of the thermal storage tank.

7. The intelligent control system for mine water waste heat recovery according to claim 6, characterized in that, It also includes a remote redundant control module and fault self-diagnosis logic; The fault self-diagnosis logic stores the device characteristic fingerprint under normal operating conditions, including the current spectrum distribution of the motor and the pressure-flow correlation curve of the water pump. When abnormal fluctuations in the current characteristics of the equipment are detected, deviating from the preset normal distribution range, the production condition sensing device sends a fault load reduction signal to the energy value analysis center, which then reconstructs the game bidding model and lowers the priority of calling the heat source associated with the faulty equipment. The remote redundancy control module, as a physically independent hardware redundancy unit, monitors the heartbeat signal of the dynamic load scheduling terminal through a data link. When the dynamic load scheduling terminal experiences a logical response stagnation, the remote redundant control module automatically takes over the bus control authority and switches to a preset emergency operation scheme based on safety priority to ensure the minimum heating temperature requirement for wellhead antifreeze load.

8. The intelligent control system for mine water waste heat recovery according to claim 1, characterized in that, The system adopts a distributed cluster control architecture, including site-level control nodes and a group-level energy brain; The production condition sensing device is constructed as a gateway with edge computing capabilities, equipped with a tensor processing unit, which is used to perform high-frequency sampling and Fourier transform on the collected current signal, and to analyze the frequency domain characteristics of the current signal at the edge and convert it into a condition status code. The site-level control nodes are distributed in various energy exchange stations in the mining area and are responsible for real-time tracking and rapid response to the local heat source status; The group-level energy brain analyzes the complementarity of waste heat at different geographical locations, formulates cross-site energy transmission instructions, and adopts a multi-agent negotiation game algorithm to treat each site-level control node as an independent game subject. By matching the energy supply price and demand price of each site, it realizes the allocation of waste heat resources throughout the entire mining area. The communication interface of the multi-media heat exchange actuator is equipped with a digital isolator and a surge protector, and uses redundant ring industrial Ethernet for data transmission.

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