Mine energy fusion light storage direct-flexible integrated energy system and control method

Abstract

The invention discloses a mine energy fusion light storage direct flexible comprehensive energy system and a control method, and relates to the technical field of mine energy. The energy integration module comprises a distributed photovoltaic assembly, an energy storage assembly, a mine card charging station assembly and a load assembly, and is connected through a direct-current power distribution bus and is matched with the controller to realize multi-energy complementation; the intelligent collaborative management module establishes a photovoltaic power generation potential evaluation model, a production load prediction model and other models based on meteorological sensing equipment and historical data, and optimizes energy storage charging and discharging, mine card energy charging planning and commercial power scheduling strategies. Through the economical efficiency target optimization control strategy, the problem of power generation, energy storage and power utilization link separation in a mine energy system is solved, the adjustability and economical efficiency of the system are improved, carbon emission is reduced, and the method is suitable for a mine comprehensive energy management scene.

Description

Technical Field

[0001] This invention belongs to the field of integrated energy technology, and specifically relates to an integrated energy system and control method that combines mining and energy, photovoltaic storage, direct current and flexible energy. Background Technology

[0002] In the mining sector, the efficiency, cleanliness, and intelligence of energy systems are crucial to production efficiency and environmental impact. However, traditional mining energy systems have long faced a structural contradiction of high energy consumption, high pollution, and low efficiency. Mining production processes (such as crushing, screening, and transportation) mainly rely on fossil fuels, with dust pollution and carbon emissions from fuel-powered mining trucks being particularly prominent. Simultaneously, the electricity supply for office and living buildings is highly dependent on municipal power, resulting in a persistently high overall carbon footprint for mines. Although hilly or mountainous areas or idle locations where mines are situated often possess abundant solar energy resources (e.g., Ding'an County in Hainan Province has an annual total solar radiation of 5560.7 MJ / m²), traditional technologies have significant limitations in developing and utilizing renewable energy, failing to achieve a deep integration of "mining scenarios + new energy."

[0003] Traditional mining energy systems rely primarily on grid electricity and fuel oil. The carbon emissions from grid power generation and the exhaust emissions from fuel-powered mining trucks make mines high-carbon emission environments within the industrial sector. Furthermore, traditional mining energy systems suffer from the following technical deficiencies: First, their energy structure is too singular, overly dependent on grid electricity and fuel oil. The lack of widespread adoption of electric mining trucks leads to severe pollution during transportation, and buildings lack renewable energy alternatives for power supply. Second, renewable energy absorption is insufficient. Distributed photovoltaic and other renewable energy sources are intermittent, and without energy storage, fluctuations cannot be mitigated. Moreover, they are mismatched with the two-shift load of mines (9:00-12:00, 14:00-18:00, and 23:00-7:00). Third, energy efficiency and losses are significant. Traditional AC power distribution systems have multiple conversion stages (e.g., photovoltaic systems require DC / AC two-stage conversion), resulting in line losses three times that of DC systems and lower building energy efficiency. Fourth, management is fragmented and inefficient, lacking a unified energy management platform, making it impossible to optimize using peak-valley electricity pricing, and leading to uneven equipment load rates. To address the aforementioned issues, there is an urgent need for a comprehensive energy solution that can achieve green energy substitution, increase the absorption rate of new energy sources, reduce energy efficiency losses, and realize intelligent management. Specifically, the following technical challenges need to be solved: The first question is how to replace traditional grid power and fuel oil with distributed photovoltaic (≥3.5MWp) and energy storage (0.6MW / 1.2MWh) integration to reduce carbon emissions from mines; Secondly, how to improve the self-consumption rate of photovoltaic power generation and mitigate grid fluctuations through the "photovoltaic-storage-DC-flexible" system (including BIPV and DC power distribution) and the energy storage peak-valley arbitrage strategy (one charge and one discharge per day); Thirdly, how to reduce conversion losses and improve energy efficiency in office settings through DC power distribution in buildings (such as cadmium telluride BIPV with 60% light transmittance) and DC-based equipment upgrades; Fourth, how to design an integrated photovoltaic and energy storage charging station to match the energy replenishment needs of electric mining trucks and achieve zero-carbon upgrades in the transportation process; Fifth, how to use an integrated energy management platform to monitor and optimize the scheduling of "source-grid-load-storage" equipment in real time and solve the problems of energy efficiency loss and high cost under the traditional management model. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a comprehensive energy system and control method that integrates mining and energy, photovoltaic storage, direct current and flexible energy, so as to solve the technical problems existing in traditional mining energy systems and improve the system's adjustability and economy.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: A comprehensive energy system integrating mining, energy storage, direct current, and flexible energy sources includes an energy integration module and an intelligent collaborative management module, wherein the energy integration module and the intelligent collaborative management module are connected through a communication component. The intelligent collaborative management module receives and stores data generated by the energy integration module, analyzes and generates optimized control strategies, and sends control commands to the energy integration module. The intelligent collaborative management module acquires meteorological parameters from the mining area through meteorological sensing equipment. These parameters provide data support for units including production load forecasting, photovoltaic power generation potential assessment, energy storage charging and discharging optimization, mining truck charging planning, and municipal power auxiliary dispatching. The intelligent collaborative management module then achieves coordinated system control through these units. Preferably, the energy integration module includes a controller, a mine automation control unit, distributed photovoltaic modules, a DC power distribution bus, an energy storage module, a mining truck charging station module, and a load module. The distributed photovoltaic modules, energy storage modules, mining truck charging station modules, and load modules are located on branches of the DC power distribution bus and are connected to the controller via communication modules. The mine automation control unit is connected to the load modules via control.

[0006] Preferably, the distributed photovoltaic module includes several photovoltaic arrays, and a first circuit breaker is provided between the several photovoltaic arrays and the DC distribution bus. The first circuit breaker is connected to the controller. Each of the several photovoltaic arrays includes a photovoltaic panel, a second DC-DC converter, and a first current sensor. The photovoltaic panel is connected to the DC distribution bus through the second DC-DC converter. The second DC-DC converter is connected to the controller through a communication component. The first current sensor is configured in conjunction with the second DC-DC converter and is connected to the controller through the communication component.

[0007] Preferably, the energy storage component includes an energy storage battery pack, a bidirectional DC-DC converter, and a second current sensor. The energy storage battery pack is connected to the DC distribution bus via the bidirectional DC-DC converter. The bidirectional DC-DC converter is connected to the controller via a communication component. A second circuit breaker is provided between the bidirectional DC-DC converter and the DC distribution bus and is connected to the controller. The second current sensor is provided in conjunction with the bidirectional DC-DC converter and is connected to the controller via the communication component.

[0008] Preferably, the mining truck charging station assembly includes a mining truck charging pile, a third circuit breaker, and a third current sensor. The mining truck charging pile is directly connected to the DC power distribution bus. The mining truck charging pile and the DC power distribution bus are equipped with a third circuit breaker and connected to the controller. The third current sensor is configured in conjunction with the input circuit of the mining truck charging pile and connected to the controller through a communication component.

[0009] Preferably, the load assembly includes several mining production equipment and office and living equipment of different power levels. Each piece of equipment is connected to the DC power distribution bus through a DC-DC converter. The DC-DC converter is connected to the controller through a communication component. A fourth circuit breaker is provided between the DC-DC converter and the DC power distribution bus and is connected to the controller. The current sensor is provided in conjunction with the DC-DC converter and is connected to the controller through the communication component.

[0010] Preferably, the DC power distribution bus is equipped with a voltage monitoring device and connected to the controller via a communication component.

[0011] Preferably, the intelligent collaborative management module is connected to the mining energy integration system and acquires meteorological parameters of the mining area through meteorological sensing equipment. The intelligent collaborative management module includes a production load prediction unit, a photovoltaic power generation potential assessment unit, an energy storage charging and discharging optimization unit, a mining truck charging planning unit, and a mains power auxiliary dispatching unit. Preferably, the production load forecasting unit works in conjunction with the mining area production plan and the data collected by the meteorological sensing equipment; the photovoltaic power generation potential assessment unit works in conjunction with the distributed photovoltaic modules and the meteorological sensing equipment; the energy storage charging and discharging optimization unit works in conjunction with the energy storage modules; the mining truck charging planning unit works in conjunction with the mining truck charging station modules; and the mains power auxiliary dispatching unit works in conjunction with the mains power access point.

[0012] A control method for an integrated energy system combining mining, energy storage, and direct current / flexible energy transmission includes the following steps: Step 1: Collect basic data such as mining area production plans, energy system configuration, and electricity pricing policies; Step 2: Initialize the operating status of the production equipment using the mine automation control system; Step 3: Based on the relationship between the mine's production plan and the data collected by the meteorological sensing equipment, determine the range of mine production load demand and the potential for photovoltaic power generation; Step 4: Based on the solar radiation data collected by the meteorological sensing equipment and combined with the historical operation data of the mining area, establish a photovoltaic power generation potential assessment model to predict the solar radiation value received by the photovoltaic panels and the photovoltaic power generation. Step 5: Establish a production load prediction model based on historical operating data of the mining area and meteorological parameters collected by meteorological sensing equipment, for the prediction of mine production load; Step 6: Establish an energy storage charging and discharging optimization model, a mining truck charging planning model, and a grid-assisted dispatching model through logical rules. These models are used to optimize the charging and discharging behavior of the energy storage battery pack, plan the charging power of the electric mining truck, and control the power drawn from or sent to the grid. Step 7: Establish the energy balance model, economically optimal objective function, and constraints of the mining-energy integration system; Step 8: Using a 24-hour natural day as the cycle, solve the joint task of the energy balance model and each module sub-model through logical deduction to obtain the time series of control parameters with the best system economy; Step 9: Monitor the DC distribution bus voltage and compare it with the set range; Step 10: If the DC distribution bus voltage is within the set range, apply the current value in the system control parameter time series to the system control; if the DC distribution bus voltage is not within the set range, the energy storage power is switched to non-communication control based on the DC distribution bus voltage as the signal: when the DC distribution bus voltage is lower than the set range, the energy storage discharges; when the DC distribution bus voltage is higher than the set range, the energy storage charges. Step 11: Feed back the current system's energy storage state of charge, energy storage unit input or output, mining area production equipment energy consumption, mains power input or output power, photovoltaic power generation power, etc., into the model, and repeat steps 8 to 11 to recalculate the control parameters for a given time point until the end of the day.

[0013] The present invention can achieve the following beneficial effects: 1. By building a multi-energy complementary and intelligent collaborative optimization platform on the basis of traditional mining energy systems, the platform receives and stores data generated by lower-level subsystems, analyzes and generates optimized control strategies, and issues control commands to lower-level subsystems, thereby solving the problem of the separation of power generation, energy storage and power consumption in mining energy systems. 2. Based on historical operating data of the mining area, fully assess the load characteristics and photovoltaic power generation potential of the mining production equipment, establish a model based on historical data, and formulate a coordinated control strategy that considers energy storage charging and discharging optimization and mining truck charging planning with economic efficiency as the goal. In the control of mining production equipment, the characteristics of different equipment should be considered. 3. Taking into account the time-of-use electricity price difference and demand-side response benefits, and with economic efficiency as the goal, the control strategy of the mining-energy integration system is optimized, resulting in good economic performance. Attached Figure Description

[0014] The present invention will be further described below with reference to the accompanying drawings and embodiments: Figure 1 This is a structural system diagram of the integrated photovoltaic-storage-direct-drive-flexible energy system of this mine. Figure 2 This is a schematic diagram of the control method for the integrated photovoltaic-storage-direct-drive flexible energy system of this mine. Figure 3 A prediction curve for a photovoltaic power generation potential assessment model; Figure 4 A load demand curve for a mine production load forecasting model; Figure 5 A graph showing the change in charging and discharging power for an optimized energy storage charging and discharging model; Figure 6 A graph showing the total charging power distribution of the mining truck charging planning model; Figure 7 The signal response curve of the DC power distribution bus voltage monitoring and control logic; Figure 8 The time series curves show the optimization results of the objective function for the best system economy. Detailed Implementation

[0015] Preferred solutions include Figures 1 to 8 As shown, a mining-energy integrated photovoltaic-storage-direct-current-flexible energy system and control method are disclosed, including an energy integration module and an intelligent collaborative management module. The energy integration module and the intelligent collaborative management module are connected in cooperation. The intelligent collaborative management module receives data generated by the energy integration module, stores data, analyzes it, generates optimized control strategies, and issues control commands to the energy integration module to solve the problem of the separation of power generation, energy storage, and power consumption in the mining energy system. Furthermore, the energy integration module includes a controller, a mine automation control unit, distributed photovoltaic modules, a DC power distribution bus, an energy storage module, a mining truck charging station module, and a load module. The distributed photovoltaic modules, energy storage modules, mining truck charging station modules, and load modules are located on branches of the DC power distribution bus and are connected to the controller via a communication module. The mine automation control unit is connected to the load module via a control connection.

[0016] Furthermore, the distributed photovoltaic module includes several photovoltaic arrays. A first circuit breaker is provided between the photovoltaic arrays and the DC distribution bus. The first circuit breaker is connected to a controller, which can control the first circuit breaker to disconnect to protect the circuit. Each of the photovoltaic arrays includes a photovoltaic panel, a second DC-DC converter, and a first current sensor. The photovoltaic panel is connected to the DC distribution bus through the second DC-DC converter to realize the output of photovoltaic DC power to the DC bus. The second DC-DC converter is connected to the controller through a communication component, and the controller can control the operation of the second DC-DC converter. The first current sensor is set up in conjunction with the second DC-DC converter and connected to the controller through the communication component to automatically detect the current value of the output after conversion and transmit it to the controller.

[0017] Furthermore, the energy storage component includes an energy storage battery pack, a bidirectional DC-DC converter, and a second current sensor. The energy storage battery pack is connected to the DC distribution bus via the bidirectional DC-DC converter, which enables the charging and discharging of the energy storage battery pack. The bidirectional DC-DC converter is connected to a controller via a communication component, and the controller can control the operation of the bidirectional DC-DC converter. A second circuit breaker is provided between the bidirectional DC-DC converter and the DC distribution bus and is connected to the controller. The controller can control the second circuit breaker to disconnect to protect the circuit. The second current sensor is provided in conjunction with the bidirectional DC-DC converter and is connected to the controller via the communication component. It is used to automatically detect the current value output after conversion and transmit it to the controller.

[0018] Furthermore, the mining truck charging station component includes a mining truck charging pile, a third circuit breaker, and a third current sensor. The mining truck charging pile is directly connected to the DC power distribution bus, and the current in the DC power distribution bus is input to the mining truck charging pile. The mining truck charging pile and the DC power distribution bus are equipped with a third circuit breaker and connected to a controller. The controller can control the third circuit breaker to disconnect to protect the circuit. The third current sensor is configured in conjunction with the input circuit of the mining truck charging pile and is connected to the controller through a communication component to automatically detect the input current value and transmit it to the controller. Furthermore, the load components include several mining production equipment and office and living equipment of different power levels. Each piece of equipment is connected to the DC power distribution bus through a DC-DC converter to realize the current output of the DC power distribution bus. The DC-DC converter is connected to the controller through a communication component. The controller can control the operation of the DC-DC converter. A fourth circuit breaker is provided between the DC-DC converter and the DC power distribution bus and is connected to the controller. The controller can control the fourth circuit breaker to disconnect to protect the circuit. The current sensor is provided in conjunction with the DC-DC converter and is connected to the controller through the communication component. It is used to automatically detect the current value of the output and input after conversion and transmit it to the controller. Furthermore, the DC power distribution bus is equipped with a voltage monitoring device and connected to the controller via a communication component, for automatically detecting the DC power distribution bus voltage and transmitting it to the controller.

[0019] Furthermore, the intelligent collaborative management module is connected to the mining energy integration system and acquires meteorological parameters of the mining area through meteorological sensing equipment. The intelligent collaborative management module includes a production load prediction unit, a photovoltaic power generation potential assessment unit, an energy storage charging and discharging optimization unit, a mining card charging planning unit, and a mains power auxiliary dispatching unit. The production load forecasting unit works in conjunction with the mine production plan and data collected by meteorological sensing equipment to forecast the production load demand of the mine under a two-shift system. The photovoltaic power generation potential assessment unit works in conjunction with distributed photovoltaic modules and meteorological sensing equipment to assess the solar radiation received by the photovoltaic panels. The energy storage charging and discharging optimization unit works in conjunction with energy storage modules to optimize the charging and discharging behavior of the energy storage battery pack. The mining truck charging planning unit works in conjunction with mining truck charging station components to plan the total charging power of electric mining trucks during the demand-side response period. The mains power auxiliary dispatching unit works in conjunction with the mains power access point to control the power drawn from or sent to the mains power grid.

[0020] A control method for an integrated energy system combining mining, energy storage, and direct current / flexible energy transmission, the control method comprising the following steps: Step 1: Collect basic data such as mining area production plans, energy system configuration, and electricity pricing policies. For example: the mining area production plan data is taken from the mining area production management platform, including a daily ore mining volume of 4,000 tons, a crushing volume of 200 tons / hour, 15 daily transport trips by mining trucks, and a one-way distance of 5 kilometers; there are 2 crushers, with start-stop periods of 9:00-12:00 and 14:00-18:00, and 10 electric mining trucks, operating in rotation from 10:00 to 19:00; the production load fluctuation range for the same season over the past 12 months is ±8%.

[0021] The energy system configuration data is taken from the design drawings and equipment ledger, including a total capacity of 3.5MWp for distributed photovoltaic modules, with a single photovoltaic panel area of ​​1.6m² and a conversion efficiency of 23%; a capacity of 1.2MWh for the energy storage battery pack and a rated charge / discharge power of 0.6MW; a crusher with a rated power of 150kW and a DC voltage of 750V; and 10 office air conditioners, each with a power of 5kW and a DC voltage of 750V.

[0022] Electricity pricing policy data is obtained from the local power grid company, including peak electricity price of 1.2 yuan / kWh, peak hours are 9:00-12:00 and 17:00-21:00; flat electricity price of 0.7 yuan / kWh, flat hours are 8:00-9:00, 12:00-17:00 and 21:00-22:00; off-peak electricity price of 0.3 yuan / kWh, off-peak hours are 22:00-8:00 the next day; during peak hours 19:00-21:00, a subsidy of 0.5 yuan / kWh can be obtained for reducing grid power consumption, and the surplus electricity price is 0.45 yuan / kWh.

[0023] Meteorological data were taken from the mining area meteorological station, including the daily solar radiation intensity for the same season over the past 5 years, recorded hourly, for example, an average of 1000W / m² at 10:00 and an average of 1100W / m² at 14:00; the average daily temperature was 28℃ and the average wind speed was 2.5m / s.

[0024] Step 2: Initialize the operating status of production equipment using the mine automation control system. For example, through the mine automation control system, the crusher is set to automatically start at 9:00 and automatically stop at 12:00, with an upper limit of 150kW and a lower limit of 50kW to avoid no-load operation; the electric mining truck is set to prioritize photovoltaic power supply when charging, and automatically cut off power after charging to 90% SOC; the office air conditioner is set to automatically turn on during working hours from 8:00 to 18:00, with the temperature set at 26℃ and the total power not exceeding 50kW; at the same time, overload protection thresholds are set for the equipment, such as automatically reducing the load when the crusher current exceeds 1.2 times the rated current.

[0025] Step 3: Based on the relationship between the mine's production plan and the data collected by meteorological sensing equipment, determine the mine's production load demand range and photovoltaic power generation potential. For example: The daily mining output is 4000 tons, which is considered full-load production. The weather sensing equipment recorded a temperature of 30℃, with no extreme weather and no production fluctuations. Based on this, the crusher's base load is determined to be 150kW, with a ±5% margin, resulting in a load range of 142.5-157.5kW; the mining truck charging base load is 900kW (60kW charging power per truck for 10 trucks), with a ±10% margin, resulting in a load range of 810-990kW; the office equipment base load is 50kW, with a ±3% margin, resulting in a load range of 48.5-51.5kW; the total system production load demand range is 1001-1200kW.

[0026] The meteorological sensing equipment collected real-time data showing that the solar radiation intensity at 10:00 AM was 1050 W / m². Based on the photovoltaic module parameters, the photovoltaic power generation potential at 10:00 AM was determined to be 3.6-3.7 MW. At 2:00 PM, the solar radiation intensity was even higher, and the photovoltaic power generation potential was 3.8-3.9 MW, which is the peak radiation period of the day.

[0027] Step 4: Based on the solar radiation data collected by meteorological sensing equipment and combined with historical operating data of the mining area, establish a photovoltaic power generation potential assessment model to predict the solar radiation received by the photovoltaic panels and the photovoltaic power generation. For example, meteorological sensing equipment collects hourly solar radiation data from 6:00 to 18:00 on a given day, with values ​​of 200 W / m² at 6:00, 600 W / m² at 8:00, and 1080 W / m² at 12:00. Combined with historical operating data from the mining area over the past five years for the same season, the average radiation at 6:00 is 180 W / m², and at 8:00 it is 580 W / m². Based on this data, a photovoltaic power generation potential assessment model is established. The model predicts that at 9:00, the solar radiation received by the photovoltaic panels will be 850 W / m², corresponding to a photovoltaic power generation of approximately 2.9 MW, calculated as the total area of ​​the photovoltaic panels (15217 m²) multiplied by 850 W / m² and then multiplied by a conversion efficiency of 23%. At 16:00, the solar radiation received by the photovoltaic panels will be 700 W / m², corresponding to a photovoltaic power generation of approximately 2.4 MW.

[0028] Step 5: Based on historical operational data of the mining area and meteorological parameters collected by meteorological sensing equipment, establish a production load prediction model for predicting mine production load. For example, historical operational data from the mining area over the past three months shows that when the mining volume is 4,000 tons, the average load of the crusher is 150kW and the average load of the mining truck charging is 880kW. Meteorological sensing equipment recorded a daily temperature of 32℃, 4℃ higher than the seasonal average, requiring additional load on the ventilation equipment. Based on this data, a production load prediction model was established. The model predicts that 14:00 on that day will be the high-temperature period, with the crusher maintaining its normal full load of 155kW. The ventilation equipment will require an additional 20kW load. The mining trucks will return for centralized charging in the afternoon, with a charging load of 920kW. The office air conditioning will also need to operate at full load due to the high temperature, with a load of 51kW. The total system production load is approximately 155 + 20 + 920 + 51 = 1146kW.

[0029] Step 6: Establish an energy storage charging and discharging optimization model, a mining truck charging planning model, and a grid-assisted dispatching model through logical rules. These models are used to optimize the charging and discharging behavior of the energy storage battery pack, plan the charging power of the electric mining truck, and control the power drawn from or supplied to the grid. For example, the energy storage charging and discharging optimization model is set to charge during off-peak hours, discharge during peak hours, and replenish energy during flat hours. Specifically, from 22:00 to 6:00 the next day, it is an off-peak period with an electricity price of 0.3 yuan / kWh, and the energy storage charges to 90% SOC with a power of 0.6MW; from 9:00 to 12:00, it is a peak period with an electricity price of 1.2 yuan / kWh, and the energy storage discharges to replenish the production load with a power of 0.4MW; from 13:00 to 16:00, it is a flat period with sufficient photovoltaic output. If the surplus photovoltaic power exceeds 0.2MW, the energy storage replenishes the power with a power of 0.2MW.

[0030] The charging planning model for mining cards is set with the following logic: prioritize charging when photovoltaic power is sufficient, reduce charging during peak periods, and supplement charging during off-peak periods. Specifically, from 10:00 to 15:00, when photovoltaic output is ≥3MW, the charging power of mining cards is maintained at 800-900kW for centralized charging; from 17:00 to 21:00, during peak periods, when grid electricity prices are high, the charging power of mining cards is reduced to 300-400kW to meet only emergency needs; from 22:00 to 24:00, during off-peak periods, the charging power of mining cards is 500kW to replenish the electricity required for the next day.

[0031] The grid-assisted dispatch model is designed to draw power from the grid when photovoltaic (PV) and energy storage outputs are insufficient, and to supply power to the grid when there is surplus output. Specifically, when the combined output of PV and energy storage is less than the production load, power is drawn from the grid; when the combined output of PV and energy storage exceeds the sum of the production load and the energy storage charging demand, the surplus power is supplied to the grid. For example, at 18:00, PV output is 1.2MW, energy storage discharge is 0.3MW, and the production load is 1.1MW. The combined output of PV and energy storage meets the production demand, so there is no need to draw power from the grid. At 12:00, PV output is 3.7MW, energy storage is not charging, and the production load is 1.1MW. PV output is surplus, and the surplus power of 2.6MW is supplied to the grid to generate revenue from grid connection.

[0032] Step 7: Establish the energy balance model, economically optimal objective function, and constraints of the integrated mining and energy system. For example, the core logic of the energy balance model is that energy supply equals energy consumption plus losses. Specifically, the relationship is: photovoltaic power generation plus energy storage charging / discharging power (discharging is positive, charging is negative) plus grid power input / output power (output is positive, output is negative), which equals the power of production equipment plus the power of office equipment plus system line losses (estimated at 2%). For example, at 10:00 AM, photovoltaic power is 3.6MW, energy storage discharge is 0.4MW, and grid power input is 0MW. The sum of production and office loads is 1.1MW, and system line losses are 0.022MW. At this time, the energy supply is 3.6 + 0.4 = 4MW, and the energy consumption plus losses is 1.1 + 0.022 = 1.122MW. The remaining 2.878MW of surplus power is fed back to the grid, satisfying the energy balance requirement.

[0033] The core objective of the economically optimal objective function is to minimize the total daily cost. The total daily cost is calculated by subtracting the revenue from surplus electricity sold to the grid from the cost of purchasing grid electricity, then subtracting demand-side subsidies, and adding equipment operation and maintenance costs. The target is set at a total daily cost ≤ 2000 yuan. For example, through model optimization, the estimated daily grid electricity purchase cost is 1200 yuan, surplus electricity revenue from the grid is 800 yuan, demand-side subsidies are 300 yuan, and equipment operation and maintenance costs are 500 yuan. The total daily cost is 1200 - 800 - 300 + 500 = 600 yuan, which satisfies the economically optimal objective.

[0034] The constraints include maintaining the energy storage SOC at 20%-90% to avoid overcharging and over-discharging, maintaining the DC power distribution bus voltage at 750-800V to ensure equipment safety, limiting the single power draw from the mains to ≤1MW to avoid impacting the power grid, and ensuring that the total daily charging capacity of the mining trucks is ≥5400kWh to meet the daily transportation needs of 10 mining trucks.

[0035] Step 8: Using a 24-hour natural day as the cycle, solve the joint task of the energy balance model and each module sub-model through logical deduction to obtain the time series of control parameters with optimal system economy. For example: Using 0:00-24:00 as the cycle, the control parameters for each hour are obtained by logically deducing and solving the joint task of the energy balance model and the sub-models of each module. For example, from 0:00 to 6:00, which is a valley period, the energy storage is charged at a power of 0.6MW, the SOC rises from 20% to 90%, and at the same time, 0.6MW of power is drawn from the grid. The production load is 0, and there is no surplus power. The control parameters for this period are: energy storage charging 0.6MW, grid power drawing 0.6MW, and mining truck charging 0kW.

[0036] From 9:00 to 10:00, the peak period is as follows: photovoltaic power 3.6MW, energy storage discharge 0.4MW, production load 1.1MW, and surplus power 2.9MW is fed into the grid. The control parameters for this period are: energy storage discharge 0.4MW, grid power supply 2.9MW, and mining truck charging 850kW.

[0037] From 19:00 to 20:00, during the peak period, the photovoltaic power is 1.0MW, the energy storage discharge is 0.3MW, and the production load is 1.0MW. No power is needed from the grid, and the demand-side energy conservation requirements are met, qualifying for a subsidy of 30 yuan. The control parameters for this period are: energy storage discharge 0.3MW, grid power 0, and mining truck charging 350kW. Through the above calculations, the hourly control parameters for 24 hours are obtained, forming the time series of control parameters with optimal system economy.

[0038] Step 9: Monitor the DC distribution bus voltage and compare it with the set range. For example: The normal range of DC power distribution bus voltage is set to 750-800V, and the voltage value is collected in real time by a bus voltage monitoring device. For example, if the voltage is monitored at 10:00 and is 775V, which is within the normal range of 750-800V, the bus voltage is determined to be normal.

[0039] At 14:00, the photovoltaic output suddenly increased from 3.6MW to 3.9MW, and the bus voltage also increased accordingly. The monitored voltage was 805V, which exceeded the upper limit of the normal range, and the bus voltage was determined to be abnormal.

[0040] At 23:00, the energy storage charging power suddenly increased from 0.3MW to 0.6MW, and the bus voltage dropped accordingly. The monitored voltage was 745V, which was lower than the lower limit of the normal range, and the bus voltage was determined to be abnormal.

[0041] Step 10: If the DC distribution bus voltage is within the set range, apply the current value in the system control parameter time series to the system control; if the DC distribution bus voltage is not within the set range, the energy storage power is controlled without communication using the DC distribution bus voltage as the signal: when the DC distribution bus voltage is lower than the set range, the energy storage discharges; when the DC distribution bus voltage is higher than the set range, the energy storage charges. For example, when the bus voltage is within the normal range, such as 775V monitored at 10:00, the current control parameters obtained in step 8 are directly applied, namely, energy storage discharge 0.4MW, mining truck charging 850kW, and mains power supply 2.9MW, and the system operates according to these parameters.

[0042] When the bus voltage is higher than the normal range, for example, if the monitored voltage is 805V at 14:00, the no-communication control is triggered, and the energy storage operation state is changed from discharging 0.4MW to charging 0.2MW to absorb excess energy. After 30 seconds, the bus voltage is monitored again and dropped to the normal range of 790V, and the original control parameters are restored.

[0043] When the bus voltage is lower than the normal range, for example, if the monitored voltage is 745V at 23:00, the no-communication control is triggered, and the energy storage operation status is changed from charging 0.6MW to discharging 0.2MW to replenish the power. After 20 seconds, the bus voltage is monitored again and rises to the normal range of 760V, and the original control parameters are restored.

[0044] Step 11: Feed back the current system's energy storage state of charge, energy storage unit input or output, mine production equipment energy consumption, mains power input or output power, photovoltaic power generation, and other statuses into the model. Repeat steps 8 to 11 to recalculate the control parameters for a given time period until the end of the day. For example, at 10:30 a.m. on the same day, the current system status data is fed back to the model, including energy storage SOC 65%, current energy storage discharge 0.4MW, production equipment energy consumption 1.12MW (slightly higher than the predicted 1.1MW), grid power output 2.85MW (slightly lower than the predicted 2.9MW), and photovoltaic power generation 3.55MW (slightly lower than the predicted 3.6MW).

[0045] Based on the actual feedback data, the logical deduction of step 8 was re-executed, and the control parameters at 11:00 were adjusted: the energy storage discharge power was increased from 0.4MW to 0.45MW to supplement the overspending of production load, the mains power output power was adjusted from 2.9MW to 2.8MW to match the actual output of photovoltaic power, and the charging power of the mining truck was kept at 850kW without any abnormalities.

[0046] The process of "status feedback - re-deduction - parameter adjustment" is repeated every 30 minutes thereafter to continuously optimize the control parameters until 24:00 on the same day, ensuring that the system operates stably with the most economical parameters throughout the day.

[0047] Example 1: As shown in the figure, the integrated energy system of mining, energy, photovoltaic, storage, direct current, and flexible power supply of this invention comprises two main parts: an energy integration module and an intelligent collaborative management module. The energy integration module consists of a controller, a mine automation control unit, distributed photovoltaic modules, a DC power distribution bus, energy storage modules, a mining truck charging station module, and load modules. The distributed photovoltaic modules, energy storage modules, mining truck charging station module, and load modules are all located on branches of the DC power distribution bus and are connected to the controller via a communication module to achieve data interaction. The mine automation control unit is directly connected to the load modules and is used for automated control of mining production equipment. In addition, the DC power distribution bus is equipped with a voltage monitoring device to detect the bus voltage in real time and transmit it to the controller.

[0048] In practical implementation, the distributed photovoltaic (PV) system consists of several PV arrays. Each PV array includes a PV panel, a second DC-DC converter, and a first current sensor. The PV panel is connected to the DC distribution bus via the second DC-DC converter, enabling the output of PV DC power to the DC bus. The second DC-DC converter is connected to the controller via a communication component. The controller can adjust the operation of the second DC-DC converter according to actual needs, thereby controlling the output power of the PV panel. Simultaneously, the first current sensor works in conjunction with the second DC-DC converter to automatically detect the output or input current value after conversion and transmit this data to the controller. To protect the circuit, a first circuit breaker is also installed between each PV array and the DC distribution bus. The first circuit breaker is also connected to the controller. When the controller detects an abnormality, it can quickly disconnect the first circuit breaker to protect the circuit.

[0049] The energy storage system includes a battery pack, a bidirectional DC-DC converter, and a second current sensor. The battery pack is connected to the DC power distribution bus via the bidirectional DC-DC converter to enable charging and discharging. The bidirectional DC-DC converter is connected to a controller via a communication component. The controller can adjust the operation of the bidirectional DC-DC converter according to system requirements, thereby controlling the charging and discharging behavior of the battery pack. The second current sensor works in conjunction with the bidirectional DC-DC converter to automatically detect the input or output current value of the energy storage system and transmit this data to the controller. Furthermore, a second circuit breaker is installed between the bidirectional DC-DC converter and the DC power distribution bus. This second circuit breaker is connected to the controller, and the controller can quickly disconnect the second circuit breaker to cut off the circuit in the event of a circuit malfunction.

[0050] The mining truck charging station components include a charging pile, a third circuit breaker, and a third current sensor. The charging pile is directly connected to the DC power distribution bus, and the current from the DC power distribution bus is input to the charging pile to charge the electric mining truck. A third circuit breaker is installed between the charging pile and the DC power distribution bus, and this third circuit breaker is connected to the controller. When the controller detects an abnormal charging situation, it can quickly disconnect the third circuit breaker to protect the circuit. The third current sensor is configured in conjunction with the input circuit of the charging pile to automatically detect the input current value and transmit this data to the controller.

[0051] The load components include several mining production equipment and office / living equipment of different power levels. Each piece of equipment is connected to the DC power distribution bus via a DC-DC converter to achieve current output from the DC power distribution bus. The DC-DC converter is connected to the controller via a communication component. The controller can adjust the operation of the DC-DC converter according to the equipment's needs, thereby controlling the equipment's power consumption. A fourth circuit breaker is installed between the DC-DC converter and the DC power distribution bus. This fourth circuit breaker is connected to the controller, and the controller can quickly disconnect the fourth circuit breaker to protect the circuit in case of equipment malfunction. In addition, each DC-DC converter is equipped with a current sensor to automatically detect the output or input current value after conversion and transmit this data to the controller.

[0052] The intelligent collaborative management module is connected to the mining energy integration system and acquires meteorological parameters of the mining area through meteorological sensing equipment. The intelligent collaborative management module includes a production load forecasting unit, a photovoltaic power generation potential assessment unit, an energy storage charging and discharging optimization unit, a mining truck charging planning unit, and a grid power auxiliary dispatching unit. The production load forecasting unit predicts the mine's two-shift production load demand based on the mine's production plan and data collected by the meteorological sensing equipment. The photovoltaic power generation potential assessment unit, combining solar radiation data collected by the meteorological sensing equipment and historical operating data of the mining area, establishes a photovoltaic power generation potential assessment model to predict the solar radiation received by the photovoltaic panels and the photovoltaic power generation. The energy storage charging and discharging optimization unit establishes an energy storage charging and discharging optimization model based on historical operating data of the mining area to optimize the charging and discharging behavior of the energy storage battery pack. The mining truck charging planning unit establishes a mining truck charging planning model based on historical operating data of the mining area to plan the total charging power of electric mining trucks during the demand-side response period. The grid power auxiliary dispatching unit works with the grid access point to control the power drawn from or supplied to the grid.

[0053] The control method of the present invention is as follows: Figure 2 As shown, the specific implementation steps are as follows: First, basic data such as the mine's production plan, energy system configuration, and electricity pricing policy are collected as input conditions; then, the mine's automated control system is used to initialize the operating status of the production equipment. Based on the relationship between the mine's production plan and the data collected by the meteorological sensing equipment, the mine's production load demand range and photovoltaic power generation potential are determined. Combining the solar radiation data collected by the meteorological sensing equipment and the mine's historical operating data, a photovoltaic power generation potential assessment model is established to predict the solar radiation received by the photovoltaic panels and the photovoltaic power generation. The photovoltaic power generation potential assessment model is expressed by the formula P_pv = A * G * η, where P_pv is the photovoltaic power generation, A is the photovoltaic panel area, G is the solar radiation intensity, and η is the photovoltaic panel conversion efficiency. Figure 3 As shown, the prediction curve of the photovoltaic power generation potential assessment model can accurately reflect the trend of photovoltaic power generation changes in different time periods.

[0054] Next, based on historical operational data of the mining area and meteorological parameters collected by meteorological sensing equipment, a production load prediction model is established for forecasting mine production load. The production load prediction model is expressed by the formula L_load = L_base + ΔL_temp + ΔL_weather, where L_load is the production load demand, L_base is the base load, ΔL_temp is the load fluctuation caused by temperature changes, and ΔL_weather is the load fluctuation caused by weather changes. Figure 4 As shown, the load demand curve of the production load forecasting model can accurately reflect the load characteristics of mining production equipment.

[0055] Furthermore, an energy storage charging and discharging optimization model, a mining truck charging planning model, and a mains power auxiliary dispatch model are established through logical rules. The energy storage charging and discharging optimization model is represented by the formula E_storage = E_initial + ∫(P_charge - P_discharge)dt, where E_storage is the remaining capacity of the energy storage battery pack, E_initial is the initial capacity, P_charge is the charging power, and P_discharge is the discharging power. Figure 5 As shown, the charging and discharging power variation curve of the energy storage charging and discharging optimization model can optimize the charging and discharging behavior of the energy storage battery pack. The mining truck charging planning model is represented by the formula P_charging =∑(P_vehicle_i * T_i), where P_charging is the total charging power of the mining truck, P_vehicle_i is the charging power of the i-th mining truck, and T_i is the charging time of the i-th mining truck. Figure 6 As shown, the total charging power distribution curve of the mining truck charging planning model can reasonably plan the charging power of electric mining trucks. The grid-assisted dispatch model is represented by the formula P_grid = P_demand - P_pv - P_storage, where P_grid is the power taken from or sent to the grid, P_demand is the total power demand of the system, P_pv is the photovoltaic power generation power, and P_storage is the output power of the energy storage battery pack.

[0056] Subsequently, an energy balance model, an economically optimal objective function, and constraints for the integrated mining and energy system were established. The energy balance model is expressed by the formula P_pv + P_storage + P_grid = P_load + P_loss, where P_pv is the photovoltaic power generation, P_storage is the output power of the energy storage battery pack, P_grid is the power drawn from or fed into the grid, P_load is the total system load power, and P_loss is the system power loss. The economically optimal objective function is expressed by the formula C_total = C_pv + C_storage + C_grid + C_penalty, where C_total is the total system cost, C_pv is the photovoltaic power generation cost, C_storage is the energy storage cost, C_grid is the grid power purchase cost, and C_penalty is the penalty cost for unmet load demand. Constraints include the energy storage state of charge (SOC_min) ≤ SOC ≤ SOC_max, and the DC distribution bus voltage (V_min) ≤ V_bus ≤ V_max.

[0057] Using a 24-hour natural day as the cycle, the energy balance model and the joint task of each module sub-model are solved through logical deduction to obtain the time series of control parameters with optimal system economy. For example... Figure 8 As shown, the time series curves of the optimization results of the objective function for optimal system economy can intuitively reflect the optimal control parameters for each time period. Simultaneously, the DC distribution bus voltage is monitored and compared with the set range. For example... Figure 7 As shown, when the DC distribution bus voltage is within the set range, the current value in the system control parameter time series is applied to the system control; when the DC distribution bus voltage is not within the set range, the energy storage power is switched to non-communication control using the DC distribution bus voltage as the signal: when the DC distribution bus voltage is lower than the set range, the energy storage discharges; when the DC distribution bus voltage is higher than the set range, the energy storage charges.

[0058] Finally, the current system's energy storage state of charge, energy storage unit input or output, mine production equipment energy consumption, mains power input or output power, and photovoltaic power generation are fed back into the model, and the above steps are repeated to recalculate the control parameters for a given moment until the end of the day. Through this method, the present invention achieves efficient operation optimization of the integrated energy system combining mining, energy, photovoltaic, energy storage, direct current, and flexible power generation, solving the problem of fragmented power generation, energy storage, and power consumption in traditional mine energy systems, and significantly improving the system's adjustability and economy.

[0059] The above embodiments are merely preferred technical solutions of the present invention and should not be considered as limitations on the present invention. The scope of protection of the present invention should be limited to the technical solutions described in the claims, including equivalent substitutions of the technical features described in the claims. That is, equivalent substitutions and improvements within this scope are also within the scope of protection of the present invention.

Claims

1. A comprehensive energy system integrating mineral energy, photovoltaic energy storage, direct current, and flexible energy, characterized in that: It includes an energy integration module and an intelligent collaborative management module, wherein the energy integration module and the intelligent collaborative management module are connected through a communication component; The intelligent collaborative management module receives and stores data generated by the energy integration module, analyzes and generates optimized control strategies, and sends control commands to the energy integration module. The intelligent collaborative management module acquires meteorological parameters of the mining area through meteorological sensing equipment. These meteorological parameters provide data support for units including production load forecasting, photovoltaic power generation potential assessment, energy storage charging and discharging optimization, mining truck charging planning, and municipal power auxiliary dispatch. The intelligent collaborative management module achieves system collaborative control through these units.

2. The integrated energy system combining mining and energy, photovoltaic storage, direct current, and flexible energy sources according to claim 1, characterized in that, The energy integration module includes a controller, a mine automation control unit, distributed photovoltaic modules, a DC power distribution bus, an energy storage module, a mining truck charging station module, and a load module. The distributed photovoltaic modules, energy storage modules, mining truck charging station modules, and load modules are located on branches of the DC power distribution bus and are connected to the controller via communication modules. The mine automation control unit is connected to the load modules via control.

3. The integrated energy system combining mining and energy, photovoltaic storage, direct current, and flexible energy sources according to claim 2, characterized in that, The distributed photovoltaic module includes several photovoltaic arrays. A first circuit breaker is provided between the photovoltaic arrays and the DC distribution bus. The first circuit breaker is connected to the controller. Each of the photovoltaic arrays includes a photovoltaic panel, a second DC-DC converter, and a first current sensor. The photovoltaic panel is connected to the DC distribution bus through the second DC-DC converter. The second DC-DC converter is connected to the controller through a communication component. The first current sensor is configured in conjunction with the second DC-DC converter and is connected to the controller through the communication component.

4. The integrated energy system combining mining and energy, photovoltaic storage, direct current, and flexible energy according to claim 2, characterized in that, The energy storage component includes an energy storage battery pack, a bidirectional DC-DC converter, and a second current sensor. The energy storage battery pack is connected to the DC distribution bus via the bidirectional DC-DC converter. The bidirectional DC-DC converter is connected to the controller via a communication component. A second circuit breaker is provided between the bidirectional DC-DC converter and the DC distribution bus and is connected to the controller. The second current sensor is provided in conjunction with the bidirectional DC-DC converter and is connected to the controller via the communication component.

5. The integrated energy system combining mining and energy, photovoltaic storage, direct current, and flexible energy sources according to claim 2, characterized in that, The mining truck charging station component includes a mining truck charging pile, a third circuit breaker, and a third current sensor. The mining truck charging pile is directly connected to the DC power distribution bus. The third circuit breaker is provided between the mining truck charging pile and the DC power distribution bus and is connected to the controller. The third current sensor is set in conjunction with the input circuit of the mining truck charging pile and is connected to the controller through a communication component.

6. The integrated energy system combining mining and energy, photovoltaic storage, direct current, and flexible energy according to claim 2, characterized in that, The load components include several mining production equipment and office and living equipment of different power levels. Each piece of equipment is connected to the DC power distribution bus through a DC-DC converter. The DC-DC converter is connected to the controller through a communication component. A fourth circuit breaker is provided between the DC-DC converter and the DC power distribution bus and is connected to the controller. The current sensor is provided in conjunction with the DC-DC converter and is connected to the controller through the communication component.

7. The integrated energy system combining mining and energy, photovoltaic storage, direct current, and flexible energy according to claim 2, characterized in that, The DC power distribution bus is equipped with a voltage monitoring device and is connected to the controller via a communication component.

8. The integrated energy system combining mining and energy, photovoltaic storage, direct current, and flexible energy sources according to claim 1, characterized in that, The intelligent collaborative management module is connected to the mining energy integration system and acquires meteorological parameters of the mining area through meteorological sensing equipment. The intelligent collaborative management module includes a production load prediction unit, a photovoltaic power generation potential assessment unit, an energy storage charging and discharging optimization unit, a mining card charging planning unit, and a mains power auxiliary dispatching unit.

9. The integrated energy system combining mining and energy, photovoltaic storage, direct current, and flexible energy sources according to claim 8, characterized in that, The production load forecasting unit works in conjunction with the mining area production plan and the data collected by the meteorological sensing equipment. The photovoltaic power generation potential assessment unit works in conjunction with the distributed photovoltaic modules and the meteorological sensing equipment. The energy storage charging and discharging optimization unit works in conjunction with the energy storage modules. The mining truck charging planning unit works in conjunction with the mining truck charging station modules. The mains power auxiliary dispatching unit works in conjunction with the mains power access point.

10. A control method for a solar-energy-storage integrated energy system combining mining and energy, according to any one of claims 1-9, characterized in that... Includes the following steps: Step 1: Collect basic data including mining area production plans, energy system configuration, and electricity pricing policies; Step 2: Initialize the operating status of the production equipment using the mine automation control system; Step 3: Based on the relationship between the mine's production plan and the data collected by the meteorological sensing equipment, determine the range of mine production load demand and the potential for photovoltaic power generation; Step 4: Based on the solar radiation data collected by the meteorological sensing equipment and combined with the historical operation data of the mining area, establish a photovoltaic power generation potential assessment model to predict the solar radiation value received by the photovoltaic panels and the photovoltaic power generation. Step 5: Establish a production load prediction model based on historical operating data of the mining area and meteorological parameters collected by meteorological sensing equipment, for the prediction of mine production load; Step 6: Establish an energy storage charging and discharging optimization model, a mining truck charging planning model, and a grid-assisted dispatching model through logical rules. These models are used to optimize the charging and discharging behavior of the energy storage battery pack, plan the charging power of the electric mining truck, and control the power drawn from or sent to the grid. Step 7: Establish the energy balance model, economically optimal objective function, and constraints of the mining-energy integration system; Step 8: Using a 24-hour natural day as the cycle, solve the joint task of the energy balance model and each module sub-model through logical deduction to obtain the time series of control parameters with the best system economy; Step 9: Monitor the DC distribution bus voltage and compare it with the set range; Step 10: If the DC distribution bus voltage is within the set range, apply the current value in the system control parameter time series to the system control; if the DC distribution bus voltage is not within the set range, the energy storage power is switched to non-communication control based on the DC distribution bus voltage as the signal: when the DC distribution bus voltage is lower than the set range, the energy storage discharges; when the DC distribution bus voltage is higher than the set range, the energy storage charges. Step 11: Feed back the current energy storage state of charge, energy storage unit input or output, mining production equipment energy consumption, mains power input or output power, and photovoltaic power generation power into the model, and repeat steps 8 to 11 to recalculate the control parameters for a given time point until the end of the day.

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