A control and power distribution system for solar street lights on urban roads

Abstract

The present invention relates to the technical field of solar street lamp control and power distribution, and specifically to a control and power distribution system for urban road solar street lamps, which includes a global power distribution strategy unit, an independent power distribution strategy unit, and a battery protection unit. When in the first lighting demand mode, the global power distribution strategy unit coordinates the electrical load within the area, then collects environmental data, combines historical environmental data and brightness records to predict future light changes, calculates the dimming demand, and generates a global power distribution strategy; when in the second lighting demand mode, the independent power distribution strategy unit determines the pre-adjusted street lamp positions by detecting the speed and direction of vehicles and pedestrians, and combines the dimming safety step length to generate an independent power distribution strategy; the battery protection unit generates a health prediction curve by diagnosing the battery health status, and formulates a battery pack load dispersion strategy in combination with the current load demand. The present invention reduces power consumption and extends the service life of the solar street lamp system by optimizing the power distribution strategy and battery management.

Description

Technical Field

[0001] The present invention relates to the technical field of solar street lamp control and power distribution, and particularly to a control and power distribution system for urban road solar street lamps. Background Art

[0002] As an environmentally friendly and efficient lighting solution, solar street lamps utilize the photovoltaic effect to convert sunlight into electrical energy through solar panels. The electrical energy is managed by a controller for storage and release, and finally drives LED lamps for lighting. For the sake of ensuring lighting stability and safety, currently, urban road solar street lamps mainly adopt the design of complementary power supply with the mains, and distribute power to the street lamps through timing control and photosensitive control.

[0003] The prior art mainly optimizes the power distribution management of solar street lamps from three aspects, including power control, dynamic adjustment, and data monitoring. For example, a power distribution method that combines solar photovoltaic components with an external intelligent microgrid is adopted, which improves the utilization rate of solar energy and reduces the dependence on municipal power; for example, by image acquisition and data analysis, the number and speed of people and vehicles on the road are monitored in real time, and the brightness of the street lamps is dynamically adjusted to reduce unnecessary power consumption; for another example, by collecting and processing data such as voltage and current, the switching of the street lamps is controlled according to real-time data, and combined with fault detection to ensure power supply safety and intelligent management.

[0004] The prior art has improved the efficiency and stability of the power distribution management of solar street lamps to a certain extent, but there are still deficiencies. The power distribution overall planning of the existing solar street lamp system ignores the problem of imbalance between power production and utilization rate in high and low load areas, and the utilization rate of solar resources needs to be improved; at the same time, the frequent switching and instantaneous changes of the brightness of the lamps will also exacerbate the wear and aging of the energy storage equipment and hardware equipment. How to extend the service life of the solar street lamp system while reducing power consumption is an urgent problem to be solved currently.

[0005] In order to improve the energy utilization efficiency of the urban road solar street lamp system and enhance the long-term operation stability of the system, the present invention proposes a control and power distribution system for urban road solar street lamps. Summary of the Invention

[0006] The object of the present invention is to provide a control and power distribution system for urban road solar street lamps, which reduces power consumption and extends the service life of the solar street lamp system by optimizing the power distribution strategy and battery management. In the first lighting demand mode, the global power distribution strategy unit collects environmental data to calculate the dimming demand, predicts future light changes by combining historical environmental data and brightness records, and coordinates the electrical load within the region to generate a global power distribution strategy; in the second lighting demand mode, the independent power distribution strategy unit determines the position of the pre-adjusted street lamps by detecting the speed and direction of vehicles and pedestrians, and generates an independent power distribution strategy in combination with the dimming safety step; the battery protection unit generates a health prediction curve by diagnosing the health status of the battery, and formulates a battery load dispersion strategy in combination with the current load demand.

[0007] To achieve the above object, the present invention provides a control and power distribution system for urban road solar street lamps, comprising:

[0008] A global power distribution strategy unit: in the first lighting demand mode, coordinating the electrical load demands of solar street lamps in multiple regions, and calculating the first dimming demand; collecting environmental data to calculate the second dimming demand; predicting future light changes according to historical environmental data and brightness adjustment records, and calculating the third dimming demand; comprehensively generating a global power distribution strategy from the first dimming demand, the second dimming demand and the third dimming demand;

[0009] An independent power distribution strategy unit: in the second lighting demand mode, detecting the speed and direction of passing vehicles and pedestrians, calculating the positions of the street lamps that need to be pre-adjusted in combination with the dimming safety step of the solar street lamps, and generating an independent power distribution strategy according to the positions of the street lamps.

[0010] A battery protection unit: obtaining the battery pack parameter data of the solar street lamp battery, diagnosing the current health status of the battery pack; obtaining the predicted health status curve of the battery pack according to the historical battery pack parameter data; obtaining the load demand of the current solar street lamp, and generating a battery load dispersion strategy according to the current health status of the battery pack and the predicted health status within a certain time step.

[0011] Further, the process of obtaining the first dimming demand includes:

[0012] Dividing the urban road solar street lamp system into multiple sub-regions according to the regional use; for each of the sub-regions, calculating the density of human and vehicle activities by detecting the area and the number of people and vehicles within the detection time;

[0013] Calculating the brightness demand of the sub-region according to the density of human and vehicle activities, and calculating and obtaining the electrical load of each sub-region in combination with the number of solar street lamps in the sub-region;

[0014] For each of the sub-regions, calculate the difference between the power consumption load of the sub-region and the average power consumption load of all sub-regions;

[0015] According to the preset regional dimming priority of each sub-region, combined with the corresponding power consumption load difference, calculate the first dimming demand.

[0016] Further, the process of obtaining the second dimming demand includes:

[0017] For each sub-region, collect the environmental data, including the light intensity L env and the air quality A env ; According to the environmental data, use the formula L req-2 =f(L env , A env ) to calculate the second dimming demand; where f(·) is a dimming demand calculation function.

[0018] Further, the process of obtaining the third dimming demand includes:

[0019] Collect historical environmental data and street lamp brightness adjustment records, and input them into the GRU network to obtain the environmental dimming relationship;

[0020] Obtain future weather prediction data, and obtain the third dimming demand through the environmental dimming relationship.

[0021] Further, the process of obtaining the global power distribution strategy includes:

[0022] Integrate the first dimming demand L req-1 , the second dimming demand L req-2 and the third dimming demand L req-3 of each sub-region to generate a comprehensive dimming demand S sub ;

[0023]

[0024] where ω1, ω2 and ω3 are the dynamic weights of the first dimming demand, the second dimming demand and the third dimming demand respectively, is the weight of the s-th sudden impact factor X s , and S is the number of the sudden impact factors;

[0025] Generate the global power distribution strategy according to the comprehensive dimming demand of all sub-regions.

[0026] Further, the process of obtaining the independent power distribution strategy includes:

[0027] Capture the vehicles and pedestrians within the radiation range of the solar street lamp, and obtain the traveling speed and traveling direction of the vehicles and pedestrians;

[0028] Set a safety step for the brightness adjustment of the street lamp according to the maximum power of the street lamp and the tolerance of the lamp hardware, and calculate the time required for the solar street lamp to adjust from the current brightness to the target brightness; combine the dimming time and the traveling speed of the vehicle or pedestrian to calculate and obtain the position of the street lamp that needs to be adjusted.

[0029] Determine the solar street lamps that need to be pre-adjusted according to the position of the street lamp, and generate the independent power distribution strategy.

[0030] Further, the process of obtaining the current health state and the predicted health state curve of the battery pack includes:

[0031] Obtain the battery pack parameter data of the solar street lamp battery, including voltage, current and temperature, analyze the health state of the battery pack according to the voltage change rate, current volatility and temperature change, and generate the health score of the battery pack.

[0032] Collect the historical parameter data, working data and historical health scores of the battery pack in the past period of time, input them into the GRU network to obtain the battery pack health relationship function; according to the real-time battery pack parameter data, obtain the predicted health state curve of the battery pack through the battery pack health relationship function.

[0033] Further, the process of obtaining the battery pack load dispersion strategy includes:

[0034] Obtain the current load demand of the solar street lamp; the load demand is generated by the global power distribution strategy and the independent power distribution strategy.

[0035] For the i-th battery in the battery pack, its current health score H battery is weighted with the predicted health state curve H predict-i within a certain time step ΔT to obtain the loadable score L loadability-i ;

[0036]

[0037] where λ1 and λ2 are the weights of the current health score and the predicted health state curve within a certain time step.

[0038] Sort the battery pack in descending order according to the loadable score.

[0039] Allocate the load demand according to the sorting; the specific allocation calculation formula is:

[0040]

[0041] where P load-i is the allocated load of the i-th battery, and P load-totalFor the load requirements of the solar street lamp, L loadability-j For the jth battery group, where m is the number of battery groups of the solar street lamp.

[0042] Furthermore, it also includes a power distribution priority mechanism for solar street lamps;

[0043] Obtain the lighting demand and demand urgency according to the real-time traffic density and real-time environmental conditions, and calculate the lighting priority score; obtain the power saving demand according to the real-time load demand and power supply situation, and calculate the power saving priority score; calculate the battery protection priority score according to the real-time battery health score and the real-time battery health status prediction curve.

[0044] Obtain the comprehensive priority score according to the lighting priority score, the power saving priority score, and the battery protection priority score.

[0045] Furthermore, the process of obtaining the comprehensive priority score is as follows:

[0046] Combine the lighting priority score P pri-light , the power saving priority score P pri-energy , and the battery protection priority score P pri-battery to obtain the comprehensive priority score P pri-final ;

[0047] P pri-final = γ1 × P pri-light + γ2 × P pri-energy + γ3 × P pri-battery ;

[0048] Where γ1, γ2, and γ3 are the dynamic weight coefficients of the lighting priority score, the power saving priority score, and the battery protection priority score respectively;

[0049] Formulate a real-time power distribution strategy according to the final comprehensive priority score P pri-final .

[0050] Compared with the prior art, the beneficial effects of the present invention are:

[0051] 1. First, according to the electricity consumption demands in different regions, the present invention coordinates the power loads among regions to achieve overall reasonable distribution. Then, it collects environmental data, including real-time light intensity and air quality, and calculates the current dimming demand. Finally, based on historical environmental data and brightness adjustment records, it predicts future light changes and optimizes the street lamp brightness in advance, which is different from the methods relying on timing and automatic light intensity adjustment in the prior art. By combining data dynamic adjustment and regional load distribution, the present invention avoids over-illumination in low-load regions during high-energy consumption modes, reduces power waste, and improves the energy utilization efficiency of the urban road solar street lamp system by optimizing the power resource distribution method, providing technical support for the long-term stable operation of the urban road solar street lamp system.

[0052] 2. The present invention captures vehicles and pedestrians within the radiation range of street lamps, detects their traveling speeds and directions, and calculates the positions of street lamps that need to be pre-dimmed in combination with the preset safety step length for brightness adjustment of solar street lamps, ensuring that the street lamp brightness is adjusted before the arrival of vehicles or pedestrians. Through gradual pre-dimming, the street lamp brightness can smoothly transition to the target brightness before the arrival of vehicles or pedestrians, solving the problems of current impact and accelerated lamp aging that may be caused by the instantaneous dimming method in the prior art. This method not only reduces the hardware loss of lamps and extends the service life of the solar street lamp system but also realizes a virtuous cycle between energy conservation and equipment durability in low-energy consumption modes.

[0053] 3. First, the present invention obtains data such as the voltage and current of the battery pack of solar street lamps, analyzes the current health status of the battery pack and generates a health score. Then, in combination with historical parameter data, it uses a GRU network to predict the future health status of the battery pack and generates a health prediction curve. Based on the current health score and the health prediction curve within a certain time step, a loadability score is given to each battery group. The load demand is allocated according to the score to avoid overusing batteries with poor health conditions and prevent damage to the batteries caused by deep discharge. By reasonably allocating the load demand, the present invention not only improves the utilization efficiency of batteries but also extends the overall life of the battery pack, thus enhancing the long-term stability of the urban road solar street lamp system. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a schematic flowchart of a control and power distribution system for an urban road solar street lamp provided by an embodiment of the present invention;

[0055] Figure 2 It is a schematic structural diagram of a control and power distribution system for an urban road solar street lamp provided by an embodiment of the present invention;

[0056] Figure 3 It is a schematic flowchart of a battery protection unit provided by an embodiment of the present invention;

[0057] Figure 4 Schematic structural diagram of the power distribution priority mechanism provided by the embodiment of the present invention for solar street lamps. Specific implementation manners

[0058] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0059] The present invention provides a control power distribution system for urban road solar street lamps. For the specific system process and system structure, refer to Figure 1 and Figure 2 . The present invention will describe the specific implementation manners through the control power distribution strategies of the urban road solar system in the first lighting demand mode and the second lighting demand mode. In addition, the specific implementation manners of the power distribution priority mechanism of the urban road solar street lamps will also be described.

[0060] Embodiment 1

[0061] As an implementation manner of the present invention, this embodiment describes the specific implementation manners of the control power distribution strategy of the urban road system in the first lighting demand mode. In the first lighting demand mode, the density and flow of people and vehicles in the area are both at a relatively high level. Therefore, a global power distribution strategy is adopted, including:

[0062] Coordinating the power load demands of solar street lamps in multiple regions, calculating the first dimming demand; collecting environmental data to calculate the second dimming demand; predicting future light changes based on historical environmental data and brightness adjustment records, and calculating the third dimming demand; comprehensively generating a global power distribution strategy from the first dimming demand, the second dimming demand, and the third dimming demand.

[0063] Further, the process of obtaining the first dimming demand includes:

[0064] Dividing the urban road solar street lamp system into multiple sub-regions according to the regional use;

[0065] Sys light →{C1, C2,... C k ,..., C n};

[0066] Among them, C k represents the kth sub-region, which includes several solar street lamps.

[0067] For each sub-region C k , through Calculate the human-vehicle activity density D of it traffic-k ; where N people-k and N vehicles-k are the population and vehicle numbers in sub-region C k within the detection area A area-k and within the detection time t, respectively.

[0068] Calculate the brightness requirement L of sub-region C k based on the human-vehicle activity density; demand-k ;

[0069] L demand-k = D traffic-k × L base-k ;

[0070] where L base-k is the minimum brightness level set according to the regional use.

[0071] Use P req-k = β1×L demand-k + β2×N light-k to calculate the power consumption load P k of sub-region C req-k , where N light-k is the number of solar street lamps in sub-region C k , and β1 and β2 are weight factors, representing the impacts of brightness requirement and the number of street lamps on the power consumption load respectively.

[0072] For each sub-region C k , calculate the difference ΔP between the power consumption load of this sub-region and the average power consumption load of all K sub-regions through the formula req-k ;

[0073] According to the preset regional dimming priority P prior-k of each sub-region, combined with the corresponding power consumption load difference ΔP req-k , calculate the first dimming requirement:

[0074]

[0075] where θ is a weight factor, representing the influence degree of the load difference on the dimming requirement.

[0076] In this embodiment, the urban road solar street lamp system is divided into multiple sub-regions according to the use, and the brightness requirement and power consumption load of each sub-region are calculated based on the human-vehicle activity density, and the electric power of the low-load sub-region is scheduled to the high-load sub-region; this method reduces the energy consumption and optimizes the overall planning and use of electric power resources on the premise of meeting the lighting requirements of different regions.

[0077] Further, collect the light intensity and air quality data of the area where the solar street lamp is located through sensors and detection instruments, and then calculate the second dimming demand; among them, the air quality data is mainly the concentration of inhalable particulate matter, and the corresponding situation is haze weather.

[0078] According to the light intensity L env and air quality A env , through L req-2 =f(L env ,A env ) calculate the first dimming demand L req-2 ; where f(·) is the dimming demand calculation function; specifically:

[0079]

[0080] Among them, ε and ξ are constants used to smooth the influence of different factors; β3 and β4 are the dynamic adjustment weights of light intensity and air quality respectively, which are adjusted according to the actual situation.

[0081] In this embodiment, by collecting the light intensity and air quality of each sub-region in real time and calculating the second dimming demand, the brightness adjustment of the street lamps in the sub-region is more targeted, ensuring that the street lamps provide sufficient lighting under various environmental conditions.

[0082] Further, the process of obtaining the third dimming demand includes:

[0083] Collect historical environmental data and street lamp brightness adjustment records, as follows:

[0084]

[0085] This historical record can be described as: at timestamp t, the light intensity L env (lux) exceeds the threshold and the concentration of inhalable particulate matter in the air reaches A env , triggering trigger, the solar street lamp is adjusted from the original brightness L1 to L2 within time t adjust .

[0086] Input the historical environmental data and street lamp brightness adjustment records into the GRU network to obtain the environmental dimming relationship; the process of obtaining the environmental dimming relationship includes:

[0087] Extract the feature vector and the target output Y t =L2 from the historical environmental data and the street lamp brightness adjustment records, and construct it into a structured data set D={(X t ,Y t )}, where each sample corresponds to one record. The structured data set D1={(X t ,Yt )} Input it into the GRU for calculation to obtain the environmental dimming relationship function.

[0088] Loss = Γ(Y, Y pred ) Λ Y pred = f gru (X) & W ← W - η▽Loss;

[0089] Among them, Γ is the loss function, Y is the true value, and Y pred is the predicted value calculated by f gru (X), η is the learning rate, and ΔLoss represents the gradient of the loss function with respect to the network weight W;

[0090] The environmental dimming relationship function g(·) is:

[0091]

[0092] Among them, δ1, δ2, and δ3 are parameters obtained by fitting the training data.

[0093] Obtain the future weather prediction data X future , including the light intensity and the air quality index, and use the environmental dimming relationship function g(·) to obtain the third dimming demand L req-3 .

[0094] L req-3 = g(X future );

[0095] In this embodiment, by combining historical environmental data and future weather predictions, a GRU network is used to establish an environmental dimming relationship model, which can provide a more scientific dimming strategy for street lights. This method can perform power scheduling in advance according to the predicted environmental conditions; ensure that the lighting intensity is adjusted in advance under low visibility conditions such as rainy or foggy weather, increasing road safety.

[0096] Integrate the first dimming demand L req-1 , the second dimming demand L req-2 and the third dimming demand L req-3 of each sub-region to generate the sub-region comprehensive dimming demand S sub ;

[0097]

[0098] Among them, ω1, ω2, and ω3 are the dynamic weights of the first dimming demand, the second dimming demand, and the third dimming demand respectively, is the s-th sudden impact factor X sThe weight, where S is the number of the sudden impact factors. The sudden impact factors refer to emergencies that require additional brightness illumination, including traffic accidents, weather mutations, emergencies, natural disasters, etc.

[0099] Generate the global power distribution strategy according to the comprehensive dimming requirements of all sub-regions; specifically, sort the comprehensive dimming requirements of all sub-regions in descending order, and schedule the power resources of the regional solar street lamp system according to the sorting.

[0100] In this embodiment, by integrating the first, second, and third dimming requirements of each sub-region, a global power distribution strategy is generated to ensure the coordinated distribution of power. This comprehensive method avoids the possible situations of power overload or shortage in a certain power area, improves the stability of the urban lighting system, and reduces energy waste.

[0101] Further, referring to Figure 3 , Figure 3 is a schematic flow chart of a battery protection unit provided in this embodiment. In the first lighting demand mode, obtain the lighting load requirements of different sub-regions through the global power distribution strategy, and evenly distribute the lighting load requirements within the solar street lamps in the sub-region; in order to reasonably distribute the load requirements borne by each solar street lamp, first obtain the health status of the solar street lamp battery pack, including:

[0102] Collect the parameter data of the i-th battery pack from time point t1 to t2, including current I, voltage V, and temperature T, calculate its voltage change rate, current volatility, and temperature change, analyze the health status of the battery pack, and generate the health score H of the i-th battery pack battery-i ;

[0103]

[0104] where ρ V , ρ I , and ρ T are the weights of the voltage change rate, current volatility, and temperature change rate respectively, which are adjusted according to the specific system configuration; σ I and μ I are the standard deviation and mean value of the current respectively.

[0105] Further, collect the historical parameter data, working data, and historical health scores of the battery pack in the past period of time, input them into the GRU network to obtain the battery pack health relationship function; according to the real-time battery pack parameter data, obtain the predicted health status curve of the battery pack through the battery pack health relationship function. The specific process includes:

[0106] Collect the historical parameter data, historical working data, and historical health score H his(t), is constructed into a battery pack historical health data set; the historical parameter data includes voltage data V his (t), current data I his (t), and temperature data T his (t); the historical working data includes charge and discharge conditions D charge and load data L his (t).

[0107] Input the battery pack historical health data set into the GRU network to learn the change trend of the battery health state, and output the battery pack health relationship function; the specific process is as follows:

[0108] For the historical health data set D2 = {[V his (t), I his (t), T his (t), D charge , L his (t]}, adopt the sliding window method to divide the time series data into multiple samples; input the samples into the GRU network for training to obtain the battery pack health relationship function;

[0109]

[0110] Among them, δ4 and δ5 are parameters obtained by fitting the training data; ε I is a constant to avoid zero values in logarithmic calculations.

[0111] Continuously collect the battery pack parameter data, and obtain the health score of the battery pack for a future period of time through the battery pack health relationship function, and combine it into the battery health prediction curve of the battery pack;

[0112] H predict ={H future (t1), H future (t2),..., H future (t q )};

[0113] In this embodiment, by monitoring and analyzing parameters such as the voltage, current, and temperature of the solar street lamp battery pack, the health status of the battery pack can be diagnosed in a timely manner; the generated health score helps to identify potential problems in advance, so as to carry out preventive maintenance; at the same time, predicting the future health status of the battery pack with the help of historical health records provides data support for the formulation of subsequent load dispersion strategies.

[0114] Furthermore, obtain the load demand of the current solar street lamp, and generate a battery pack load dispersion strategy according to the current health status of the battery pack and the predicted health status within a certain time step. The specific process includes;

[0115] For the i-th battery group in the battery pack, its current health score H battery-i is weighted with the predicted health state curve H predict-i within a certain time step ΔT to obtain the loadable score L loadability-i ;

[0116]

[0117] where λ1 and λ2 are the weights of the current health score and the predicted health state curve within the certain time step;

[0118] The battery pack is sorted in descending order according to the loadable score; the load demand is allocated according to the sort of the loadable scores;

[0119]

[0120] where P load-total is the load demand of the solar street lamp, P load-i is the allocated load of the i-th battery group, L loadability-j is the j-th battery group, and m is the number of battery groups of the solar street lamp.

[0121] It should be noted that in the first lighting demand mode, when the stored power of the solar street lamp system is insufficient to support the lighting demand, the power supply mode of the system is switched to mains power supply.

[0122] This embodiment first obtains the load demand of the solar street lamp, and then calculates the loadable score of each battery group according to the health state and the predicted health state curve of the battery group of the solar street lamp; the load demand is sorted according to the loadable score for load dispersion. This method can prevent some battery groups with intersecting health states from being overloaded or failing, improves the working efficiency of the battery group, and realizes more efficient load allocation.

[0123] Embodiment 2

[0124] As an implementation manner of the present invention, referring to Figure 4 , this embodiment describes the specific implementation manner of the control power distribution strategy of the urban road system in the second lighting demand mode. In the second lighting demand mode, the density and flow of people and vehicles in the area are both at a relatively low level, so an independent power distribution strategy is adopted, including:

[0125] Detect the passing speed and direction of vehicles and pedestrians, calculate the positions of street lamps that need to be pre-adjusted in combination with the dimming safety step of the solar street lamp, and generate an independent power distribution strategy according to the positions of the street lamps.

[0126] Further, through the image acquisition device and the sensing device deployed on the solar street lamp, the vehicle or pedestrian targets passing on the urban road are captured, and the traveling direction and speed of the targets are detected.

[0127] Set the safety step ΔL of the street lamp brightness adjustment according to the maximum power of the street lamp and the hardware tolerance of the lamp. adj , and calculate the time t required for the solar street lamp to be adjusted from the current brightness L current to the target brightness L desired ; adj ;

[0128]

[0129] Combined with the dimming time t adj and the traveling speed v of the vehicle or pedestrian, estimate the position x of the street lamp to be adjusted adj ;

[0130] x adj = x current + v·t adj ;

[0131] where, x current is the current position of the solar street lamp, that is, the position of the street lamp for vehicle and pedestrian detection.

[0132] According to the pre-adjusted street lamp position, determine the solar street lamps to be pre-adjusted and generate an independent power distribution strategy. Specifically, the solar street lamp corresponding to the street lamp position x adj will adjust the street lamp brightness to the target value with a safety step before the target arrives; when a vehicle or pedestrian is detected to have left the area radiated by the position detection device at the x adj position, the solar street lamp corresponding to the street lamp position x adj will adjust from the target brightness L adj to the original brightness with a safety step. desired

[0133] This embodiment first captures the dynamic information of vehicles and pedestrians within the radiation range of the street lamp, determines the position of the pre-adjusted street lamp in combination with the safety step of the street lamp brightness adjustment, and pre-increases the street lamp brightness before the pedestrian or vehicle arrives for safe lighting. This method avoids the accelerated hardware loss of the solar street lamp caused by instantaneous dimming while ensuring the lighting demand, and prolongs the service life of the equipment.

[0134] Further, in the second lighting demand mode, calculate the load demand of the pre-adjusted street lamp through the independent power distribution strategy;

[0135] P load (x adj ) = P min + 2·P step + PLdesired ;

[0136] Among them, P load (x adj ) is the load demand of the pre-adjusted street lamp, and P min is the load demand corresponding to the lowest brightness level; P step is the load demand during the brightness adjustment process; P Ldesired is the load demand for the continuous target brightness.

[0137] Obtain the street lamp position x adj corresponding to the battery pack parameter data of the solar street lamp battery, including voltage, current and temperature, analyze the health status of the battery pack according to the voltage change rate, current volatility and temperature change, and generate the health score of the battery pack; the predicted health status curve of the battery pack through the battery pack health prediction model.

[0138] Calculate the loadable score of the battery pack according to the load demand of the pre-adjusted street lamp generated by the independent power distribution strategy;

[0139] Perform load distribution by sorting the load demands according to the loadable score.

[0140] In the second lighting demand mode, when the power storage of the pre-adjusted solar street lamp is insufficient to support the lighting demand, switch the power supply mode of the solar street lamp to mains power supply.

[0141] Embodiment III

[0142] As an implementation manner of the present invention, this embodiment describes the specific implementation manner of the power distribution priority mechanism for urban road solar street lamps. Refer to Figure 4 , Figure 4 is the schematic structural diagram of the power distribution priority mechanism for solar street lamps provided by the embodiment of the present invention. According to different actual application scenarios, the priorities of lighting demand, power saving demand and battery protection are often in dynamic change. Therefore, in order to meet the specific requirements in the actual application scenarios, it is necessary to flexibly judge the importance of the three to formulate the priority strategy, and execute the corresponding control power distribution strategy according to the comprehensive priority.

[0143] Further, the power distribution priority mechanism for urban road solar street lamps includes:

[0144] Formulate the lighting priority strategy for urban road solar street lamps;

[0145] According to the traffic density and environmental conditions, through L rt = α1×D traffic-rt + α2×L env-rt Obtain the current lighting demand L rt ; where D traffic-rtis the current traffic density, L env-rt is the current environmental condition; α1 and α2 reflect the influence of traffic density and environmental condition on lighting demand; then, calculate the real-time demand urgency U urgency ;

[0146]

[0147] wherein, L history is the lighting demand in the same mode in the historical record; D traffic-rt is the current traffic density, D history-traffic is the traffic density in the same mode in the historical record; φ1 and φ2 are used to balance the influence of lighting demand and traffic density on the real-time demand urgency; the historical record includes historical experience and historical recorded data.

[0148] By obtain the current lighting priority score; wherein and are used to balance the influence of lighting demand and urgency;

[0149] According to the current load demand and power supply situation, through E demand = φ3 × P load + φ4 × C energy calculate the power saving demand; wherein E demand is the power saving demand, P load is the load demand, C energy is the power supply situation, φ1 and φ2 reflect the influence of load demand and power supply situation on the degree of power saving demand;

[0150] By obtain the current power saving priority score; wherein and are used to balance the influence of power saving demand and load demand;

[0151] According to the current battery health score and health prediction curve, calculate the battery protection priority score P pri-battery ;

[0152]

[0153] wherein, and are used to balance the influence of battery health score and health prediction curve.

[0154] This embodiment calculates the priority scores of lighting, power saving, and battery protection by comprehensively considering the real-time environmental conditions, traffic density, load demand, power supply situation, and battery health according to the specific situation in the actual application scenario, providing a data basis for the subsequent formulation of the power distribution strategy.

[0155] Comprehensively described lighting priority score P pri-light , power saving priority score P pri-energy and battery protection priority score P pri-battery , to obtain the comprehensive priority score P pri-final ;

[0156] P pri-final = γ1×P pri-light + γ2×P pri-energy + γ3×P pri-battery ;

[0157] Wherein, γ1, γ2 and γ3 are respectively the dynamic weight coefficients of the lighting priority score, the power saving priority score and the battery protection priority score.

[0158] Based on the final comprehensive priority score P pri-final Formulate a real-time power distribution strategy.

[0159] In this embodiment, by formulating a lighting priority mechanism for solar street lights, the power distribution can be controlled according to the specific conditions of the actual scenario; this method improves the flexibility of the control power distribution system of a kind of urban road solar street light proposed by the present invention, ensures the efficient operation of the system in a changing environment, and improves the emergency response ability of the system.

[0160] A control power distribution system for urban road solar street lights provided by an embodiment of the present invention intelligently regulates the brightness and power consumption load of street lights under different lighting demand modes, while improving the energy utilization rate of solar street lights and extending the service life of the solar street light system. In the first lighting demand mode, by analyzing environmental data and the flow of people and vehicles, a dimming demand is accurately generated to optimize the utilization efficiency of electric energy. In the second lighting demand mode, by analyzing the traveling speed and direction of people and vehicles, the position of the pre-adjusted street light is determined and dimming is advanced in advance, avoiding the loss problems of the storage battery and the lamp caused by frequent switching and instantaneous dimming in the prior art; finally, the health status of the storage battery is monitored in real time, and according to historical data, the future health strategy of the battery is predicted to reasonably disperse the load demand generated in the first lighting demand mode and the second lighting demand mode. The present invention not only alleviates the problem of excessive loss of the storage battery caused by frequent dimming in the prior art, but also improves the power saving effect and the equipment life of solar street lights, realizing more environmentally friendly and efficient urban lighting management.

[0161] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A control and power distribution system for solar street lights on urban roads, characterized in that, Including: Global power distribution strategy unit: In the first lighting demand mode, coordinate the power load demands of multiple area solar street lamps, and calculate the first dimming demand; Collect environmental data to calculate the second dimming demand; Predict future light changes based on historical environmental data and brightness adjustment records, and calculate the third dimming demand; Synthesize the first dimming demand, the second dimming demand, and the third dimming demand to generate a global power distribution strategy; Independent power distribution strategy unit: In the second lighting demand mode, detect the passing speed and direction of vehicles and pedestrians, and calculate the positions of street lamps that need to be pre-adjusted in combination with the safe step length of street lamp dimming, and generate an independent power distribution strategy based on the street lamp positions; Battery protection unit: Obtain the parameter data of the solar street lamp battery pack, and diagnose the current health status of the battery pack; Based on historical battery pack data, obtain the predicted health status curve of the battery pack; Obtain the current load demand of the street lamp, and generate a battery pack load dispersion strategy according to the current health status and the predicted health status curve within a certain time step; The load demand is generated by the global power distribution strategy and the independent power distribution strategy; The load dispersion strategy includes: For each group of batteries in the battery pack, perform a weighted calculation of its current health score and the predicted health status curve within a certain time step to obtain the loadable score of each group of batteries; Allocate the current load demand according to the descending order of the loadable scores.

2. The control and power distribution system of a solar street lamp for urban roads according to claim 1, characterized in that, The process of obtaining the first dimming demand includes: Divide the urban road solar street lamp system into multiple sub-areas according to the area usage; For the sub-areas, calculate the density of human and vehicle activities by detecting the area and the number of people and vehicles within the detection time; Calculate the brightness demand of the sub-area according to the density of human and vehicle activities, and calculate the power load of the sub-area in combination with the number of solar street lamps in the sub-area; For each sub-area, calculate the difference between the power load of this sub-area and the average power load of all sub-areas; According to the preset regional dimming priority of each sub-area, combine the corresponding power load difference to calculate the first dimming demand.

3. The control and power distribution system of a solar street lamp for urban roads according to claim 1, characterized in that, The process of obtaining the second dimming demand includes: For each sub-region, collect the environmental data, including the light intensity and the air quality ; according to the environmental data, use the formula to calculate the second dimming requirement; where is the dimming requirement calculation function.

4. The control and power distribution system of a solar street lamp for urban roads according to claim 1, characterized in that, The process of obtaining the third dimming demand includes: Collect historical environmental data and street lamp brightness adjustment records, and input them into the GRU network to obtain the environmental dimming relationship; Obtain future weather prediction data, and obtain the third dimming demand through the environmental dimming relationship.

5. The control and power distribution system of a solar street lamp for urban roads according to claim 1, characterized in that, The process of obtaining the global power distribution strategy includes: Combining the first dimming requirements of all sub-regions , the second dimming requirement and the third dimming requirement , to generate a combined dimming requirement for the sub-region ; ； Among them, , and are the dynamic weights of the first dimming requirement, the second dimming requirement, and the third dimming requirement respectively, is the weight of the nth sudden impact factor , and is the quantity of the sudden impact factors; Generate the global power distribution strategy according to the comprehensive dimming demands of all sub-areas.

6. The control and power distribution system of a solar street lamp for urban roads according to claim 1, characterized in that, The process of obtaining the independent power distribution strategy includes: Capture vehicles and pedestrians within the radiation range of the solar street lamp, and obtain the traveling speed and direction of the vehicles and pedestrians; Set the safe step length of street lamp brightness adjustment according to the maximum power of the street lamp and the hardware tolerance of the lamp, and calculate the time required for the solar street lamp to be adjusted from the current brightness to the target brightness; Combine the required time and the traveling speed to calculate the positions of the street lamps that need to be adjusted; Determine the solar street lamps that need to be pre-adjusted according to the street lamp positions, and generate the independent power distribution strategy.

7. The control and power distribution system of an urban road solar street lamp according to claim 1, characterized in that, The process of obtaining the current health state of the battery pack and the predicted health state curve includes: Obtain the battery pack parameter data of the solar street lamp battery, including voltage, current, and temperature, analyze the health state of the battery pack according to the voltage change rate, current volatility, and temperature change, and generate the health score of the battery pack; Collect the historical parameter data, working data, and historical health scores of the battery pack over a period of time in the past, input them into the GRU network to obtain the battery pack health relationship function; according to the real-time battery pack parameter data, obtain the predicted health state curve of the battery pack through the battery pack health relationship function.

8. The control and power distribution system of a solar street lamp for urban roads according to claim 1, characterized in that, The process of obtaining the battery pack load dispersion strategy includes: For the group of batteries in the battery pack, weight the current health score against the predicted health state curve within a certain time step to obtain the loadable score ; ； Among them, and are the weights of the current health score and the predicted health state curve within a certain time step; Sort the battery packs in descending order according to the loadable score; Allocate the load demands according to the sorting; the specific allocation calculation formula is: ； Among them, is the allocated load of the th group of batteries, is the load demand of the solar street lamp, is the th group of batteries, is the number of battery groups of the solar street lamp.

9. The control and power distribution system of a solar street lamp for urban roads according to claim 1, characterized in that, It also includes a lighting power distribution priority mechanism for solar street lamps; Obtain the lighting demand and demand urgency according to the real-time traffic density and real-time environmental conditions, and calculate the lighting priority score; obtain the power saving demand according to the real-time load demand and power supply situation, and calculate the power saving priority score; Calculate the battery protection priority score according to the real-time battery health score and the real-time battery health state prediction curve; Obtain the comprehensive priority score according to the lighting priority score, the power saving priority score, and the battery protection priority score.

10. The control and power distribution system of a solar street lamp for urban roads according to claim 9, characterized in that, The calculation process of the comprehensive priority score is: Comprehensive lighting priority score and the power saving priority score and the battery protection priority score , calculate the comprehensive priority score ; ； Wherein, , and are the dynamic weight coefficients of the lighting priority score, the power saving priority score, and the battery protection priority score respectively; Based on the comprehensive priority score Formulate a real-time power distribution strategy.

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