Garden landscape lamp intelligent control method and system

Abstract

The invention discloses an intelligent control method and system for a garden landscape lamp, and belongs to the technical field of computers. The method comprises the following steps: constructing a local collaborative energy supply network between garden landscape lamps, and forming a node group capable of realizing electric energy interaction through physical or logic connection; each lamp collects the running state of the lamp in real time and periodically exchanges state information with adjacent lamps through short-distance wireless communication; on the basis of the state information, the local controller of each lamp autonomously executes a distributed electric energy scheduling algorithm, dynamically shares electric energy among nodes, and adaptively adjusts the illumination brightness according to the overall energy condition of the region; meanwhile, the lamps execute local fault self-diagnosis in parallel and report faults through neighbor nodes in a relay mode when the faults are diagnosed. According to the system, through decentralized cooperative control, energy mutual aid, fault self-healing and illumination guarantee of the landscape lamp group without external centralized intervention are realized, and the overall energy efficiency, illumination continuity and operation reliability of the system are effectively improved.

Description

Technical Field

[0001] This invention belongs to the field of computer technology, specifically relating to an intelligent control method and system for garden landscape lighting. Background Technology

[0002] With the development of smart city and green ecological concepts, solar landscape lights have been widely used in various garden lighting scenarios due to their advantages such as energy saving, environmental protection, and flexible installation. Currently, these lights typically adopt an "autonomous single-lamp" architecture with independent power supply, possessing photovoltaic power generation, energy storage, and lighting functions.

[0003] However, existing technical solutions have significant shortcomings: First, the lack of energy interaction between individual lamps creates "energy islands," which can lead to premature extinguishing of some lamps during periods of uneven lighting or continuous cloudy weather, affecting the continuity of lighting. Second, system faults are mainly detected through manual inspections, making timely warnings and location difficult. Third, the closed-loop energy system of individual lamps means that excess power generated by lamps cannot be utilized by neighboring lamps that are short of power, resulting in low overall energy efficiency. Furthermore, although some solutions introduce remote centralized control, their energy scheduling is constrained by network latency and stability, making it difficult to achieve rapid local response.

[0004] Therefore, existing technologies lack a landscape lighting control scheme that can achieve intelligent energy sharing, collaborative status perception, and autonomous fault handling among lighting fixtures based on local autonomy. Summary of the Invention

[0005] To address the aforementioned technical problems, this application provides an intelligent control method and system for garden landscape lighting, the specific solution of which is shown below:

[0006] Firstly, a method for intelligent control of garden landscape lighting includes:

[0007] Construct a local collaborative power supply network among garden landscape lights, enabling each light fixture to physically or logically interact with electrical energy;

[0008] Each lamp's local controller collects its own lamp's operating status data in real time and periodically exchanges status information with neighboring lamps via short-range wireless communication.

[0009] Each lamp's local controller autonomously executes a distributed power dispatch algorithm based on its own and the status information received from neighboring lamps, in order to achieve dynamic power sharing among lamps within the collaborative power supply network.

[0010] The local controller of each lamp adaptively adjusts its lighting output based on the overall energy status of the coordinated power supply network.

[0011] Each lamp's local controller performs local fault self-diagnosis in parallel, and when a fault is diagnosed, it relays the fault information to neighboring lamps via the short-range wireless communication.

[0012] Preferably, constructing a local collaborative energy supply network includes:

[0013] The DC bus interfaces of adjacent garden landscape lights are connected one-to-one by physical wires to form a local DC microgrid;

[0014] Each lamp is connected to the common DC bus of the DC microgrid via its built-in bidirectional DC converter.

[0015] Preferably, the topology of the DC microgrid is a tree structure or a ring structure;

[0016] The number of interconnected lamps within a single collaborative power supply network does not exceed a preset threshold, and different collaborative power supply networks are electrically isolated from each other through series diodes.

[0017] Preferably, the periodic exchange of state information is achieved through a time-division multiple access-based self-organizing network protocol;

[0018] The status information includes at least the state of charge of the energy storage unit, photovoltaic input power, load power consumption, and fault flag bits.

[0019] Preferably, the distributed power dispatch algorithm includes:

[0020] Based on the preset guaranteed power capacity, calculate the dispatchable power margin of this lamp and the power gap of each adjacent lamp.

[0021] If the lamp has a power dispatchable margin and at least one adjacent lamp has a power shortage, dispatch pairing is initiated.

[0022] The scheduling weight is determined based on the proportion of the available power capacity of this lamp in the total local power capacity, and the proportion of the power shortage of the lamps near the target in the total local power shortage.

[0023] The bidirectional DC-DC converter is controlled according to the scheduling weights to perform power transmission of a specific power and duration.

[0024] Preferably, the guaranteed power is calculated based on the load power required to maintain the minimum illuminance, the preset guarantee duration, and the comprehensive efficiency coefficient.

[0025] Preferably, adaptive adjustment of lighting output includes:

[0026] The regional average state of charge is calculated based on the state of charge data obtained from nearby luminaires.

[0027] When the average state of charge of the area is lower than a first threshold, the lighting of the decorative area lights is turned off;

[0028] When the average state of charge in the area is lower than a second threshold below the first threshold, the illumination brightness of the secondary path lights is reduced.

[0029] When the average state of charge of the area is below a third threshold that is below the second threshold, only the critical path luminaires are maintained to operate at rated power.

[0030] Preferably, the local fault self-diagnosis includes light source fault diagnosis and energy storage unit aging diagnosis;

[0031] The light source fault diagnosis is based on whether the load current detected in the light-up command state is continuously lower than the judgment threshold.

[0032] The energy storage unit aging diagnosis is based on whether the rate of voltage drop at the terminals, monitored when the system is in a near-static state, exceeds a preset slope threshold.

[0033] Preferably, the method further includes:

[0034] A gateway node is set up in the collaborative energy supply network. The gateway node is used to aggregate the status information of lamps in the area, receive structured fault reports, and interact with the remote management platform through a remote communication module.

[0035] Secondly, a smart control system for garden landscape lighting, the system comprising multiple garden landscape lighting units, each garden landscape lighting unit comprising:

[0036] Photovoltaic charging unit, energy storage unit, LED light source and load circuit for powering it;

[0037] A bidirectional DC-DC converter is connected between the energy storage unit and the DC bus interface to enable power exchange with the coordinated power supply network.

[0038] A local controller, configured to collect operating status data and execute the control logic as described in claim 1;

[0039] A short-range wireless communication module, connected to the local controller, is used to exchange status information with nearby lamps;

[0040] In this configuration, the DC bus interfaces of adjacent lamps are connected by physical wires to form a local collaborative power supply network; or, the lamps are connected by the short-range wireless communication module to form a logical collaborative network.

[0041] In summary, this application includes at least one of the following beneficial technical effects:

[0042] 1. This invention enables dynamic energy sharing among landscape lighting fixtures by constructing a decentralized local collaborative network, effectively breaking down "energy silos" and allowing for autonomous adjustment of energy surplus and shortage in local areas, thereby improving the overall energy utilization efficiency of the system and ensuring the continuity and reliability of lighting services.

[0043] 2. This invention integrates local fault self-diagnosis and a neighbor-based collaborative information relay reporting mechanism, which can autonomously discover and locate lighting faults without relying on manual inspections or stable remote communication, thereby significantly reducing the difficulty and cost of operation and maintenance, and enhancing the system's autonomous operation and self-healing capabilities.

[0044] 3. This invention can coordinate and adjust the lighting brightness of each lamp in a hierarchical manner according to the real-time perceived overall energy status of the area. It can intelligently ensure lighting of critical paths when the system energy is insufficient and provide comfortable panoramic lighting when the energy is sufficient, thus achieving a dynamic balance and optimization between energy saving and service quality. Attached Figure Description

[0045] Figure 1 This is a flowchart illustrating an intelligent control method for garden landscape lighting according to the present invention.

[0046] Figure 2 This is a flowchart illustrating the decentralized landscape lighting cluster local collaborative power supply network in this invention.

[0047] Figure 3 This is a schematic diagram of the process of coordinated execution of distributed energy scheduling and fault self-diagnosis in this invention. Detailed Implementation

[0048] This invention provides a method and system for intelligent control of garden landscape lighting. Its core lies in constructing a decentralized local collaborative energy supply network architecture, forming a DC microgrid through physical wire interconnection, and combining a distributed energy dispatching algorithm and a self-diagnostic communication mechanism to achieve dynamic energy sharing among lighting fixtures, fault self-identification, and adaptive adjustment of lighting strategies without cloud intervention.

[0049] To further illustrate the technical means and effects adopted by the present invention in order to achieve the intended purpose, the following detailed description is provided in conjunction with the accompanying drawings and preferred embodiments, based on specific implementation methods of the present invention.

[0050] Example 1

[0051] A method for intelligent control of garden landscape lighting includes the following steps:

[0052] S1: The hardware foundation for building a decentralized, locally collaborative power supply network. This includes the following:

[0053] S101: Inside each garden landscape light, there is an integrated photovoltaic charging unit for converting solar energy into electrical energy, an energy storage unit for storing electrical energy, a DC bus interface for electrical energy exchange, a local controller for intelligent control, and a short-range wireless communication module for proximity communication.

[0054] S102: Through the DC bus interface, adjacent garden landscape lights are connected one-to-one using physical wires, thereby constructing a physically interconnected DC microgrid in a local area.

[0055] The specific connection method is as follows: Each lamp's DC bus interface includes two polarity terminals, positive and negative, which are connected to the corresponding terminals of adjacent lamps in a "parallel connection" manner through a two-core cable, so that all connected lamps can operate in parallel on the same pair of DC buses to form a shared DC voltage platform.

[0056] The bus voltage is supported by the energy storage units of each lamp and remains stable near the rated voltage during normal operation.

[0057] It should be noted that this parallel connection is not a simple electrical direct connection. Each lamp is connected to the common bus through its built-in bidirectional DC-DC converter. This converter operates under the management of the local controller and can realize controllable energy exchange between the lamp's energy storage unit and the bus. On the one hand, this avoids the circulating current problem that may occur when different batteries are directly connected in parallel. On the other hand, it provides the hardware-level execution foundation for subsequent distributed energy dispatch, ensuring that each lamp can not only support the bus voltage together, but also flexibly adjust its own charging and discharging state according to dispatch instructions.

[0058] S103: The DC bus interface uses a dual-core waterproof aviation plug with a rated operating voltage of 24V and a rated operating current of 10A.

[0059] The plug integrates an electronic fuse with a fusing current threshold set at 12A, ensuring that the local circuit can be quickly cut off in the event of a short circuit or overcurrent, effectively preventing the fault from spreading to the entire network.

[0060] S104: The topology of a DC microgrid can be flexibly configured as a tree or ring.

[0061] In a tree structure, the lights are connected by branches, which is suitable for scenarios where they are arranged along a path. The structure is simple but the reliability is low. In a ring structure, the lights at the beginning and end are also connected to each other to form a closed loop, which can provide redundant power supply paths. It is suitable for key areas with high reliability requirements. In actual deployment, the appropriate topology can be selected according to the site layout and power supply reliability requirements.

[0062] The number of interconnected lights within a single collaborative area is recommended to not exceed 32. This number is determined based on a comprehensive consideration of the neighbor meter capacity of a typical narrowband IoT node, the communication load during the status broadcast cycle, and the local energy dispatch efficiency, in order to strike a balance between management complexity and collaborative benefits. Electrical isolation between different areas is achieved through series-connected Schottky diodes. The diodes have a rated current of not less than 15A and a forward voltage drop of less than 0.5V to reduce isolation losses.

[0063] In actual operation, the system's control logic works in conjunction with the aforementioned hardware topology. For the ring structure, its redundant power supply path primarily provides reliability at the physical layer, while the energy scheduling algorithm is still logically executed based on neighbor state information. Protocol design avoids scheduling command conflicts or loops caused by physical loops. The recommended limit on the number of lamps in a single area is mainly to ensure that the state information of all nodes can be reliably exchanged and distributed computing can be completed within a 2-second communication cycle. This value is based on experimental verification under typical hardware configurations. In addition, the forward voltage drop of diodes between areas has been uniformly considered in the system efficiency design. If necessary, compensation can be made by fine-tuning the reference value of the bus voltage of the preceding area to ensure power supply balance.

[0064] S2: Distributed state awareness and neighbor information interaction.

[0065] S201: The local controller of each garden landscape light collects the operating status data of the light in real time.

[0066] The specific data collected includes: real-time input power of the photovoltaic charging unit, current state of charge (SOC) of the energy storage unit, real-time load power consumption of the LED light source, and ambient light intensity.

[0067] It should be noted that the local controller reads the voltage, current, and light intensity analog signals from the corresponding sensors through its built-in analog-to-digital converter (ADC), and the power value is calculated in real time from the collected voltage and current values. For the state of charge of the energy storage unit, the local controller uses the coulomb integration method combined with open-circuit voltage calibration to estimate it.

[0068] Specifically, during normal operation, the battery current is integrated to accumulate changes in power. After the lamp has been idle for a long time, such as at night when there is no load and no charging, the measured battery open-circuit voltage is used to consult a preset voltage-SOC correspondence table for periodic calibration to eliminate the cumulative error of integration and ensure the long-term reliability of the SOC estimate.

[0069] S202: Each local controller periodically broadcasts information packets containing the above-mentioned operating status to the surrounding area through its integrated short-range wireless communication module; at the same time, it also continuously listens for and receives similar status information broadcast from nearby lighting fixtures.

[0070] Through the above steps S201 and S202, each lamp not only grasps its own real-time operating status, but also obtains the status information of neighboring lamps. By aggregating these local and neighboring status data, a complete information foundation is formed for subsequent intelligent collaborative decision-making, specifically including power scheduling and lighting adjustment.

[0071] S203: Short-range wireless communication module. Its core uses an RF transceiver chip operating in the 470MHz to 510MHz unlicensed frequency band. It supports GFSK modulation and the inter-node communication follows a self-organizing network protocol based on the Time Division Multiple Access (TDMA) principle.

[0072] This self-organizing network protocol is implemented in software on the local controller. Each communication cycle is fixed at 2 seconds and divided into three time slots:

[0073] Synchronization slots: Nodes in the network align their clocks by listening to and following the first received synchronization beacon, achieving coarse-grained time synchronization. The beacon can be sent by any normally functioning node in the area during its broadcast slot.

[0074] Broadcast time slots: Each node sends its own status information packet within its own time window, which is either pre-allocated or determined after random backoff. The information packet adopts a fixed-length format and includes a frame header, device ID, current SOC (2 bytes), photovoltaic input power (2 bytes), load power consumption (2 bytes), ambient light intensity (1 byte), fault flag bit (1 byte), and cyclic redundancy check code.

[0075] Response slot: Used for optional point-to-point acknowledgment. When a node receives a status packet from a neighbor that contains a scheduling request or fault alarm for this node, it can reply with a short acknowledgment frame within this time period to enhance the reliability of critical information exchange.

[0076] S204: Hardware and protocol design of the short-range wireless communication module, ensuring an effective communication distance of no less than 50 meters in a typical garden environment, with penetration loss through obstacles such as vegetation not exceeding 15dB. Typical RF parameters are: configurable transmit power of +17dBm, receive sensitivity better than -120dBm@1200bps, and the use of a spring antenna or PCB antenna with a gain of approximately 2dBi. This ensures stable status information exchange between adjacent or nearby lighting fixtures in real-world scenarios with significant obstruction from trees and shrubs.

[0077] S3: Distributed power coordinated dispatch and adaptive lighting guarantee.

[0078] S301: Each local controller periodically executes a distributed energy scheduling algorithm based on the status information of neighboring lights obtained in step S2 and its own real-time status information, in order to dynamically decide whether to interact with neighboring lights through the DC bus interface.

[0079] It should be noted that the preset thresholds (first, second, third, and fourth thresholds) are configurable system parameters. They are mainly used for quick preliminary screening at the beginning of the scheduling cycle to determine whether to initiate subsequent detailed scheduling calculations; they do not directly determine the scheduling volume themselves.

[0080] For example, a typical setup is as follows: when the state of charge of the lamp's energy storage unit is below 30% (first threshold) and there is a neighboring lamp with a state of charge above 80% (second threshold), the lamp can request to receive electrical energy; when the state of charge of the lamp's energy storage unit is above 85% (third threshold) and there is a neighboring lamp with a state of charge below 35% (fourth threshold), the lamp can actively output electrical energy.

[0081] The specific threshold can be adjusted according to the actual battery characteristics and lighting requirements.

[0082] S302: The specific sub-steps for executing the distributed energy scheduling algorithm are as follows:

[0083] S302a: Calculate the available power reserve of this lamp. .

[0084] Calculation formula: ;

[0085] in: This is the current charge level of the lamp's energy storage unit. To ensure power supply.

[0086] S302b: Calculate the power shortage of each adjacent light fixture. .

[0087] Calculation formula: ;

[0088] in: To provide the guaranteed power for the nth adjacent light fixture, Its current battery level.

[0089] The above steps assess the power supply and demand situation in the area by calculating the remaining capacity of this lamp and the gap with neighboring lamps, based on the concept of guaranteed power supply.

[0090] S302c: Perform scheduling pairing judgment.

[0091] Pairing conditions: and .

[0092] It should be noted that, in order to simplify decision-making and avoid conflicts, this embodiment adopts a "one-to-one" dominant scheduling mode. That is, within a single scheduling cycle, a lamp with spare capacity (power supply) selects only the neighbor with the largest gap as the scheduling object; at the same time, a lamp with a gap (power receiving) only accepts the power supply that first initiates a valid scheduling response to it. This rule is coordinated through the scheduling intention flag bit included in the status broadcast.

[0093] Under this mechanism, the first response is usually determined by the order in which the power receiving party receives the dispatch response message locally. To reduce pairing conflicts, after sending a response, the power supplier will continuously declare its current dispatch target in subsequent broadcasts until the dispatch is completed or a timeout occurs; if the power receiving party has already accepted another power supplier, it will notify the other party through a broadcast reply.

[0094] S302d: Assign scheduling weight W to the pairing relationship.

[0095] Calculation steps:

[0096] Calculate the percentage of remaining margin: ;

[0097] Calculate the gap percentage: ;

[0098] in, and These refer to the total surplus of all neighbors with the intention to supply power, and the total shortage of all neighbors with the intention to receive power, calculated by the current controller based on the received neighbor status information.

[0099] Determine the weights: .

[0100] S302e: Performs power dispatch based on weights.

[0101] Calculate the target power: ;

[0102] A PWM signal is generated to control the bidirectional DC-DC converter and adjust the power transmission capacity. The scheduling duration is 30 seconds.

[0103] S302f: Scheduling cycle management.

[0104] The complete scheduling algorithm is executed every 5 minutes, and pauses after 30 seconds of each scheduling to enter a monitoring and waiting period.

[0105] The above steps achieve dynamic and orderly sharing of electrical energy within the region through periodic supply and demand matching, weight allocation, and precise power control.

[0106] S303: Define and calculate the guaranteed power supply .

[0107] Calculation formula: .

[0108] in:

[0109] The load power required to maintain the minimum illuminance, measured in watts (W), can be determined through calculation or measurement based on the lighting standards of the target area (e.g., 15 lx) and the luminous efficacy and optical design of the selected LED luminaires, ensuring that... The minimum required illuminance can be achieved at the specified power level.

[0110] : Guarantee duration, i.e., the system requirement to maintain operation even under the most unfavorable conditions. The duration of power operation is set to 7200 seconds by default, but can be adjusted according to local climate characteristics and management requirements.

[0111] η: Overall efficiency, which mainly considers the energy loss during storage and transmission, including the average charging and discharging efficiency of the battery, the operating efficiency of the bidirectional DC-DC converter, and line losses, etc. It is usually taken as an empirical value of 0.92, which can be calibrated according to the actual hardware performance selected.

[0112] Example values, such as those based on typical LED lighting fixtures:

[0113] Primary path (requires 15 lx): ≈3W;

[0114] Secondary path (requires 8lx): ≈1.5W;

[0115] Decorative areas (require 3lx): ≈0.6W.

[0116] It should be noted that the above-mentioned guaranteed power supply The calculation formulas and parameter settings provide a clear design benchmark for the system. In practical applications, the system supports calibration of relevant parameters based on operational data or adjustment according to management strategies, thereby enabling energy dispatch and guarantee strategies to better adapt to changes in actual conditions during long-term operation.

[0117] S304: Set adaptive lighting priority strategy.

[0118] Zone division and illuminance requirements:

[0119] Primary route (main road, entrance / exit): 15 lx;

[0120] Secondary path (side paths, rest areas): 8 lx;

[0121] Decorative areas (flower beds, water features): 3 lx;

[0122] Based on average state of charge The lighting adjustment strategy is as follows:

[0123] when When the value is less than 0.4, turn off the landscape lighting output in all decorative areas.

[0124] when When the value is less than 0.25, based on the control of the previous level, the lighting brightness of the secondary path landscape lights is reduced to 50% of their rated brightness, for example, by limiting their LED drive current to 50% of the rated value.

[0125] when When the value is less than 0.15, based on the first two levels of control, only the first-level path landscape lights will be maintained to operate at normal rated power to ensure minimum safe illuminance.

[0126] To ensure that all luminaires in the area can coordinately and consistently perform the aforementioned graded lighting adjustments when energy decreases, the system design incorporates the following measures:

[0127] First, all the lights follow the same The calculation rules, including data sources, weights, and algorithms, maintain basic data synchronization based on periodic state broadcasts. Secondly, the thresholds set in the strategy, such as 0.4, 0.25, and 0.15, will introduce appropriate hysteresis intervals in practical applications. For example, around the 0.25 threshold, only when... Load throttling is triggered only after the value remains below 0.24 for a period of time, and is only deactivated after the value recovers to above 0.26 for a period of time, in order to avoid [further issues]. The frequent or contradictory switching actions caused by small fluctuations around the threshold effectively ensure the consistency of zonal lighting adjustment decisions in most cases.

[0128] It should be noted that the above The thresholds are empirical values ​​set after comprehensively considering the discharge characteristics of lithium iron phosphate batteries, the importance weight of lighting in different areas, and the duration of typical cloudy and rainy weather. They aim to gradually and systematically reduce non-core loads as system energy decreases, thereby maximizing the lighting time of the critical path. In practical applications, these thresholds can be fine-tuned based on specific battery models and operational strategies.

[0129] S4: Local fault self-diagnosis, hardware system and information collaboration.

[0130] S401: Fault Self-Diagnosis and Local Judgment

[0131] S401a: The local controller synchronously executes fault self-diagnosis logic at fixed intervals.

[0132] S401b: LED light source fault diagnosis.

[0133] Judgment criteria: When the controller outputs a normal lighting command, that is, the duty cycle of the PWM signal controlling the LED is greater than the preset lighting threshold, such as 90%, and the load current flowing through the LED light source is less than 10 mA for 5 consecutive self-diagnostic cycles.

[0134] Judgment Logic: This condition excludes normal situations where automatic dimming due to sufficient ambient light results in minimal current. Only when there is an "on command but no effective current" is the LED light source deemed to be faulty or the driver circuit open-circuited. The design of five consecutive cycles is to avoid misjudgments caused by momentary interference, striking a balance between reliability and fault response speed.

[0135] S401c: Energy storage unit aging fault determination.

[0136] Judgment Criteria: Under near-static conditions that meet the criteria of "no photovoltaic energy input" and "extremely low load energy output," such as when the photovoltaic panel output voltage is lower than the battery voltage and the total load current is less than 1mA, the system can be considered to have entered deep standby mode, and this is monitored continuously for 30 minutes. In this state, if the rate of decrease of the energy storage unit's terminal voltage measured online exceeds a preset slope threshold, for example, greater than 5 mV / min, then the energy storage unit is judged to be aging.

[0137] Judgment Criteria: Based on the extremely low self-discharge rate of lithium iron phosphate batteries in a healthy state, an abnormally rapid drop in voltage usually indicates aging phenomena such as increased internal resistance and electrolyte drying. The example threshold (5 mV / min) is a typical empirical value at room temperature for the aforementioned specification (12V / 20Ah) of lithium iron phosphate batteries. Appropriate calibration is required for batteries of different capacities or types.

[0138] Once the local fault determination is completed, the conclusion will immediately affect the coordinated behavior of the luminaire. If the fault is determined to be an LED light source failure or an aging energy storage unit, the luminaire's local controller, in addition to setting a fault flag and broadcasting it, will adjust its coordinated strategy according to the fault type. For example, for a luminaire with a failed LED, its load power consumption is considered zero, and it may act more proactively as a power supplier when calculating the available power reserve; for a luminaire with an aging battery, its guaranteed power supply will be appropriately reduced. The calculation benchmark or maximum output power is used to reflect the decline in its energy storage capacity. Therefore, fault information can not only be reported, but also be directly and intelligently integrated into local energy dispatch decisions, enabling the system as a whole to make adaptive adjustments to unit faults and demonstrating true self-healing capabilities.

[0139] S402: Controller and Key Hardware Configuration.

[0140] S402a: The local controller can be a microcontroller with sufficient processing power and corresponding peripherals, such as a 32-bit microcontroller with a main frequency of 72MHz. It must have at least the following key peripherals built-in to support the control logic of this invention:

[0141] Analog-to-digital converter (ADC): Used to acquire analog signals from photovoltaic input voltage / current, energy storage unit terminal voltage, load current, and ambient light intensity sensor output.

[0142] Pulse Width Modulation (PWM) Generator: Used to generate the duty cycle signal for controlling the bidirectional DC-DC converter to precisely regulate power.

[0143] Universal Asynchronous Receiver / Transmitter (UART): Used for serial data exchange with short-range wireless communication modules.

[0144] S402b: The local controller is equipped with non-volatile memory to store the lamp's unique device identifier ID, geographical coordinates, installation date, cumulative working time, and historical fault records. The geographical coordinates can be manually entered during installation or obtained with the assistance of the gateway node.

[0145] S402c: A DC-DC converter that supports bidirectional energy flow, for example, employing a bidirectional synchronous rectification buck / boost topology to achieve flexible input and output of electrical energy. In a specific design, its parameters are configured as follows:

[0146] Input / output voltage range: Covers the normal operating voltage range of the energy storage unit, such as 10V to 16V.

[0147] Switching frequency: for example, 500kHz, to balance efficiency and size.

[0148] Key power device parameters: for example, inductance 10μH, output capacitance 470μF, the specific values ​​are determined according to the power level and ripple requirements.

[0149] Control signal requirements: To achieve precise power control, the PWM signal resolution should be no less than 10 bits, with an update frequency of, for example, 20kHz, to ensure power regulation accuracy better than 1%.

[0150] S402d: A photovoltaic charging unit typically includes a photovoltaic panel and its associated charging controller. For example, a monocrystalline silicon photovoltaic panel with a peak power of approximately 20W can be used, along with a charging controller that has maximum power point tracking and a high conversion efficiency, such as no less than 95%, to efficiently convert solar energy into electrical energy and charge the energy storage unit.

[0151] S402e: The energy storage unit preferably uses battery types with long cycle life and high safety, such as lithium iron phosphate cells with a nominal voltage of 12V and a rated capacity of 20Ah. Furthermore, this energy storage unit has a built-in battery management system (BMS) with overcharge, over-discharge, overcurrent, and temperature protection functions. It can monitor the cell status in real time and cut off the circuit in case of abnormalities, ensuring the safe and reliable operation of the system. The specific voltage and capacity of the battery can be selected based on the power consumption of a single lamp and the lighting conditions of the deployment location.

[0152] S403: System Architecture and Networking.

[0153] S403a: Several garden landscape lighting units are interconnected by physical wires through a DC bus interface to form an independent DC microgrid. This microgrid constitutes a basic collaborative area, the range of which is defined by the accessibility of the physical connection and the effective coverage of the short-range wireless communication in the aforementioned step S2, so as to ensure that all lights in the area can not only achieve power sharing, but also conduct stable status information exchange.

[0154] S403b: A gateway node is installed at the edge of each DC microgrid area. This node is typically deployed at the physical or logical boundary of the area, such as near the power access point or management room. Specifically, this node includes:

[0155] Enhanced local controller: Employs a microcontroller with stronger processing power and larger storage capacity than ordinary lighting controllers to handle real-time processing and buffer storage of regional data. For example, it can cache detailed regional operation logs for the past 7 days, providing a data foundation for operation and maintenance analysis.

[0156] Short-range wireless communication module: used to maintain communication with all lights in the area and receive their periodically broadcast status information.

[0157] Remote communication module: Supports low-power wide area network protocols such as NB-IoT or LoRa, and is responsible for establishing a connection with the remote management platform to realize remote data transmission.

[0158] S403c: In addition to possessing all the hardware and local autonomy functions of ordinary lighting fixtures, such as energy scheduling and fault self-diagnosis, the gateway node also undertakes the tasks of aggregating regional status information, relaying and structuring fault information, and communicating with remote platforms, specifically including:

[0159] Regional status information aggregation: Continuously receives status packets broadcast by each lamp within the region, extracts key information such as the SOC, photovoltaic power, and fault indicators of each lamp, and can calculate regional-level indicators according to preset rules, such as the regional average state of charge for adaptive lighting strategies. .

[0160] Fault Information Relay Reception and Structuring: As the final destination of the fault information relay forwarding mechanism within the area, the gateway receives and confirms fault reports forwarded layer by layer from neighboring lights. The gateway structures and organizes the received fault information and stores it in the local operation and maintenance report buffer. The fault information includes device ID, location, fault type, timestamp, etc.

[0161] Communication with remote platforms: According to preset strategies, such as timed triggering, event triggering, or platform querying, the aggregated regional status summary and buffered fault reports are uploaded to the remote management platform through the remote communication module. At the same time, it can also receive and send non-real-time commands such as configuration parameter updates from the platform.

[0162] The above architecture combines local distributed autonomous decision-making with centralized aggregation and reporting of regional information, ensuring high reliability and low latency local response while providing visual management capabilities for large-scale deployed systems.

[0163] It should be noted that for regional status indicators such as The gateway's calculations are primarily used to generate regional summaries for the reporting platform. Its algorithm is, in principle, consistent with the local calculations of the lighting fixtures to ensure data consistency. At the local autonomy level, the gateway, as an ordinary node within the region, follows the same energy scheduling algorithm and lighting adjustment strategy as other lighting fixtures. Its scheduling behavior has no special priority or rules, thus maintaining the fairness and consistency of distributed decision-making within the region.

[0164] S404: Implementation details of energy dispatch and fault information transmission.

[0165] S404a: Based on the distributed scheduling algorithm of S302 mentioned above, the scheduling decision process of each lighting fixture's local controller is as follows:

[0166] 1. Read the current state of charge (SOC_self) of this lamp's energy storage unit.

[0167] 2. Calculate the guaranteed power supply of this lamp based on the lighting level of the area where the lamp is located: .in, The default value is 7200 seconds, and η can be set to 0.92.

[0168] 3. Based on rated capacity Calculate the current available power reserve for this lamp: .

[0169] 4. Parse the received neighbor state information. For each neighbor, determine its charge state. Multiply by rated capacity We obtain its current power level; then we calculate its power shortage: .

[0170] 5. Determine if the scheduling pairing conditions are met: This light >0, and has neighbors >0.

[0171] 6. If the conditions are met, calculate the weight W for this scheduling. The weight is determined based on the proportion of the current lamp's remaining capacity and the target neighbor's gap in the local supply and demand, for example: .in, and These represent the total available capacity and total gap of currently known neighbors with scheduling intentions, respectively.

[0172] 7. Based on the weight W and the maximum schedulable power set by the system. Calculate the target power: And control the bidirectional DC-DC converter to perform power through PWM signal. Electrical energy transmission that lasts for a certain period of time, such as 30 seconds.

[0173] S404b: The fault information transmission process is as follows:

[0174] 1. When the local controller determines that a fault has occurred, such as LED failure or battery aging, it immediately sets the corresponding fault flag bit in its periodically broadcast status information packet, along with basic information such as the device ID and geographical location of the lamp.

[0175] 2. When other lights in the area receive a broadcast packet with a fault flag, if they are not gateway nodes, they will append the fault information to the end of the status packet they broadcast to the outside world in their next broadcast cycle and continue to forward it to their neighbors, thus achieving relay dissemination of information.

[0176] 3. When the gateway node receives the fault information, whether it comes directly from the faulty light or through relay from a neighbor, it becomes the final receiving point of the information. The gateway performs structured processing on the received raw information, such as adding timestamps and accumulated working hours, and stores it in the local operation and maintenance report buffer.

[0177] 4. The gateway node uploads the fault reports summarized in the buffer to the remote management platform through its remote communication module according to the preset strategy, thus completing the entire reporting process.

[0178] During the relay transmission of fault information, the system employs conventional engineering measures to ensure its effectiveness and network efficiency. For example, each fault report includes a unique sequence number or a unique identifier combining the fault light ID and a timestamp, allowing gateway nodes to identify and filter duplicate reports. Simultaneously, a simple hop count counter can be carried along with the fault information during forwarding. Once the preset maximum hop count is exceeded, and if the estimated diameter of the coverage area is reached, forwarding will cease to prevent invalid loops within the network. After successfully receiving and processing the fault information, the gateway node can optionally include a brief reception acknowledgment flag in its next status broadcast for relevant nodes to be aware of.

[0179] S5: Adaptive lighting assurance based on regional energy status.

[0180] S501: In the absence of external communication, such as when the remote platform is disconnected or the communication module fails, the local controller of each lamp will independently adjust the lighting brightness according to the preset lighting priority strategy.

[0181] S502: The controller periodically calculates the average state of charge of all luminaire energy storage units within its cooperative area, denoted as... This value is obtained in the following way:

[0182] Data source: The status information packets broadcast by all neighboring lights periodically received in step S2 are parsed, and the SOC values ​​contained therein are extracted. To improve the timeliness and reliability of the calculation, the controller typically uses valid SOC data received within the most recent complete communication cycle for calculation.

[0183] Calculation method: Calculate the weighted average of all collected SOC values.

[0184] Weighting: Different weights are assigned based on the lighting priority of the area where the luminaires are located. For example, luminaires in the primary path have a weight of 1.0, luminaires in the secondary path have a weight of 0.6, and luminaires in decorative areas have a weight of 0.3. The purpose of setting weights is to reflect the importance of different levels of luminaires to the overall lighting guarantee of the area in the average calculation, so that the SOC_avg index can better reflect the energy reserves of the critical path.

[0185] In actual operation, the controller will determine the calculation... The controller checks whether the effective neighbor SOC data has reached a minimum requirement, for example, receiving data from at least half of the neighbors. If this condition cannot be met for several consecutive cycles, the controller will temporarily abandon the test. Instead of adopting a regional coordination strategy, it manages the lighting of its lamps solely based on the SOC of its own energy storage unit, according to a more conservative, pre-defined individual brightness adjustment curve, to ensure basic and safe individual operation even under the most unfavorable communication conditions.

[0186] It should be noted that, although each light fixture in the area is calculated independently... However, since it relies on the same neighbor state broadcasting mechanism and follows the same calculation rules, and the lighting adjustment threshold setting has a certain hysteresis range, it can maintain the consistency of regional lighting adjustment decisions in most cases and achieve coordinated adaptive load reduction.

[0187] S503: Based on calculations The value automatically adjusts the lighting output in layers according to a preset threshold strategy:

[0188] when When the value is less than 0.4, turn off the landscape lighting output in all decorative areas.

[0189] when When <0.25: Based on the previous level of control, the illumination brightness of the secondary path landscape lights is reduced to 50% of their rated brightness, for example, by limiting their LED drive current to 50% of the rated value.

[0190] when When the value is less than 0.15: Based on the first two levels of control, only the first-level path landscape lights are maintained at normal rated power to ensure minimum safe illuminance.

[0191] In practice, the aforementioned tiered adjustments can be implemented using a smooth transition to improve the visual experience and reduce the impact on the circuitry. For example, when it is necessary to reduce the brightness to 50%, the controller can gradually adjust the PWM duty cycle or drive current to the target value over several seconds, rather than switching instantaneously. The shutdown operation can also be achieved through a similar gradual dimming process.

[0192] In summary, this embodiment combines physical DC bus interconnection with local autonomous control to achieve energy coordination, fault self-healing, and intelligent dimming of solar landscape lighting groups. All decisions are made locally without relying on cloud commands. The system uses mature and reliable hardware components and a simple and efficient communication protocol, balancing performance and cost, and is suitable for large-scale garden deployment.

[0193] Example 2

[0194] This embodiment provides an intelligent control method for garden landscape lighting, the core of which lies in a fully distributed power collaborative scheduling decision-making method. Unlike Embodiment 1, this embodiment does not rely on a specific physical wiring interconnection architecture between lighting fixtures. Instead, it focuses on achieving state coordination through a wireless communication network and utilizes the power interface of each lighting fixture as a controllable power interaction channel to logically achieve collaborative energy scheduling. This method is particularly suitable for intelligent upgrading and transformation of existing landscape lighting systems, or for building intelligent lighting cluster systems on hardware different from that of Embodiment 1.

[0195] The control method in this embodiment includes the following steps:

[0196] Step 1: Construct a distributed state awareness and communication network.

[0197] Each landscape lighting unit includes a power supply unit, an LED light source, a local controller, and a short-range wireless communication module. There is no need for dedicated physical wires to interconnect the lights, but they need to maintain stable status information exchange with at least one neighboring light through the short-range wireless communication module.

[0198] The local controller collects real-time operating status data of the lamp, including at least the current output capacity of the power supply unit or the state of charge of the energy storage unit, and the real-time load power consumption of the LED light source. Each controller periodically broadcasts information packets containing the above status through its short-range wireless communication module, and listens for and receives similar information from neighboring lamps.

[0199] To achieve reliable distributed coordination, the short-range wireless communication module operates according to a preset cycle, employing a time-division multiplexing-based self-organizing protocol to ensure that the status information of each lamp within a local area can be broadcast in an orderly manner and reliably received by neighboring nodes. Each lamp dynamically maintains an effective neighbor list within its communication range for subsequent scheduling decisions. To further enhance network stability, status information is allowed to be relayed within a limited number of hops, ensuring that critical scheduling information can still be transmitted within the local area even when direct communication is blocked.

[0200] Step 2: Define the collaborative benchmark, i.e. calculate the dynamic guaranteed power supply.

[0201] Each luminaire calculates its own dynamic backup power based on its lighting duty level and the system's preset backup requirements. This serves as the energy benchmark for subsequent coordinated scheduling. The calculation formula is:

[0202]

[0203] in:

[0204] This is the minimum guaranteed power that this luminaire must maintain, and its unit is W. This value is determined by the lighting zone level to which its installation location belongs, such as primary path or secondary path, and is usually determined based on the corresponding illuminance standard and luminous efficacy of the luminaire.

[0205] This is the duration required to guarantee critical loads for the system, which can be set to 2 hours. It is a parameter that can be adjusted according to the operation and maintenance strategy.

[0206] To account for the overall efficiency coefficient that takes into account the losses in the energy storage and conversion process, an empirical value based on typical hardware efficiency is usually taken, such as 0.92.

[0207] The above , and The parameters can be preset during system deployment or configured via management commands. Each lamp's local controller calculates its own parameters based on these parameters. This value is directly used in subsequent steps to assess one's own energy surplus or deficit and to analyze the energy needs of neighbors.

[0208] Step 3: Execute fully distributed power dispatch decisions.

[0209] Each luminaire's local controller independently and periodically executes the following scheduling decision process. First, the basis for power calculation needs to be clarified: each luminaire's energy storage unit or power supply unit has a known rated capacity. This parameter is determined and stored in the local controller during system deployment. The controller calculates the state of charge based on real-time data acquisition or estimation. To obtain the current battery level.

[0210] Step 3.1: Self-state assessment.

[0211] Based on the real-time status and rated capacity of its own power supply unit, the lamp's relative guaranteed power capacity is calculated. Energy state offset ΔE.

[0212] If the current battery level ,but It is defined as "support margin".

[0213] If the current battery level ,but This is defined as a "gap to be filled".

[0214] Step 3.2: Neighbor state resolution.

[0215] Parse all status broadcast packets from neighboring lights received in the most recent communication cycle. For each neighbor n, based on its broadcast SOC and rated capacity information (its rated capacity can be obtained during network synchronization or considered a known system parameter), calculate its current power consumption. Furthermore, combined with its guaranteed power supply The energy state offset can be calculated by parsing from broadcast packets or by inferring from their illumination levels. They are also categorized as either "surplus" or "gap".

[0216] Step 3.3: Scheduling Trigger and Partner Selection.

[0217] This light controller is based on its own and its neighbors'... The type determines whether to initiate or respond to a scheduling request:

[0218] If this light is a "surplus" light and a "gap" light is found among the neighbors, then this light is eligible to be a candidate for power supply.

[0219] If this light is in a "gap" position and a "surplus" position is found among its neighbors, then this light is eligible to be a candidate for receiving electricity.

[0220] To simplify decision-making and avoid conflicts, the system employs a priority-based pairing mechanism:

[0221] 1. Gap Priority Ranking: All "gap" parties are ranked according to the size of their gaps ( Sort them in descending order; the larger the gap and the more urgent the need, the higher the priority.

[0222] 2. Margin Response Contention: When multiple "margin" parties simultaneously detect the same high-priority "gap," they compete based on their margin ratio, signal strength, or random delay rules. Ultimately, only one "margin" party is qualified to supply power to the "gap" party. For example, different response delays can be set based on the margin ratio; the larger the margin, the faster the response.

[0223] 3. The pairing relationship is locked within the scheduling cycle and declared through status broadcast to avoid duplicate scheduling.

[0224] Step 3.4: Scheduling power calculation and execution.

[0225] For successfully paired "power supply-receiver" light fixture pairs, schedule power. Determined according to the following principles:

[0226]

[0227] in:

[0228] This represents the available support margin for the power supplier.

[0229] This is the gap to be filled for the power receiving party.

[0230] α and β are configurable conservative coefficients, such as 0.8, used to reserve a buffer to prevent overshoot.

[0231] This represents the maximum transmission power allowed by the hardware.

[0232] The scheduled time window is 300 seconds.

[0233] The power supply's local controller, based on the calculated By adjusting the output of its power supply unit, such as adjusting the output of its bidirectional DC-DC converter or temporarily boosting the inverter output of its solar charge controller, the power supply unit transfers electrical energy to the power receiver, which in turn adjusts its input receiving circuit accordingly. In this architecture without a dedicated energy bus, the aforementioned power dispatch mainly achieves logical energy transfer by coordinating the power output of the power supplier and the power receiver on the shared power line.

[0234] Step 4: Adaptive lighting management in coordination with scheduling.

[0235] While running the distributed scheduling algorithm, the system performs adaptive lighting management in parallel as a system-level energy guarantee measure. This management includes two aspects:

[0236] 1. Neighbor-based collaborative area dimming: Each luminaire calculates the average state of charge (SOC) within its local communication network based on the SOC information broadcast by its communication neighbors. Based on this The brightness of the decorative area is reduced when the value is below 0.4, and the brightness of the secondary path is reduced when the value is below 0.25. Each lamp adjusts its own brightness autonomously and in coordination to prioritize key lighting when the system energy is insufficient.

[0237] 2. Individual derating protection after dispatch failure: If a lamp fails to replenish energy after multiple dispatch attempts and its own power drops below the preset safety threshold, the lamp will automatically switch to a low-power maintenance mode, such as maintaining only a dim light, and broadcast an emergency status to attempt to trigger a new round of dispatch assistance.

[0238] Step 5: Method scalability and management integration.

[0239] To enable remote monitoring and policy optimization of the distributed scheduling system, data interaction can be achieved between the gateway node and the management platform. The gateway periodically summarizes and uploads the core status of the lights in the area and key scheduling events to the platform. Based on data analysis, the platform can issue policy parameter update commands, which are then distributed to each light fixture via the gateway. After verifying the commands, the local controller of each light fixture will update its corresponding internal parameters. The new parameters will automatically take effect in the following local autonomous scheduling cycle, thus achieving seamless integration between remote management and local autonomous decision-making.

[0240] In summary, this embodiment provides a distributed energy collaborative scheduling method that does not rely on a specific physical hardwired topology and is entirely based on software logic and wireless communication. This method introduces "guaranteed power" as a collaborative benchmark and utilizes local information interaction to achieve self-organized supply and demand matching and power allocation. Based on the existing system architecture, it can endow landscape lighting groups with intelligent energy sharing and dynamic guarantee capabilities at a lower transformation cost. This is a concrete manifestation of the core idea of ​​this invention in a wider range of application scenarios.

[0241] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention. Therefore, the embodiments should be regarded as exemplary and non-limiting in all respects.

[0242] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment includes only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A method for intelligent control of garden landscape lighting, characterized in that, include: Construct a local collaborative power supply network among garden landscape lights, enabling each light fixture to physically or logically interact with electrical energy; Each lamp's local controller collects its own lamp's operating status data in real time and periodically exchanges status information with neighboring lamps via short-range wireless communication. Each lamp's local controller autonomously executes a distributed power dispatch algorithm based on its own and the status information received from neighboring lamps, in order to achieve dynamic power sharing among lamps within the collaborative power supply network. The local controller of each lamp adaptively adjusts its lighting output based on the overall energy status of the coordinated power supply network. Each lamp's local controller performs local fault self-diagnosis in parallel, and when a fault is diagnosed, it relays the fault information to neighboring lamps via the short-range wireless communication.

2. The intelligent control method for garden landscape lighting according to claim 1, characterized in that, Building a local collaborative energy supply network includes: The DC bus interfaces of adjacent garden landscape lights are connected one-to-one by physical wires to form a local DC microgrid; Each lamp is connected to the common DC bus of the DC microgrid via its built-in bidirectional DC converter.

3. The intelligent control method for garden landscape lighting according to claim 2, characterized in that, The topology of a DC microgrid can be a tree structure or a ring structure; The number of interconnected lamps within a single collaborative power supply network does not exceed a preset threshold, and different collaborative power supply networks are electrically isolated from each other through series diodes.

4. The intelligent control method for garden landscape lighting according to claim 1, characterized in that, The periodic exchange of state information is achieved through a time-division multiple access-based self-organizing network protocol; The status information includes at least the state of charge of the energy storage unit, photovoltaic input power, load power consumption, and fault flag bits.

5. The intelligent control method for garden landscape lighting according to claim 1, characterized in that, Executing distributed power dispatch algorithms includes: Based on the preset guaranteed power capacity, calculate the dispatchable power margin of this lamp and the power gap of each adjacent lamp. If the lamp has a power dispatchable margin and at least one adjacent lamp has a power shortage, dispatch pairing is initiated. The scheduling weight is determined based on the proportion of the available power capacity of this lamp in the total local power capacity, and the proportion of the power shortage of the lamps near the target in the total local power shortage. The bidirectional DC-DC converter is controlled according to the scheduling weights to perform power transmission of a specific power and duration.

6. The intelligent control method for garden landscape lighting according to claim 5, characterized in that, The guaranteed power is calculated based on the load power required to maintain the minimum illuminance, the preset guarantee duration, and the overall efficiency coefficient.

7. The intelligent control method for garden landscape lighting according to claim 1, characterized in that, Adaptive adjustment of lighting output includes: The regional average state of charge is calculated based on the state of charge data obtained from nearby luminaires. When the average state of charge of the area is lower than a first threshold, the lighting of the decorative area lights is turned off; When the average state of charge in the area is lower than a second threshold below the first threshold, the illumination brightness of the secondary path lights is reduced. When the average state of charge of the area is below a third threshold that is below the second threshold, only the critical path luminaires are maintained to operate at rated power.

8. The intelligent control method for garden landscape lighting according to claim 1, characterized in that, The local fault self-diagnosis includes light source fault diagnosis and energy storage unit aging diagnosis. The light source fault diagnosis is based on whether the load current detected in the light-up command state is continuously lower than the judgment threshold. The energy storage unit aging diagnosis is based on whether the rate of voltage drop at the terminals, monitored when the system is in a near-static state, exceeds a preset slope threshold.

9. The intelligent control method for garden landscape lighting according to claim 1, characterized in that, The method further includes: A gateway node is set up in the collaborative energy supply network. The gateway node is used to aggregate the status information of lamps in the area, receive structured fault reports, and interact with the remote management platform through a remote communication module.

10. A smart control system for garden landscape lighting, characterized in that, The system is applied to the intelligent control method for garden landscape lighting according to any one of claims 1 to 9, the system comprising multiple garden landscape lighting units, each garden landscape lighting unit comprising: Photovoltaic charging unit, energy storage unit, LED light source and load circuit for powering it; A bidirectional DC-DC converter is connected between the energy storage unit and the DC bus interface to enable power exchange with the coordinated power supply network. A local controller, configured to collect operating status data and execute the control logic as described in claim 1; A short-range wireless communication module, connected to the local controller, is used to exchange status information with nearby lamps; In this configuration, the DC bus interfaces of adjacent lamps are connected by physical wires to form a local collaborative power supply network; or, the lamps are connected by the short-range wireless communication module to form a logical collaborative network.

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