Intelligent street lamp intelligent regulation and control method and system, electronic equipment and storage medium

Abstract

The invention provides an intelligent regulation and control method and system for an intelligent street lamp, electronic equipment and a storage medium, belongs to the technical field of street lamp regulation and control, and is used for solving the problems that an existing intelligent street lamp depends on manual inspection and maintenance after breaking down, a temporary light supplementing mode is extensive, and a systematic fine compensation scheme is lacked. The method comprises the following steps: when a street lamp fault is detected, obtaining a position coordinate and carrying out gridding division on a coverage area; searching candidate street lamps by taking the fault street lamp as a center, and acquiring a light distribution curve, an installation parameter and a brightness adjustment upper limit; calculating illumination contribution according to the geometrical relationship and the light distribution parameters, and generating an illumination contribution matrix; screening street lamps with effective compensation capability to form a compensation set; the compensation street lamps are combined and optimized, the illumination compensation degree, the energy consumption and the glare value are calculated, and a comprehensive scoring model is constructed in combination with the road and the traffic flow; and through scoring and constraint condition screening, an optimal illumination compensation scheme is determined, and refined and intelligent dynamic compensation of illumination of the fault road section is realized.

Description

Technical Field

[0001] This invention belongs to the field of street light control technology, specifically relating to a smart street light intelligent control method, system, electronic device and storage medium. Background Technology

[0002] This invention belongs to the field of smart city road lighting control technology, specifically relating to a smart street light intelligent control method, system, electronic device and storage medium.

[0003] As a core component of smart city infrastructure, smart streetlights not only provide basic lighting for urban roads, parks, and streets, but also integrate multiple technologies such as the Internet of Things, sensors, intelligent control, and communication transmission, becoming a crucial node for realizing urban perception, data collection, and intelligent management. The continuity, stability, and illuminance uniformity of road lighting directly affect road traffic safety, pedestrian visual experience, and regional traffic efficiency, and are important evaluation indicators for the urban public service guarantee system. The lighting requirements for main urban roads, transportation hubs, and areas surrounding residential areas are particularly stringent.

[0004] In the actual operation of smart streetlights, due to various factors such as the complex outdoor natural environment, long-term aging of equipment, circuit contact failures, and damage from extreme weather, single or multiple streetlights are prone to lighting failures, resulting in blind spots in their rated coverage area. Currently, the handling of smart streetlight failures still revolves around waiting for manual inspection, repair, and parts replacement after a failure. Even though some smart streetlight systems are equipped with simple fault detection modules that can automatically identify and alarm for faults, before the fault is repaired, temporary lighting can only be supplemented by crudely increasing the brightness of surrounding streetlights. There is still no systematic and refined intelligent control and compensation solution. Summary of the Invention

[0005] In view of this, the present invention provides a smart street light intelligent control method, system, electronic device and storage medium to solve the problem that the current handling of smart street light faults in the prior art still relies on manual inspection, repair and parts replacement after a fault occurs as the core process. Even if some smart street light systems are equipped with simple fault detection modules that can realize automatic fault identification and alarm, before the fault is repaired, they can only temporarily supplement lighting by crudely increasing the brightness of surrounding street lights. There is no systematic and refined intelligent control and compensation solution.

[0006] The technical solution adopted in this invention is as follows: A smart street light intelligent control method, characterized by comprising: Step 1: When a street light malfunction is detected, obtain the location coordinates of the malfunctioning street light and perform gridding on the coverage area of ​​the malfunctioning street light. Step 1 specifically includes: The operating current and voltage data of each street light are collected in real time through the street light control terminal. When the operating current or voltage of a street light exceeds the preset normal range and the duration exceeds the preset threshold, the street light is determined to be faulty and the location coordinates of the faulty street light are obtained. A Cartesian coordinate system is established with the location coordinates of the faulty streetlight as the origin. The rated coverage area of ​​the faulty streetlight is divided into M×N uniform grids according to a preset grid size. The coordinates of each grid point are... ,in , M and N are both positive integers.

[0007] Step 2: Using the faulty street light as the center, perform a candidate street light search according to the preset search radius, and obtain the light distribution curve function, installation height, installation tilt angle, current position coordinates and brightness adjustment limit of each candidate street light; Step 2 specifically includes: Based on the rated illumination radius of the faulty street light Preset search radius ,satisfy , Dynamically adjust according to the actual lighting needs of the fault area; Centered on the faulty streetlight, search within a preset radius. Search for all working streetlights within the range and identify them as candidate streetlights; Collect and obtain the light distribution curve function, installation height, installation tilt angle, current position coordinates, and brightness adjustment limit of each candidate street light; the light distribution curve function is the light intensity distribution function of the candidate street light under different illumination angles. , Let be the angle between the illumination direction of the candidate streetlight and the vertical direction. For candidate streetlights at illumination angle The intensity of light below.

[0008] Step 3: For each candidate street light, calculate its actual illuminance contribution to the fault area based on its light distribution curve function and geometric relationship with each grid point in the fault area, and generate an illuminance contribution matrix. Step 3 specifically includes: Step 3.1: For the k-th candidate street light and the grid point in the i-th row and j-th column within the fault area, calculate the straight-line distance between them. The calculation formula is: .

[0009] in, Let K be the coordinates of the k-th candidate street light. Let be the installation height of the k-th candidate street light; Step 3.2: Calculate the incident angle of the k-th candidate streetlight to the grid point in the i-th row and j-th column. This angle is the angle between the line connecting the candidate streetlight and the grid point and the horizontal plane where the grid point is located. The calculation formula is: .

[0010] Step 3.3, based on the light distribution curve function Straight-line distance and angle of incidence Calculate the actual illuminance value of the k-th candidate streetlight for the grid point in the i-th row and j-th column under the current brightness. The calculation formula is: .

[0011] in, The installation tilt angle and incident angle of the k-th candidate street light The difference, The luminous efficacy coefficient of the candidate streetlights; Step 3.4, Illuminance Contribution Matrix Generation: This involves generating the illuminance contribution matrix for each candidate streetlight at its current brightness across all grid points. Construct an illuminance contribution matrix using elements. The matrix has dimensions K×M×N, where K is the number of candidate streetlights.

[0012] Step 4: Based on the illuminance contribution matrix and the upper limit of brightness adjustment, select candidate streetlights that can compensate for the brightness of faulty streetlights to form a set of actual compensated streetlights. Step 4 specifically includes: For the k-th candidate street light, calculate its average illuminance value for all grid points in the fault area under the current brightness. The calculation formula is: .

[0013] Set the preset effective illuminance threshold , The value of is not lower than the minimum illuminance requirement for the corresponding road grade in the urban road lighting design standard; if the average illuminance value of the kth candidate street light If the brightness adjustment limit is greater than 1, then the candidate street light will be included in the actual compensation street light set.

[0014] Step 5: Arrange and combine each street light in the actual compensation street light set to generate several compensation combinations. Each compensation combination includes a subset of street lights and the brightness adjustment coefficient of each street light in the subset. Calculate the fault area illuminance compensation, additional energy consumption, and glare value for oncoming drivers for each compensation combination. Combine the road type and real-time traffic flow distribution weight coefficients to complete the index normalization process and construct a comprehensive scoring model. Step 5 specifically includes: Step 5.1: Let the number of streetlights in the actual compensation streetlight set be L, and the brightness adjustment coefficient of the l-th actual compensation streetlight be... , ,and The brightness adjustment limit of the street light shall not exceed the upper limit of the street light's brightness adjustment; based on the actual set of compensated street lights, generate all non-empty street light subsets, and assign preset multi-level discrete brightness adjustment coefficients to each street light in each street light subset, forming several distinct compensation combinations. The decision variable vector for a single compensation combination is: t represents the number of streetlights in the streetlight subset of this compensation combination. ; Step 5.2: For each compensation combination, calculate the illuminance compensation degree for the fault area. Additional energy consumption Glare value for oncoming drivers : Step 5.2.1, Calculation of Illumination Compensation in the Fault Area: The calculation formula is as follows: .

[0015] in, This represents the actual illuminance value of the l-th streetlight within the streetlight subset in this compensation combination for the grid point in the i-th row and j-th column under the current brightness. This represents the rated illuminance value of the grid point in the i-th row and j-th column when the faulty street light is working normally. Step 5.2.2, Calculation of Additional Energy Consumption: The calculation formula is as follows: .

[0016] in, The rated power of the l-th street light in the subset of street lights in this compensation combination. To compensate for the duration; Step 5.2.3, Calculation of glare value for oncoming drivers: The calculation formula is as follows: .

[0017] Where Q represents the number of driver observation points in the opposite lanes surrounding the fault area. Let be the angle between the illumination of the l-th street light and the m-th observation point within the street light subset of the compensation combination. The distance between the l-th street light and the m-th observation point within the street light subset of the compensation combination is given by [reference to street light location]. Let be the glare weighting coefficient for the m-th observation point, with a value range of . ; Step 5.3: Combine all compensations , , Perform maximum and minimum value normalization separately to obtain the normalized index values. , , ; Step 5.4: Obtain the road type and real-time traffic flow data for the current road segment, and allocate regional illuminance compensation. Additional energy consumption Glare value for oncoming drivers Weighting coefficients , , And satisfy The higher the road grade and the greater the traffic volume, and The larger, The smaller; The comprehensive scoring model is constructed, and the calculation formula is as follows: .

[0018] Where S is the comprehensive score of a single compensation combination.

[0019] Step 6: Calculate the comprehensive score of each compensation combination based on the comprehensive scoring model, select effective compensation combinations based on the constraints, and select the compensation combination with the highest comprehensive score as the final optimal lighting compensation scheme.

[0020] Step 6 specifically includes: For each compensation combination, determine whether all grid points in the fault area meet the requirements. If the conditions are not met, the compensation combination will be removed. This is the minimum guaranteed illuminance value for the fault area; For each compensation combination, determine its glare value. Does it meet the requirements? , The maximum permissible glare value is preset. If it is exceeded, the overall score of the compensation combination will be downgraded by 30% to 50% of the original score. If the score after downgrading is lower than the average score of all valid combinations, the compensation combination will be removed. For each compensation combination, determine the brightness adjustment coefficient of each street light within its subset. Does it meet the requirements? And it does not exceed the upper limit of the brightness adjustment of the street light; if it does not meet the requirements, the compensation combination is removed. The effective compensation combinations after screening are sorted from high to low according to the comprehensive score S; the compensation combination with the highest score is taken as the final optimal lighting compensation scheme, and the street light subset of the compensation combination and the corresponding brightness adjustment coefficient are output. .

[0021] A faulty street light illumination compensation system based on dynamic optical matching includes: The fault detection module is used to detect the working status of streetlights in real time. When a fault is detected in a streetlight, the location coordinates of the faulty streetlight are obtained. The area division module is used to perform grid-based division of the coverage area of ​​faulty streetlights and determine the coordinates of each grid point; The candidate search module is used to perform a candidate street light search with the faulty street light as the center and according to a preset search radius, and to obtain the light distribution curve function, installation height, installation tilt angle, current position coordinates and brightness adjustment limit of each candidate street light; The illuminance calculation module is used to calculate the actual illuminance contribution of each candidate street light to the fault area under the current brightness, based on its light distribution curve function and geometric relationship with each grid point in the fault area, and generate an illuminance contribution matrix. The street light filtering module is used to filter and form a set of actual compensated street lights based on the illuminance contribution matrix and the brightness adjustment limit. The combination generation module is used to generate several compensation combinations based on the actual set of compensation streetlights and determine the decision variable vector for each compensation combination. The index calculation module is used to calculate the illuminance compensation degree, additional energy consumption, and glare value for oncoming drivers corresponding to each compensation combination, and to complete the index normalization process. The weight allocation module is used to acquire road type and real-time traffic flow data, and allocate weight coefficients for the three types of evaluation indicators. The comprehensive scoring module is used to calculate the comprehensive score for each compensation combination based on normalized indicators and weighting coefficients. The scheme selection module is used to select effective compensation combinations based on constraints, score, rank and verify the effective compensation combinations, and select the compensation combination with the highest comprehensive score as the optimal lighting compensation scheme. The execution module is used to send the subset of streetlights with the optimal lighting compensation scheme and the corresponding brightness adjustment coefficients to the control terminals of each streetlight participating in the compensation, and control the streetlights to adjust to the corresponding brightness.

[0022] An electronic device includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of a smart street light intelligent control method.

[0023] A computer-readable storage medium storing a computer program that, when executed by a processor, implements a smart street light intelligent control method.

[0024] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: 1. This invention divides the coverage area of ​​a faulty street light into a grid, and combines the light distribution curves, installation parameters, and spatial geometric relationships of candidate street lights to accurately calculate and construct an illuminance contribution matrix. This can quantify the actual illuminance contribution of each street light to the faulty blind area, replacing the crude compensation method of simply increasing the brightness of surrounding street lights in the prior art. This fundamentally solves the problems of uneven lighting and poor compensation effect in the faulty area, ensuring the continuity and uniformity of lighting.

[0025] 2. This invention comprehensively considers three core indicators: illuminance compensation in the fault area, additional energy consumption, and glare value for oncoming drivers. It also combines road type and real-time traffic flow to dynamically allocate weights and construct a scientific scoring model. This model ensures lighting safety on high-grade, high-traffic road sections while strictly controlling energy waste and glare interference, achieving the optimal balance between lighting protection, energy saving and consumption reduction, and driving safety. Attached Figure Description

[0026] The present invention will be described by way of example and with reference to the accompanying drawings, wherein: Figure 1 This is a schematic diagram of the process structure of the present invention; Figure 2 This is a schematic diagram of the process structure for step 5 of the present invention. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0028] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0029] It should be noted that, unless otherwise specified, the embodiments and features described in this invention can be combined with each other.

[0030] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0031] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of the second feature includes the first feature directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0032] It should be noted that, unless otherwise specified, the embodiments and features described in this invention can be combined with each other.

[0033] Example 1

[0034] like Figures 1-2 As shown in the figure, an intelligent street light control method is disclosed in this embodiment of the invention, characterized by comprising: Step 1: When a street light malfunction is detected, obtain the location coordinates of the malfunctioning street light and perform gridding on the coverage area of ​​the malfunctioning street light. Step 1 specifically includes: collecting real-time operating current and voltage data of each street light through the street light control terminal; when the operating current or voltage of a street light exceeds a preset normal range and the duration exceeds a preset threshold, the street light is determined to be faulty, and the location coordinates of the faulty street light are obtained; a Cartesian coordinate system is established with the location coordinates of the faulty street light as the origin, and the rated coverage area of ​​the faulty street light is divided into M×N uniform grids according to a preset grid size, with the coordinates of each grid point being... ,in , M and N are both positive integers.

[0035] It should be understood that the current sensor built into the street light control terminal has an accuracy of 0.01A, and the voltage sensor has an accuracy of 0.1V. The sampling frequency is set to 5 seconds / time to ensure timely detection of abnormal electrical parameters. The preset normal range is calibrated according to the rated power of the street light. For example, the normal operating current of a 200W LED street light is preset to 0.9A~1.1A, and the normal operating voltage is 220V±5V. The preset continuous threshold is set to 30 seconds to avoid misjudgment caused by instantaneous voltage fluctuations (such as temporary rises and falls in grid voltage). The location coordinates of the faulty street light are obtained from the device files of the smart street light IoT management platform. These coordinates are pre-entered through the GPS positioning module, with an error controlled within ±0.3 meters to ensure accurate location of the fault area. The preset grid size for gridding is dynamically adjusted according to road lighting requirements: a fine grid of 0.5m × 0.5m is used for scenarios with high requirements for uniform illumination, such as urban main roads and highways; a grid of 2m × 2m can be used for scenarios such as park roads and rural roads; the values ​​of M and N are determined by the rated coverage area of ​​the faulty street light. For example, a street light with a rated illumination radius of 20m is divided into a 40×40 grid (20m × 2 = 40m, corresponding to 40 0.5m grids) in the main road scenario and a 10×10 grid (20m × 2 = 40m, corresponding to 10 2m grids) in the park road scenario. By gridding, the faulty area is decomposed into quantifiable spatial units, laying the foundation for subsequent point-by-point calculation of illuminance contribution.

[0036] Step 2: Using the faulty street light as the center, perform a candidate street light search according to the preset search radius, and obtain the light distribution curve function, installation height, installation tilt angle, current position coordinates and brightness adjustment limit of each candidate street light; Step 2 specifically includes: Based on the rated illumination radius of the faulty street light Preset search radius ,satisfy , The search is dynamically adjusted based on the actual lighting needs of the faulty area; with the faulty streetlight as the center, a preset search radius is established. The system searches for all normally functioning streetlights within the specified range and identifies them as candidate streetlights. It then collects and obtains the light distribution curve function, installation height, installation tilt angle, current location coordinates, and brightness adjustment limit for each candidate streetlight. The light distribution curve function represents the light intensity distribution function of the candidate streetlight under different illumination angles. , Let be the angle between the illumination direction of the candidate streetlight and the vertical direction. For candidate streetlights at illumination angle The intensity of light below.

[0037] It should be understood that the preset search radius The dynamic adjustment logic is as follows: Areas with high lighting demand and high pedestrian and vehicular traffic, such as urban core areas, transportation hubs, and areas surrounding schools, should be selected... Ensure a sufficient number of candidate streetlights are available for supplemental lighting; for scenarios such as suburban roads and roads within industrial parks, select... To avoid energy waste caused by too many streetlights participating in supplemental lighting; if the fault area spans two road types, the road type with higher priority will be used to determine the cause of the fault. (For example, at the intersection of a main road and a secondary road, the standard value is taken according to the main road). The search for candidate streetlights is achieved through the spatial indexing function of the smart streetlight IoT management platform. The platform is based on a GIS geographic information system, with the planar coordinates of the faulty streetlight as the center. Draw a circular search area with a radius, automatically filter streetlights within the area whose status is "normal" (judged by the working status identifier reported in real time by the streetlight control terminal, the status includes normal, fault, offline), and generate a candidate streetlight list. The core parameters of the candidate streetlights are collected as follows: installation height, installation tilt angle, and location coordinates are retrieved from the platform's equipment archives. The installation height is typically 6m-14m (12m-14m for main road streetlights and 6m-8m for residential streetlights), and the installation tilt angle is typically 0°-20° (designed according to road width and installation spacing). The light distribution curve function is the calibration parameter at the time of manufacture of the luminaire, provided by the manufacturer as a discrete angle-luminous intensity comparison table in Excel format (each 0.5° interval of θ corresponds to an I(θ) value), which is imported into the platform and stored as a database table structure. The upper limit of brightness adjustment is dynamically calibrated based on the service life of the luminaire and the light decay test results: the upper limit of brightness adjustment for brand new LED streetlights is 2.0, for those used for 1-2 years it is adjusted to 1.8, for those used for 2-5 years it is adjusted to 1.5, and for those used for more than 5 years it is adjusted to 1.2. If the light decay test shows that the actual brightness of the luminaire is less than 60% of the rated value, it will be directly removed from the candidate streetlight range.

[0038] Step 3: For each candidate street light, calculate its actual illuminance contribution to the fault area based on its light distribution curve function and geometric relationship with each grid point in the fault area, and generate an illuminance contribution matrix. Step 3 specifically includes: Step 3.1: For the k-th candidate street light and the grid point in the i-th row and j-th column within the fault area, calculate the straight-line distance between them. The calculation formula is: .

[0039] in, Let K be the coordinates of the k-th candidate street light. Let be the installation height of the k-th candidate street light; It should be understood that the calculation of straight-line distance is completed through the numerical calculation unit of the cloud server, using double-precision floating-point arithmetic (retaining 6 decimal places) to ensure the accuracy of geometric parameter calculation; for example, if the location coordinates of a candidate street light are (25.3m, 42.8m) and the installation height is 12m, and the coordinates of a grid point within the fault area are (30.1m, 48.5m), then the horizontal distance is... The straight-line distance is It uses three-dimensional spatial distance calculation to match the actual light propagation path, avoiding illuminance errors caused by two-dimensional distance calculation.

[0040] Step 3.2: Calculate the incident angle of the k-th candidate streetlight to the grid point in the i-th row and j-th column. This angle is the angle between the line connecting the candidate streetlight and the grid point and the horizontal plane where the grid point is located. The calculation formula is: .

[0041] Step 3.3, based on the light distribution curve function Straight-line distance and angle of incidence Calculate the actual illuminance value of the k-th candidate streetlight for the grid point in the i-th row and j-th column under the current brightness. The calculation formula is: .

[0042] in, The installation tilt angle and incident angle of the k-th candidate street light The difference, The luminous efficacy coefficient of the candidate streetlights; Step 3.4, Illuminance Contribution Matrix Generation: This involves generating the illuminance contribution matrix for each candidate streetlight at its current brightness across all grid points. Construct an illuminance contribution matrix using elements. The matrix has dimensions K×M×N, where K is the number of candidate streetlights.

[0043] It should be understood that the illuminance contribution matrix is ​​stored in a three-dimensional array format in an in-memory database (such as Redis) on a cloud server. The row index of the matrix corresponds to the candidate street light number (1-K), the column index corresponds to the row number of the grid (1-M), and the layer index corresponds to the column number of the grid (1~N). Each element... The unique identifier is "the actual illuminance value of the k-th candidate street light for the grid point in the i-th row and j-th column"; for example, a matrix with K=5, M=30, and N=30 contains 5×30×30=4500 elements, each element occupies 4 bytes of storage space, and the whole matrix occupies 18KB, which is highly efficient and facilitates quick calling and traversal calculation in subsequent steps; the matrix is ​​generated through multi-threaded parallel computing, with each candidate street light assigned an independent thread to calculate its illuminance value for all grid points, which greatly improves processing efficiency, and the matrix generation time for a single fault is ≤1 second.

[0044] Step 4: Based on the illuminance contribution matrix and the upper limit of brightness adjustment, select candidate streetlights that can compensate for the brightness of faulty streetlights to form a set of actual compensated streetlights. Step 4 specifically includes: For the k-th candidate street light, calculate its average illuminance value for all grid points in the fault area under the current brightness. The calculation formula is: .

[0045] Set the preset effective illuminance threshold , The value of is not lower than the minimum illuminance requirement for the corresponding road grade in the urban road lighting design standard; if the average illuminance value of the kth candidate street light If the brightness adjustment limit is greater than 1, then the candidate street light will be included in the actual compensation street light set.

[0046] It should be understood that the average illuminance value The calculation is obtained by iterating through all elements in the k-th row of the illuminance contribution matrix, summing them, and then dividing by the total number of grid cells (M×N). For example, if the total illuminance value of a candidate streetlight for a 30×30 grid is 2700 lx, then the average illuminance value is... Preset effective illuminance threshold Strictly adhering to the "Urban Road Lighting Design Standard" (CJJ45-2015): for urban expressways and main roads Secondary trunk roads Secondary roads and residential roads To ensure that the selected candidate streetlights have basic supplementary lighting capabilities, the logic for determining the upper limit of brightness adjustment is as follows: only streetlights with an upper limit of brightness adjustment > 1.0 are included in the set, meaning they have room for brightness adjustment. For example, streetlights with upper limits of brightness adjustment of 1.2, 1.5, 1.8, and 2.0 all meet the requirements, while streetlights with an upper limit of brightness adjustment = 1.0 (cannot be adjusted upwards) or < 1.0 (severe aging of the lamp) are directly eliminated to avoid invalid brightness adjustment operations.

[0047] Step 5: Arrange and combine each street light in the actual compensation street light set to generate several compensation combinations. Each compensation combination includes a subset of street lights and the brightness adjustment coefficient of each street light in the subset. Calculate the fault area illuminance compensation, additional energy consumption, and glare value for oncoming drivers for each compensation combination. Combine the road type and real-time traffic flow distribution weight coefficients to complete the index normalization process and construct a comprehensive scoring model. Step 5 specifically includes: Step 5.1: Let the number of streetlights in the actual compensation streetlight set be L, and the brightness adjustment coefficient of the l-th actual compensation streetlight be... , ,and The brightness adjustment limit of the street light shall not exceed the upper limit of the street light's brightness adjustment; based on the actual set of compensated street lights, generate all non-empty street light subsets, and assign preset multi-level discrete brightness adjustment coefficients to each street light in each street light subset, forming several distinct compensation combinations. The decision variable vector for a single compensation combination is: t represents the number of streetlights in the streetlight subset of this compensation combination. ; It should be understood that the generation of non-empty street light subsets is based on the power set principle of sets. When the actual compensation street light set has L street lights, the total number of non-empty subsets is... For example, when L=4 (the actual compensated streetlights are A, B, C, and D), the non-empty subsets include: {A}, {B}, {C}, {D}, {A,B}, {A,C}, {A,D}, {B,C}, {B,D}, {C,D}, {A,B,C}, {A,B,D}, {A,C,D}, {B,C,D}, {A,B,C,D}, a total of 15 subsets; the brightness adjustment coefficient is preset with five discrete values: 1.2, 1.4, 1.6, 1.8, and 2.0, balancing the supplementary lighting effect with equipment lifespan and avoiding the combination explosion caused by continuous values. Each streetlight within each streetlight subset independently selects any one of the five coefficient levels, but must satisfy... The upper limit for the brightness adjustment of this street light, for example, if the upper limit for the brightness adjustment of street light A is 1.5, then its selectable coefficients are 1.2 and 1.4, and 1.6, 1.8, and 2.0 are not selectable; the total number of compensation combinations is calculated as follows: for each non-empty subset (containing t street lights), the corresponding number of coefficient combinations is... The total number of compensation combinations is For example, when L=4, the total number of compensation combinations is The system covers all reasonable lighting solutions while keeping the computational load within an acceptable range.

[0048] Step 5.2: For each compensation combination, calculate the illuminance compensation degree for the fault area. Additional energy consumption Glare value for oncoming drivers : Step 5.2.1, Calculation of Illumination Compensation in the Fault Area: The calculation formula is as follows: .

[0049] in, This represents the actual illuminance value of the l-th streetlight within the streetlight subset of the compensation combination for the grid point in the i-th row and j-th column under the previous brightness. This represents the rated illuminance value of the grid point in the i-th row and j-th column when the faulty street light is working normally. Step 5.2.2, Calculation of Additional Energy Consumption: The calculation formula is as follows: .

[0050] in, The rated power of the l-th street light in the subset of street lights in this compensation combination. To compensate for the duration; Step 5.2.3, Calculation of glare value for oncoming drivers: The calculation formula is as follows: .

[0051] in, Let be the luminous intensity of the l-th streetlight in the direction of illumination, and Q be the number of driver observation points in the opposite lanes surrounding the fault area. Let be the angle between the illumination of the l-th street light and the m-th observation point within the street light subset of the compensation combination. The distance between the l-th street light and the m-th observation point within the street light subset of the compensation combination is given by [reference to street light location]. Let be the glare weighting coefficient for the m-th observation point, with a value range of . ; It should be understood that the rules for setting the driver observation point Q are as follows: For single-lane roads, take 3 observation points (left, middle, and right sides of the lane, 1.2m high, corresponding to the driver's eye level while seated); for two-way two-lane roads, take 6 observation points (3 in each direction); for four-way two-lane roads, take 10 observation points (5 in each direction). The coordinates of the observation points are entered into the platform through on-site surveying; glare weighting coefficient. Based on distance and line-of-sight angle: observation points within 5m of the streetlights and with a line-of-sight angle ≤30°. (Dazzling effect is greatest) Observation points at a distance of 5m-10m and with a line-of-sight angle ≤45° =0.7, observation points 10m-15m away and with a line-of-sight angle ≤60° Observation points at a distance of more than 15m or with a line-of-sight angle greater than 60° (Glare effect is negligible); The angle between the streetlight and the observation point, i.e., the angle between the direction of the streetlight's illumination and the direction of the observation point's line of sight, directly affects the intensity of glare. The smaller the angle, the stronger the glare.

[0052] Step 5.3: Combine all compensations , , Perform maximum and minimum value normalization separately to obtain the normalized index values. , , ; It should be understood that the formula for normalizing the maximum and minimum values ​​is: ,in , These are the maximum and minimum values ​​of the indicator across all compensation combinations, after normalization. This ensures that indicators with different dimensions and numerical ranges can directly participate in the comprehensive scoring; for example, all compensation combinations... The maximum value is 1.2, and the minimum value is 0.6. What is the value of a certain combination? Then the normalized If all combinations of values ​​for a certain indicator are the same (e.g., all combinations of values ​​are the same) (All are 2kWh), then after normalization all This avoids scoring bias caused by the lack of difference in indicators.

[0053] Step 5.4: Obtain the road type and real-time traffic flow data for the current road segment, and allocate regional illuminance compensation. Additional energy consumption Glare value for oncoming drivers Weighting coefficients , , And satisfy The higher the road grade and the greater the traffic volume, and The larger, The smaller; The comprehensive scoring model is constructed, and the calculation formula is as follows: .

[0054] Where S is the comprehensive score of a single compensation combination.

[0055] It should be understood that real-time traffic flow data is obtained through an API interface connected to the city's traffic management platform, with a data update frequency of 5 minutes per update, and the traffic flow statistics unit is vehicles per hour; the dynamic allocation rule for the weighting coefficients is as follows: Urban expressways and arterial roads with high traffic volume (≥600 vehicles / hour): , , (Prioritize lighting performance and driving safety); Secondary arterial roads in the city with moderate traffic volume (300-600 vehicles / hour): , , (Balancing lighting, safety, and energy consumption); Secondary roads and residential roads + passenger traffic (<300 vehicles / hour): , , (Prioritize energy consumption control); In the comprehensive scoring model, It is a positive indicator (the higher the score, the better). and As a negative indicator (the lower the score, the better), the weighting coefficient reflects the decision priority of different scenarios. The higher the final score S, the more suitable the compensation combination is for the current scenario requirements.

[0056] Step 6: Calculate the comprehensive score of each compensation combination based on the comprehensive scoring model, select effective compensation combinations based on the constraints, and select the compensation combination with the highest comprehensive score as the final optimal lighting compensation scheme.

[0057] Step 6 specifically includes: For each compensation combination, determine whether all grid points in the fault area meet the requirements. If the conditions are not met, the compensation combination will be removed. The minimum guaranteed illuminance value for the fault area; for each compensation combination, determine its glare value. Does it meet the requirements? , To preset the maximum permissible glare value, if it is exceeded, the overall score of the compensation combination will be downgraded by 30% to 50% of the original score. If the downgraded score is lower than the average score of all valid combinations, the compensation combination will be removed. For each compensation combination, the brightness adjustment coefficient of each street light in its street light subset will be determined. Does it meet the requirements? The brightness adjustment limit of the street light must be met; otherwise, the compensation combination is discarded. The effective compensation combinations are then sorted from highest to lowest according to their comprehensive score S. The top-ranked compensation combination is taken as the final optimal lighting compensation scheme, and the subset of street lights associated with that combination and its corresponding brightness adjustment coefficient are output. .

[0058] Example 2

[0059] This embodiment proposes a faulty street light lighting compensation system based on dynamic optical matching, based on embodiment 1, including: The fault detection module is used to detect the working status of streetlights in real time. When a fault is detected in a streetlight, the location coordinates of the faulty streetlight are obtained. The area division module is used to perform grid-based division of the coverage area of ​​faulty streetlights and determine the coordinates of each grid point; The candidate search module is used to perform a candidate street light search with the faulty street light as the center and according to a preset search radius, and to obtain the light distribution curve function, installation height, installation tilt angle, current position coordinates and brightness adjustment limit of each candidate street light; The illuminance calculation module is used to calculate the actual illuminance contribution of each candidate street light to the fault area under the current brightness, based on its light distribution curve function and geometric relationship with each grid point in the fault area, and generate an illuminance contribution matrix. The street light filtering module is used to filter and form a set of actual compensated street lights based on the illuminance contribution matrix and the brightness adjustment limit. The combination generation module is used to generate several compensation combinations based on the actual set of compensation streetlights and determine the decision variable vector for each compensation combination. The index calculation module is used to calculate the illuminance compensation degree, additional energy consumption, and glare value for oncoming drivers corresponding to each compensation combination, and to complete the index normalization process. The weight allocation module is used to acquire road type and real-time traffic flow data, and allocate weight coefficients for the three types of evaluation indicators. The comprehensive scoring module is used to calculate the comprehensive score for each compensation combination based on normalized indicators and weighting coefficients. The scheme selection module is used to select effective compensation combinations based on constraints, score, rank and verify the effective compensation combinations, and select the compensation combination with the highest comprehensive score as the optimal lighting compensation scheme. The execution module is used to send the subset of streetlights with the optimal lighting compensation scheme and the corresponding brightness adjustment coefficients to the control terminals of each streetlight participating in the compensation, and control the streetlights to adjust to the corresponding brightness.

[0060] Example 3

[0061] This embodiment proposes an electronic device based on embodiment 1, including a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of a smart street light intelligent control method.

[0062] Example 4

[0063] This embodiment proposes a computer-readable storage medium based on embodiment 1. The computer-readable storage medium stores a computer program, which, when executed by a processor, implements a smart street light intelligent control method.

[0064] The circuits, electronic components, and modules involved are all existing technologies, which can be fully implemented by those skilled in the art, and need not be elaborated upon. The scope of protection of this invention does not involve any improvement to the software and methods.

[0065] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0066] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A smart street light intelligent control method, characterized in that, include: Step 1: When a street light malfunction is detected, obtain the location coordinates of the malfunctioning street light and perform gridding on the coverage area of ​​the malfunctioning street light. Step 2: Using the faulty street light as the center, perform a candidate street light search according to the preset search radius, and obtain the light distribution curve function, installation height, installation tilt angle, current position coordinates and brightness adjustment limit of each candidate street light; Step 3: For each candidate street light, calculate its actual illuminance contribution to the fault area based on its light distribution curve function and geometric relationship with each grid point in the fault area, and generate an illuminance contribution matrix. Step 4: Based on the illuminance contribution matrix and the upper limit of brightness adjustment, select candidate streetlights that can compensate for the brightness of faulty streetlights to form a set of actual compensated streetlights. Step 5: Arrange and combine each street light in the actual compensation street light set to generate several compensation combinations. Each compensation combination includes a subset of street lights and the brightness adjustment coefficient of each street light in the subset. Calculate the fault area illuminance compensation, additional energy consumption, and glare value for oncoming drivers for each compensation combination. Combine the road type and real-time traffic flow distribution weight coefficients to complete the index normalization process and construct a comprehensive scoring model. Step 6: Calculate the comprehensive score of each compensation combination based on the comprehensive scoring model, select effective compensation combinations based on the constraints, and select the compensation combination with the highest comprehensive score as the final optimal lighting compensation scheme.

2. The intelligent street light control method according to claim 1, characterized in that, Step 1 specifically includes: The operating current and voltage data of each street light are collected in real time through the street light control terminal. When the operating current or voltage of a street light exceeds the preset normal range and the duration exceeds the preset threshold, the street light is determined to be faulty and the location coordinates of the faulty street light are obtained. A Cartesian coordinate system is established with the location coordinates of the faulty streetlight as the origin. The rated coverage area of ​​the faulty streetlight is divided into M×N uniform grids according to a preset grid size. The coordinates of each grid point are... ,in , M and N are both positive integers.

3. The intelligent control method for smart streetlights according to claim 1, characterized in that, Step 2 specifically includes: Based on the rated illumination radius of the faulty street light Preset search radius ,satisfy , Dynamically adjust according to the actual lighting needs of the fault area; Centered on the faulty streetlight, search within a preset radius. Search for all working streetlights within the range and identify them as candidate streetlights; Collect and obtain the light distribution curve function, installation height, installation tilt angle, current position coordinates, and brightness adjustment limit of each candidate street light; the light distribution curve function is the light intensity distribution function of the candidate street light under different illumination angles. , Let be the angle between the illumination direction of the candidate streetlight and the vertical direction. For candidate streetlights at illumination angle The intensity of light below.

4. The intelligent control method for smart streetlights according to claim 1, characterized in that, Step 3 specifically includes: Step 3.1: For the k-th candidate street light and the grid point in the i-th row and j-th column within the fault area, calculate the straight-line distance between them. The calculation formula is: ； in, Let K be the coordinates of the k-th candidate street light. Let be the installation height of the k-th candidate street light; Step 3.2: Calculate the incident angle of the k-th candidate streetlight to the grid point in the i-th row and j-th column. This angle is the angle between the line connecting the candidate streetlight and the grid point and the horizontal plane where the grid point is located. The calculation formula is: ； Step 3.3, based on the light distribution curve function Straight-line distance and angle of incidence Calculate the actual illuminance value of the k-th candidate streetlight for the grid point in the i-th row and j-th column under the current brightness. The calculation formula is: ； in, The installation tilt angle and incident angle of the k-th candidate street light The difference, The luminous efficacy coefficient of the candidate streetlights; Step 3.4, Illuminance Contribution Matrix Generation: This involves generating the illuminance contribution matrix for each candidate streetlight at its current brightness across all grid points. Construct an illuminance contribution matrix using elements. The matrix has dimensions K×M×N, where K is the number of candidate streetlights.

5. The intelligent control method for smart streetlights according to claim 1, characterized in that, Step 4 specifically includes: For the k-th candidate street light, calculate its average illuminance value for all grid points in the fault area under the current brightness. The calculation formula is: ； Set the preset effective illuminance threshold , The value of is not lower than the minimum illuminance requirement for the corresponding road grade in the urban road lighting design standard; if the average illuminance value of the kth candidate street light If the brightness adjustment limit is greater than 1, then the candidate street light will be included in the actual compensation street light set.

6. The intelligent control method for smart streetlights according to claim 1, characterized in that, Step 5 specifically includes: Step 5.1: Let the number of streetlights in the actual compensation streetlight set be L, and the brightness adjustment coefficient of the l-th actual compensation streetlight be... , ,and The brightness adjustment limit of the street light shall not exceed the upper limit of the street light's brightness adjustment; based on the actual set of compensated street lights, generate all non-empty street light subsets, and assign preset multi-level discrete brightness adjustment coefficients to each street light in each street light subset, forming several distinct compensation combinations. The decision variable vector for a single compensation combination is: t represents the number of streetlights in the streetlight subset of this compensation combination. ; Step 5.2: For each compensation combination, calculate the illuminance compensation degree for the fault area. Additional energy consumption Glare value for oncoming drivers : Step 5.3: Combine all compensations , , Perform maximum and minimum value normalization separately to obtain the normalized index values. , , ; Step 5.4: Obtain the road type and real-time traffic flow data for the current road segment, and allocate regional illuminance compensation. Additional energy consumption Glare value for oncoming drivers Weighting coefficients , , And satisfy The higher the road grade and the greater the traffic volume, and The larger, The smaller; The comprehensive scoring model is constructed, and the calculation formula is as follows: ； Where S is the comprehensive score of a single compensation combination.

7. The intelligent control method for smart streetlights according to claim 1, characterized in that, Step 6 specifically includes: For each compensation combination, determine whether all grid points in the fault area meet the requirements. If the conditions are not met, the compensation combination will be removed. This is the minimum guaranteed illuminance value for the fault area; For each compensation combination, determine its glare value. Does it meet the requirements? , The maximum permissible glare value is preset. If it is exceeded, the overall score of the compensation combination will be downgraded by 30% to 50% of the original score. If the score after downgrading is lower than the average score of all valid combinations, the compensation combination will be removed. For each compensation combination, determine the brightness adjustment coefficient of each street light within its subset. Does it meet the requirements? And it does not exceed the upper limit of the brightness adjustment of the street light; if it does not meet the requirements, the compensation combination is removed. The effective compensation combinations after screening are sorted from high to low according to the comprehensive score S; the compensation combination with the highest score is taken as the final optimal lighting compensation scheme, and the street light subset of the compensation combination and the corresponding brightness adjustment coefficient are output. .

8. A faulty street light illumination compensation system based on dynamic optical matching, characterized in that, A method for implementing a smart street light intelligent control according to any one of claims 1 to 7 includes: The fault detection module is used to detect the working status of streetlights in real time. When a fault is detected in a streetlight, the location coordinates of the faulty streetlight are obtained. The area division module is used to perform grid-based division of the coverage area of ​​faulty streetlights and determine the coordinates of each grid point; The candidate search module is used to perform a candidate street light search with the faulty street light as the center and according to a preset search radius, and to obtain the light distribution curve function, installation height, installation tilt angle, current position coordinates and brightness adjustment limit of each candidate street light; The illuminance calculation module is used to calculate the actual illuminance contribution of each candidate street light to the fault area under the current brightness, based on its light distribution curve function and geometric relationship with each grid point in the fault area, and generate an illuminance contribution matrix. The street light filtering module is used to filter and form a set of actual compensated street lights based on the illuminance contribution matrix and the brightness adjustment limit. The combination generation module is used to generate several compensation combinations based on the actual set of compensation streetlights and determine the decision variable vector for each compensation combination. The index calculation module is used to calculate the illuminance compensation degree, additional energy consumption, and glare value for oncoming drivers corresponding to each compensation combination, and to complete the index normalization process. The weight allocation module is used to acquire road type and real-time traffic flow data, and allocate weight coefficients for the three types of evaluation indicators. The comprehensive scoring module is used to calculate the comprehensive score for each compensation combination based on normalized indicators and weighting coefficients. The scheme selection module is used to select effective compensation combinations based on constraints, score, rank and verify the effective compensation combinations, and select the compensation combination with the highest comprehensive score as the optimal lighting compensation scheme. The execution module is used to send the subset of streetlights with the optimal lighting compensation scheme and the corresponding brightness adjustment coefficients to the control terminals of each streetlight participating in the compensation, and control the streetlights to adjust to the corresponding brightness.

9. An electronic device, characterized in that, The method includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the intelligent street light control method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the intelligent control method for smart streetlights as described in any one of claims 1 to 7.

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