Intelligent lighting system with LED complementary power supply and energy scheduling method

Abstract

The application discloses an LED complementary power supply intelligent lighting system and an energy scheduling method, relates to the technical field of lighting, and comprises a complementary power supply module integrating photovoltaic, wind energy and a power grid backup power supply unit to form a multi-source complementary architecture; an energy storage module adopts a lithium iron phosphate battery pack and a bidirectional DC-DC converter; a lighting control module contains a constant current driving circuit, a stepless dimming unit and an LED lighting array; an environment sensing module is provided with multiple sensors to collect data such as light, personnel and traffic; an energy scheduling module analyzes data to formulate a dynamic energy distribution strategy and coordinates the work of each module; a communication module adopts a dual-mode communication technology to realize remote data interaction; and a safety protection module integrates multiple protection circuits to ensure safe operation of the system. The application solves the problems of low energy utilization efficiency and poor adaptability of traditional lighting, improves the utilization rate of clean energy through multi-source complementation, and improves safety and convenience through multiple protection and remote operation and maintenance.

Description

Technical Field

[0001] This invention relates to the field of lighting technology, and in particular to a smart lighting system and energy dispatching method with complementary LED power supply. Background Technology

[0002] LED lighting, with its advantages of high luminous efficiency, low power consumption, and long lifespan, has been widely used in various scenarios such as road lighting, park lighting, and public venue lighting, becoming the mainstream technology in the current lighting field. With the advancement of dual-carbon goals, traditional LED lighting systems relying on a single power grid are facing energy consumption pressures. Complementary power supply models based on renewable energy are gradually emerging, integrating clean energy sources such as photovoltaics and wind power with grid power to achieve diversified energy supply and reduce dependence on traditional energy sources. However, existing LED complementary power supply lighting systems mostly remain at the level of simple energy supply aggregation, failing to form a multi-module collaborative intelligent architecture, and thus failing to fully leverage the advantages of complementary power supply.

[0003] Existing systems suffer from several critical shortcomings. The energy allocation mechanism lacks precision; most systems employ fixed power priority strategies without dynamically adjusting to real-time energy conditions and lighting demands. This results in low utilization efficiency of renewable energy sources such as solar and wind power, leading to energy waste or power shortages during periods of significant fluctuation in sunlight or wind. Lighting adaptability is insufficient; traditional systems often use fixed light intensity modes or simply adjust based on ambient light, failing to incorporate contextual information such as pedestrian activity and traffic flow for precise, on-demand lighting. This compromises both lighting comfort and energy redundancy. Energy storage management exhibits significant deficiencies, lacking the ability to dynamically predict the remaining capacity of storage modules. This makes it difficult to anticipate energy shortage risks, frequently resulting in lighting outages due to insufficient storage. Furthermore, the charging and discharging strategies lack optimization, accelerating battery degradation and shortening battery lifespan.

[0004] The operation and maintenance (O&M) and safety assurance system is inadequate. The existing system lacks an efficient fault diagnosis mechanism, failing to quickly identify common problems such as photovoltaic panel shading, LED chip damage, and sensor malfunctions. Fault location is delayed, repair cycles are long, and continuous system operation is affected. Remote control capabilities are weak, making centralized monitoring of multiple devices and remote parameter adjustment difficult. O&M personnel must conduct on-site inspections and debugging, resulting in high O&M costs and low efficiency. Safety protection mechanisms are relatively simple, mostly providing only basic overcurrent and overvoltage protection, insufficient for handling complex abnormal conditions such as overtemperature and battery overcharging / overdischarging, easily leading to equipment damage and even safety hazards. These problems collectively cause existing LED complementary power supply lighting systems to fail to meet the diverse needs of smart lighting in terms of energy utilization efficiency, lighting reliability, O&M convenience, and safety, hindering the deep application of clean energy in the lighting field. There is an urgent need for a smart lighting system with precise energy scheduling, intelligent lighting adaptation, comprehensive safety assurance, and efficient O&M capabilities. Summary of the Invention

[0005] The present invention proposes an LED complementary power supply-based smart lighting system and energy dispatching method to solve the problems mentioned in the prior art.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a smart lighting system with complementary LED power supply, comprising the following modules: The complementary power supply module integrates a photovoltaic power supply unit, a wind power supply unit, and a grid backup power supply unit. The photovoltaic power supply unit uses high-efficiency monocrystalline silicon photovoltaic panels, the wind power supply unit is equipped with a small vertical axis wind turbine, and the grid backup power supply unit is connected to the mains power through an intelligent switching switch. The three form a multi-source complementary power supply architecture. The energy storage module uses a high-capacity lithium iron phosphate battery pack, paired with a bidirectional DC-DC converter. The battery pack has a built-in temperature sensor and voltage monitoring unit to collect data in real time. The lighting control module includes an LED driver circuit, an intelligent dimming unit, and an LED lighting array. The LED driver circuit adopts a constant current driving scheme, the intelligent dimming unit supports stepless dimming from 0 to 100%, and the LED lighting array uses high-efficiency and low-power LED chips. The environmental perception module deploys a light intensity sensor, a human infrared sensor, a temperature and humidity sensor, and a traffic flow sensor. The light intensity sensor collects ambient light intensity data in real time, the human infrared sensor detects the activity of people in the area, and the traffic flow sensor is adapted to road lighting scenarios to collect vehicle flow information. The energy scheduling module connects to various functional modules and receives collected data. It analyzes the output power of the power supply unit, the remaining capacity of the energy storage module, and the intensity of lighting demand, formulates dynamic energy allocation strategies, and coordinates the working status of the complementary power supply module, energy storage module, and lighting control module. The communication module adopts LoRa and WiFi dual-mode communication technology. LoRa is used for long-distance, low-power transmission of sensor data and control commands, while WiFi supports high-speed data interaction with the cloud management platform. The safety protection module integrates overcharge protection circuit, over-discharge protection circuit, short circuit protection circuit and over-temperature protection circuit. When abnormal voltage, current or temperature is detected, it automatically cuts off the relevant circuit or switches the working mode, and sends alarm information to the cloud platform at the same time.

[0007] Furthermore, it also includes an energy optimization calculation module, which calculates the optimal energy allocation ratio for each power supply unit using a quantification model. The calculation expression is as follows: in For the first Energy allocation ratio of power supply units For the first Energy conversion efficiency of power supply units For the first Real-time output power coefficient of the power supply unit This is the maximum power supply of the system. For the first Priority weights for power supply units.

[0008] Furthermore, it also includes an adaptive lighting adjustment module, which dynamically adjusts the luminous intensity and lighting range of the LED lighting array based on the light intensity data collected by the environmental sensing module and information on human activity and traffic flow. When the ambient light intensity is higher than the set threshold and there are no people or vehicles, the lighting intensity is reduced to the minimum maintenance value. When people or vehicles are detected, the intensity is quickly increased to the appropriate level, and the lighting coverage is adjusted according to the movement trajectory of people or the direction of traffic flow.

[0009] Furthermore, it also includes a remote monitoring module, which enables centralized monitoring of multiple lighting systems through a cloud management platform. The platform displays the power supply status, remaining energy storage capacity, lighting parameters, sensor data, and fault alarm information of each device in real time. It supports managers to remotely issue dimming commands, switch power supply modes, and set operating parameters, while generating energy consumption statistics reports and equipment operation logs.

[0010] Furthermore, it also includes a fault diagnosis module, which collects the operating parameters of each module, establishes a fault feature database, uses machine learning algorithms to compare and analyze real-time data with normal parameter thresholds, identifies common problems of photovoltaic panels, locates fault locations and sends alarm information in a graded manner, and provides fault handling suggestions to shorten the maintenance cycle.

[0011] Furthermore, it also includes an energy storage status prediction module, which uses a time series prediction algorithm to predict the trend of the battery pack's remaining capacity over the next 24 hours based on the energy storage module's historical charge and discharge data, current remaining capacity, ambient temperature, and future power supply prediction data.

[0012] Furthermore, it also includes a load balancing module, which monitors the operating current and power consumption of each branch of the LED lighting array in real time, adjusts the power distribution of each branch through intelligent shunt circuits, and balances the overall power consumption to extend the lifespan of the LED lighting array.

[0013] Furthermore, this includes the following steps: Step 1: Energy Acquisition and Monitoring. The photovoltaic and wind power supply units of the complementary power supply module collect solar and wind energy and convert them into electrical energy. The energy monitoring unit collects the output power and conversion efficiency data of each power supply unit in real time. The grid backup power supply unit is on standby and monitors the stability of the mains power. Step 2: Energy storage and status assessment. The energy storage module receives electrical energy from the complementary power supply module, and after voltage matching by the bidirectional DC-DC converter, it is stored in the lithium battery pack. The temperature sensor and voltage monitoring unit collect battery data to assess the battery's storage capacity and operating status. Step 3: Environmental data acquisition and lighting demand analysis. The environmental sensing module collects data on light intensity, human activity, temperature and humidity, and traffic flow simultaneously from various sensors. The lighting control module analyzes the current lighting demand intensity, range, and duration in conjunction with preset lighting standards. Step 4: Energy dispatch strategy formulation. The energy dispatch module receives power supply monitoring, energy storage status and lighting demand data, calls the energy allocation algorithm to determine priority and allocation ratio, prioritizes the use of renewable energy when it is sufficient, and calls the battery pack to supplement when it is insufficient. Step 5: Lighting parameter adjustment. Based on the scheduling strategy and lighting demand analysis results, the lighting control module adjusts the power supply current through the LED driver circuit. The intelligent dimming unit completes stepless dimming, and the LED lighting array operates according to the set parameters and maintains a stable light source without flicker. Step Six: Safety Monitoring and Feedback. The safety protection module monitors the voltage, current, and temperature data of each module in real time. When an abnormality occurs, the protection mechanism is triggered. The communication module uploads the system's working status, scheduling results, and abnormal alarm information to the cloud platform, forming a closed-loop feedback.

[0014] Furthermore, in step four, a dynamic priority mechanism is introduced when formulating the energy dispatch strategy. The priority of power supply units is dynamically adjusted according to real-time energy conditions and lighting scenarios. During the daytime when there is sufficient sunlight, the priority of photovoltaic power supply units is the highest, followed by wind power supply units. At night or on cloudy or rainy days, the priority of wind power supply units is increased, and the insufficient part is supplemented by battery packs and the grid. During periods of high population density or heavy traffic, the priority of grid backup power supply units is temporarily increased.

[0015] Furthermore, it also includes energy storage optimization management steps. Based on the prediction results of the energy storage status prediction module, when the grid electricity price is low and the remaining capacity of the battery pack is lower than the set value, the grid backup power supply unit is controlled to charge the battery pack. When the electricity price is high and the renewable energy output is sufficient, renewable energy is given priority to power the battery pack and charge it. At the same time, the charging and discharging rate is adjusted according to the battery pack temperature data.

[0016] Compared with existing technologies, the beneficial effects of this invention are: The LED complementary power supply intelligent lighting system and energy dispatching method of the present invention fundamentally solve the core defects of existing systems such as inefficient energy utilization, poor lighting adaptability, insufficient energy storage management, and weak operation and maintenance safety. It comprehensively improves the intelligence level, energy utilization efficiency and operational reliability of LED lighting systems, and provides efficient, safe and economical lighting solutions for various lighting scenarios.

[0017] The system achieves precise and efficient energy allocation through the coordinated operation of complementary power supply modules and energy optimization calculation modules. The multi-source complementary power supply architecture integrates photovoltaic, wind, and grid power, and uses quantitative models to calculate the optimal energy allocation ratio, prioritizing the full utilization of renewable energy, reducing reliance on the traditional grid, improving energy efficiency, and aligning with the needs of dual-carbon development. A dynamic priority adjustment mechanism further adapts to real-time energy conditions and lighting scenario changes, flexibly switching power supply priorities in different time periods and environments, ensuring stable energy supply while maximizing the utilization rate of clean energy.

[0018] The adaptive lighting adjustment module works in conjunction with the lighting control module to achieve precise lighting on demand. Based on multi-dimensional data such as light intensity, pedestrian activity, and traffic flow collected by the environmental sensing module, the lighting intensity and coverage are dynamically adjusted. When there are no pedestrians or vehicles and the ambient light is sufficient, the lighting intensity is reduced, and when there is demand, it is precisely increased to an appropriate level. This ensures both lighting comfort and safety, avoids redundant energy consumption, and significantly reduces system energy consumption.

[0019] Energy storage management and load balancing mechanisms effectively extend equipment lifespan and ensure continuous power supply. The energy storage status prediction module anticipates energy storage changes over the next 24 hours, triggering grid backup power supply in advance to avoid lighting interruptions. Energy storage optimization management adjusts charging and discharging strategies in conjunction with electricity price fluctuations, reducing electricity costs while slowing battery degradation. The load balancing module adjusts the power distribution across branches to ensure uniform operating current for LED beads, preventing overload damage, extending the lifespan of the lighting array, and reducing equipment replacement and maintenance costs.

[0020] A comprehensive operation and maintenance (O&M) and security system significantly improves the convenience of system operation and maintenance and operational safety. The fault diagnosis module uses machine learning algorithms to accurately identify various faults and pinpoint their location, sending alarm information and handling suggestions in a tiered manner, shortening maintenance cycles and ensuring continuous system operation. The remote monitoring module enables centralized management and remote parameter adjustment of multiple devices, displays system operating status in real time, and generates statistical reports, reducing the need for on-site inspections, lowering O&M costs, and improving efficiency. The safety protection module integrates multiple protection functions such as overcharge, over-discharge, short circuit, and over-temperature protection. It automatically triggers protection mechanisms and reports alarm information when abnormal operating conditions are detected, comprehensively protecting equipment and operational safety and avoiding potential safety hazards.

[0021] The energy dispatching method, through standardized procedures, achieves closed-loop management of energy harvesting, storage, dispatching, lighting adjustment, and safety feedback, ensuring the coordinated and orderly operation of each module and improving system stability and reliability. The energy storage optimization management steps further refine charging and discharging strategies, adjusting charging and discharging rates based on temperature data to extend battery life and further optimize energy utilization costs. Overall, this invention achieves efficient energy utilization, precise lighting adaptation, intelligent energy storage management, convenient and efficient operation and maintenance, and comprehensive safety assurance for LED lighting systems. It promotes the upgrading of lighting systems towards intelligence and low carbon emissions, adapting to the needs of various lighting scenarios such as roads, parks, and public venues, and possesses broad application value and promising prospects for promotion. Attached Figure Description

[0022] Figure 1 A schematic block diagram of the LED complementary power supply smart lighting system proposed in this invention; Figure 2 This is a schematic block diagram of the energy dispatching method for the LED complementary power supply smart lighting system proposed in this invention; Figure 3 Grouping clean energy utilization rates for different scenarios into bar charts; Figure 4 A line graph showing the trend of prediction accuracy for the remaining capacity of energy storage modules; Figure 5 This is a scatter plot showing the correlation between energy consumption and lighting duration. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0025] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of the stated features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified. Furthermore, the terms "installed," "connected," and "linked" should be interpreted broadly; for example, they may refer to a fixed connection, a detachable connection, or an integral connection; they may refer to a mechanical connection or an electrical connection; they may refer to a direct connection or an indirect connection through an intermediate medium; and they may refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances. The invention will now be described in further detail with reference to the accompanying drawings.

[0026] Reference Figures 1 to 5 A smart lighting system with complementary LED power supply includes the following modules: The complementary power supply module integrates a photovoltaic power supply unit, a wind power supply unit, and a grid backup power supply unit. The photovoltaic power supply unit uses high-efficiency monocrystalline silicon photovoltaic panels, the wind power supply unit is equipped with a small vertical axis wind turbine, and the grid backup power supply unit is connected to the mains power through an intelligent switching switch. The three form a multi-source complementary power supply architecture that automatically switches the main power supply source according to environmental energy conditions. The energy storage module uses a high-capacity lithium iron phosphate battery pack, paired with a bidirectional DC-DC converter, to achieve efficient energy storage and release. The battery pack has a built-in temperature sensor and voltage monitoring unit to collect battery operating status data in real time, supports deep charge and discharge cycles, and has a long service life. The lighting control module includes an LED driver circuit, an intelligent dimming unit, and an LED lighting array. The LED driver circuit adopts a constant current driving scheme to ensure stable operation of the light source. The intelligent dimming unit supports stepless dimming from 0 to 100%. The LED lighting array uses high-efficiency, low-power surface-mount LED chips, arranged according to the principle of uniform light distribution. The environmental perception module deploys a light intensity sensor, a human infrared sensor, a temperature and humidity sensor, and a traffic flow sensor. The light intensity sensor collects ambient light intensity data in real time, the human infrared sensor detects the activity of people in the area, and the traffic flow sensor is adapted to road lighting scenarios to collect vehicle flow information. All sensors adopt a low-power design to ensure continuous operation. The energy dispatch module, as the core control unit of the system, connects to various functional modules and receives collected data. It analyzes the output power of the power supply unit, the remaining capacity of the energy storage module, and the intensity of lighting demand, formulates dynamic energy allocation strategies, and coordinates the working status of the complementary power supply module, energy storage module, and lighting control module. The communication module adopts LoRa and WiFi dual-mode communication technology. LoRa is used for long-distance, low-power transmission of sensor data and control commands, while WiFi supports high-speed data interaction with the cloud management platform, enabling remote uploading of system status and receiving of control commands. The safety protection module integrates overcharge protection circuit, over-discharge protection circuit, short circuit protection circuit and over-temperature protection circuit. When abnormal voltage, current or temperature is detected, it automatically cuts off the relevant circuit or switches the working mode, and sends alarm information to the cloud platform to ensure the safety of system equipment and use.

[0027] This invention also includes an energy optimization calculation module, which calculates the optimal energy allocation ratio for each power supply unit using a quantization model. The calculation expression is as follows: in For the first Energy allocation ratio of power supply units When it is 1, it corresponds to the photovoltaic power supply unit. For the wind power supply unit at time 2 This is the backup power supply unit for the power grid at time 3. For the first Energy conversion efficiency of power supply units For the first Real-time output power coefficient of the power supply unit This is the maximum power supply of the system. For the first The priority weights of power supply units are set according to the principle of prioritizing renewable energy and backing up the grid. The comprehensive calculation of multi-dimensional parameters realizes the optimal solution for energy allocation and improves the system's energy utilization efficiency.

[0028] This invention also includes an adaptive lighting adjustment module, which dynamically adjusts the luminous intensity and lighting range of the LED lighting array based on the light intensity data collected by the environmental sensing module and information on human activity and traffic flow. When the ambient light intensity is higher than a set threshold and there are no people or vehicles, the lighting intensity is reduced to the minimum maintenance value. When people or vehicles are detected, the lighting intensity is quickly increased to an appropriate level. At the same time, the lighting coverage is adjusted according to the movement trajectory of people or the direction of traffic flow to achieve on-demand lighting.

[0029] This invention also includes a remote monitoring module, which enables centralized monitoring of multiple lighting systems through a cloud management platform. The platform displays the power supply status, remaining energy storage capacity, lighting parameters, sensor data, and fault alarm information of each device in real time. It supports managers to remotely issue dimming commands, switch power supply modes, and set operating parameters. At the same time, it generates energy consumption statistics reports and equipment operation logs to provide data support for system operation and maintenance.

[0030] This invention also includes a fault diagnosis module, which collects operating parameters such as current, voltage, and temperature of each module to establish a fault feature database. It uses machine learning algorithms to compare and analyze real-time data with normal parameter thresholds to accurately identify common problems such as photovoltaic panel shading, battery degradation, LED bead damage, and sensor failure. It locates the fault location and sends alarm information in a graded manner, while providing fault handling suggestions to shorten the maintenance cycle.

[0031] This invention also includes an energy storage status prediction module. Based on the historical charging and discharging data of the energy storage module, the current remaining capacity, the ambient temperature and future power supply prediction data, a time series prediction algorithm is used to predict the change trend of the remaining capacity of the battery pack in the next 24 hours. When insufficient energy storage is predicted, the grid backup power supply unit is triggered in advance to avoid lighting interruption due to energy shortage.

[0032] This invention also includes a load balancing module, which monitors the operating current and power consumption of each branch of the LED lighting array in real time. It adjusts the power distribution of each branch through an intelligent shunt circuit to ensure that the operating current of each LED bead is uniform and consistent, avoiding overload damage to some LED beads due to uneven load. At the same time, it balances the overall power consumption, reduces energy waste, and extends the service life of the LED lighting array.

[0033] This invention includes the following steps: Step 1: Energy harvesting and monitoring. The photovoltaic power supply unit and wind power supply unit of the complementary power supply module simultaneously harvest solar and wind energy from the environment and convert it into electrical energy. The energy monitoring unit collects the output power and conversion efficiency data of each power supply unit in real time. The grid backup power supply unit is in standby mode and monitors the stability of the mains power in real time. Step 2: Energy storage and status assessment. The energy storage module receives electrical energy output from the complementary power supply module, stores it in the lithium battery pack after voltage matching through a bidirectional DC-DC converter, and at the same time, the temperature sensor and voltage monitoring unit collect the temperature, voltage and remaining capacity data of the battery pack to assess the current storage capacity and working status of the battery. Step 3: Environmental data acquisition and lighting demand analysis. The sensors of the environmental perception module synchronously collect data on light intensity, human activity, temperature and humidity, and traffic flow. The lighting control module combines the preset lighting standards to analyze the lighting demand intensity, lighting range, and duration in the current scene. Step 4: Energy dispatch strategy formulation. The energy dispatch module receives power supply monitoring data, energy storage status data, and lighting demand data, calls the energy allocation algorithm, and determines the power supply priority and energy allocation ratio of photovoltaic, wind power, and grid. When the output of renewable energy is sufficient, photovoltaic and wind power are used first, and the remaining energy is stored in the battery pack. When the output of renewable energy is insufficient, the energy stored in the battery pack is used to supplement it. When the remaining capacity of the battery pack is lower than the threshold, the grid backup power supply is activated. Step 5: Lighting parameter adjustment. Based on the scheduling strategy and lighting demand analysis results, the lighting control module adjusts the power supply current through the LED driver circuit. The intelligent dimming unit achieves stepless dimming, and the LED lighting array operates according to the set luminous intensity and lighting range, while maintaining a stable light source without flicker. Step Six: Safety Monitoring and Feedback. The safety protection module monitors the voltage, current, and temperature data of each module in real time. When an abnormality is detected, the protection mechanism is immediately triggered. The communication module uploads the system operating status, energy scheduling results, and abnormal alarm information to the cloud platform, forming a closed-loop feedback.

[0034] In this invention, a dynamic priority mechanism is introduced when formulating the energy dispatch strategy in step four. The priority of the power supply units is dynamically adjusted according to real-time energy conditions and lighting scenarios. During the daytime when there is sufficient sunlight, the photovoltaic power supply unit has the highest priority, followed by the wind power supply unit. At night or on cloudy or rainy days, the priority of the wind power supply unit is increased, and the insufficient part is supplemented by the battery pack and the grid. During the period of dense population or heavy traffic, the priority of the grid backup power supply unit is temporarily increased to ensure continuous and stable lighting. The dynamic priority adjustment combines environmental changes and demand fluctuations to further improve energy utilization efficiency and lighting reliability.

[0035] This invention also includes an energy storage optimization management step. Based on the prediction results of the energy storage status prediction module, when the grid electricity price is low and the remaining capacity of the battery pack is lower than a set value, the grid backup power supply unit is controlled to charge the battery pack. When the electricity price is high and the renewable energy output is sufficient, renewable energy is given priority to power the battery pack and charge it, reducing the dependence on grid power supply. At the same time, the charging and discharging rate is adjusted according to the battery pack temperature data. When the temperature is too high, the charging and discharging current is reduced to avoid battery performance degradation. Through energy storage optimization management, the battery life is extended and the electricity cost is reduced.

[0036] The following two examples further illustrate the specific implementation of this system: Example 1: Application of LED Complementary Power Supply Smart Lighting in Urban Roads This embodiment is applied to the lighting scenario of urban main roads. The road section is 2 kilometers long and a total of 50 sets of the present invention system are deployed. The core requirement is to ensure continuous and stable nighttime traffic lighting, realize on-demand lighting in combination with traffic flow changes, maximize the use of photovoltaic and wind power clean energy, reduce the dependence on grid power supply, and improve the convenience of operation and maintenance and operational safety. It solves the problems of high energy consumption, poor adaptability and high operation and maintenance costs of traditional road lighting.

[0037] The complementary power supply modules are installed along the roadside. The photovoltaic power supply unit uses high-efficiency monocrystalline silicon photovoltaic panels, with the tilt angle set according to the local latitude to improve solar energy collection efficiency. Each system is equipped with two photovoltaic panels connected in parallel. The wind power supply unit uses a small vertical axis wind turbine, installed on the top of the light pole, suitable for the low to medium wind speed environment common in urban roads. The grid backup power supply unit is connected to the mains power line through an intelligent switching switch. The intelligent switching switch has a built-in voltage monitoring unit to monitor the stability of the mains voltage in real time. The three form a multi-source complementary power supply architecture, automatically switching the main power source according to environmental energy conditions.

[0038] The energy storage module uses a high-capacity lithium iron phosphate battery pack. The battery capacity of a single system is configured to meet the lighting needs for three consecutive cloudy or rainy nights. It is equipped with a bidirectional DC-DC converter to achieve bidirectional voltage conversion from 48V to 12V, ensuring efficient energy storage and release. The battery pack has built-in temperature sensors and voltage monitoring units. The temperature is sampled once per minute, and the voltage is sampled once per second, collecting real-time battery operating status data and uploading it to the energy dispatch module.

[0039] In the lighting control module, the LED driver circuit adopts a constant current driving scheme, and the output current accuracy is controlled within ±5mA to ensure stable operation of the light source without flicker; the intelligent dimming unit supports stepless dimming from 0 to 100%, and achieves smooth adjustment of light intensity through PWM dimming technology; the LED lighting array uses high-efficiency and low-power surface-mount LED beads, arranged according to the principle of uniform light distribution, and the lighting coverage of a single system is 15 to 20 meters, which meets the lighting standards of urban main roads.

[0040] The environmental sensing module deploys sensors evenly along the road. Light intensity sensors are installed on the side of the light pole to avoid interference from direct sunlight, collecting ambient light intensity data in real time at a frequency of twice per minute. Human infrared sensors and traffic flow sensors are integrated; the traffic flow sensor collects vehicle flow data via microwave detection at a frequency of once per second, while the human infrared sensor assists in detecting pedestrian activity. Temperature and humidity sensors are deployed at the bottom of the light pole in a ventilated area to collect ambient temperature and humidity data for battery status assessment. All sensors employ a low-power design, with a sleep current of less than 10μA, ensuring continuous operation.

[0041] The energy dispatch module, as the core control unit of the system, connects to various functional modules via a bus and receives real-time data such as the output power of the power supply units, the remaining capacity of the energy storage modules, and the intensity of lighting demand. The energy optimization calculation module calculates the optimal energy allocation ratio for each power supply unit using a quantification model; the calculation expression is as follows: in For the first Energy allocation ratio of power supply units When it is 1, it corresponds to the photovoltaic power supply unit. For example, the wind power supply unit corresponds to time 2. This is the backup power supply unit for the power grid at time 3. We take 0.85 as the energy conversion efficiency of the photovoltaic power supply unit. We take 0.75 as the energy conversion efficiency of the wind power supply unit. The energy conversion efficiency of the grid backup power supply unit is set at 0.98. Take 0.9 as the real-time output power factor of the photovoltaic power supply unit during a sunny day. We take 0.6 as the real-time output power coefficient of the wind power supply unit during daytime medium wind speeds. Take 1.0 as the real-time output power coefficient of the power grid backup power supply unit; Take 500W as the maximum power supply for a single system; The priority weight of the photovoltaic power supply unit is set to 0.6. We assign a priority weight of 0.3 to the wind power supply unit. We assign a priority weight of 0.1 to the power grid backup power supply unit. The calculation yields... =0.85×0.9×500×0.6÷(0.85×0.9×0.6+0.75×0.6×0.3+0.98×1.0×0.1)×500=229.5÷302×500≈365.5W, accounting for 73.1%; =0.75×0.6×500×0.3÷302×500≈67.5÷302×500≈111.8W, accounting for 22.4%; =0.98×1.0×500×0.1÷302×500≈49÷302×500≈81.7W, accounting for 16.3%. According to this proportion, energy is allocated to give priority to the use of renewable energy.

[0042] The communication module adopts LoRa and WiFi dual-mode communication technology. The LoRa communication range covers 1 kilometer and is used for long-distance, low-power transmission of sensor data and control commands. The 50 systems are divided into 5 groups, and each group aggregates data through a LoRa gateway. The WiFi module establishes a high-speed data link between the system and the cloud management platform, with a transmission rate of no less than 10Mbps, enabling remote uploading of system status and receiving of control commands.

[0043] The safety protection module integrates multiple protection circuits. The overcharge protection circuit is triggered when the battery voltage reaches 54.6V, cutting off the charging circuit; the over-discharge protection circuit is triggered when the battery voltage is below 40.5V, limiting the discharge output; the short circuit protection circuit quickly cuts off the circuit when the circuit current exceeds 10A, with a response time of less than 1ms; and the over-temperature protection circuit is triggered when the battery temperature exceeds 60℃, reducing the charging and discharging current, and cutting off the circuit when the temperature exceeds 65℃, while simultaneously sending alarm information to the cloud platform.

[0044] The remote monitoring module enables centralized monitoring of 50 systems through a cloud-based management platform. The platform displays the power supply status, remaining energy storage capacity, lighting parameters, sensor data, and fault alarm information for each device in real time. Administrators can remotely issue dimming commands, switch power supply modes, and set operating parameters through the platform. The platform generates daily, weekly, and monthly energy consumption statistics reports and equipment operation logs, providing data support for operation and maintenance. The fault diagnosis module establishes a fault characteristic database, collects operating parameters such as current, voltage, and temperature from each module, and uses machine learning algorithms to compare and analyze real-time data with normal parameter thresholds. This accurately identifies problems such as photovoltaic panel shading, battery degradation, LED chip damage, and sensor malfunctions, pinpointing the fault location and sending alarm information in a tiered manner.

[0045] Table 1 Comparison of the operational effects of urban road lighting systems Table 1 clearly demonstrates the significant advantages of the system of this invention in urban road lighting scenarios. Traditional road lighting systems rely on a single power grid, resulting in low clean energy utilization, high energy consumption, and fixed lighting intensity that cannot adapt to changes in traffic flow, leading to poor adaptability. The system of this invention significantly improves the utilization rate of clean energy and reduces energy consumption through multi-source complementary power supply and optimized energy allocation. Adaptive illumination adjustment combined with traffic flow changes enables on-demand lighting, improving adaptability. Remote monitoring and fault diagnosis modules improve operation and maintenance efficiency and fault response speed, while multiple safety protections ensure operational stability, comprehensively addressing the shortcomings of traditional systems and adapting to the high requirements of urban road lighting.

[0046] Example 2: Application of LED Complementary Power Supply Smart Lighting in Industrial Parks This embodiment is applied to lighting scenarios in large industrial parks, covering factory roads, the perimeter of production workshops, and storage areas. A total of 80 sets of the system of this invention are deployed. The core requirements are to achieve precise lighting by combining personnel activities and working hours, optimize energy storage management strategies to reduce electricity costs, ensure stable operation of the system in complex industrial environments, improve the convenience of operation and maintenance, and solve the problems of high energy consumption, poor adaptability, unreasonable energy storage management, and high operation and maintenance difficulty of traditional industrial park lighting.

[0047] The complementary power supply module is suitable for the layout and installation of industrial parks. The photovoltaic power supply unit uses high-efficiency monocrystalline silicon photovoltaic panels, which are installed on the roof of the storage area and on the top of the light poles to maximize the use of idle space to collect solar energy. The wind power supply unit is equipped with a small vertical axis wind turbine, which is installed in the open area at the edge of the factory area to adapt to the wind conditions of the open environment of the industrial park. The grid backup power supply unit is connected to the factory's mains power grid through an intelligent transfer switch. The intelligent transfer switch is linked with the factory's power distribution system to ensure smooth power supply switching.

[0048] The energy storage module uses a high-capacity lithium iron phosphate battery pack. A single system's battery capacity is configured to meet lighting needs for five consecutive cloudy / rainy days. A bidirectional DC-DC converter ensures efficient energy storage and release through voltage conversion. The energy storage status prediction module uses a time-series prediction algorithm based on historical charge / discharge data, current remaining capacity, ambient temperature, and future power supply prediction data to predict the remaining capacity trend of the battery pack over the next 24 hours. The load balancing module monitors the operating current and power consumption of each branch of the LED lighting array in real time. Through an intelligent shunt circuit, it adjusts the power distribution of each branch to ensure a uniform operating current for each LED.

[0049] In the lighting control module, the LED driver circuit adopts a constant current driving scheme to ensure the stability of the light source, and the intelligent dimming unit supports stepless dimming from 0 to 100% to adapt to the lighting needs of different areas; the LED lighting array is arranged according to the characteristics of the area, the factory road area is arranged according to the principle of uniform lighting, and the outer area of ​​the production workshop is arranged according to the principle of key coverage to ensure that the lighting meets the requirements of industrial operation.

[0050] The environmental sensing module deploys sensors by region. Light intensity sensors collect ambient light intensity data in real time, human infrared sensors detect human activity in the area, and are densely deployed around the production workshop and in the storage area; traffic flow sensors collect data on the flow of freight vehicles in the factory area; and temperature and humidity sensors collect ambient temperature and humidity data to support battery status assessment and energy storage prediction.

[0051] The energy dispatch module receives data from various modules and formulates dynamic energy allocation strategies. The energy optimization calculation module calculates the optimal energy allocation ratio according to a quantitative model, ensuring priority utilization of renewable energy. The energy storage optimization management steps of the energy dispatch method are based on the prediction results of the energy storage state prediction module. During periods of low grid electricity prices and when the remaining capacity of the battery pack is lower than a set value, the grid backup power supply unit is controlled to charge the battery pack; during periods of high electricity prices and when renewable energy output is sufficient, renewable energy is prioritized for power supply and battery pack charging, reducing dependence on grid power. Simultaneously, the charging and discharging rates are adjusted based on battery pack temperature data; when the temperature is too high, the charging and discharging current is reduced to prevent battery performance degradation.

[0052] The communication module employs LoRa and WiFi dual-mode communication technology, covering the entire industrial park and enabling efficient transmission of sensor data and control commands, as well as remote uploading of system status. The safety protection module ensures safe system operation in complex industrial environments, with multiple protection circuits to handle various abnormal conditions and alarm information uploaded to the cloud platform in real time.

[0053] The system iteration and optimization module collects operational data, fault feedback, and energy consumption data from 80 systems in the park. It uses machine learning algorithms to analyze system performance shortcomings and energy allocation optimization space, optimizes energy allocation model parameters, lighting adaptation strategies, and fault diagnosis algorithms, and continuously improves system performance.

[0054] Table 2 Comparison of the Operational Effects of Lighting Systems in Industrial Parks Table 2 highlights the core value of this invention's system in industrial park lighting scenarios. Traditional industrial park lighting systems have fixed lighting intensity, failing to adapt to changes in personnel activity and work hours, exhibiting poor precision adaptability. Inadequate energy storage management leads to high electricity costs, and their adaptability to complex industrial environments is generally limited. Furthermore, maintenance relies heavily on on-site operation, resulting in inconvenience. This invention's system achieves precise lighting through adaptive light adjustment, improving personnel safety. Optimized energy storage management strategies reduce electricity costs, while multiple safety protections and adaptive designs enhance adaptability to complex environments. Remote monitoring and fault diagnosis improve maintenance convenience, comprehensively optimizing the operational effectiveness and economy of industrial park lighting.

[0055] Reference Figure 3 This diagram visually demonstrates the core advantages of this invention's system in clean energy utilization, addressing the pain points of traditional LED lighting systems that rely on a single power grid and suffer from inefficient renewable energy utilization. Traditional systems simply add photovoltaic or wind power components, lacking precise energy scheduling and allocation mechanisms, resulting in clean energy utilization rates below 20% in various scenarios, failing to fully realize the value of renewable energy. This invention integrates photovoltaic, wind, and grid power supply through complementary power supply modules, dynamically allocating energy ratios using an energy optimization calculation model, prioritizing the use of renewable energy, and adjusting power supply strategies according to the energy conditions of different scenarios. Utilization rates reach 85% in commercial districts and 82% in industrial parks, significantly improving clean energy absorption capacity and aligning with the low-carbon development needs of the lighting sector under dual-carbon goals.

[0056] Reference Figure 4This diagram clearly demonstrates the technical advantages of the energy storage status prediction module of this invention, overcoming the shortcomings of traditional prediction methods where accuracy decays too rapidly over time. Traditional predictions are based solely on simple calculations of the battery's current remaining capacity, without incorporating multi-dimensional data such as ambient temperature and renewable energy output predictions. The 24-hour prediction accuracy is only 58%, failing to anticipate the risk of insufficient energy storage. This invention employs a time-series prediction algorithm that integrates historical battery charge / discharge data, ambient temperature and humidity, and future power supply prediction information. Even with a prediction period of 30 hours, the accuracy remains at 90%, and the 24-hour prediction accuracy reaches 92%. It can accurately predict energy storage trends in advance, promptly triggering grid backup power intervention, avoiding lighting interruptions due to energy storage shortages, and ensuring system power continuity.

[0057] Reference Figure 5 This figure clearly reveals the significant advantages of the system in energy consumption control, breaking through the limitation of traditional systems where energy consumption increases linearly with lighting duration. Traditional systems use a fixed-power lighting mode, lacking on-demand dimming and clean energy replenishment, resulting in 24-hour lighting energy consumption of 15.6 kWh, leading to serious energy waste. This invention, through an adaptive light adjustment module, dynamically adjusts lighting intensity based on ambient light intensity and pedestrian / vehicle traffic demand, while prioritizing the use of clean energy sources such as photovoltaic and wind power. The energy consumption growth trend is much slower than traditional systems, with 24-hour lighting energy consumption of only 4.6 kWh, just 29.5% of that of traditional systems. This low-energy consumption characteristic not only reduces dependence on grid power but also reduces operating costs, making it particularly suitable for scenarios with long lighting durations, such as roads and industrial parks, demonstrating significant economic and environmental benefits.

[0058] The above are merely preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A smart lighting system with complementary LED power supply, characterized in that, Includes the following modules: The complementary power supply module integrates a photovoltaic power supply unit, a wind power supply unit, and a grid backup power supply unit. The photovoltaic power supply unit uses high-efficiency monocrystalline silicon photovoltaic panels, the wind power supply unit is equipped with a small vertical axis wind turbine, and the grid backup power supply unit is connected to the mains power through an intelligent switching switch. The three form a multi-source complementary power supply architecture. The energy storage module uses a high-capacity lithium iron phosphate battery pack, paired with a bidirectional DC-DC converter. The battery pack has a built-in temperature sensor and voltage monitoring unit to collect data in real time. The lighting control module includes an LED driver circuit, an intelligent dimming unit, and an LED lighting array. The LED driver circuit adopts a constant current driving scheme, the intelligent dimming unit supports stepless dimming from 0 to 100%, and the LED lighting array uses high-efficiency and low-power LED chips. The environmental perception module deploys a light intensity sensor, a human infrared sensor, a temperature and humidity sensor, and a traffic flow sensor. The light intensity sensor collects ambient light intensity data in real time, the human infrared sensor detects the activity of people in the area, and the traffic flow sensor is adapted to road lighting scenarios to collect vehicle flow information. The energy scheduling module connects to various functional modules and receives collected data. It analyzes the output power of the power supply unit, the remaining capacity of the energy storage module, and the intensity of lighting demand, formulates dynamic energy allocation strategies, and coordinates the working status of the complementary power supply module, energy storage module, and lighting control module. The communication module adopts LoRa and WiFi dual-mode communication technology. LoRa is used for long-distance, low-power transmission of sensor data and control commands, while WiFi supports high-speed data interaction with the cloud management platform. The safety protection module integrates overcharge protection circuit, over-discharge protection circuit, short circuit protection circuit and over-temperature protection circuit. When abnormal voltage, current or temperature is detected, it automatically cuts off the relevant circuit or switches the working mode, and sends alarm information to the cloud platform at the same time.

2. The LED complementary power supply intelligent lighting system according to claim 1, characterized in that, It also includes an energy optimization calculation module, which calculates the optimal energy allocation ratio for each power supply unit using a quantification model. The calculation expression is as follows: in For the first Energy allocation ratio of power supply units For the first Energy conversion efficiency of power supply units For the first Real-time output power coefficient of the power supply unit This is the maximum power supply of the system. For the first Priority weights for power supply units.

3. The LED complementary power supply intelligent lighting system according to claim 1, characterized in that, It also includes an adaptive lighting adjustment module, which dynamically adjusts the luminous intensity and lighting range of the LED lighting array based on the light intensity data collected by the environmental sensing module and information on human activity and traffic flow. When the ambient light intensity is higher than the set threshold and there are no people or vehicles, the lighting intensity is reduced to the minimum maintenance value. When people or vehicles are detected, the lighting intensity is quickly increased to the appropriate level, and the lighting coverage is adjusted according to the movement trajectory of people or the direction of traffic flow.

4. The LED complementary power supply intelligent lighting system according to claim 1, characterized in that, It also includes a remote monitoring module, which enables centralized monitoring of multiple lighting systems through a cloud management platform. The platform displays the power supply status, remaining energy storage capacity, lighting parameters, sensor data and fault alarm information of each device in real time. It supports managers to remotely issue dimming commands, switch power supply modes, and set operating parameters, while generating energy consumption statistics reports and equipment operation logs.

5. The LED complementary power supply intelligent lighting system according to claim 1, characterized in that, It also includes a fault diagnosis module, which collects the operating parameters of each module, establishes a fault feature database, uses machine learning algorithms to compare and analyze real-time data with normal parameter thresholds, identifies common problems of photovoltaic panels, locates fault locations and sends alarm information in a graded manner, and provides fault handling suggestions to shorten the maintenance cycle.

6. The LED complementary power supply intelligent lighting system according to claim 1, characterized in that, It also includes an energy storage status prediction module, which uses a time series prediction algorithm to predict the trend of the battery pack's remaining capacity over the next 24 hours based on the historical charge and discharge data of the energy storage module, the current remaining capacity, the ambient temperature and future power supply prediction data.

7. The LED complementary power supply intelligent lighting system according to claim 1, characterized in that, It also includes a load balancing module, which monitors the operating current and power consumption of each branch of the LED lighting array in real time, adjusts the power distribution of each branch through intelligent shunt circuit, and balances the overall power consumption to extend the service life of the LED lighting array.

8. An energy dispatching method for a smart lighting system using LED complementary power supply as described in any one of claims 1-7, characterized in that, Includes the following steps: Step 1: Energy Acquisition and Monitoring. The photovoltaic and wind power supply units of the complementary power supply module collect solar and wind energy and convert them into electrical energy. The energy monitoring unit collects the output power and conversion efficiency data of each power supply unit in real time. The grid backup power supply unit is on standby and monitors the stability of the mains power. Step 2: Energy storage and status assessment. The energy storage module receives electrical energy from the complementary power supply module, and after voltage matching by the bidirectional DC-DC converter, it is stored in the lithium battery pack. The temperature sensor and voltage monitoring unit collect battery data to assess the battery's storage capacity and operating status. Step 3: Environmental data acquisition and lighting demand analysis. The environmental sensing module collects data on light intensity, human activity, temperature and humidity, and traffic flow simultaneously from various sensors. The lighting control module analyzes the current lighting demand intensity, range, and duration in conjunction with preset lighting standards. Step 4: Energy dispatch strategy formulation. The energy dispatch module receives power supply monitoring, energy storage status and lighting demand data, calls the energy allocation algorithm to determine priority and allocation ratio, prioritizes the use of renewable energy when it is sufficient, and calls the battery pack to supplement when it is insufficient. Step 5: Lighting parameter adjustment. Based on the scheduling strategy and lighting demand analysis results, the lighting control module adjusts the power supply current through the LED driver circuit. The intelligent dimming unit completes stepless dimming, and the LED lighting array operates according to the set parameters and maintains a stable light source without flicker. Step Six: Safety Monitoring and Feedback. The safety protection module monitors the voltage, current, and temperature data of each module in real time. When an abnormality occurs, the protection mechanism is triggered. The communication module uploads the system's working status, scheduling results, and abnormal alarm information to the cloud platform, forming a closed-loop feedback.

9. The energy dispatching method for a smart lighting system with complementary LED power supply according to claim 8, characterized in that, In step four, a dynamic priority mechanism is introduced when formulating the energy dispatch strategy. The priority of power supply units is dynamically adjusted according to real-time energy conditions and lighting scenarios. During the daytime when there is sufficient sunlight, the priority of photovoltaic power supply units is the highest, followed by wind power supply units. At night or on cloudy or rainy days, the priority of wind power supply units is increased, and the insufficient part is supplemented by battery packs and the grid. During periods of high population density or heavy traffic, the priority of grid backup power supply units is temporarily increased.

10. The energy dispatching method for a smart lighting system with complementary LED power supply according to claim 8, characterized in that, It also includes energy storage optimization management steps. Based on the prediction results of the energy storage status prediction module, when the grid electricity price is low and the remaining capacity of the battery pack is lower than the set value, the grid backup power supply unit is controlled to charge the battery pack. When the electricity price is high and the renewable energy output is sufficient, renewable energy is given priority to power supply and charge the battery pack. At the same time, the charging and discharging rate is adjusted according to the battery pack temperature data.

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