Digital twin tunnel light storage flat urgent power supply control method

Abstract

This invention relates to the field of power supply in highway tunnels, specifically a digital twin method for controlling the power supply of photovoltaic-storage systems in both normal and emergency situations. It includes: constructing a digital twin model of the tunnel power system and synchronizing the real-time operating status of the AC system, DC system, wireless charging system, and energy storage units; executing a control mode algorithm based on the digital twin model, including a normal operating mode and an emergency power supply mode; in the normal operating mode, optimizing the scheduling of the AC, DC systems, and energy storage with the goals of maximizing operational economy, power supply reliability, and renewable energy absorption; in the emergency mode, monitoring the grid status in real time and immediately switching to the emergency mode upon interruption, prioritizing energy storage and photovoltaic power supply for critical loads. This invention achieves state perception and optimized control through digital twins, improving photovoltaic absorption and economic efficiency during normal operation and extending the power supply time for critical loads in emergencies, making it suitable for intelligent power supply scenarios in highway tunnels.

Description

Technical Field

[0001] This invention relates to the field of power supply in highway tunnels, specifically a digital twin tunnel optical energy storage emergency power supply control method. Background Technology

[0002] As highway tunnel operation and management evolves towards digitalization and intelligence, an increasing number of electronic and electrical devices are being deployed within tunnels, including various sensors, video surveillance equipment, lighting fixtures, ventilation equipment, and drones and Bluetooth-enabled inspection vehicles used for safety inspections. These devices have diverse power requirements, placing higher demands on the power supply system, such as the need to simultaneously support AC power, DC power, and wireless charging. However, existing highway tunnel power distribution systems typically employ a traditional AC grid power supply model, drawing 380V AC voltage from the substation's low-voltage switchgear to the tunnel's distribution box, and then supplying power to various devices via an AC busbar. This single AC power supply architecture struggles to directly meet the power demands of DC devices (such as LED lights and illuminance detection equipment) and mobile inspection equipment (requiring wireless charging), often necessitating the additional configuration of multiple power conversion devices, resulting in a complex system structure and redundant wiring.

[0003] In traditional power supply and distribution schemes, tunnel lighting systems primarily rely on AC power, which is transmitted through cables into the tunnel to drive the AC lighting fixtures. This approach suffers from energy conversion efficiency issues. For example, LED lights are inherently DC loads and require rectification and conversion in an AC power supply system, resulting in energy loss. Furthermore, traditional lighting systems are inadequate in terms of light uniformity and brightness adjustment, making it difficult to meet the refined lighting needs of different sections such as the tunnel entrance, transition, basic, and exit sections. In addition, tunnel lighting is functionally divided into enhanced lighting, basic lighting, and emergency lighting. Traditional schemes typically require multiple busbar power supply circuits for separate control, increasing the complexity of the power distribution system and construction costs.

[0004] To ensure the normal operation of tunnels, existing highway tunnels are typically equipped with dedicated UPS power supplies to provide emergency power support for critical systems such as emergency lighting, monitoring, and fire protection. However, UPS power supplies have limited capacity and power supply duration, and still rely on the power grid for charging. If the external power supply is interrupted for an extended period, it is difficult to ensure continuous power supply to important loads. Meanwhile, with the increasing demand for tunnel safety monitoring, mobile devices such as inspection drones and Bluetooth inspection vehicles are gradually being used. These devices generally require wireless charging for power replenishment, but existing highway tunnel AC / DC microgrids do not integrate wireless charging functionality, creating a power supply bottleneck for the widespread application of intelligent inspection equipment.

[0005] In terms of new energy utilization, traditional tunnel power supply and distribution systems generally lack DC buses and DC distribution networks. If a photovoltaic (PV) power generation system is connected as a supplementary power source, the DC power generated by the PV must first be inverted into AC power before entering the AC bus, and then rectified back into DC power to supply DC loads or energy storage batteries. This multiple "DC-AC-DC" conversion process not only increases energy loss but also reduces the utilization efficiency of PV power generation, thus limiting the application of clean energy in highway tunnels. Furthermore, due to the lack of coordination with energy storage systems, the volatility and intermittency of PV power generation further exacerbate the dependence on the traditional power grid, resulting in high operating costs.

[0006] In summary, existing power supply and distribution technologies for highway tunnels suffer from problems such as a single power source, difficulty in efficiently meeting the diverse power demands, strong dependence on traditional power resources, and low utilization rate of new energy sources. In particular, in emergency power supply scenarios, there is a lack of coordinated scheduling capabilities for energy storage and new energy sources, making it difficult to ensure long-term safe power supply for critical loads such as lighting, ventilation, and monitoring when external power is interrupted. Summary of the Invention

[0007] To address the above issues, this invention proposes a control method for the normal and emergency power supply modes of a digital twin tunnel multifunctional power source incorporating new energy sources and energy storage. Based on a digital twin power controller, the operating status of the AC system, DC system, wireless charging system, and energy storage unit is synchronized in real time. In normal mode, the AC / DC system and energy storage charging and discharging are optimized and scheduled, prioritizing the consumption of photovoltaic power generation. In emergency mode, when the grid fails, the system automatically switches to energy storage and photovoltaic power to supply power to critical loads such as emergency lighting and monitoring.

[0008] To achieve the above objectives, the present invention specifically adopts the following solution: A method for controlling the power supply during normal and emergency use of a digital twin tunnel optical energy storage system includes the following steps: A digital twin model of the tunnel power system is constructed, which synchronizes the operating status and electrical parameters of the AC system, DC system, wireless charging system and energy storage unit in the physical system in real time. Based on the digital twin model, a control mode algorithm is executed by the digital twin power controller, which includes a normal operation mode and an emergency power supply mode. Under the normal operating mode, the AC system, DC system and energy storage unit are optimized and scheduled with the comprehensive goals of maximizing system operating economy, power supply reliability and new energy consumption. In the emergency power supply mode, the connection status between the AC system and the public power grid is monitored in real time. When an external AC power interruption is detected, the system immediately switches to the emergency power supply mode, prioritizing the use of energy storage units and new energy power generation systems to supply power to preset important loads.

[0009] Furthermore, the optimized scheduling of the normal operating mode is based on the following objective function:

[0010] Where T is the scheduling period; The electricity price during time period t; The power exchanged with the grid during time period t (purchased power is positive); This is the energy storage unit loss cost coefficient; The change in the output of the energy storage unit during time period t; The incentive coefficient for new energy consumption; The distributed renewable energy power consumed during time period t.

[0011] Furthermore, in the emergency power supply mode, the digital twin power controller evaluates the remaining energy storage capacity, the real-time power generation capacity of new energy sources, and the load demand in real time based on the digital twin model, and dynamically adjusts the power supply strategy to extend the power supply duration of important loads.

[0012] Furthermore, in emergency power supply mode, the system automatically cuts off non-essential loads and prioritizes the use of energy storage units and photovoltaic power generation systems in the DC system to supply power to at least one important load in the emergency lighting, ventilation equipment, and monitoring and communication systems.

[0013] Furthermore, during emergency power supply, the system continuously monitors the status of the external power grid. When it detects that the public AC power grid has been restored, the digital twin power controller automatically or after safety verification, smoothly switches the control system from emergency power supply mode back to normal operation mode and initiates the recovery charging process of the energy storage system.

[0014] Furthermore, the normal operation mode also includes: performing multi-time-scale optimization calculations based on short-term load forecasts, new energy power generation forecasts, and grid dispatch instructions, generating dispatch instructions and issuing them to the physical system for execution, and making rolling corrections based on actual feedback and forecast deviations during the execution process.

[0015] Furthermore, the wireless charging system wirelessly charges the inspection equipment inside the tunnel according to the scheduling instructions of the digital twin power controller.

[0016] Furthermore, the DC system is connected to the photovoltaic power generation system, and the photovoltaic power generated can be directly used for DC loads or stored in energy storage units without the need for AC-DC conversion.

[0017] Correspondingly, the present invention also provides a multifunctional power system for a digital twin tunnel that includes new energy sources and energy storage, comprising: An AC system, wherein the AC system is electrically connected to a public AC power grid; A DC system, which is electrically connected to both a photovoltaic power generation system and an energy storage unit; A wireless charging system, wherein the wireless charging system is electrically connected to the DC system; A digital twin power controller, which is communicatively connected to the AC system, the DC system and the wireless charging system respectively.

[0018] Furthermore, the AC system includes an AC bus, to which AC loads are electrically connected; the AC loads include at least one of a fan, a water pump, fire-fighting equipment, monitoring equipment, and entrance / exit lighting equipment.

[0019] Furthermore, the DC system includes a DC bus, on which a photovoltaic power generation system, the energy storage unit, and a DC load are electrically connected respectively; the DC load includes at least one of LED DC lamps, an emergency lighting system, an illuminance detection device, a sensor, and a vehicle.

[0020] Furthermore, the photovoltaic power generation system and the DC load are electrically connected to the DC bus via a DC / DC converter; the energy storage unit is electrically connected to the DC bus via a bidirectional DC / DC converter.

[0021] Furthermore, the AC system and the DC system are electrically connected via a bidirectional AC / DC converter.

[0022] Furthermore, the DC system and the wireless charging system are electrically connected via a DC / DC converter, which is used to convert the voltage of the DC bus to the voltage level required by the wireless charging system.

[0023] Furthermore, the wireless charging system includes a wireless charging DC bus and a high-frequency inverter module, and the wireless charging system is used to charge the inspection equipment or connect to an AC load after conversion.

[0024] Furthermore, the wireless charging DC bus is connected to a DC / AC high-frequency inverter converter, which converts DC power into high-frequency AC power and inputs it to the inspection equipment or AC load equipment through the transmitting coil.

[0025] Furthermore, an AC / DC converter and a DC / DC converter are sequentially connected between the DC / AC high-frequency inverter and the inspection equipment, and an AC / DC converter and a DC / AC converter are sequentially connected between the DC / AC high-frequency inverter and the AC load equipment.

[0026] Furthermore, the digital twin power controller is wirelessly connected to AC load devices, photovoltaic power generation systems, energy storage units, DC load devices, and various converters via electrical signals.

[0027] Compared with the prior art, the present invention has the following beneficial technical effects: In normal operation mode, this invention optimizes the scheduling of AC systems, DC systems, and energy storage units with the comprehensive objectives of system operation economy, power supply reliability, and maximizing renewable energy consumption. Based on short-term load forecasting, renewable energy generation forecasting, and grid dispatch instructions, it performs multi-timescale optimization calculations and rolling corrections, effectively reducing the electricity costs of tunnel operation, decreasing dependence on the public grid, and maximizing the self-consumption ratio of clean energy such as photovoltaics. In emergency power supply mode, this invention monitors the connection status of the AC system and the public grid in real time. Upon detecting an external power outage, it immediately switches to emergency power supply mode, prioritizing energy storage units and photovoltaic power generation systems to power critical loads such as emergency lighting, ventilation equipment, and monitoring and communication systems. Compared to the limitations of traditional UPS power supplies with limited capacity and short power supply time, this solution uses a digital twin model to assess the remaining energy storage capacity, photovoltaic power generation capacity, and load demand in real time, dynamically adjusting the power supply strategy to extend the emergency power supply duration for critical loads and improve tunnel operational safety.

[0028] By directly connecting the photovoltaic power generation system to the DC system, the generated energy can be directly used for DC loads or stored in energy storage units without AC-DC conversion. This avoids the energy losses caused by multiple "DC-AC-DC" conversions in traditional solutions, improves the utilization efficiency of photovoltaic power generation, and also reduces the complexity and failure rate of system equipment. A wireless charging system is installed, and wireless charging is provided for inspection drones and inspection vehicles in the tunnel according to the scheduling instructions of the digital twin power controller. This solves the problem that traditional tunnel power supply systems cannot provide energy replenishment for mobile inspection equipment, ensuring the continuous and stable operation of the inspection equipment.

[0029] The AC / DC bus is interconnected through a bidirectional AC / DC converter between the AC and DC systems. Within the DC system, flexible access to photovoltaic, energy storage, and DC loads is achieved through DC / DC converters and bidirectional DC / DC converters. This hybrid AC / DC grid architecture not only meets the needs of various types of electrical equipment within the tunnel but also enables coordinated operation of photovoltaic, energy storage, and loads, improving the overall energy efficiency and power supply flexibility of the system. Attached Figure Description

[0030] Figure 1 A schematic diagram of an existing highway tunnel microgrid; Figure 2 This is an AC / DC power grid system architecture according to a specific embodiment of the present invention; Figure 3 This is a schematic diagram of the AC / DC power grid system according to a specific embodiment of the present invention. Detailed Implementation

[0031] Figure 1This is a schematic diagram of an existing microgrid in a highway tunnel. As shown, the existing tunnel power supply and distribution system typically adopts a traditional AC power grid supply mode, drawing 380V AC voltage from the low-voltage switchgear of the substation to the distribution box inside the tunnel, and then supplying power to various equipment through the AC bus. This single AC power supply architecture is difficult to directly meet the power needs of DC equipment (such as LED lights and illuminance detection equipment) and mobile inspection equipment (which requires wireless charging), often requiring the additional configuration of multiple power conversion devices, resulting in a complex system structure and redundant wiring.

[0032] Please see Figure 2 The multifunctional power supply system for highway tunnels proposed in this invention includes an AC system A, a DC system B, a wireless charging system C, and a digital twin power controller D. AC system A is electrically connected to the public AC power grid to meet the power supply needs of existing AC equipment within the tunnel. It can also dynamically draw green electricity from the grid and transmit signals regarding the tunnel's power consumption status to relevant management departments. DC system B is electrically connected to both a photovoltaic power generation system and an energy storage unit to meet the power needs of DC equipment. The energy storage unit is also installed to better absorb the clean energy generated by the photovoltaic system, eliminating the energy loss associated with the back-and-forth inversion of the photovoltaic power generation system. Wireless charging system C is electrically connected to DC system B to wirelessly charge inspection equipment such as inspection drones and Bluetooth vehicles installed within the tunnel. The digital twin power controller D is communicatively connected to AC system A, DC system B, and wireless charging system C, serving as the control and coordination unit of the system and constructing a virtual mapping model based on the physical power system.

[0033] Please see Figure 3 After adopting the highway tunnel power supply with multiple power supply modes of the present invention, the highway tunnel microgrid takes AC bus and DC bus as the core backbone. AC loads are connected to the AC bus, and photovoltaic power generation system, energy storage unit, DC load and wireless charging system are connected to the DC bus.

[0034] The AC bus is electrically connected to the public AC power grid, and AC loads, including fans, pumps, fire-fighting equipment, monitoring equipment, and entrance / exit lighting, are connected to it. The DC bus is electrically connected to a photovoltaic (PV) power generation system, energy storage units, and DC loads, including LED DC lamps, emergency lighting systems, illuminance detection equipment, and sensors. The PV system and DC loads are electrically connected to the DC bus via DC / DC converters, and the energy storage units are electrically connected to the DC bus via bidirectional DC / DC converters. The AC and DC buses are electrically connected via bidirectional AC / DC converters, creating a unified microgrid structure. A wireless charging system C is also connected to the DC bus. DC system B is electrically connected to wireless charging system C via a DC / DC converter, which converts the DC bus voltage to the voltage level required by the wireless charging system.

[0035] The wireless charging system C includes a wireless charging DC bus and a high-frequency inverter module. The wireless charging DC bus is electrically connected to the DC system B via a DC / DC converter to receive DC power after voltage conversion. The wireless charging DC bus is connected to a DC / AC high-frequency inverter to convert the DC power into high-frequency AC power, which is then used to wirelessly charge the inspection equipment via a transmitting coil. Specifically, an AC / DC converter and a DC / DC converter are sequentially connected between the DC / AC high-frequency inverter and the inspection equipment (such as an inspection drone or robot) to rectify and regulate the received high-frequency AC power before supplying power to the inspection equipment. Simultaneously, the wireless charging DC bus is also connected to another DC / AC inverter to convert the DC power into industrial frequency AC power to supply AC loads, meeting the power needs of some AC equipment within the tunnel.

[0036] The digital twin power controller D is connected to AC load devices, photovoltaic power generation systems, energy storage units, DC load devices, and various converters via a communication network. This controller collects and monitors real-time operating data from the AC bus, DC bus, bidirectional AC / DC converter, photovoltaic input, energy storage units, and various electrical devices. It incorporates a digital twin model of the tunnel power system, enabling dynamic simulation and prediction of microgrid conditions and achieving optimized energy dispatch decisions. Through a human-machine interface, maintenance personnel can intuitively grasp the overall system situation and perform remote control and strategy settings.

[0037] In actual operation, the digital twin power controller D first constructs a digital twin model of the tunnel power system. This model synchronizes in real time the operating status and electrical parameters of the AC system A, DC system B, wireless charging system C, and energy storage unit in the physical system. Based on this digital twin model, the controller executes a control mode algorithm, which includes normal operation mode D1 and emergency power supply mode D2.

[0038] Under normal operating mode D1, the public AC power grid supplies power normally. Based on real-time model data, short-term load forecasts, renewable energy generation forecasts, and grid dispatch instructions, the controller performs multi-timescale optimization calculations with the comprehensive objectives of maximizing system operating economy, power supply reliability, and renewable energy absorption. The core decision model for the optimization calculation adopts the following objective function:

[0039] Where T is the scheduling period; The electricity price during time period t; The power exchanged with the grid during time period t (purchased power is positive); This is the energy storage unit loss cost coefficient; The change in the output of the energy storage unit during time period t; The incentive coefficient for new energy consumption; The distributed renewable energy power consumed during time period t.

[0040] Short-term load forecasting refers to predicting the power consumption of various loads (lighting, fans, monitoring, etc.) in the tunnel over a future period (e.g., 24 hours). The controller generates short-term load forecast curves based on historical load data, tunnel traffic flow data, holiday information, and weather forecasts (which affect lighting demand) using time series analysis or machine learning algorithms.

[0041] New energy power generation forecasting mainly refers to photovoltaic power generation forecasting. The digital twin power controller D obtains data such as solar irradiance, ambient temperature, and cloud cover for the next 24 hours by connecting to a meteorological service interface. Combined with the historical output data of the photovoltaic array, it generates a photovoltaic output forecast curve using physical models or statistical methods.

[0042] Grid dispatch instructions refer to demand response signals, power curtailment orders, or time-of-use pricing information issued by the power grid company. The digital twin power controller D interacts with the grid dispatch center in real time through a communication interface to obtain the next day's time-of-use pricing curve, demand limit value, or time period requirements for participating in demand response.

[0043] Operational economics is quantified by the total operating cost of the system, specifically including: ① the cost of purchasing electricity from the grid. ② Cost of energy storage unit charging and discharging The sum of the two items is the total operating cost of the system, and the optimization objective is to minimize this sum.

[0044] Power supply reliability is reflected by two indicators: ① the power guarantee rate of critical loads (monitoring, communication, emergency lighting), which must always meet the minimum requirements; ② the system operating parameters (voltage, frequency, power factor) must always be within the allowable range of national standards. These two items are reflected as constraints in the optimization process.

[0045] Maximizing renewable energy consumption is quantified through photovoltaic (PV) utilization rate, which is the proportion of DC power generated by PV that is directly used for DC loads or stored in energy storage units. The digital twin power controller D improves utilization rate by prioritizing direct supply of PV power to DC loads and reducing AC-side inversion or backfeeding to the grid, corresponding to the renewable energy consumption reward term in the objective function. .

[0046] The controller receives load forecasts, photovoltaic forecasts, and grid commands as inputs, and uses optimization algorithms to calculate the equipment output for each time period, so as to minimize the total operating cost, maximize the photovoltaic utilization rate, and ensure the power supply safety of important loads and the stable operation of the system.

[0047] The controller sends the optimized scheduling instructions to the physical system for execution. These instructions include power allocation for each system, energy storage charging and discharging plans, and wireless charging system start-up and shutdown strategies. During execution, the controller performs rolling corrections based on actual feedback and prediction deviations, achieving dynamic closed-loop optimization control.

[0048] Specifically, during execution, the controller collects real-time operational data from the physical system as feedback. This feedback includes: voltage, frequency, and active power at the AC system grid connection point; actual output of photovoltaic power, real-time state of charge (SOC) and charging / discharging power of energy storage, and actual power of DC loads in the DC system; status of each charging station in the wireless charging system and the power level of the monitoring equipment; and measured irradiance and ambient temperature from an external weather station. All feedback data is collected through sensors and monitoring modules deployed on the equipment and synchronized to the digital twin model.

[0049] Forecast deviation refers to the difference between the actual feedback value at the current moment and the predicted value at the corresponding moment in the most recent optimized plan. Common types of deviation include: load forecast deviation (the difference between actual load power and planned load power), photovoltaic forecast deviation (the difference between actual photovoltaic output and planned photovoltaic output), and energy storage state deviation (the difference between actual SOC and planned SOC). The controller presets deviation thresholds; for example, if the power deviation exceeds 5% or 10kW, or the SOC deviation exceeds 5 percentage points, the deviation is considered too large and needs to be corrected.

[0050] Rolling corrections can employ a mechanism of "intraday rolling optimization + real-time feedback correction." Each 15-minute rolling cycle begins with the digital twin power controller D, which, starting from the current moment, re-runs the optimization algorithm based on the latest measured data and updated ultra-short-term forecasts (15 minutes to 4 hours ahead) to generate correction instructions for future periods. If a large instantaneous deviation occurs between rolling cycles (such as a sudden drop in photovoltaic output), the digital twin power controller D immediately triggers real-time feedback correction, recalculating and issuing instructions through a model predictive control algorithm to enable the system to quickly track planned values. Corrected instructions include adjusting the power of the bidirectional AC / DC converter, the charging and discharging power of energy storage, the operating mode of the photovoltaic DC / DC converter, and the start / stop of wireless charging.

[0051] After the DC system is connected to the photovoltaic power generation system, the photovoltaic power generated can be directly used for DC loads or stored in energy storage units without AC-DC conversion, thus avoiding energy loss caused by multiple conversions in traditional solutions. The wireless charging system, according to the scheduling instructions of the digital twin power controller, wirelessly charges the inspection drones and inspection vehicles inside the tunnel at appropriate times, ensuring the continuous and stable operation of the inspection equipment.

[0052] In emergency power supply mode D2, the controller monitors the connection status between AC system A and the public power grid in real time. When an external AC power interruption is detected, the digital twin power controller D immediately activates emergency power supply mode D2. In emergency power supply mode, the system automatically disconnects non-essential loads, prioritizing power supply from the energy storage units and photovoltaic power generation system in DC system B to at least one critical load in the emergency lighting, ventilation equipment, and monitoring and communication systems. Based on the digital twin model, the controller dynamically adjusts the power supply strategy in real time to assess the remaining energy storage capacity, the real-time power generation capacity of new energy sources, and load demand, thereby extending the power supply duration for critical loads and achieving the longest possible autonomous operation of the system in emergency situations.

[0053] During emergency power supply, the system continuously monitors the external power grid status. When the restoration of power supply to the public AC grid is detected, the digital twin power controller D automatically or after safety verification, smoothly switches the control system from emergency power supply mode D2 back to normal operation mode D1 and initiates the recovery charging process of the energy storage system. During the switching process, the controller first adjusts the DC bus voltage through a bidirectional AC / DC converter to make it approximately consistent with the AC grid voltage amplitude, frequency, and phase. Then, it closes the grid connection switch between the AC system and the grid to establish an electrical connection. Subsequently, it restores power supply to non-essential loads step by step. Finally, it sets the energy storage unit to charging mode, prioritizing photovoltaic power generation for charging, with the grid supplementing any shortfall.

[0054] Through the above methods, this invention realizes the control of normal and emergency power supply modes for a digital twin tunnel multifunctional power supply containing new energy and energy storage. It optimizes the system's operating economy and new energy consumption in normal mode, and ensures the continuous and safe power supply to important loads in emergency mode, thus comprehensively improving the adaptability, economy and intelligence of the tunnel power supply system.

Claims

1. A method for controlling the power supply during normal and emergency use of optical twin tunnels, characterized in that, Includes the following steps: A digital twin model of the tunnel power system is constructed, which synchronizes the operating status and electrical parameters of the AC system, DC system, wireless charging system and energy storage unit in the physical system in real time. Based on the digital twin model, a control mode algorithm is executed by the digital twin power controller, which includes a normal operation mode and an emergency power supply mode. Under the normal operating mode, the AC system, DC system and energy storage unit are optimized and scheduled with the comprehensive goals of maximizing system operating economy, power supply reliability and new energy consumption. In the emergency power supply mode, the connection status between the AC system and the public power grid is monitored in real time. When an external AC power interruption is detected, the system immediately switches to the emergency power supply mode, prioritizing the use of energy storage units and new energy power generation systems to supply power to preset important loads.

2. The control method according to claim 1, characterized in that, The optimized scheduling of the normal operation mode is based on the following objective function: Where T is the scheduling period; The electricity price during time period t; The power exchanged with the power grid during time period t; This is the energy storage unit loss cost coefficient; The change in the output of the energy storage unit during time period t; The incentive coefficient for new energy consumption; The distributed renewable energy power consumed during time period t.

3. The control method according to claim 1, characterized in that, In the emergency power supply mode, the digital twin power controller evaluates the remaining energy storage capacity, the real-time power generation capacity of new energy sources, and the load demand in real time based on the digital twin model, and dynamically adjusts the power supply strategy to extend the power supply duration of important loads.

4. The control method according to claim 1, characterized in that, In emergency power supply mode, the system automatically cuts off non-essential loads and prioritizes the use of energy storage units and photovoltaic power generation systems in the DC system to supply power to at least one important load in the emergency lighting, ventilation equipment, and monitoring and communication systems.

5. The control method according to claim 1, characterized in that, During emergency power supply, the system continuously monitors the status of the external power grid. When the public AC power grid is detected to be restored, the digital twin power controller automatically or after safety verification, smoothly switches the control system from emergency power supply mode back to normal operation mode and initiates the recovery charging process of the energy storage system.

6. The control method according to claim 1, characterized in that, The normal operation mode also includes: performing multi-time-scale optimization calculations based on short-term load forecasts, new energy power generation forecasts, and grid dispatch instructions, generating dispatch instructions and issuing them to the physical system for execution, and making rolling corrections based on actual feedback and forecast deviations during the execution process.

7. The control method according to claim 1, characterized in that, The wireless charging system wirelessly charges the inspection equipment inside the tunnel according to the scheduling instructions of the digital twin power controller.

8. The control method according to claim 1, characterized in that, The DC system is connected to the photovoltaic power generation system, and the photovoltaic power generated can be directly used for DC loads or stored in energy storage units without AC-DC conversion.

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