Complex regional traffic signal multiple power supply mode and coordination control system and method

Abstract

The application discloses a complex regional traffic signal multiple power supply mode and a coordination control system and method, and belongs to the intelligent traffic and new energy technology field.The system comprises a photovoltaic power generation module, a wind power generation module, an energy storage battery module, a battery management system (BMS), a multi-mode Internet of Things communication module, a remote monitoring cloud platform and a main control unit.According to the SOC and SOH collected by the BMS and the future 24-hour weather forecast, the main control unit dynamically generates a wind-solar complementary discharge control strategy, and gradually reduces the brightness of the signal lamp or shortens the lighting time according to the SOC drop degree; the Internet of Things communication module mainly communicates through LoRa, and automatically switches to NB-IoT, 4G Cat.1 or Beidou short message within 3 seconds when the signal is deteriorated; and the alarm is pushed in stages when a fault is detected.The application realizes green and reliable power supply, intelligent energy scheduling and multi-mode redundant communication of the traffic signal lamp in the mountainous area, significantly prolongs the service life of the energy storage, and guarantees the operation of the signal lamp under extreme weather.

Description

Technical Field

[0001] This application relates to the fields of intelligent transportation and new energy technology, specifically to multiple power supply methods and coordinated control systems and methods for traffic signals in complex areas. Background Technology

[0002] Traffic lights are a crucial infrastructure for ensuring road traffic safety and orderly passage. In complex areas such as mountains, canyons, islands, and deserts, the normal operation of traffic lights faces two major challenges: power supply and communication.

[0003] In terms of power supply, complex areas typically have the following characteristics: First, the power grid coverage is weak, or even completely without grid power. If new transmission lines are built, tens of kilometers of lines need to be erected, resulting in long construction periods, extremely high engineering costs, and damage to the ecological environment. Second, sunlight conditions are significantly affected by terrain shading. Valleys or dense forests have short sunshine hours and unstable photovoltaic power generation. Relying solely on photovoltaic power supply is insufficient to cope with continuous rainy or foggy weather. Third, although wind energy resources have potential, wind speed fluctuates greatly and changes drastically in an instant. A single wind power source cannot guarantee a continuous and reliable power supply. Fourth, the climate conditions are harsh, with frequent occurrences of rain, fog, ice, and snow. Traditional solar power systems are prone to failure in winter or under prolonged periods of no sunlight, causing traffic lights to stop working and leading to serious traffic accidents.

[0004] In terms of communications, the public network infrastructure in complex areas is lagging behind, with 4G / 5G and NB-IoT signals often failing to provide coverage or exhibiting extremely weak signals, making it difficult to implement traditional public network-based IoT remote monitoring solutions. Even with weak signals, interruptions are frequently caused by weather, terrain, and other factors, failing to meet the real-time monitoring and remote maintenance needs of traffic lights. Once equipment malfunctions, maintenance personnel struggle to promptly ascertain the fault status and location, resulting in extremely high on-site inspection and repair costs.

[0005] Existing technologies include wind-solar hybrid streetlights and monitoring systems, but power management systems specifically designed for traffic lights in complex areas are still immature. Existing wind-solar hybrid systems are mostly used for general lighting or security monitoring, and their energy management strategies are relatively simple, often switching between charging and discharging based solely on the current battery voltage. They lack refined dynamic assessment of battery state of charge (SOC) and state of health (SOH), and also lack forward-looking energy dispatch capabilities based on weather forecasts. When power generation is insufficient, the load is usually directly cut off, causing the traffic lights to suddenly go out, posing a significant safety hazard. Furthermore, existing solutions typically rely on a single public network or lack long-distance communication capabilities, making them unable to adapt to the variability and unreliability of communication environments in complex areas.

[0006] Therefore, there is an urgent need to develop a traffic signal power supply coordination and management system that is designed for complex areas, integrates photovoltaic and wind power generation, and has intelligent energy dispatch based on battery status and weather forecasts, multi-mode redundant communication, and environmental adaptive protection functions, so as to achieve green, reliable, and intelligent power supply for traffic signals in complex areas. Summary of the Invention

[0007] To overcome the shortcomings of existing technologies, this application provides a multi-power supply mode and coordinated control system and method for traffic signals in complex areas, in order to solve the problems of coarse energy dispatching of wind-solar hybrid power supply, lack of fine control based on battery status, poor communication reliability, and lack of adaptive capability in mountainous environments in existing technologies, so as to realize green, reliable and intelligent power supply guarantee for traffic lights in mountainous areas.

[0008] To achieve the above objectives, this application provides the following solution: A multi-power supply and coordinated control system for traffic signals in complex areas, characterized by comprising: Photovoltaic power generation modules are used to convert solar energy into electrical energy; Wind power generation module, used to convert wind energy into electrical energy; An energy storage battery module is electrically connected to the photovoltaic power generation module and the wind power generation module respectively, and is used to store electrical energy and supply power to traffic lights; The battery management system (BMS) is electrically connected to the energy storage battery module and is used to collect battery status parameters in real time and calculate the battery state of charge (SOC) and state of health (SOH). The Internet of Things (IoT) communication module includes a main communication unit and a backup communication unit. The main communication unit adopts LoRa wireless communication, and the backup communication unit adopts one or more of NB-IoT, 4G Cat.1, or BeiDou short message, supporting dual-mode adaptive switching. The remote monitoring cloud platform communicates with the local control system through the IoT communication module to receive operating status data and push alarm information; The main control unit is electrically connected to the photovoltaic power generation module, wind power generation module, energy storage battery module, battery management system, and IoT communication module, respectively. The main control unit is configured to perform the following operations: a. Based on the real-time SOC and SOH data collected by the battery management system and combined with the obtained 24-hour mountain weather forecast data, a wind-solar complementary discharge control strategy is dynamically generated; b. In the charging and discharging control strategy, the brightness of the traffic lights is gradually reduced or the lighting duration is shortened according to the degree of SOC decrease, wherein there is a one-to-one linkage relationship between the SOC threshold range and the brightness adjustment level of the traffic lights; c. Monitor the signal strength of the main communication unit in the IoT communication module in real time. When the signal strength of the main communication unit is lower than the preset threshold or the connection is interrupted, automatically switch to the backup communication unit within 3 seconds, and automatically switch back after the main communication unit signal is restored and stabilized for a preset time. d. When a fault is detected in any module, the fault type and location information are uploaded to the remote monitoring cloud platform through the IoT communication module.

[0009] Furthermore, the wind-solar complementary discharge control strategy dynamically generated by the main control unit includes: when only photovoltaic power generation is greater than or equal to the load power, or only wind power generation is greater than or equal to the load power, and the SOC is lower than a first preset threshold, the remaining power of this energy source is used to charge the energy storage battery; when the sum of photovoltaic power generation and wind power generation is greater than or equal to the load power and the SOC is lower than the first preset threshold, the remaining power is used to charge the energy storage battery; when the sum of photovoltaic power generation and wind power generation is less than the load power, the energy storage battery supplements the difference in power, and the discharge depth is limited to a safe range after comprehensive evaluation based on SOC and SOH; when the SOC is lower than a second preset threshold, the system automatically switches to energy-saving mode and requests access to a backup power source.

[0010] Furthermore, the linkage relationship of gradually reducing the brightness of traffic lights or shortening the lighting duration is as follows: when the SOC is in the range of 20% to 30%, the brightness of the traffic lights is reduced to 80% of the rated brightness; when the SOC is in the range of 10% to 20%, the brightness of the traffic lights is reduced to 50% of the rated brightness and a flashing yellow light mode is used during off-peak hours; when the SOC is below 10%, the system automatically switches to backup power supply.

[0011] Furthermore, the main control unit is also equipped with a low-power sleep-wake mechanism: when there are no abnormalities in the system and the SOC of the energy storage battery is higher than the safety threshold, the main control unit enters a microampere-level sleep state, retaining only the heartbeat monitoring function of the IoT communication module; when an abnormal event is detected or a wake-up command is received from the cloud platform, the main control unit wakes up in milliseconds and executes the corresponding control operation.

[0012] Furthermore, the battery management system employs an SOC estimation algorithm based on an equivalent circuit model and an SOH prediction algorithm based on a capacity decay model, with the SOC estimation error controlled within 3% and the SOH prediction error controlled within 5%.

[0013] Furthermore, according to claim 1, the multi-power supply mode and coordinated control system for traffic signals in complex areas is characterized in that the dual-mode adaptive switching of the IoT communication module is configured as follows: real-time monitoring of the signal strength RSRP of the main communication unit; when three consecutive heartbeat packet transmission failures or RSRP is below -110dBm for more than 30 seconds, the main communication link is determined to be abnormal and switching is triggered; when the RSRP of the main communication unit is above -105dBm and remains stable for 1 minute, automatic reverting is performed.

[0014] Furthermore, according to claim 1, the multi-power supply mode and coordinated control system for traffic signals in complex areas is characterized in that the remote monitoring cloud platform includes a data storage unit, a data analysis unit, and an alarm push unit. The data analysis unit establishes a mountain photovoltaic power prediction model, a wind power prediction model, and a load power prediction model based on historical operating data, and introduces a mountain terrain shading correction coefficient to attenuate the photovoltaic prediction value. The alarm push unit sends alarm information to maintenance personnel using one or more of the following methods according to the fault level: APP push, SMS, WeChat mini-program, and Beidou short message. The fault identification types include photovoltaic module faults, wind turbine generator faults, energy storage battery faults, charging and discharging circuit faults, communication module faults, and traffic light load faults.

[0015] Furthermore, it also includes a mountain environment sensing unit, comprising a light sensor, a wind speed and direction sensor, a temperature and humidity sensor, a rainfall sensor, and a snow and ice detection sensor. This mountain environment sensing unit is electrically connected to the main control unit and is used to collect on-site environmental parameters. The main control unit also dynamically adjusts its operating strategy based on these environmental parameters: when the wind speed exceeds the cut-off wind speed, it controls the wind power generation module to automatically brake for protection; when the battery temperature is below 0°C, the charging current is limited to 30% of the rated current; when the battery temperature is below -10°C, the battery heating device is activated to bring the temperature up to 5°C before charging is allowed; when snow accumulation is detected on the surface of the photovoltaic modules, a snow removal alarm is pushed through the cloud platform, and the electric heating snow melting device is remotely activated.

[0016] A collaborative control method for traffic signal systems with multiple power supply modes and coordinated control systems in complex areas, characterized by the following steps: S1: Real-time acquisition of photovoltaic power generation P_pv, wind power generation P_wind, SOC and SOH of energy storage batteries, and signal light load power P_load; S2: Obtain mountain weather forecast data for the next 24 hours, including predicted values ​​of solar radiation intensity and wind speed, and combine them with the mountain terrain shading correction coefficient to correct for photovoltaic power attenuation; S3: Based on SOC and SOH data, combined with meteorological forecast data, dynamically generate wind-solar complementary discharge control strategies; S4: Executing the charge and discharge control strategy, including: When P_pv ≥ P_load and SOC < 90%, charge the energy storage battery with the remaining photovoltaic power; When P_wind ≥ P_load and SOC < 90%, charge the energy storage battery with the remaining wind power; When P_pv + P_wind ≥ P_load and SOC < 90%, charge the energy storage battery with the remaining power; When P_pv + P_wind < P_load, the energy storage battery supplements the power difference, and the brightness of the signal lamp is gradually reduced or the lighting duration is shortened according to the decrease degree of SOC; S5: Monitor the signal strength of the main communication unit in the IoT communication module in real time. When the signal strength of the main communication unit is lower than a preset threshold or the connection is interrupted, automatically switch to the backup communication unit within 3 seconds, and automatically switch back after the signal of the main communication unit is restored and stably maintained for a preset period of time; S6: When a fault is detected, upload the fault type and positioning information to the remote monitoring cloud platform through the IoT communication module, and push alarms by levels according to the fault severity.

[0017] Further, the specific linkage relationship of gradually reducing the brightness of the signal lamp or shortening the lighting duration according to the decrease degree of SOC in step S4 is: When SOC > 50%, discharge normally, and the signal lamp maintains the rated brightness; When 30% < SOC ≤ 50%, the discharge current limit is 70% of the rated current; When 20% < SOC ≤ 30%, the discharge current limit is 50% of the rated current, and the brightness of the signal lamp is reduced to 80% of the rated brightness; When 10% < SOC ≤ 20%, the brightness of the signal lamp is reduced to 50% of the rated brightness, and the flashing yellow light mode is adopted during off-peak hours (22:00-06:00); When SOC ≤ 10%, automatically switch to backup power supply, and send an emergency power supply request to the cloud platform.

[0018] Beneficial effects of the technical solution of the present application: The present invention organically integrates three core technologies: wind-solar complementary power generation, refined energy scheduling based on SOC / SOH, and dual-mode adaptive communication, forming a closed-loop control link of "battery status → power supply strategy → load response → communication guarantee", which produces a technical synergy effect of 1+1+1>3.

[0019] This invention uses real-time SOC and SOH data collected by BMS, combined with weather and load forecasts, to dynamically generate the optimal charging and discharging strategy. It also establishes a linkage adjustment mechanism between multi-level SOC thresholds and traffic light brightness, extending the lifespan of energy storage batteries by more than 30% and avoiding traffic risks caused by sudden power outages.

[0020] In response to the poor public network coverage in mountainous areas, LoRa is used as the primary communication method (covering 5-15 kilometers), NB-IoT / 4G is used as a backup, and Beidou short message service is used as a third-level emergency channel to ensure that the system status can be reported and commands can be issued under any circumstances.

[0021] It integrates special protection functions such as automatic braking when the wind speed is too high, current limiting and battery heating when charging at low temperatures, photovoltaic snow accumulation detection and remote snow melting, and is adapted to extreme climate conditions such as high altitude, large temperature difference, ice and snow, and strong wind in mountainous areas.

[0022] The fault identification system covers more than 200 fault modes in five categories, and alarms are issued according to the fault level. It supports remote snow removal, remote restart, parameter adjustment and other operation and maintenance operations, which greatly reduces the on-site maintenance cost of traffic signal facilities in mountainous areas. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a block diagram of the overall structure of the system of the present invention; Figure 2 This is a flowchart of the control method of the main control unit of the present invention; Figure 3 This is a decision logic diagram of the wind-solar complementary discharge control strategy of the present invention; Figure 4 This is a flowchart of the dual-mode adaptive switching process for the IoT communication module of the present invention; Figure 5 This is a block diagram of the SOC / SOH estimation algorithm for the energy storage battery management system (BMS) of this invention; Figure 6 This is a schematic diagram of the GIS display interface of the remote monitoring cloud platform for mountainous sites according to the present invention. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of this invention clearer, the specific embodiments of this invention will be described in great detail below with reference to the accompanying drawings. This description is intended to provide sufficient information for those skilled in the art to understand and implement this invention. It should be noted that the following description contains numerous specific details and parameters, but these should not be considered as limitations on the scope of protection of this invention, but only as examples of preferred embodiments. For those skilled in the art, several modifications and improvements can be made without departing from the spirit and essence of this invention, and these will all fall within the scope of protection of the claims of this invention.

[0026] like Figure 1 As shown, the complex area traffic signal multi-power supply mode and coordinated control system provided in this embodiment includes a photovoltaic power generation module, a wind power generation module, an energy storage battery module, a battery management system (BMS), an Internet of Things (IoT) communication module, a remote monitoring cloud platform, and a main control unit.

[0027] The photovoltaic power generation module consists of four monocrystalline silicon solar cell modules with a total peak power of 1200W. It is installed on the top bracket of the traffic signal pole, and the bracket tilt angle can be manually adjusted according to the local latitude to adapt to mountain slope and seasonal changes. The wind power generation module uses a 300W vertical axis wind turbine with a starting wind speed of 2.0m / s, a rated wind speed of 12m / s, and a cut-off wind speed of 25m / s. It is installed on a 10-meter-high independent tower next to the traffic light, a location typically chosen at a valley wind gap to obtain relatively stable wind resources. The energy storage battery module uses eight 12V / 100Ah gel lead-acid batteries connected in series to form a 48V system with a total capacity of 4.8kWh. The gel batteries are suitable for a wide temperature range of -20℃ to 50℃ and are maintenance-free. The battery box is installed in an insulated protective box with a PTC heating plate at the bottom.

[0028] The Battery Management System (BMS) is electrically connected to the energy storage battery module. Each battery cell is equipped with voltage and temperature sensors, with a sampling frequency of 0.5Hz. The BMS main control chip is a TIBQ76940, employing a State of Charge (SOC) estimation algorithm based on an equivalent circuit model and a State of Harshness (SOH) prediction algorithm based on a capacity decay model. The SOC estimation error is controlled within 3%, and the SOH prediction error is controlled within 5%. In low-temperature environments, the BMS automatically activates the heating plate when the battery temperature drops below -10°C, and only allows charging after the temperature rises to 5°C.

[0029] The IoT communication module includes a main communication unit and a backup communication unit. The main communication unit uses LoRa wireless communication and connects to the cloud platform via a self-built LoRa gateway. The backup communication unit uses a 4GCat.1 module and automatically switches when a weak 4G signal is available at a distance of 3 kilometers. In addition, the module also integrates a BeiDou short message communication unit as a third-level backup communication channel. This is used to report core operational status data, including SOC, fault codes, and location, every 30 minutes when both LoRa and terrestrial cellular networks are unavailable, and to receive control commands from the cloud platform via the BeiDou command terminal.

[0030] The remote monitoring cloud platform uses a time-series database to store data, and the front end uses a GIS map to display the location of each mountain station. Mouse hover displays real-time SOC, power generation, load power, communication status, and alarm information. The cloud platform integrates a meteorological API to obtain hourly weather forecasts for the next 24 hours for each station location, and corrects the photovoltaic forecast values ​​for attenuation based on the user-preset mountain terrain shading coefficient.

[0031] The main control unit uses an STM32L476 low-power microcontroller and runs the FreeRTOS system. The main control unit communicates with the BMS and the wind-solar hybrid controller via RS485, and controls the signal light drive circuit via GPIO.

[0032] like Figure 2 As shown, the main control unit executes the following control flow. After system initialization, the main control unit self-checks the status of each module and reads the initial SOC and SOH values ​​of the energy storage battery through the BMS. If there are no abnormalities and the SOC is higher than 30%, the main control unit enters a low-power sleep state with a sleep current of less than 10μA, retaining only the heartbeat monitoring function of the IoT communication module, with a timed wake-up cycle of 1 minute.

[0033] Upon each wake-up, the main control unit collects real-time data on photovoltaic power generation (P_pv), wind power generation (P_wind), the current SOC and SOH values ​​of the energy storage battery, signal light load power (P_load), and data on irradiance, wind speed and direction, temperature, humidity, rainfall, and snow accumulation collected by the environmental sensing unit. Then, through the IoT communication module, it obtains 24-hour mountain weather forecast data from the cloud platform, including predicted solar irradiance, wind speed, and weather type, and uses a mountain terrain shading correction coefficient to correct for photovoltaic power attenuation.

[0034] The main control unit invokes the wind-solar complementary discharge control strategy decision module to generate the current optimal control command based on SOC, SOH, and meteorological forecast data. This includes adjusting the MPPT operating mode, charging current, depth of discharge, and indicator light brightness. After executing the control command, the main control unit uploads data such as system power generation, SOC, SOH, load power, communication status, and fault codes to the cloud platform.

[0035] If a fault is detected in any module, where the fault includes abnormal output of the photovoltaic module, overspeed of the wind turbine, over-limit of the cell monomer voltage, communication interruption, etc., the main control unit records the fault code and fault time, reports to the cloud platform through the IoT communication module, and triggers a local audible and visual alarm. If there is no fault and the SOC is higher than 30%, the main control unit enters the low-power sleep mode again and waits for the next scheduled wake-up; if the SOC is ≤30% or there is a fault, the main control unit remains in the wake-up state and shortens the data acquisition period to 1 minute.

[0036] As Figure 3 shown, the specific decision logic of the wind-solar hybrid charging and discharging control strategy is illustrated. The total generated power P_total is defined as P_pv + P_wind. When P_pv ≥ P_load and SOC < 90%, the photovoltaic power supplies power to the signal lamp alone, and the remaining power charges the energy storage battery; when P_wind ≥ P_load and SOC < 90%, the wind power supplies power to the signal lamp alone, and the remaining power charges the energy storage battery; when P_total ≥ P_load and SOC < 90%, the wind and solar power jointly supply power to the signal lamp, and the remaining power charges the energy storage battery. The three-stage strategy is adopted for the charging process: in the constant current stage, the maximum charging current is adopted when the SOC is 0% to 80%, but limited by the battery temperature, the current is limited to 0.05C when the temperature is lower than 0°C, and heating is performed before charging when the temperature is lower than -10°C; in the constant voltage stage, the charging voltage is maintained constant when the SOC is 80% to 95%, and the current gradually decreases; in the float charging stage, a tiny current is used for maintenance when the SOC ≥ 95%. When P_total ≥ P_load and SOC ≥ 90%, wind and solar power are preferentially used for power supply, and the excess electric energy is consumed through the load-dumping resistor or part of the photovoltaic modules are disconnected through MPPT regulation.

[0037] When P_total < P_load, the deficit power is supplemented by the discharge of the energy storage battery. The discharge depth is limited within a safe range after comprehensive evaluation based on SOC and SOH, and the specific classifications are as follows: when SOC > 50%, normal discharge is performed, and the signal lamp maintains the rated brightness; when 30% < SOC ≤ 50%, the discharge current limit is 70% of the rated current, and the signal lamp maintains the rated brightness; when 20% < SOC ≤ 30%, the discharge current limit is 50% of the rated current, and the brightness of the signal lamp drops to 80% of the rated brightness; when 10% < SOC ≤ 20%, the brightness of the signal lamp drops to 50% of the rated brightness, and the flashing yellow light mode is adopted during off-peak hours (22:00-06:00); when SOC ≤ 10%, the power supply is automatically switched to the standby power supply, and an emergency power supply request is sent to the cloud platform.

[0038] In addition, the system also has a weather forecast and pre-scheduling function. The main control unit obtains the weather forecast for the next 24 hours. If the forecast is for continuous darkness (solar intensity below 100W / m²) and no wind (wind speed below the cut-in wind speed of 2.5m / s) for more than 24 hours, the energy-saving pre-scheduling strategy will be activated in advance when the current SOC is still sufficient. This will proactively reduce the brightness of the signal lights to 70% of the rated brightness and reduce unnecessary power consumption to extend the power supply time in preparation for the upcoming energy shortage period.

[0039] like Figure 4 As shown, this illustrates the dual-mode adaptive switching mechanism of the IoT communication module. In mountainous scenarios, LoRa serves as the primary communication method. The LoRa gateway is deployed at a high point, covering a radius of 5–15 kilometers, with each traffic light station acting as a LoRa terminal node.

[0040] The communication module is equipped with an independent communication status monitoring unit to monitor the signal strength RSRP and connection status of the main communication unit in real time. LoRa sends a heartbeat packet every 15 minutes. If three consecutive heartbeat packet transmissions fail or the RSRP remains below -110dBm for more than 30 seconds, the main communication link is considered abnormal. At this time, the main control unit immediately starts the backup communication unit: first, it attempts to use 4GCat.1; otherwise, it switches to BeiDou short message service. BeiDou short message service only reports core data: SOC, fault code, location, and timestamp. The switching process is completed within 3 seconds. After the switch is completed, the cloud platform records the communication status change log and sends an alarm notification through the backup channel.

[0041] Once the main communication unit signal recovers and the RSRP is above -105dBm and remains stable for 1 minute, the system automatically switches back to the LoRa main communication unit to reduce the occupancy and power consumption of the backup communication network. All switching actions are timestamped and reported to the cloud platform. For extremely remote mountainous areas without any terrestrial network, only BeiDou short messages can be used, with the cloud platform issuing commands through the BeiDou command terminal.

[0042] The environmental sensing unit includes a light sensor, wind speed and direction sensor, temperature and humidity sensor, rainfall sensor, and snow and ice detection sensor. These sensors are electrically connected to the main control unit to collect real-time environmental parameters. The main control unit dynamically adjusts its operating strategy based on these environmental parameters. High wind protection: When the wind speed exceeds 20m / s, the wind turbine decelerates through electromagnetic braking; when the wind speed exceeds 25m / s, the wind power generation module is automatically braked for protection, the mechanical brake is locked and the output relay is disconnected.

[0043] Low temperature charging protection: When the battery temperature is below 0℃, the charging current limit is 30% of the rated current; when the battery temperature is below -10℃, the battery heating device will be activated to 5℃ before charging is allowed.

[0044] Snow removal: When the snow and ice detection sensor detects snow on the surface of the photovoltaic module, the main control unit pushes a "snow removal alarm" through the cloud platform. The system is equipped with an electric heating film, which can be remotely activated to heat and melt the snow.

[0045] Icing protection: When the temperature and humidity sensor detects that the air temperature is below 0℃ and the humidity is above 85%, the wind turbine will automatically switch to anti-icing mode.

[0046] The cloud platform data analysis unit has established a fault feature database based on historical operating data, covering five major categories of fault modes: photovoltaic module faults, including module open circuit, short circuit, shading, hot spot effect, snow cover, etc.; wind turbine faults, including blade imbalance, generator overheating, abnormal overspeed braking, icing, etc.; energy storage battery faults, including abnormal single cell voltage, excessive temperature, SOC jump, rapid SOH decay, etc.; charging and discharging circuit faults, including MPPT failure, overcurrent, overvoltage, undervoltage, etc.; and communication module faults, including signal loss, excessively high data packet loss rate, failure to send and receive Beidou short messages, etc., identifying a total of more than 200 fault modes.

[0047] When a fault is detected, the cloud platform pushes alarms according to the fault level, which is divided into three levels. Level 1 faults, including battery thermal runaway, main circuit short circuit, and wind turbine overrun, are simultaneously alerted within 1 second via four methods: APP push, SMS, WeChat mini-program, and Beidou short message. Level 2 faults, including low SOC, communication interruption, and severe shading of photovoltaic modules, are alerted via APP push and WeChat mini-program. Level 3 faults, including slight shading of photovoltaic modules, battery imbalance, and wind speed sensor malfunction, are only recorded via APP push. The alarm information includes the complete content of fault type, fault location, fault occurrence time, and suggested handling measures.

[0048] Maintenance personnel can remotely view the system's real-time operating data, historical data curves, fault records, and maintenance logs through the cloud platform's web or mobile app. It also supports remotely issuing control commands, including switching power supply modes, adjusting signal light brightness, manually waking up dormant devices, and starting heating for snow melting.

[0049] When the system is functioning normally and the battery's state of charge (SOC) is above the safety threshold, the main control unit enters a microampere-level sleep state. Specifically, the main control unit disables unnecessary peripherals, retaining only the heartbeat monitoring function of the IoT communication module and a timed wake-up timer. The measured sleep current is less than 10μA. The timed wake-up cycle is set to 1 minute. After each wake-up, the main control unit completes data acquisition, strategy calculation, and control execution within milliseconds before entering sleep mode again.

[0050] When an abnormal event is detected, the main control unit immediately exits sleep mode and remains awake, while simultaneously reporting the abnormal event to the cloud platform via the IoT communication module. Furthermore, the cloud platform can also wake up the main control unit at any time via downlink commands. When maintenance personnel need to remotely adjust signal light parameters or activate snow melting heating, the cloud platform sends a wake-up command, and the main control unit responds and executes the corresponding operation within milliseconds.

[0051] The above system was deployed at a sharp bend in a mountain road in southwestern China for field testing. During the test, there were five consecutive days of extreme overcast and rainy weather with no wind and no sunlight (solar intensity below 50W / m², wind speed below 1.5m / s). The comparison system using traditional single photovoltaic power supply dropped to below 10% on the second day, and the traffic lights went out completely. However, the wind-solar hybrid system of the present invention extended the operating time to 5.5 days under the same conditions through the following measures: (1) Weather forecasting and pre-scheduling actively reduced the brightness of the traffic lights to 70% on the first day; (2) SOC hierarchical linkage control: when the SOC dropped to 25% on the second day, the brightness was reduced to 80%; when the SOC dropped to 18% on the third day, the brightness was reduced to 50% and the yellow lights flashed at night; (3) The lighting time was shortened during off-peak hours (22:00-06:00). Finally, when the SOC dropped to 10% on the 5.5th day, it automatically switched to the backup diesel generator. The traffic lights did not go out completely throughout the entire process, ensuring the safety of traffic on mountain roads.

[0052] The embodiments described above are merely preferred embodiments of this application and are not intended to limit the scope of this application. Any modifications and improvements made by those skilled in the art to the technical solutions of this application without departing from the spirit of this application shall fall within the protection scope defined by the claims of this application.

Claims

1. A multi-power supply mode and coordinated control system for traffic signals in complex areas, characterized in that, include: Photovoltaic power generation modules are used to convert solar energy into electrical energy; Wind power generation module, used to convert wind energy into electrical energy; An energy storage battery module is electrically connected to the photovoltaic power generation module and the wind power generation module respectively, and is used to store electrical energy and supply power to traffic lights; The battery management system (BMS) is electrically connected to the energy storage battery module and is used to collect battery status parameters in real time and calculate the battery state of charge (SOC) and state of health (SOH). The Internet of Things (IoT) communication module includes a main communication unit and a backup communication unit. The main communication unit adopts LoRa wireless communication, and the backup communication unit adopts one or more of NB-IoT, 4G Cat.1, or BeiDou short message, supporting dual-mode adaptive switching. The remote monitoring cloud platform communicates with the local control system through the IoT communication module to receive operating status data and push alarm information; The main control unit is electrically connected to the photovoltaic power generation module, wind power generation module, energy storage battery module, battery management system, and IoT communication module, respectively. The main control unit is configured to perform the following operations: a. Based on the real-time SOC and SOH data collected by the battery management system and combined with the obtained 24-hour mountain weather forecast data, a wind-solar complementary discharge control strategy is dynamically generated; b. In the charging and discharging control strategy, the brightness of the traffic lights is gradually reduced or the lighting duration is shortened according to the degree of SOC decrease, wherein there is a one-to-one linkage relationship between the SOC threshold range and the brightness adjustment level of the traffic lights; c. Monitor the signal strength of the main communication unit in the IoT communication module in real time. When the signal strength of the main communication unit is lower than the preset threshold or the connection is interrupted, automatically switch to the backup communication unit within 3 seconds, and automatically switch back after the main communication unit signal is restored and stabilized for a preset time. d. When a fault is detected in any module, the fault type and location information are uploaded to the remote monitoring cloud platform through the IoT communication module.

2. The multi-power supply method and coordinated control system for traffic signals in complex areas according to claim 1, characterized in that, The wind-solar complementary discharge control strategy dynamically generated by the main control unit includes: when only photovoltaic power generation is greater than or equal to the load power, or only wind power generation is greater than or equal to the load power, and the SOC is lower than a first preset threshold, the remaining power of this energy source is used to charge the energy storage battery; when the sum of photovoltaic power generation and wind power generation is greater than or equal to the load power and the SOC is lower than the first preset threshold, the remaining power is used to charge the energy storage battery; when the sum of photovoltaic power generation and wind power generation is less than the load power, the energy storage battery supplements the difference in power, and the discharge depth is limited to a safe range after comprehensive evaluation based on SOC and SOH; when the SOC is lower than a second preset threshold, the system automatically switches to energy-saving mode and requests access to a backup power source.

3. The multi-power supply method and coordinated control system for traffic signals in complex areas according to claim 1, characterized in that, The linkage relationship for gradually reducing the brightness of traffic lights or shortening the lighting duration is as follows: when the SOC is in the range of 20% to 30%, the brightness of the traffic lights is reduced to 80% of the rated brightness; when the SOC is in the range of 10% to 20%, the brightness of the traffic lights is reduced to 50% of the rated brightness and a flashing yellow light mode is used during off-peak hours; when the SOC is below 10%, the system automatically switches to backup power supply.

4. The multi-power supply method and coordinated control system for traffic signals in complex areas according to claim 2, characterized in that, The main control unit is also equipped with a low-power sleep-wake mechanism: when there is no system abnormality and the SOC of the energy storage battery is higher than the safety threshold, the main control unit enters a microampere-level sleep state, retaining only the heartbeat monitoring function of the IoT communication module; when an abnormal event is detected or a wake-up command is received from the cloud platform, the main control unit wakes up in milliseconds and executes the corresponding control operation.

5. The multi-power supply method and coordinated control system for traffic signals in complex areas according to claim 1, characterized in that, The battery management system employs an SOC estimation algorithm based on an equivalent circuit model and an SOH prediction algorithm based on a capacity decay model. The SOC estimation error is controlled within 3%, and the SOH prediction error is controlled within 5%.

6. The multi-power supply method and coordinated control system for traffic signals in complex areas according to claim 1, characterized in that, The dual-mode adaptive switching of the IoT communication module is configured as follows: real-time monitoring of the signal strength RSRP of the main communication unit; when three consecutive heartbeat packet transmission failures or RSRP below -110dBm for more than 30 seconds, the main communication link is determined to be abnormal and switching is triggered; when the RSRP of the main communication unit is above -105dBm and remains stable for 1 minute, automatic switching back is performed.

7. The multi-power supply method and coordinated control system for traffic signals in complex areas according to claim 1, characterized in that, The remote monitoring cloud platform includes a data storage unit, a data analysis unit, and an alarm push unit. The data analysis unit establishes a mountain photovoltaic power prediction model, a wind power prediction model, and a load power prediction model based on historical operating data, and introduces a mountain terrain shading correction coefficient to attenuate the photovoltaic prediction value. The alarm push unit sends alarm information to maintenance personnel using one or more of the following methods according to the fault level: APP push, SMS, WeChat mini-program, and Beidou short message. The fault identification types include photovoltaic module faults, wind turbine faults, energy storage battery faults, charging and discharging circuit faults, communication module faults, and signal light load faults.

8. The multi-power supply method and coordinated control system for traffic signals in complex areas according to claim 1, characterized in that, It also includes a mountain environment sensing unit, comprising a light sensor, a wind speed and direction sensor, a temperature and humidity sensor, a rainfall sensor, and a snow and ice detection sensor. The mountain environment sensing unit is electrically connected to the main control unit and is used to collect on-site environmental parameters. The main control unit also dynamically adjusts the operating strategy according to the environmental parameters: when the wind speed exceeds the cut-off wind speed, it controls the wind power generation module to automatically brake for protection; when the battery temperature is below 0°C, the charging current is limited to 30% of the rated current; when the battery temperature is below -10°C, the battery heating device is activated to 5°C before charging is allowed; when snow accumulation is detected on the surface of the photovoltaic module, a snow removal alarm is pushed through the cloud platform and the electric heating snow melting device is remotely activated.

9. A method for multiple power supply modes and coordinated control of traffic signals in complex areas, characterized in that, Includes the following steps: S1: Real-time acquisition of photovoltaic power generation P_pv, wind power generation P_wind, SOC and SOH of energy storage batteries, and signal light load power P_load; S2: Obtain mountain weather forecast data for the next 24 hours, including predicted values ​​of solar radiation intensity and wind speed, and combine them with the mountain terrain shading correction coefficient to correct for photovoltaic power attenuation; S3: Based on SOC and SOH data, combined with meteorological forecast data, dynamically generate wind-solar complementary discharge control strategies; S4: Execute the charge / discharge control strategy, including: When P_pv≥P_load and SOC<90%, the remaining photovoltaic power is used to charge the energy storage battery. When P_wind ≥ P_load and SOC < 90%, the energy storage battery is charged with the surplus wind power; When P_pv + P_wind ≥ P_load and SOC < 90%, the energy storage battery is charged with the surplus power; When P_pv + P_wind < P_load, the energy storage battery supplements the power deficit, and the brightness of the signal lamp is reduced step by step or the lighting duration is shortened according to the decrease degree of SOC; S5: Real-time monitor the signal strength of the main communication unit in the IoT communication module. When the signal strength of the main communication unit is lower than a preset threshold or the connection is interrupted, automatically switch to the backup communication unit within 3 seconds, and automatically switch back after the signal of the main communication unit is restored and remains stable for a preset period; S6: When a fault is detected, upload the fault type and positioning information to the remote monitoring cloud platform through the IoT communication module, and push alarms in different levels according to the fault severity.

10. A remote power supply management method for traffic lights in mountainous areas based on wind-solar hybrid energy storage and the Internet of Things, as described in claim 9, is characterized in that... The specific linkage relationship of reducing the brightness of the signal lamp step by step or shortening the lighting duration according to the decrease degree of SOC in step S4 is as follows: When SOC > 50%, discharge is performed normally, and the signal lamp maintains the rated brightness; When 30% < SOC ≤ 50%, the discharge current limit is 70% of the rated current; When 20% < SOC ≤ 30%, the discharge current limit is 50% of the rated current, and the brightness of the signal lamp is reduced to 80% of the rated brightness; When 10% < SOC ≤ 20%, the brightness of the signal lamp is reduced to 50% of the rated brightness, and the flashing yellow light mode is adopted during off-peak hours (22:00-06:00); When SOC ≤ 10%, automatically switch to the backup power supply for power supply, and send an emergency power supply request to the cloud platform.

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