Solar street lamp intelligent regulation and control method and system based on illumination prediction

Abstract

The application discloses a kind of solar street lamp intelligent regulation and control method and system based on illumination prediction, belong to novel lighting technical field, including the following steps: determining target lighting area and target lighting cycle and collecting each street lamp basic data;Establish static lighting correlation base table;Before lighting, initial allocable lighting power is formed by illumination prediction;In each regulation round, current remaining deployable power, remaining lighting support margin and identify energy supply risk lamp are determined;Determine compensation target area, illuminance gap value and candidate compensation neighbor lamp set;Generate and execute neighbor lamp collaborative compensation scheme.The application realizes the technical effect of future period-oriented regional-level neighbor lamp collaborative compensation and reasonable distribution by illumination prediction before lighting and evaluating single lamp subsequent lighting support capability after lighting and carrying out regional collaborative compensation regulation, solve the problem of insufficient foresight, localized compensation decision and subsequent regulation imbalance in the prior art.

Description

Technical Field

[0004]

[0001] The present invention relates to the field of new lighting technologies, and particularly to an intelligent control method and system for solar street lamps based on light prediction. Background Art

[0002] With the continuous development of smart cities, green lighting, and new energy infrastructure, solar street lamps are widely used in road lighting, park lighting, community lighting, rural lighting, and other scenarios due to their characteristics of independent power supply, flexible layout, energy conservation, and environmental protection. In such applications, the operating effect of solar street lamps not only depends on the remaining battery power and current lighting state of a single lamp but also is closely related to daytime lighting conditions, changes in nighttime lighting requirements, spatial lighting relationships between adjacent lamp positions, and the collaborative deployment ability among multiple lamps in the area. Therefore, establishing an intelligent control method and system that can combine lighting information, lighting state, and regional collaborative relationships for unified control around solar street lamps has become an important direction for the development of related technologies.

[0003] Existing solar street lamp control systems usually adjust the brightness, irradiation range, or lighting duration of a single street lamp by collecting information such as the remaining battery power, ambient brightness, preset lighting timing, fault status, and pedestrians, vehicles, or time periods of a single street lamp to achieve single-lamp lighting control, energy-saving control, or power supply stability control; when there is insufficient illumination, insufficient energy supply at individual lamp positions, or local faults in a local area, the existing system will also improve the local lighting effect by increasing the brightness of adjacent street lamps or performing simple linkage supplementary lighting. In some implementations, the lighting coverage range is also analyzed in combination with the light distribution parameters of the lamp, installation height, and spatial position relationship, and the illumination or power change results are collected after the compensation execution for status monitoring or parameter adjustment.

[0004] For example, a solar street lamp and its control system disclosed in a Chinese invention patent with the publication number CN116456554A includes: a lighting module, a switching module, a control module, and a data acquisition module. The lighting module is used to provide lighting light; the switching module is used to switch the irradiation parameters of the lighting light emitted by the lighting module according to a control instruction; the data acquisition module is used to obtain control reference data; the control module is used to receive the control reference data and generate a control instruction according to the control reference data; the irradiation parameters specifically include light color, irradiation range, and irradiation intensity.

[0005] However, the above existing technologies mainly deal with the stability of single-lamp charge and discharge control, the adjustment of single-lamp irradiation parameters, or local supplementary lighting after current triggering. There is still room for further improvement in the regional adjacent lamp collaborative control based on the future energy supply capacity differences of single lamps, the compensation distribution combined with the overlapping lighting relationship of adjacent street lamps, and the closed-loop correction mechanism driven by the compensation execution results.

[0006] In the process of implementing the inventive technical solutions in the embodiments of this application, it was found that the above-mentioned technology has at least the following technical problems: In existing technologies, the control of solar streetlights is typically based on the remaining battery power, current ambient illuminance, current fault status, or preset lighting sequence, with the control primarily focused on the current state. Especially during the transition from natural to artificial lighting in the evening—specifically, from the period before the lights are turned on until the start of the target lighting cycle—residual sunlight often remains in the area. This residual sunlight continues to affect the actual charging results, initial available power, and subsequent lighting maintenance capacity of each streetlight at the beginning of the lighting cycle. Existing technologies do not adequately consider the continued impact of residual sunlight during this transition period on the subsequent lighting state. This makes it difficult to establish an initial control basis that accurately reflects the subsequent lighting maintenance capacity before and after the start of the target lighting cycle, easily leading to inaccurate initial lighting allocation, unstable subsequent control starting points, and delayed subsequent adjustment judgments.

[0007] Existing solar street light control schemes do not adequately consider the illuminance distribution at different locations within the road lighting area. In particular, they are difficult to accurately characterize uneven lighting in local areas, the location of dark areas, and their impact over time. As a result, after the target lighting cycle begins, areas with insufficient illuminance are not easily identified in a timely and accurate manner, which can easily lead to problems such as discontinuous lighting, prolonged darkness in local areas, or insufficient improvement in illuminance in local areas during subsequent periods.

[0008] In existing solar street light control schemes, the control process is usually based on the current state of a single lamp or the local instantaneous state. It does not adequately consider the relationship between the lighting responsibility of each street light in the area, the energy consumption process, and the lighting maintenance needs in subsequent periods. As a result, when there is uneven local illumination or the lighting capacity of individual lamps decreases, problems such as brightness distribution deviation, excessive burden on some lamps, uneven overall energy consumption, and reduced lighting guarantee capacity in subsequent periods are likely to occur during the subsequent control process. Summary of the Invention

[0009] To address the shortcomings of existing technologies, such as insufficient foresight, localized compensation decisions, and subsequent imbalances in regulation, this invention provides a method and system for intelligent regulation of solar streetlights based on illumination prediction. The technical solution is as follows: On the one hand, a method for intelligent regulation of solar streetlights based on illumination prediction is provided. This method is used in the control processing unit of a cloud control platform and includes the following steps: determining the target lighting area and target lighting cycle under current control and collecting basic data of each streetlight; establishing a static lighting association basic table based on the basic data of each streetlight and the spatial range of the target lighting area; performing illumination prediction based on the target lighting area, target lighting cycle, and basic data of each streetlight before the start of the target lighting cycle to form the initial available lighting power of each streetlight; after the start of the target lighting cycle, determining the current remaining adjustable power and remaining lighting support margin and identifying power supply risk lamp positions at the start of each regulation round based on the initial available lighting power; selecting the compensation target area based on the static lighting association basic table and power supply risk lamp positions, calculating the illuminance gap value of each analysis unit in each compensation target area, and screening the candidate compensation neighbor lamp set; constructing and selecting the feasible scheme with the minimum total incremental energy consumption based on the candidate compensation neighbor lamp set as the neighbor lamp collaborative compensation scheme for the current regulation round, and executing the neighbor lamp collaborative compensation scheme.

[0010] On the other hand, a solar street light intelligent control system based on illumination prediction is provided. This system is applied to a solar street light intelligent control method based on illumination prediction. The system includes: a cloud control platform and multiple solar street lights communicatively connected to the cloud control platform; the cloud control platform includes: a region determination and data acquisition module, used to determine the currently controlled target lighting area and target lighting cycle and collect basic data from each street light; a static lighting association module, used to establish a static lighting association basic table based on the basic data of each street light and the spatial range of the target lighting area; and an illumination prediction and initial lighting power generation module, used to perform illumination prediction based on the target lighting area, target lighting cycle, and basic data of each street light before the start of the target lighting cycle. The system includes: a light prediction module to determine the initial available lighting power for each street light; a power supply risk identification module to determine the current remaining adjustable power and remaining lighting support margin at the start of each control round based on the initial available lighting power after the target lighting cycle begins, and to identify power supply risk lamp positions; a compensation area and candidate neighbor lamp determination module to select the compensation target area based on the static lighting association table and power supply risk lamp positions, calculate the illuminance gap value of each analysis unit in each compensation target area, and screen the candidate compensation neighbor lamp set; a compensation scheme generation module to construct and select the feasible scheme with the minimum total incremental energy consumption as the neighbor lamp collaborative compensation scheme for the current control round based on the candidate compensation neighbor lamp set; and an execution module to execute the neighbor lamp collaborative compensation scheme.

[0011] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following: The present invention provides a method and system for intelligent control of solar streetlights based on illumination prediction. This method predicts illumination before the target lighting cycle begins and combines this prediction with basic data for each streetlight to determine its initial available lighting power. This ensures that each streetlight has an initial power base that matches its subsequent lighting maintenance capacity at the start of the target lighting cycle. During the transition from natural to artificial lighting in the evening, residual illumination typically remains in the area for a period before the lights are turned on and before the start of the target lighting cycle. This residual illumination continues to affect the actual charging results, initial available power, and subsequent lighting maintenance capacity of each streetlight at the beginning of the lighting cycle. If the judgment is based solely on the current remaining battery power or current ambient illuminance, it is difficult to accurately reflect the continued impact of residual illumination on the subsequent lighting state during this transition period. This can easily lead to inaccurate initial lighting allocation, unstable control starting points, and delayed subsequent control judgments. Through the above processing, the remaining adjustable power and remaining lighting support margin are formed after the lights are turned on. This allows for early reflection of the differences in lighting maintenance capabilities of each street light in subsequent periods during the initial control phase. This effectively improves the problem in the existing technology of insufficient control basis and difficulty in forming a reasonable starting control basis during the transition phase before and after the start of the target lighting cycle.

[0012] By establishing a static lighting correlation table, the illuminance coverage relationship at different locations within the area is expressed. Furthermore, it identifies power supply risk lamps, determines compensation target areas, filters candidate compensation neighbor lamp sets, and generates single-lamp compensation schemes and multi-lamp joint compensation schemes. This allows subsequent regulation to move beyond localized, immediate brightening, and instead achieve comprehensive regional allocation based on the illuminance needs of the compensation target area, the responsibility area constraints of participating neighbor lamps, and the remaining lighting support margin. This enables more accurate identification of areas with insufficient illuminance and improves the continuity and targeting of illuminance regulation in subsequent periods. It effectively addresses the problems in existing technologies where insufficient consideration of regional illuminance distribution leads to inaccurate identification of areas with insufficient illuminance and inadequate illuminance improvement.

[0013] By calculating the illuminance gap in the target compensation area, comparing the total incremental energy consumption corresponding to different compensation schemes, and collecting data on actual illuminance, actual power or actual electricity consumption, and changes in remaining battery power after compensation execution, the compensation sharing ratio coefficient and compensation brightness increment in subsequent control rounds are corrected. This ensures that the control process simultaneously considers local illuminance improvement, maintaining illuminance in the responsible areas of the participating streetlights, and overall energy consumption balance. Consequently, the compensation allocation results in subsequent control rounds can be continuously optimized, reducing the risk of excessive burden on some streetlights and uneven overall energy consumption. This effectively improves the problems of insufficient regional coordination, easy brightness allocation deviations in subsequent control, and decreased lighting guarantee capacity in subsequent periods in existing technologies. Attached Figure Description

[0014] Figure 1 A flowchart of the intelligent control method for solar streetlights based on illumination prediction provided in Embodiment 1 of this application; Figure 2 A flowchart of the initial lighting power generation method based on illumination prediction provided in Embodiment 1 of this application; Figure 3 This is a flowchart of the closed-loop correction process for the neighboring light collaborative compensation scheme provided in Embodiment 2 of this application; Figure 4 This is a schematic diagram of the structure of the intelligent control system for solar streetlights based on illumination prediction provided in Embodiment 3 of this application. Detailed Implementation

[0015] In this embodiment, taking a road lighting scenario as an example, the execution entity is the control processing unit in the cloud control platform, and the controlled objects are multiple solar streetlights that are communicatively connected to the cloud control platform. Each solar streetlight is spaced along the road direction, and each streetlight corresponds to a specific basic responsible lighting area. The cloud control platform executes neighboring light collaborative compensation control in a rolling manner according to the control cycle within the target lighting period. This mainly includes: establishing a static lighting association table, identifying streetlights with power supply risks, determining the compensation target area, screening candidate compensation neighboring light sets, generating a neighboring light collaborative compensation scheme, and executing compensation and collecting actual execution results. Through the above processing, the system can, under the current control cycle, form a neighboring light collaborative compensation scheme for streetlights with insufficient power supply or insufficient illuminance risks, combining the spatial lighting relationship between adjacent streetlights and the constraints of each neighboring light itself, targeting the compensation target area. Unless otherwise stated, all preset values ​​mentioned in this document are predetermined based on the road lighting design parameters, street light equipment rated parameters, controller resolution, battery specifications, meteorological forecast data granularity, illuminance sampling cycle, controller status reporting cycle, and deployment acceptance calibration results at the time of project deployment, in accordance with the above calculation rules, and are stored as known parameters on the cloud control platform. In the same project, the above preset values ​​remain consistent, or are pre-configured according to the corresponding street light model and road type.

[0016] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0017] Example 1: As Figure 1 The flowchart shown is a method for intelligent control of solar streetlights based on illumination prediction. The cloud control platform determines the target lighting area currently under control and determines the target lighting cycle according to preset lighting on and off rules.

[0018] The rules for determining whether to turn on the lights and the rules for determining whether to turn off the lights are pre-set and known operating rules of the system. Specifically, when the ambient illuminance of the target lighting area is lower than the lighting threshold for N consecutive samplings, the target lighting cycle is determined to begin. If the ambient illuminance of the target lighting area has not been lower than the lighting threshold for N consecutive samplings before this, but the preset latest lighting time has been reached, the target lighting cycle is also determined to begin. When the target lighting area reaches the preset earliest lighting time, if the ambient illuminance is higher than the lighting threshold for N consecutive samplings, the target lighting cycle is determined to end. If the ambient illuminance does not meet the requirement of being higher than the lighting threshold for N consecutive samplings, the target lighting cycle is extended until the ambient illuminance meets the requirement of being higher than the lighting threshold for N consecutive samplings. The number of consecutive samplings N is predetermined based on the ambient illuminance sampling cycle, the anti-vibration requirements for switching lights on and off, and the characteristics of ambient illuminance fluctuations on site. The illuminance thresholds for turning lights on and off are predetermined based on the project lighting design requirements, the ambient illuminance level of the target area, and the lighting maintenance requirements when switching from natural light to artificial lighting. The preset latest time to turn on lights and the preset earliest time to turn off lights are predetermined based on the seasonal changes in sunlight in the project area, the road usage time requirements, and the lighting management requirements, and are stored as known parameters on the cloud control platform.

[0019] The cloud-based control platform collects basic data for each street light. This basic data includes at least the street light location, pole spacing, installation height, light distribution parameters, photovoltaic panel orientation and tilt angle, local fixed shading information, current remaining battery power, and historical power generation and consumption within the most recent consecutive preset statistical window.

[0020] The cloud-based control platform establishes a static lighting association table based on the location of each street light, the spacing between light poles, the installation height, the light distribution parameters of the light fixtures, and the spatial range of the target lighting area.

[0021] The static lighting association base table refers to a set of lighting space mapping results pre-established based on the fixed spatial layout and fixed light distribution parameters of streetlights. It is used to characterize the responsibility relationship and illuminance contribution relationship between streetlights and analysis units.

[0022] In road-type scenarios, the midpoint between adjacent streetlights is used as the boundary of adjacent basic responsible lighting zones along the road's extension direction. Perpendicular to the road, the effective lighting width of the road is used as the lateral boundary to delineate the basic responsible lighting zones of each streetlight. When the actual lighting coverage of adjacent streetlights overlaps within the effective lighting width of the road, the allocation of the basic responsible lighting zone in the overlapping area is not determined by the actual lighting coverage overlap, but by the midpoint boundary line along the road's extension direction. The area on one side of the midpoint boundary line belongs to the basic responsible lighting zone of one streetlight, and the area on the other side belongs to the basic responsible lighting zone of the other streetlight. Following preset fixed spatial division rules, each basic responsible lighting zone is divided into multiple analysis units of fixed size or fixed boundary rules, maintaining consistency within the same project. The center point of each analysis unit is used as the representative location point for that unit. Then, the horizontal distance, relative orientation, and spatial relationship formed by the installation height between adjacent streetlights and the representative location point are determined. Based on the light distribution data of the corresponding luminaire at the current brightness level, the illuminance value of the adjacent streetlight at the representative location of the analysis unit under the current condition without increasing brightness is obtained by looking up or interpolation, and this illuminance value is determined as the basic illuminance contribution of the adjacent streetlight to the analysis unit. Further, at a preset higher brightness level or a preset higher output level, the illuminance value of the adjacent streetlight at the representative location of the analysis unit after increasing output is obtained according to the same positional relationship and the same light distribution lookup method; then, the illuminance value after increasing output is compared with the basic illuminance contribution corresponding to the current brightness level, and the difference between the two is determined as the incremental illuminance contribution of the adjacent streetlight to the analysis unit. When the illuminance value after increasing output is less than or equal to the basic illuminance contribution corresponding to the current brightness level, the incremental illuminance contribution is recorded as zero. After the above processing, the basic responsible lighting area, analysis unit division results, basic illuminance contribution, and incremental illuminance contribution are uniformly recorded and indexed to form a static lighting association basic table. The street light locations, pole spacing, installation height, effective road lighting width, and luminaire light distribution parameters are known parameters during project deployment. The preset fixed space division rules are fixed rules pre-set by the system and maintained consistently within the same project. In road-type scenarios, the longitudinal boundary of the basic responsible lighting area is defined by the midpoint between adjacent street lights, and the lateral boundary is defined by the effective road lighting width. Each basic responsible lighting area is then divided into analysis units according to a fixed grid. The side length of the analysis unit along the road extension direction is one-tenth of the distance between adjacent street lights, and the side length along the lateral direction of the road is one-quarter of the effective road lighting width. When the side length cannot be divided evenly by the corresponding boundary length, the remaining part at the boundary is incorporated into the adjacent analysis unit. The above division results are maintained consistently within the same project.The preset higher brightness level refers to the level immediately preceding the current brightness level when the streetlight uses discrete brightness level control. If the current brightness level is already at its highest level, it will still be used. The preset higher output level refers to the output level obtained by adding a minimum adjustable output step to the current output level when the streetlight uses continuous output control. If the result exceeds the rated output limit, the rated output limit will be used. The above data and rules are predetermined based on the existing objective conditions of the project.

[0023] like Figure 2 The flowchart shown illustrates the initial lighting power generation method based on illumination prediction. Specifically, before the target lighting cycle begins, the cloud control platform determines the predicted time range for each predicted period from the start time of the current pre-lighting control cycle to the start time of the target lighting cycle, provided that the sunshine duration information is greater than 0.

[0024] During the transition from natural light to artificial lighting in the evening, the start of the target lighting cycle does not mean that natural light in the area has completely disappeared. This is especially true in scenarios with long summer days, persistent afterglow after sunset, and areas where there is still diffused light in the sky. For the initial period after the lights are turned on, residual light remains. Taking roadside solar streetlights as an example, when the system has reached the preset lighting conditions and entered the target lighting cycle, streetlights near the open western area can still receive strong afterglow and diffused light. Therefore, their actual charging results and initial available power are usually higher than those of streetlights blocked by buildings, trees, or mountains. If the judgment is based solely on the remaining battery power at the moment of lighting, without predicting and calculating the remaining light within the predicted time range before lighting, these two types of streetlights are easily mistaken for an approximate state, leading to a distorted assessment of subsequent lighting maintenance capabilities. By organizing the predicted irradiance, weather conditions, and sunshine duration within the predicted time range before the start of the target lighting cycle, and further forming the effective light received value and initial available lighting power of each street light, the actual energy supply status still affected by residual light at the beginning of the lighting cycle can be more realistically reflected. This provides a more accurate starting power basis for subsequent regulation and improves the accuracy of subsequent energy supply risk identification and compensation allocation.

[0025] The predicted time range before the lights are turned on is divided into multiple consecutive prediction periods with a fixed time period length. For each prediction period, the predicted regional irradiance, weather status information and sunshine duration information are obtained and organized according to the order of the start time of the prediction period to form regional illumination prediction information. The fixed time period length is taken as the smallest time granularity published by the meteorological forecast data source; when the meteorological forecast data source contains multiple time granularities, the smallest time granularity consistent with the control period is taken; if the control period is not an integer multiple of the meteorological forecast time granularity, the meteorological forecast time granularity that is no greater than the control period and closest to the control period is taken; regional illumination forecast information refers to the set of forecast data organized in the order of forecast time periods within the forecast time range before the lights are turned on for the target lighting area; regional predicted irradiance is the cumulative irradiance within the forecast time period; sunshine duration information is used to characterize the actual duration of being in the sunshine interval within the forecast time period and participates in the formation of regional predicted irradiance; weather state information is obtained from weather elements in the same meteorological forecast data source, and continuous weather elements are averaged by area, while discrete weather elements are selected from the category with the largest coverage area or the longest duration; sunshine duration information is obtained by calculating the overlap duration between each forecast time period and the sunshine interval based on the geographical location, date, and sunrise and sunset times of the target lighting area. Weather elements include at least continuous and discrete weather elements. Continuous weather elements are weather data that can be numerically represented and compared, and include at least one or more of cloud cover, temperature, relative humidity, wind speed, and precipitation intensity. Discrete weather elements are weather data represented in categorical form, and include at least one or more of sunny, partly cloudy, cloudy, overcast, rainy, snowy, and foggy. Specifically, for continuous weather elements, the area of ​​intersection between the target illumination area and each meteorological forecast grid is used as the weight to perform an area-weighted average of the continuous weather element values ​​corresponding to each meteorological forecast grid, thus obtaining the continuous weather element values ​​for the target illumination area during the forecast period. For discrete weather elements, the forecast period is divided into multiple equal-length sub-periods. The sum of the products of area and duration of each discrete weather category within the target illumination area is calculated, and the weather category with the largest sum of area and duration is determined as the weather state category for the forecast period. When the sum of the products of area and duration of two or more weather categories is the same, the weather category with the larger coverage area is selected. If the coverage area is still the same, the weather category with the longer duration is selected.

[0026] The cloud-based control platform, based on pre-lighting regional illumination forecasts and considering factors such as the orientation and tilt angle of each streetlight's photovoltaic panels, localized fixed shading information, historical light reception deviations, and historical power generation reductions, performs individual-lamp corrections on the regional predicted irradiance for each forecast period before lighting is turned on. This results in the effective light reception value for each streetlight during each forecast period before lighting is turned on. The regional predicted irradiance refers to the cumulative irradiance of the target lighting area during a specific forecast period, and its formation process already incorporates the influence of weather conditions and sunshine duration during that forecast period. The effective light reception value refers to the light reception result for a specific streetlight during a specific forecast period, which, after considering its installation conditions, localized fixed shading, historical light reception deviations, and historical power generation reductions, can actually be used to estimate the power generation of that streetlight.

[0027] For a given street light during a specific forecast period, the cloud-based control platform first determines the orientation and tilt angle correction coefficients, as well as the local fixed shading correction coefficients. Then, it multiplies the predicted irradiance of the area corresponding to the forecast period by the orientation and tilt angle correction coefficients and the local fixed shading correction coefficients in sequence to obtain the reference irradiance value of the street light during the forecast period. Finally, it multiplies the reference irradiance value by the historical irradiance deviation correction coefficient and the historical power generation reduction correction coefficient in sequence to obtain the effective irradiance value of the street light during the forecast period.

[0028] Specifically, the correction factors are determined according to the following rules: Based on the orientation and tilt angle of the photovoltaic panel of the street light, the normal direction of the photovoltaic panel is determined; based on the solar azimuth and solar altitude angle corresponding to the center time of the forecast period, the solar incidence direction is determined; then, the cosine value of the angle between the normal direction of the photovoltaic panel and the solar incidence direction is calculated, and this cosine value is used as the orientation and tilt angle correction coefficient. When the cosine value is less than 0, the orientation and tilt angle correction coefficient is recorded as 0; otherwise, the cosine value is directly used. The value range of the orientation and tilt angle correction coefficient is 0 to 1.

[0029] The prediction period is divided into multiple sampling sub-times with a fixed time step of 5 minutes. The number of sampling sub-times, K, is the total duration of the prediction period divided by 5 minutes and rounded up, with K not less than 3. For each sampling sub-time, the coverage area of ​​the shading projection on the effective light-receiving surface of the photovoltaic panel is calculated based on the local fixed shading information of the street light, the installation location of the photovoltaic panel, and the solar azimuth and solar altitude angles corresponding to that sampling sub-time. This coverage area is then divided by the effective light-receiving area of ​​the photovoltaic panel to obtain the shading coverage ratio for that sampling sub-time. The average shading coverage ratio of the K sampling sub-times is calculated to obtain the average shading coverage ratio for the prediction period. The local fixed shading correction coefficient is obtained by subtracting the average shading coverage ratio from 1. When the average shading coverage ratio is 0, the local fixed shading correction coefficient is recorded as 1; when the average shading coverage ratio is 1, the local fixed shading correction coefficient is recorded as 0; in other cases, the result of subtracting the average shading coverage ratio from 1 is directly taken. The value range of the local fixed shading correction coefficient is from 0 to 1.

[0030] Within the most recent consecutive preset statistical window, historical samples that simultaneously meet the following criteria for the current forecast period: the same weather condition category, the same time period number, normal equipment operation, and no new changes in local fixed shading status. For each historical sample, the predicted irradiance for the corresponding area is multiplied sequentially by the orientation and tilt correction coefficients and the local fixed shading correction coefficient to obtain the baseline light reception value for that historical sample. Then, the actual photovoltaic input energy recorded by the street light controller within the corresponding time period is obtained, and this actual photovoltaic input energy is divided by the product of the effective light-receiving area of ​​the photovoltaic module and the nominal conversion capacity of the module to obtain the actual equivalent light reception value for that historical sample. Finally, the actual equivalent light reception value is divided by the baseline light reception value to obtain the light reception deviation ratio for that historical sample. The light reception deviation ratios of all valid historical samples within the most recent consecutive preset statistical window are sorted by value, and the median is taken as the historical light reception deviation correction coefficient. When the number of valid historical samples is less than the preset minimum sample number, the historical light reception deviation correction coefficient is recorded as 1. When the median is greater than the preset upper limit, the value of the preset upper limit is used; when the median is less than the preset lower limit, the value of the preset lower limit is used. The historical light reception deviation correction coefficient ranges from the preset lower limit to the preset upper limit. The light reception deviation ratios of all valid historical samples within the most recent consecutive preset statistical window are sorted according to their numerical values. The first quartile value Q1, the third quartile value Q3, and the interquartile range IQR = Q3 - Q1 are calculated. The preset upper limit is set to Q3 + 1.5 × IQR, and the preset lower limit is set to Q1 - 1.5 × IQR. When the preset lower limit is less than 0, it is set to 0. The preset minimum sample size is the result of rounding up 30% of the total number of historical samples meeting the screening criteria within the most recent consecutive preset statistical window, and is not less than 5.

[0031] Within the most recent consecutive preset statistical window, historical samples are selected that meet the following criteria: the battery is not in a fully charged state, the controller is not in a current-limiting state, and the equipment is operating normally. For each historical sample, the corrected effective solar energy received is first calculated according to the aforementioned rules; then, this corrected effective solar energy received is multiplied by the effective solar energy received area of ​​the photovoltaic module and the module's nominal conversion capacity to obtain the baseline power generation of the historical sample; finally, the actual photovoltaic input power recorded by the controller during the historical sample period is divided by the baseline power generation to obtain the power generation reduction ratio of the historical sample. The power generation reduction ratios of all valid historical samples within the most recent consecutive preset statistical window are sorted by value, and the median is taken as the historical power generation reduction correction coefficient. When the number of valid historical samples is less than the preset minimum sample number, the historical power generation reduction correction coefficient is recorded as 1. When the median is greater than 1, it is taken as 1; when the median is less than the preset minimum reduction value, it is taken as the preset minimum reduction value. The historical power generation reduction correction factor ranges from a preset minimum reduction value to 1. The preset minimum sample size is the result of rounding up 30% of the total number of historical samples that meet the screening criteria within the most recent consecutive preset statistical window, and is not less than 5. The preset minimum reduction value is the larger of the following two values: one is the minimum output capacity ratio at the end of the life given by the photovoltaic module manufacturer, and the other is the fifth percentile value of the power generation reduction ratio of all valid historical samples within the most recent consecutive preset statistical window.

[0032] After completing the above corrections, the effective light received value of the street light during the predicted period is obtained. In the same project, when the regional predicted irradiance, sunshine duration information, photovoltaic panel orientation and tilt angle, local fixed shading information, historical sample set, and preset threshold are the same, the resulting effective light received value is uniquely determined.

[0033] Furthermore, the cloud control platform determines the available energy storage capacity of each street light at the start of the target lighting cycle based on the remaining battery power, the effective light received during each predicted period before the lights are turned on, and the expected charging results for the corresponding predicted periods. Then, it subtracts the battery safety reserve capacity and the cross-cycle minimum reserve capacity from the available energy storage capacity to obtain the initial available lighting power for each street light at the start of the target lighting cycle. If the result of subtracting the battery safety reserve capacity and the cross-cycle minimum reserve capacity from the available energy storage capacity is less than zero, the initial available lighting power is recorded as zero. The battery safety reserve capacity equals the rated available battery capacity multiplied by the minimum permissible state of charge threshold, which is taken from the minimum permissible state of charge value set by the battery management system. The cross-cycle minimum reserve capacity equals the minimum guaranteed lighting duration of the next lighting cycle multiplied by the power consumption parameter per unit time of the corresponding street light at the minimum lighting output level. The minimum guaranteed lighting duration of the next lighting cycle is taken from the minimum guaranteed duration pre-written in the project's lighting operation plan. The power consumption parameter per unit time of the corresponding street light at the lowest lighting output level is taken as the average power value of the street light during a complete metering cycle of continuous operation at the lowest lighting output level.

[0034] The expected charging result refers to the estimated amount of electricity that the corresponding street light will actually charge its battery during a predicted period before it is turned on. The available energy storage base refers to the energy storage result of a street light at the start of the target lighting cycle, formed by summing the current remaining battery power and the expected charging results for each predicted period before the light is turned on, before deducting the battery's safety reserve capacity and cross-cycle minimum reserve capacity. Specifically, for any street light during any predicted period before it is turned on, the cloud control platform multiplies the effective light reception value corresponding to that predicted period with the street light's pre-stored single-lamp charging conversion parameters to obtain the preliminary expected charging amount for that street light during that predicted period. The single-lamp charging conversion parameters are pre-determined based on the rated power and / or effective light reception area of ​​the corresponding street light's photovoltaic modules, the charging controller model, the line configuration, and the deployment acceptance calibration results, and are stored as known parameters in the cloud control platform. Furthermore, the cloud control platform limits the initial estimated charging amount based on the maximum allowable charging amount of the street light and the remaining charging capacity of the battery during the predicted period, and determines the result of the limiting process as the expected charging result of the street light during the predicted period; when the effective light reception value during the predicted period is zero, the expected charging result during the predicted period is recorded as zero.

[0035] Initial available lighting power refers to the amount of power that a street light can actually use for regulation and allocation during the target lighting cycle, after deducting the necessary reserved power.

[0036] After the target lighting cycle begins, the cloud control platform executes control rounds in a rolling fashion according to a preset fixed control duration. The preset fixed control duration is the maximum value among the ambient illuminance sampling period, the street light controller status reporting period, and the brightness adjustment stabilization time. In the first control round after the target lighting cycle begins, the cloud control platform determines the initial available lighting power as the current remaining adjustable power of the corresponding street light, thus determining the current remaining adjustable power of the street light in the first control round; when the result after deduction is less than zero, the current remaining adjustable power is recorded as zero. In subsequent control rounds, the cloud control platform determines the current remaining adjustable power of the street light in the current control round by deducting the corresponding reserved power from the actual remaining power after the end of the previous control round. The current remaining adjustable power refers to the power that a street light, after deducting the battery safety reserve power and the cross-cycle minimum reserve power predetermined by the system at the beginning of the current control round, can still be used for lighting allocation in the current round and subsequent time periods.

[0037] Furthermore, the cloud control platform determines the subsequent minimum lighting power demand of each street light based on the system's pre-set minimum lighting maintenance requirements, minimum lighting output level, and the corresponding street light's power consumption parameters per unit time at the minimum lighting output level, combined with the remaining lighting duration from the start of the current control cycle to the end of the target lighting cycle; and forms the remaining lighting support margin for each street light based on the difference between the current remaining adjustable power of each street light and the corresponding subsequent minimum lighting power demand; and then identifies the power supply risk of each street light by combining the static lighting association basic table. Among them, the energy supply risk lamp position refers to the street light that needs to be judged for subsequent compensation because, under the current control cycle, there is insufficient electricity available for subsequent lighting allocation, and / or it is difficult to ensure that the basic responsibility lighting area can continuously meet the minimum illuminance requirement under the current output conditions; the minimum lighting maintenance requirement is the larger value between the minimum average illuminance requirement in the lighting standard corresponding to the target road level and the minimum safe lighting requirement set in the project operation plan; the minimum lighting output level is the larger value between the following two values: one is the minimum stable output level supported by the street light controller, and the other is the minimum output level that can ensure that the average illuminance of the basic responsibility lighting area is not lower than the minimum lighting maintenance requirement.

[0038] When the remaining lighting support margin of a street light is less than zero, the street light is identified as a power supply risk position. Alternatively, based on the static lighting association table, if, under the current output conditions of the street light, the current total illuminance value of any analysis unit within its basic responsible lighting area is lower than the minimum illuminance requirement corresponding to that analysis unit, the street light is also identified as a power supply risk position. The minimum illuminance requirement is determined according to the project lighting design requirements, road grade requirements, and / or the minimum lighting maintenance rules preset by the system, and is stored as a known parameter on the cloud control platform. The current total illuminance value refers to the total illuminance value that a certain analysis unit can obtain under the current control cycle and current output conditions. Specifically, for any analysis unit, the illuminance contribution of the power supply risk position to the analysis unit under the current output level and the basic illuminance contribution of each adjacent street light to the analysis unit under the current condition of not increasing brightness are read; then, the above illuminance contributions are added together to obtain the current total illuminance value of the analysis unit.

[0039] For identified power supply risk lamp positions, the cloud control platform, in conjunction with the static lighting correlation table, further identifies insufficient illuminance in each analysis unit within its basic responsibility lighting area. When the current total illuminance value of an analysis unit is lower than the minimum illuminance requirement, and the analysis unit is within the effective incremental lighting range of at least one adjacent street light, the analysis unit is identified as a compensation-needed analysis unit. Spatially adjacent analysis units corresponding to the same power supply risk lamp position are merged to form a compensation target area. The compensation target area refers to the set of analysis units that, under a certain control cycle, suffer from insufficient illuminance due to power supply risk lamp positions, are within the effective incremental lighting range of at least one adjacent street light, and can be improved through neighboring lamp compensation.

[0040] Furthermore, the cloud-based control platform calculates the illuminance gap value for each analysis unit within each compensation target area, and forms the regional illuminance gap value for the corresponding compensation target area based on the illuminance gap values ​​of each analysis unit. The illuminance gap value refers to the amount of illuminance that a particular analysis unit or compensation target area still lacks relative to the minimum illuminance requirement. Specifically, when the minimum illuminance requirement of an analysis unit is greater than the current total illuminance value, the difference is determined as the illuminance gap value of that analysis unit; when the minimum illuminance requirement of an analysis unit is less than or equal to the current total illuminance value, the illuminance gap value of that analysis unit is recorded as zero. For any compensation target area, the illuminance gap values ​​of each analysis unit within that area are weighted and summed according to the area of ​​the corresponding analysis unit to form the regional illuminance gap value for that compensation target area. The regional illuminance gap value refers to the amount of illuminance that is still insufficient for each analysis unit within a certain compensation target area relative to its respective minimum illuminance requirement. It is a regional-level illuminance deficiency characterization value formed by weighting and summing the corresponding analysis unit areas. It is used to quantify the overall degree of illuminance deficiency in the compensation target area and serves as the basis for subsequent candidate compensation neighbor lamp screening, neighbor lamp collaborative compensation scheme generation, and comparison of the effects of different compensation schemes.

[0041] After determining the target compensation area and its illuminance deficit value, the cloud control platform filters a set of candidate neighboring lights for each target compensation area. Specifically, for any street light adjacent to the target compensation area, if it contributes incremental illuminance to at least one analysis unit within the target compensation area and the incremental illuminance contribution is not zero, and after undertaking compensation, its own basic responsibility lighting area still meets the minimum illuminance requirement, its remaining lighting support margin is not less than zero, and its output level after undertaking compensation does not exceed the maximum allowable luminance limit or the maximum allowable power limit, then the adjacent street light is determined as a candidate neighboring light for the target compensation area. The maximum allowable brightness limit or maximum allowable power limit is used to constrain the maximum allowable output level of adjacent streetlights after compensation. When the streetlight adopts discrete brightness level control, the maximum allowable brightness limit is the lower of the highest brightness level supported by the luminaire controller and the highest operating brightness level allowed by the project configuration. When the streetlight adopts continuous output control, the maximum allowable power limit is the minimum value among the rated maximum power of the luminaire, the maximum allowable output power of the driver, and the maximum allowable output power of the controller. When the controller has a power corresponding to real-time protection current limiting, the smaller value between the minimum value and the power corresponding to real-time protection current limiting is further taken. When the output level of an adjacent streetlight after compensation is higher than the maximum allowable brightness limit or maximum allowable power limit, the adjacent streetlight is not identified as a candidate compensation neighbor light.

[0042] The set of neighboring lights for compensation may include one or more adjacent streetlights; when a target area for compensation is located between two adjacent streetlights, and both adjacent streetlights meet the above conditions, the two adjacent streetlights are allowed to jointly constitute the set of candidate neighboring lights for compensation of the target area.

[0043] After forming a set of candidate neighboring lights for compensation, the cloud control platform constructs single-light compensation schemes and multi-light joint compensation schemes for the corresponding compensation target areas. For each candidate compensation scheme, the cloud control platform first performs a feasibility assessment. When the candidate compensation scheme simultaneously meets the following requirements: the illuminance of the compensation target area meets the standard, the illuminance of the basic responsibility lighting area of ​​the participating neighboring lights meets the standard, the remaining lighting support margin of the participating neighboring lights is not less than zero, and the output of the participating neighboring lights does not exceed the upper limit of brightness or power, the candidate compensation scheme is determined as a feasible scheme.

[0044] After obtaining all feasible solutions, the cloud control platform calculates the total incremental energy consumption corresponding to each feasible solution and sorts the feasible solutions in ascending order of total incremental energy consumption. The feasible solution with the smallest total incremental energy consumption after sorting is selected as the neighbor lamp collaborative compensation solution for the current control round.

[0045] When there are multiple feasible schemes with the same total incremental energy consumption, the scheme with the fewest neighboring lights participating in the compensation is selected first; when the number of neighboring lights participating in the compensation is still the same, the scheme with the largest minimum remaining lighting support margin after compensation is selected first.

[0046] The total incremental energy consumption refers to the sum of the increased power consumption of all participating neighbor lights relative to their current output level during the corresponding compensation execution period of the candidate compensation scheme. Specifically, the cloud control platform determines the power consumption of each participating neighbor light at the current output level and the power consumption at the output level corresponding to the increase in compensation brightness during the compensation execution period. The difference between the two is determined as the incremental energy consumption of the participating neighbor light. The incremental energy consumption of all participating neighbor lights is then added together to form the total incremental energy consumption corresponding to the candidate compensation scheme.

[0047] When no solution exists that can ensure the illuminance of the target compensation area meets the standard, the cloud control platform calculates the remaining illuminance gap value of the compensated area after the execution of each candidate compensation solution. Specifically, it first calculates the total illuminance value of each analysis unit within the target compensation area after the execution of the candidate compensation solution. Then, it compares the total illuminance value after compensation with the minimum illuminance requirement of the corresponding analysis unit to determine the remaining illuminance gap value of each analysis unit. The remaining illuminance gap values ​​of each analysis unit are then weighted and summed according to the area of ​​the corresponding analysis unit to form the remaining illuminance gap value of the compensated area corresponding to the candidate compensation solution. Under the premise that the illuminance of the basic responsibility lighting area of ​​the participating neighboring lamps meets the standard, the remaining lighting support margin of the participating neighboring lamps is not less than zero, and the output does not exceed the upper limit of brightness or power, the solution with the smallest remaining illuminance gap value of the compensated area is selected as the neighboring lamp collaborative compensation solution for the current control round. When there are multiple solutions with the same remaining illuminance gap value of the compensated area, the solution with the smallest total incremental energy consumption is further selected.

[0048] The adjacent lamp collaborative compensation scheme refers to the overall control scheme determined under the current control cycle to make up for the illuminance gap in a certain compensation target area, which includes the combination of adjacent lamps participating in the compensation, the sharing ratio coefficient of each adjacent lamp, the compensation brightness increment of each adjacent lamp, and the compensation execution period. The adjacent lamp compensation scheme is further divided into single lamp compensation scheme and multi-lamp joint compensation scheme.

[0049] For a single-lamp compensation scheme, each adjacent street lamp in the candidate compensation neighbor set is taken as the unique compensation neighbor lamp. Starting from the current output level of the adjacent street lamp, its compensation brightness increment is gradually increased. After each increase, the total illuminance value after compensation of each analysis unit in the compensation target area, the current total illuminance value of each analysis unit in the basic responsibility lighting area of ​​the adjacent street lamp, and the remaining lighting support margin of the adjacent street lamp after compensation are recalculated. When the illuminance of the compensation target area meets the standard, the illuminance of the basic responsibility lighting area of ​​the adjacent street lamp meets the standard, the remaining lighting support margin of the adjacent street lamp is not less than zero, and the output level does not exceed the upper limit of brightness or power, the corresponding result is recorded as a feasible single-lamp compensation scheme.

[0050] For multi-lamp joint compensation schemes, priority is given to constructing a two-lamp joint compensation scheme using directly adjacent streetlights on both sides of the compensation target area. When the two-lamp joint compensation scheme cannot meet the requirements, a multi-lamp joint compensation scheme including the next adjacent streetlight is constructed. For each joint compensation combination, the increase in illuminance compensation and corresponding increase in power consumption of each adjacent streetlight in the combination after increasing the corresponding compensation brightness increment are calculated. The adjacent streetlight with the larger illuminance compensation per unit incremental energy consumption is selected first, and its compensation brightness increment is further increased. Then, the remaining illuminance gap in the compensation target area, the illuminance status of the basic responsibility lighting area of ​​each participating adjacent streetlight, and the remaining lighting support margin of each participating adjacent streetlight are updated. The above process is repeated until the illuminance gap in the compensation target area is filled, or all adjacent streetlights in the combination reach the constraint boundary and can no longer be compensated. When the illuminance gap is filled, the current result is recorded as a feasible multi-lamp joint compensation scheme.

[0051] The compensation brightness increment refers to the increase in brightness of the adjacent lights participating in the compensation relative to the current output level in the current control cycle; the compensation brightness increment is taken according to the minimum adjustable brightness resolution supported by the street light controller.

[0052] The sharing ratio coefficient of each participating neighboring light refers to the proportion of compensation tasks undertaken by each participating neighboring light in the target compensation area within a multi-light joint compensation scheme. Specifically, the cloud control platform first calculates the contribution of each participating neighboring light to the increased illuminance of each analysis unit within the target compensation area under the current compensation scheme; then, it weights and sums the contributions of each participating neighboring light to the increased illuminance of each analysis unit within the target compensation area according to the area of ​​the analysis unit, forming the regional compensation contribution amount corresponding to each participating neighboring light; finally, the ratio of the regional compensation contribution amount of a participating neighboring light to the total regional compensation contribution of all participating neighboring lights is determined as the sharing ratio coefficient of that participating neighboring light. When a target compensation area is compensated by only one neighboring light, the sharing ratio coefficient of that neighboring light is determined to be 1; when a target compensation area is compensated by multiple neighboring lights, the sharing ratio coefficient of each participating neighboring light is determined according to the above rules, and the sum of the sharing ratio coefficients of all participating neighboring lights equals 1.

[0053] After determining the neighboring light collaborative compensation scheme for the current control round, the cloud control platform extracts the compensation target area number, the neighboring light numbers participating in the compensation, the sharing ratio coefficient of each participating neighboring light, the compensation brightness increment corresponding to each participating neighboring light, and the compensation execution start time and compensation execution end time from the neighboring light collaborative compensation scheme. It then organizes the corresponding compensation control information according to the neighboring light numbers participating in the compensation; and sends the compensation control information to the participating neighboring lights, and continuously collects the actual execution results within the current control round.

[0054] The actual execution results include at least: the actual illuminance value of each compensation target area; the actual illuminance value of each participating neighboring lamp's own basic responsibility lighting area; the actual power or actual power consumption of each participating neighboring lamp; the change in the remaining battery power of each participating neighboring lamp; and the actual start and end duration of compensation for each participating neighboring lamp.

[0055] Example 2: Based on the neighboring light collaborative compensation scheme generated in Example 1, this example further provides a closed-loop correction process for the neighboring light collaborative compensation scheme in order to provide feedback correction based on the actual execution results.

[0056] like Figure 3The diagram shows the closed-loop correction process for the neighboring lamp collaborative compensation scheme. The cloud control platform determines the actual illuminance increment of each compensation target area within the current control cycle based on illuminance measurement results before and after compensation execution. Specifically, the actual illuminance value after compensation execution is compared with the actual illuminance value before compensation execution; the difference is determined as the actual illuminance increment of the corresponding compensation target area. When the difference is less than or equal to zero, the actual illuminance increment is recorded as zero. Simultaneously, the cloud control platform determines the actual incremental energy consumption of each participating neighboring lamp within the current control cycle based on the power or energy consumption changes before and after compensation execution. Specifically, the actual energy consumption of the participating neighboring lamp after compensation execution is compared with its baseline energy consumption during the corresponding compensation execution period at the current output level; the difference is determined as the actual incremental energy consumption of that participating neighboring lamp. When the difference is less than or equal to zero, the actual incremental energy consumption is recorded as zero.

[0057] Specifically, the cloud-based control platform compares the compensation efficiency of each participating neighboring lamp based on its actual contribution to the increase in illuminance and its actual increase in energy consumption in the current control cycle.

[0058] When the actual illuminance value of the target compensation area is lower than the minimum illuminance requirement, it indicates that the compensation effect in the current control round is insufficient. The cloud control platform compares the correspondence between the actual illuminance increment contribution and the actual increment energy consumption of each participating neighbor lamp in the current control round, prioritizes increasing the contribution ratio coefficient of participating neighbor lamps with higher compensation efficiency, and correspondingly increases the compensation brightness increment of the participating neighbor lamp to improve the compensation effect in the next control round. Specifically, the ratio of the actual illuminance increment contribution of a participating neighbor lamp to the target compensation area to the actual increment energy consumption of the participating neighbor lamp is calculated, and the obtained ratio is used as the compensation efficiency value of the participating neighbor lamp; the larger the compensation efficiency value, the greater the actual illuminance improvement brought by the unit increment energy consumption of the participating neighbor lamp, and the higher the compensation efficiency.

[0059] When the actual illuminance value of a participating neighboring lamp's basic responsibility lighting area is lower than the minimum illuminance requirement, and / or the remaining lighting support margin of the participating neighboring lamp drops below the preset safety threshold, it indicates that the participating neighboring lamp is undertaking too much compensation task in the current control round. The cloud control platform reduces the sharing ratio coefficient of the participating neighboring lamp and correspondingly reduces the compensation brightness increment of the participating neighboring lamp, while redistributing the reduced compensation task to other participating neighboring lamps that meet the conditions. The preset safety threshold is taken as the minimum subsequent lighting power demand corresponding to one control round.

[0060] When the actual illuminance value of the target compensation area meets the minimum illuminance requirement, the cloud control platform calculates the compensation efficiency value of each participating neighboring lamp based on the actual illuminance increment and actual incremental energy consumption. Under the premise that the total illuminance value of the target compensation area after compensation is still not lower than the minimum illuminance requirement, the illuminance of each participating neighboring lamp's own basic responsibility lighting area meets the standard, and the remaining lighting support margin is not less than zero, the platform gradually redistributes the sharing ratio coefficient of each participating neighboring lamp according to the preset minimum allocation adjustment unit. It also gradually reduces the compensation brightness increment of participating neighboring lamps with lower compensation efficiency according to the minimum adjustable brightness resolution. After each adjustment, the platform recalculates the total illuminance value of the target compensation area after compensation, as well as the illuminance status of each participating neighboring lamp's own basic responsibility lighting area and the remaining lighting support margin. If the adjusted result still meets the above conditions, the adjustment result is retained; otherwise, the adjustment result is revoked, thus forming a neighboring lamp collaborative compensation scheme with lower total incremental energy consumption. Among them, the preset minimum allocation adjustment unit is taken from the participating neighboring lights, and is the ratio of the minimum newly added area compensation contribution to the compensation target area to the total current area compensation contribution of all participating neighboring lights when the compensation brightness increment is increased by a minimum adjustable brightness resolution.

[0061] After each adjustment of the sharing ratio coefficient or the increase in compensated brightness, the cloud control platform recalculates the total illuminance value of the target area after compensation, the illuminance status of the basic responsibility lighting area of ​​each participating neighboring lamp, and the remaining lighting support margin. If the adjusted result still meets the requirements of illuminance in the target area, illuminance in the basic responsibility lighting area of ​​each participating neighboring lamp, and the remaining lighting support margin is not less than zero, the adjustment result is retained; otherwise, the adjustment result is revoked.

[0062] After completing the above corrections, the cloud control platform regenerates the neighboring light collaborative compensation scheme for the next control round based on the corrected compensation neighboring light sharing ratio coefficient and compensation brightness increment.

[0063] Example 3: To realize the generation process of the neighboring light collaborative compensation scheme, this example further provides a solar street light intelligent control system based on illumination prediction. For example... Figure 4 The diagram shows a structural schematic of a solar street light intelligent control system based on illumination prediction. The cloud control platform is used to uniformly control and coordinate compensation control of multiple solar street lights in the area; each solar street light is used to execute the compensation control information issued by the cloud control platform.

[0064] The cloud control platform includes the following modules: The area determination and data acquisition module is used to determine the currently controlled target lighting area and target lighting cycle, and to collect basic data for each street light. Specifically, this module is used to determine the currently controlled target lighting area and target lighting cycle, and to collect basic data such as the location of each street light, the distance between light poles, the installation height, the light distribution parameters of the luminaire, the orientation and tilt angle of the photovoltaic panel, local fixed shading information, the current remaining battery power, and historical power generation and consumption. This provides input data for subsequent static lighting association establishment, illumination prediction, and energy supply risk identification.

[0065] The static lighting association module is used to establish a static lighting association basic table based on the basic data of each street light and the spatial range of the target lighting area. Specifically, this module is used to delineate the basic responsibility lighting area of ​​each street light, form the analysis unit division results, and establish the correspondence between the basic illuminance contribution and incremental illuminance contribution of each adjacent street light to each analysis unit, thereby providing a spatial mapping basis for subsequent energy supply risk identification, compensation target area determination, and compensation scheme generation.

[0066] The illumination prediction and initial lighting power generation module is used to predict illumination based on the target lighting area, target lighting cycle, and basic data of each street light before the start of the target lighting cycle, and to generate the initial available lighting power for each street light. Specifically, this module is used to determine the prediction time range before the lights are turned on before the start of the target lighting cycle, generate regional illumination prediction information, and combine it with the basic data of each street light to generate the initial available lighting power for each street light at the start of the target lighting cycle, thereby providing the initial power basis for the first control round after the start of the target lighting cycle.

[0067] The energy supply risk identification module is used to determine the current remaining adjustable power and remaining lighting support margin at the beginning of each control round after the target lighting cycle begins, based on the initial available lighting power. Specifically, this module determines the current remaining adjustable power based on the initial available lighting power of each street light, the current remaining battery power, and the corresponding battery safety reserve power and cross-cycle minimum reserve power. It then combines this with the subsequent minimum lighting demand to form the remaining lighting support margin. Based on the remaining lighting support margin and the current total illuminance value of each analysis unit within the basic responsible lighting area, it identifies street lights with insufficient energy supply or insufficient illuminance risk in the current control round, thus providing input for the subsequent determination of compensation target areas and the generation of compensation schemes.

[0068] The compensation area and candidate neighbor light determination module is used to select compensation target areas based on the static lighting association table and power supply risk light positions, calculate the illuminance gap value of each analysis unit in each compensation target area, and screen the candidate compensation neighbor light set. Specifically, this module is used to identify insufficient illuminance in each analysis unit within the basic responsibility lighting area of ​​power supply risk light positions, determine the compensation target areas that need neighbor light compensation, and calculate the regional illuminance gap value; at the same time, based on the incremental illuminance contribution of adjacent streetlights to the compensation target area, the illuminance constraints of their own basic responsibility lighting area, the remaining lighting support margin constraints, and the output upper limit constraints, it screens the candidate compensation neighbor light set that can participate in the compensation, thereby providing a candidate object basis for the subsequent generation of neighbor light collaborative compensation schemes.

[0069] The compensation scheme generation module is used to construct and select the feasible scheme with the minimum total incremental energy consumption based on the candidate set of neighboring lights for compensation, as the neighboring light collaborative compensation scheme for the current control round. Specifically, this module is used to construct single-lamp compensation schemes and multi-lamp joint compensation schemes based on the candidate set of neighboring lights for compensation, and calculate the total incremental energy consumption of each feasible compensation scheme under the condition of making up for the illuminance gap in the area. Under the premise that the illuminance of the target compensation area meets the standard, the illuminance of the basic responsibility lighting area of ​​the candidate compensation neighboring light meets the standard, and the remaining lighting support margin of the candidate compensation neighboring light is not less than zero, the feasible scheme with the minimum total incremental energy consumption is selected; or, if the standard cannot be fully met, the scheme with the minimum remaining illuminance gap after compensation is selected as the neighboring light collaborative compensation scheme for the current control round.

[0070] The execution module is used to execute the neighboring light collaborative compensation scheme. Specifically, this module is used to send corresponding compensation control information to the neighboring lights participating in the compensation according to the neighboring light collaborative compensation scheme, so that the corresponding street lights perform compensation according to the sharing ratio coefficient, the compensation brightness increment, and the compensation execution period.

Claims

1. A method for intelligent control of solar streetlights based on illumination prediction, characterized in that, A control processing unit for a cloud-based control platform, wherein the cloud-based control platform is communicatively connected to multiple solar streetlights within a region, the method includes: Determine the currently controlled target lighting area and target lighting cycle, and collect basic data for each street light; Based on the basic data of each street light and the spatial range of the target lighting area, establish a basic table for static lighting association; Before the start of the target lighting cycle, illumination prediction is made based on the target lighting area, target lighting cycle, and basic data of each street light to form the initial available lighting power for each street light; After the target lighting cycle begins, the current remaining adjustable power, remaining lighting support margin, and power supply risk lamp positions are determined at the beginning of each control round based on the initial available lighting power. Based on the static lighting correlation table and the power supply risk lamp positions, the compensation target area is selected, the illuminance gap value of each analysis unit in each compensation target area is calculated, and the candidate compensation neighbor lamp set is screened. Based on the candidate set of neighboring lights for compensation, the feasible scheme with the minimum total incremental energy consumption is selected as the neighboring light collaborative compensation scheme for the current control round. Implement the neighboring light collaborative compensation scheme.

2. The intelligent control method for solar streetlights based on illumination prediction according to claim 1, characterized in that, The step of predicting illumination based on the target lighting area, target lighting cycle, and basic data of each street light to form the initial available lighting power for each street light also includes: Before the target lighting cycle begins, the predicted time range before lighting is determined as the time range from the start time of the current pre-lighting control cycle to the start time of the target lighting cycle, where the sunshine duration information is greater than 0. The predicted time range before the lights are turned on is divided into multiple consecutive prediction periods with a fixed time period length. For each prediction period, the predicted irradiance, weather status information and sunshine duration information are obtained and organized in the order of time periods to form regional light prediction information. Based on the regional illumination prediction information before the lights are turned on, and combined with the orientation and tilt angle of the photovoltaic panels of each street light, local fixed shading information, historical light reception deviation and historical power generation reduction, the regional illumination prediction information for each prediction period before the lights are turned on is corrected for each light, forming the effective light reception value of each street light in each prediction period before the lights are turned on. Based on the remaining battery power of each street light, the effective light received during each predicted period before the lights are turned on, and the expected charging results for the corresponding predicted period, the available energy storage capacity of each street light at the start of the target lighting cycle is determined. Then, the battery safety reserve capacity and the cross-cycle minimum reserve capacity are deducted from the available energy storage capacity to form the initial available lighting power of each street light at the start of the target lighting cycle.

3. The intelligent control method for solar streetlights based on illumination prediction according to claim 1, characterized in that, The target illumination cycle includes: The target lighting cycle is determined based on preset light-on and light-off rules. The rules for determining whether to turn on the lights and the rules for determining whether to turn off the lights are pre-set and known operating rules of the system. When the ambient illuminance of the target lighting area is lower than the lighting threshold for N consecutive samplings, the target lighting cycle is determined to start. If the ambient illuminance of the target lighting area has not been lower than the lighting threshold for N consecutive samplings before this, but the preset latest lighting time has been reached, the target lighting cycle is also determined to start. When the target lighting area reaches the preset earliest time to turn off the lights, and when the ambient illuminance is higher than the light-off illuminance threshold for N consecutive times, the target lighting cycle is determined to end. If the ambient illuminance does not meet the threshold of being higher than the light-off threshold for N consecutive times, extend the target lighting cycle until the ambient illuminance meets the threshold of being higher than the light-off threshold for N consecutive times.

4. The intelligent control method for solar streetlights based on illumination prediction according to claim 1, characterized in that, The establishment of the static lighting association base table includes: In road-type scenarios, the midpoint between adjacent streetlights is used as the boundary of the adjacent basic responsibility lighting area along the road extension direction; along the direction perpendicular to the road, the effective lighting width of the road is used as the lateral boundary to delineate the basic responsibility lighting area of ​​each streetlight. According to the preset fixed space division rules, each basic responsible lighting area is divided into multiple analysis units of fixed size or fixed boundary rules, and the same rules are maintained in the same project; Based on the basic street light data, determine the basic illuminance contribution and incremental illuminance contribution of each adjacent street light to each analysis unit; The basic responsibility lighting area, analysis unit division results, basic illuminance contribution, and incremental illuminance contribution are uniformly recorded and indexed to form a static lighting association basic table.

5. The intelligent control method for solar streetlights based on illumination prediction according to claim 1, characterized in that, The process of determining the current remaining adjustable power, remaining lighting support margin, and identifying power supply risk lamp positions at the beginning of each control round based on the initial available lighting power is as follows: In the first control round after the start of the target lighting cycle, the initial available lighting power generated by each street light is determined as the current remaining adjustable power of the corresponding street light. In subsequent control rounds, the actual remaining power after the end of the previous control round is subtracted from the corresponding reserved power, and the result is determined as the current remaining adjustable power of the street light in the current control round. Based on the minimum subsequent lighting demand from the start of the current control cycle to the end of this target lighting cycle, determine the minimum subsequent lighting demand for each street light, and based on the difference between the current remaining adjustable power of each street light and the corresponding minimum subsequent lighting demand, form the remaining lighting support margin for each street light. When the remaining lighting support margin is less than zero, the street light is identified as a power supply risk light position; Alternatively, by combining the static lighting association table, if the current total illuminance value of any analysis unit within the basic responsible lighting area of ​​the street light is lower than the minimum illuminance requirement corresponding to that analysis unit under the current output conditions of the street light, the street light will also be identified as a power supply risk lamp position.

6. The intelligent control method for solar streetlights based on illumination prediction according to claim 1, characterized in that, The compensation target area is selected based on the static lighting correlation table and the power supply risk lamp positions. The illuminance gap value of each analysis unit in each compensation target area is calculated, specifically as follows: For any analysis unit, when the minimum illuminance requirement of the analysis unit is greater than the current total illuminance value, the difference between the two is determined as the illuminance gap value of the analysis unit. When the minimum illuminance requirement of the analysis unit is less than or equal to the current total illuminance value, the illuminance gap value of the analysis unit is recorded as zero; For any target compensation area, the illuminance gap values ​​of each analysis unit within the area are weighted and summed according to the area of ​​the corresponding analysis unit to form the regional illuminance gap value of the target compensation area.

7. The intelligent control method for solar streetlights based on illumination prediction according to claim 1, characterized in that, The set of candidate compensation neighbor lights includes: For any street light adjacent to the compensation target area, if it contributes incremental illuminance to at least one analysis unit within the compensation target area and the incremental illuminance contribution is not zero, and after undertaking compensation, its own basic responsibility lighting area still meets the minimum illuminance requirement, its remaining lighting support margin is not less than zero, and its output level does not exceed the preset brightness limit or power limit, then the adjacent street light is determined as a candidate compensation neighbor light for the compensation target area. The candidate compensation neighbor light set may include one or more adjacent street lights. When a compensation target area is located between two adjacent street lights, the left and right adjacent street lights are allowed to jointly form the candidate compensation neighbor light set.

8. The intelligent control method for solar streetlights based on illumination prediction according to claim 1, characterized in that, The step of constructing and selecting the feasible scheme with the minimum total incremental energy consumption based on the candidate set of neighboring lights for compensation is specifically as the neighboring light collaborative compensation scheme for the current control round: Based on the set of candidate compensation neighbor lights, construct a single-lamp compensation scheme and a multi-lamp joint compensation scheme for the corresponding compensation target area. For each candidate compensation scheme, first perform a feasibility judgment. When the candidate compensation scheme simultaneously meets the following conditions: the illuminance of the compensation target area meets the standard, the illuminance of the basic responsibility lighting area of ​​the participating compensation neighbor light meets the standard, the remaining lighting support margin of the participating compensation neighbor light is not less than zero, and the output of the participating compensation neighbor light does not exceed the upper limit of brightness or power, the candidate compensation scheme is determined as a feasible scheme. After obtaining all feasible solutions, the cloud control platform calculates the total incremental energy consumption corresponding to each feasible solution, sorts the feasible solutions in order of total incremental energy consumption from small to large, and selects the feasible solution with the smallest total incremental energy consumption as the neighboring lamp collaborative compensation solution for the current control round. When there are multiple feasible schemes with the same total incremental energy consumption, the scheme with the fewest neighboring lights participating in the compensation is selected first. When the number of neighboring lights participating in the compensation is still the same, the scheme with the largest minimum remaining lighting support margin after compensation is selected first.

9. The intelligent control method for solar streetlights based on illumination prediction according to claim 1, characterized in that, Also includes: Implement the neighboring light coordination compensation scheme and collect the actual implementation results; The actual execution results include the actual illuminance value of the compensation target area and the actual illuminance value of the basic responsibility lighting area of ​​a neighboring lamp participating in the compensation; The actual execution result is compared with the target corresponding to the executed neighboring light collaborative compensation scheme; When the actual illuminance value of the target compensation area is lower than the minimum illuminance requirement, the sharing ratio coefficient of the neighboring lamps participating in the compensation with a larger actual illuminance increment corresponding to the unit incremental energy consumption is increased, and the compensation brightness increment of the neighboring lamp participating in the compensation is increased. When the actual illuminance value of the basic responsibility lighting area of ​​a neighboring lamp participating in compensation is lower than the minimum illuminance requirement, and / or the remaining lighting support margin of the neighboring lamp participating in compensation drops below the preset safety threshold, the sharing ratio coefficient of the neighboring lamp participating in compensation is reduced, and the compensation brightness increment of the neighboring lamp participating in compensation is reduced. When the actual illuminance value of the compensation target area has met the minimum illuminance requirement, and the total illuminance value after compensation in the compensation target area is still not lower than the minimum illuminance requirement, the illuminance of the basic responsibility lighting area of ​​each participating neighbor lamp meets the standard, and the remaining lighting support margin is not less than zero, the sharing ratio coefficient of each participating neighbor lamp is reallocated, and the compensation brightness increment of participating neighbor lamps with lower compensation efficiency is reduced, so as to form a neighbor lamp collaborative compensation scheme with lower total incremental energy consumption.

10. A solar street light intelligent control system based on illumination prediction, characterized in that, include: A cloud-based control platform, and multiple solar streetlights that are communicatively connected to the cloud-based control platform; The cloud control platform includes: The area determination and data acquisition module is used to determine the currently controlled target lighting area and target lighting cycle, and to collect basic data of each street light. The static lighting association module is used to establish a static lighting association base table based on the basic data of each street light and the spatial range of the target lighting area. The illumination prediction and initial lighting power generation module is used to predict illumination based on the target lighting area, target lighting cycle and basic data of each street light before the start of the target lighting cycle, and to generate the initial available lighting power for each street light. The energy supply risk identification module is used to determine the current remaining adjustable power and remaining lighting support margin at the beginning of each control round after the target lighting cycle begins, based on the initial available lighting power. It also identifies the lamp positions with energy supply risks. The compensation area and candidate neighbor lamp determination module is used to select the compensation target area based on the static lighting association basic table and the power supply risk lamp position, calculate the illuminance gap value of each analysis unit in each compensation target area, and screen the candidate compensation neighbor lamp set. The compensation scheme generation module is used to construct and select the feasible scheme with the minimum total incremental energy consumption as the neighboring lamp collaborative compensation scheme for the current control round based on the candidate compensation neighbor lamp set. The execution module is used to execute the neighboring light collaborative compensation scheme.

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