Intelligent energy management method and system

Abstract

The invention discloses an intelligent energy management method and system, and relates to the technical field of energy management. The method comprises the steps of obtaining second weather data based on first weather data and historical weather data; obtaining a second average electric quantity based on the first average electric quantity, the first weather data and the second weather data; when the second electric quantity is larger than a preset electric quantity threshold value, the power of the solar power supply street lamps in the preset area is adjusted based on the area condition information, the first average electric quantity and the second average electric quantity; and when the second electric quantity is not greater than a preset electric quantity threshold value, adjusting the power of the solar power supply street lamp in the preset area based on the area condition information, the first weather data, the second weather data, the first average electric quantity and the second electric quantity. According to the technical scheme, the power of the solar power supply street lamp can be accurately adjusted, and therefore the energy management efficiency of the solar power supply street lamp is improved.

Description

Technical Field

[0001] The present application relates to the field of energy management technology, and specifically to an intelligent energy management method and system. Background Art

[0002] Solar-powered street lights use solar energy as the main energy source, providing energy for nighttime lighting by converting sunlight into electrical energy. The amount of electricity supplied by such street lights directly depends on the conversion efficiency of solar energy, which is significantly affected by sunlight conditions. Therefore, the energy reserves of solar-powered street lights will fluctuate under different weather conditions. Specifically, insufficient sunlight will cause the energy reserves to decrease. If the street lights continue to operate at standard power at this time, there may be a risk of energy shortage during future nighttime lighting periods, which directly affects the energy management efficiency of solar-powered street lights.

[0003] Therefore, how to accurately adjust the power of solar-powered street lights to improve the energy management efficiency of solar-powered street lights has become an urgent problem to be solved. Summary of the invention

[0004] The present application provides an intelligent energy management method and system, which can accurately adjust the power of solar-powered street lights, thereby improving the energy management efficiency of solar-powered street lights.

[0005] In a first aspect, the present application provides an intelligent energy management method, the method comprising: obtaining regional situation information corresponding to a preset area; obtaining first weather data for a current time period and historical weather data for a preset historical time period; predicting weather data for a future time period based on the first weather data and the historical weather data to obtain second weather data; obtaining a first average power of solar-powered street lamps in the preset area during the current time period; obtaining a second average power of solar-powered street lamps in the preset area during the future time period based on the first average power, the first weather data, and the second weather data; when the second power is greater than a preset power threshold, then during the current time period and the future time period, based on the regional situation information, the first average power, and the second average power, adjusting the power of the solar-powered street lamps in the preset area; when the second power is not greater than the preset power threshold, then during the current time period and the future time period, based on the regional situation information, the first weather data, the second weather data, the first average power, and the second power, adjusting the power of the solar-powered street lamps in the preset area.

[0006] By adopting the above technical solution, by obtaining the regional situation information corresponding to the preset area, the specific needs and conditions of the area can be better understood and adapted. By obtaining the first weather data of the current time period and the historical weather data of the preset historical time period, the foundation for the accurate prediction of future weather conditions is laid. By predicting the weather data of the future time period based on the first weather data and the historical weather data, the second weather data is obtained, so as to adjust the energy allocation strategy in advance to adapt to the expected weather changes. By obtaining the first average power of the solar-powered street lights in the preset area during the current time period, the energy consumption and power level can be monitored in real time. By obtaining the second average power of the solar-powered street lights in the preset area during the future time period based on the first average power, the first weather data and the second weather data, accurate energy demand prediction and planning can be performed. When the second power is greater than the preset power threshold, the power of the solar-powered street lights in the preset area is adjusted based on the regional situation information, the first average power and the second average power, so as to maintain the stability of energy supply and prevent excessive consumption. When the second power level is not greater than a preset power threshold, the power of the solar-powered street lights in the preset area is adjusted based on the regional situation information, the first weather data, the second weather data, the first average power level and the second power level, thereby optimizing power usage when power is insufficient to ensure that lighting needs are met, thereby achieving precise adjustment of the power of the solar-powered street lights to improve the energy management efficiency of the solar-powered street lights.

[0007] Optionally, the first weather data includes a first sunshine duration, a first temperature and a first cloud cover; the second weather data includes a second sunshine duration, a second temperature and a second cloud cover; the second average power of the solar-powered street lamps in the preset area during the future time period is obtained based on the first average power, the first weather data and the second weather data, specifically including: obtaining the maximum sunshine duration and the ideal temperature; calculating the power influence coefficient based on the first sunshine duration, the first temperature, the first cloud cover, the second sunshine duration, the second temperature, the second cloud cover, the maximum sunshine duration and the ideal temperature; obtaining the corresponding power attenuation correction factor based on a preset power attenuation correction curve and the power influence coefficient; obtaining the second average power based on the power attenuation correction factor and the first average power.

[0008] By adopting the above technical solution and obtaining comprehensive weather data, it is possible to accurately evaluate the impact of current and future weather on solar power generation, so as to more effectively plan strategies for lighting power adjustment. The maximum sunshine duration and ideal temperature are obtained to determine the performance of solar panels under optimal and non-optimal conditions. The power impact coefficient is calculated to quantify the actual impact of weather conditions on solar power generation, making power adjustment more accurate. Based on the preset power attenuation correction curve and the calculated power impact coefficient, the power attenuation correction factor is obtained, and combined with the power attenuation correction factor and the current first average power, the second average power in the future time period is predicted, so that the calculation of the second average power is more accurate, and key data is provided for the power adjustment of solar-powered street lights.

[0009] Optionally, the calculating of the power impact coefficient based on the first sunshine duration, the first temperature, the first cloud cover, the second sunshine duration, the second temperature, the second cloud cover, the maximum sunshine duration and the ideal temperature specifically includes: calculating the power impact coefficient by the following formula: Wherein, E is the power impact coefficient, S1 is the first sunshine duration, S2 is the second sunshine duration, T1 is the first temperature, T2 is the second temperature, C1 is the first cloud cover, C2 is the second cloud cover, S m is the maximum sunshine duration, T b is the ideal temperature, w1 is the first power generation influence weight, w2 is the second power generation influence weight, and w3 is the third power generation influence weight.

[0010] Optionally, the regional situation information includes street lamp distribution, geographical location, traffic flow and population density; in the current time period and the future time period, based on the regional situation information, the first average power and the second average power, the power of the solar-powered street lamps in the preset area is adjusted, specifically including: determining the geographical location influence coefficient based on the geographical location; calculating the regional lighting demand coefficient corresponding to the preset area based on the traffic flow, the population density and the geographical location influence coefficient; determining the first standard power corresponding to the preset area based on the regional lighting demand coefficient and the street lamp distribution; in the current time period, based on the first standard power and the first average power, the power of the solar-powered street lamps in the preset area is adjusted; in the future time period, based on the first standard power and the second average power, the power of the solar-powered street lamps in the preset area is adjusted.

[0011] By adopting the above technical solution, through regional information such as street lamp distribution, geographical location, traffic flow and population density, we can deeply understand the specific needs and conditions of each area, so that the lighting strategy is more in line with the actual situation. Determine the influence coefficient according to the geographical location of each area to reflect the importance of its lighting needs. Calculate the lighting demand coefficient of each preset area through traffic flow, population density and geographical location influence coefficient to more accurately quantify the lighting needs of each area and ensure efficient and reasonable resource allocation. Based on the regional lighting demand coefficient and street lamp distribution, determine a first standard power for each area, thereby providing a benchmark for each area. In the current time period, adjust the power according to the first average power and the first standard power, and in the future time period, adjust according to the second average power and the first standard power, so that the power adjustment of solar-powered street lamps is more accurate.

[0012] Optionally, the calculating of the regional lighting demand coefficient corresponding to the preset area based on the traffic flow, the population density and the geographical location influence coefficient specifically includes: obtaining the maximum traffic flow and the maximum population density corresponding to the preset area; calculating the regional lighting demand coefficient corresponding to the preset area based on the maximum traffic flow, the maximum population density, the traffic flow, the population density and the geographical location influence coefficient.

[0013] Optionally, the calculating the regional lighting demand coefficient corresponding to the preset area based on the maximum traffic flow, the maximum population density, the traffic flow, the population density and the geographical location influence coefficient specifically includes: calculating the regional lighting demand coefficient by the following formula: Wherein, C is the regional lighting demand coefficient, k is the geographical location influence coefficient, F is the traffic flow, R is the population density, and F max is the maximum traffic flow, R max is the maximum population density.

[0014] Optionally, the regional situation information also includes important regional identification points and regional priority coefficients; the power of the solar-powered street lights in the preset area is adjusted based on the regional situation information, the first weather data, the second weather data, the first average power, and the second power in the current time period and the future time period, specifically including: dividing the preset area based on the important regional identification points to obtain key preset areas and general preset areas; determining the key area priority coefficient corresponding to the key preset area and the general area priority coefficient corresponding to the general preset area based on the regional priority coefficient; determining the second standard power corresponding to the key preset area based on the key area priority coefficient; determining the third standard power corresponding to the general preset area based on the general area priority coefficient. rate; determining a first weather influence coefficient based on the first weather data, and determining a second weather influence coefficient based on the second weather data; in the current time period, adjusting the power of the solar-powered street lamps in the key preset area based on the second standard power and the first weather influence coefficient, and adjusting the power of the solar-powered street lamps in the general preset area based on the third standard power, the first average power and the first weather influence coefficient; in the future time period, adjusting the power of the solar-powered street lamps in the key preset area based on the second standard power and the second weather influence coefficient, and adjusting the power of the solar-powered street lamps in the general preset area based on the third standard power, the second average power and the second weather influence coefficient.

[0015] By adopting the above technical solution, the preset area is divided based on the important area identification points to obtain the key preset area and the general preset area, so as to realize the precise management of the area and the optimal allocation of resources. By determining the key area priority coefficient corresponding to the key preset area and the general area priority coefficient corresponding to the general preset area based on the area priority coefficient, it is ensured that each area can reasonably allocate resources according to its importance. By determining the second standard power corresponding to the key preset area based on the key area priority coefficient; and determining the third standard power corresponding to the general preset area based on the general area priority coefficient, the lighting intensity of each area is adjusted to adapt to its importance and actual needs. By determining the first weather impact coefficient based on the first weather data, and determining the second weather impact coefficient based on the second weather data, the energy management system can respond to the impact of weather changes in real time. In the current time period, the power of the solar-powered street lights in the key preset area is adjusted based on the second standard power and the first weather impact coefficient, and the power of the solar-powered street lights in the general preset area is adjusted based on the third standard power, the first average power and the first weather impact coefficient, so as to optimize the instant energy management. In the future time period, the power of solar-powered street lights in the key preset area will be adjusted based on the second standard power and the second weather impact coefficient, and the power of solar-powered street lights in the general preset area will be adjusted based on the third standard power, the second average power and the second weather impact coefficient, so as to ensure the balance of future energy supply and demand and further optimize future energy management.

[0016] In a second aspect of the present application, an intelligent energy management system is provided, the system comprising an acquisition module, a processing module and a power regulation module; the acquisition module is used to acquire regional situation information corresponding to a preset area; the acquisition module is also used to acquire first weather data for a current time period and historical weather data for a preset historical time period; the processing module is used to predict weather data for a future time period based on the first weather data and the historical weather data to obtain second weather data; the acquisition module is also used to acquire a first average power consumption of solar-powered street lamps in the preset area during the current time period; the processing module is also used to obtain, based on the first average power consumption, the first weather data and the second weather data, the second average power of the solar-powered street lights in the preset area during the future time period; the power regulating module is used to regulate the power of the solar-powered street lights in the preset area based on the regional situation information, the first average power and the second average power during the current time period and the future time period when the second power is greater than the preset power threshold; the power regulating module is also used to regulate the power of the solar-powered street lights in the preset area based on the regional situation information, the first weather data, the second weather data, the first average power and the second power during the current time period and the future time period when the second power is not greater than the preset power threshold.

[0017] In the third aspect of the present application, an electronic device is provided, including a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes any method as described in the first aspect of the present application.

[0018] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program that can be loaded by a processor and execute the method as described in any one of the first aspects of the present application.

[0019] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: By obtaining the regional situation information corresponding to the preset area, the specific needs and conditions of the area can be better understood and adapted. By obtaining the first weather data of the current time period and the historical weather data of the preset historical time period, the foundation for accurate prediction of future weather conditions is laid. By predicting the weather data of the future time period based on the first weather data and the historical weather data, the second weather data is obtained, so as to adjust the energy allocation strategy in advance to adapt to the expected weather changes. By obtaining the first average power of the solar-powered street lights in the preset area during the current time period, the energy consumption and power level can be monitored in real time. By obtaining the second average power of the solar-powered street lights in the preset area during the future time period based on the first average power, the first weather data and the second weather data, accurate energy demand prediction and planning can be performed. When the second power is greater than the preset power threshold, the power of the solar-powered street lights in the preset area is adjusted based on the regional situation information, the first average power and the second average power, so as to maintain the stability of energy supply and prevent excessive consumption. When the second power level is not greater than a preset power threshold, the power of the solar-powered street lights in the preset area is adjusted based on the regional situation information, the first weather data, the second weather data, the first average power level and the second power level, thereby optimizing power usage when power is insufficient to ensure that lighting needs are met, thereby achieving precise adjustment of the power of the solar-powered street lights to improve the energy management efficiency of the solar-powered street lights. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is one of the flow charts of an intelligent energy management method provided in an embodiment of the present application; Figure 2 This is the second flow chart of an intelligent energy management method provided in an embodiment of the present application; Figure 3 This is a third flow chart of an intelligent energy management method provided in an embodiment of the present application; Figure 4 This is a fourth flow chart of an intelligent energy management method provided in an embodiment of the present application; Figure 5 It is a structural diagram of an intelligent energy management system provided by an embodiment of the present application; Figure 6 It is a structural schematic diagram of an electronic device disclosed in an embodiment of the present application.

[0021] Explanation of the reference numerals: 1. Acquisition module; 2. Processing module; 3. Power regulation module; 600. Electronic device; 601. Processor; 602. Communication bus; 603. User interface; 604. Network interface; 605. Memory. DETAILED DESCRIPTION

[0022] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0023] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0024] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" can explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0025] This application provides an intelligent energy management method, referring to Figure 1 , which shows one of the flow diagrams of a smart energy management method provided in an embodiment of the present application. The method includes steps S1-S7, which are as follows: Step S1: Obtaining regional situation information corresponding to a preset area.

[0026] Specifically, in this technical solution, the server obtains regional situation information corresponding to the preset area. The server is the urban street light management terminal. The server obtains street light distribution data from the municipal management department or the power company, including but not limited to the specific location, quantity, type, power, etc. of the street lights. GIS (Geographic Information System) tools are used to map and visualize the street light distribution to facilitate understanding of the lighting coverage of each area, and to classify the areas according to their geographical locations, such as residential areas, commercial areas, industrial areas, etc., and thereby determine the regional situation information corresponding to multiple preset areas.

[0027] Step S2: Acquire the first weather data of the current time period and the historical weather data of the preset historical time period.

[0028] Specifically, in this technical solution, the server will use the data provided by the meteorological bureau, the online weather service or the real-time data provided by the weather monitoring station installed in the area to obtain the first weather data of the current time period; and obtain the historical weather data within the preset historical time period through the archives of the meteorological bureau, the historical weather database or the meteorological monitoring equipment installed in the area for a long time. Among them, the preset historical time period is preferably 7 days, and the preset historical time period can also be specifically set according to the actual situation.

[0029] Step S3: forecasting the weather data for a future time period based on the first weather data and the historical weather data to obtain the second weather data.

[0030] Specifically, in this technical solution, the server will predict the weather data of the future time period based on the first weather data and the historical weather data to obtain the second weather data. That is, the server inputs the first weather data and the historical weather data into the weather prediction model and outputs the second weather data of the future time period. The future time period is preferably the next day.

[0031] Step S4: Obtain a first average power consumption of solar-powered street lights in a preset area during the current time period.

[0032] Specifically, in this technical solution, the server will obtain the power of all solar-powered street lights in the preset area during the current time period, and add up the power of all solar-powered street lights to obtain the average value to obtain the first average power. The current time period refers to the time period from when the solar-powered street lights are turned on to when they are turned off on that day, and the time when the first average power of the solar-powered street lights in the preset area is obtained is the time when the solar-powered street lights are turned on on that day.

[0033] Step S5: Based on the first average power consumption, the first weather data and the second weather data, obtain a second average power consumption of the solar-powered street lights in a preset area in a future time period.

[0034] Specifically, in the present technical solution, the server obtains the second average power consumption of the solar-powered street lights in a preset area in a future time period based on the first average power consumption, the first weather data and the second weather data.

[0035] The first weather data includes the first sunshine duration, the first temperature and the first cloud cover; the second weather data includes the second sunshine duration, the second temperature and the second cloud cover. In step S2 and step S3, the weather parameters that have the greatest impact on solar power generation in the first weather data and the second weather data are obtained, including the sunshine duration, temperature and cloud cover. Therefore, in order to improve the accuracy of predicting the second average power of solar-powered street lights in a preset area in the future time period, it is necessary to predict based on the first average power, the first sunshine duration, the first temperature, the first cloud cover, the second sunshine duration, the second temperature and the second cloud cover.

[0036] The following embodiment will explain in detail a method for the server to obtain the second average power consumption of solar-powered street lights in a preset area in a future time period based on the first average power consumption, the first weather data and the second weather data.

[0037] In one possible implementation, refer to Figure 2 , which shows the second flow chart of a smart energy management method provided in an embodiment of the present application. Step S5 specifically includes steps S51-S54: Step S51: Obtain the maximum sunshine duration and ideal temperature.

[0038] Specifically, in this technical solution, the server obtains the maximum sunshine duration and the ideal temperature. The server can determine the maximum sunshine duration in a day for the geographical location corresponding to the preset area from the meteorological data; and determine the temperature point with the highest power generation efficiency of the solar panel, that is, the ideal temperature, through the data provided by the solar panel manufacturer.

[0039] Step S52: Calculate the power impact coefficient based on the first sunshine duration, the first temperature, the first cloud cover, the second sunshine duration, the second temperature, the second cloud cover, the maximum sunshine duration and the ideal temperature.

[0040] Specifically, in this technical solution, the server calculates the power impact coefficient based on the first sunshine duration, the first temperature, the first cloud cover, the second sunshine duration, the second temperature, the second cloud cover, the maximum sunshine duration and the ideal temperature.

[0041] In a possible implementation, step S52 specifically includes the following steps: The power impact coefficient is calculated by the following formula: Among them, E is the power impact coefficient, S1 is the first sunshine duration, S2 is the second sunshine duration, T1 is the first temperature, T2 is the second temperature, C1 is the first cloud cover, C2 is the second cloud cover, S m is the maximum sunshine duration, T bis the ideal temperature, w1 is the first power generation influence weight, w2 is the second power generation influence weight, and w3 is the third power generation influence weight.

[0042] Specifically, in this technical solution, the first power generation impact weight is the weight ratio of the sunshine duration on the solar power generation, the second power generation impact weight is the weight ratio of the temperature on the solar power generation, and the third power generation impact weight is the weight ratio of the cloud cover on the solar power generation. The first power generation impact weight, the second power generation impact weight, and the third power generation impact weight need to be specifically set according to actual conditions.

[0043] Step S53: Based on the preset power decay correction curve and power influence coefficient, a corresponding power decay correction factor is obtained.

[0044] Specifically, in the present technical solution, the server obtains the corresponding power attenuation correction factor based on the preset power attenuation correction curve and the power influence coefficient. There is a one-to-one correspondence between multiple power influence coefficients and multiple power attenuation correction factors in the preset power attenuation correction curve. The power attenuation correction curve describes the trend of the solar panel efficiency decaying with the factors affecting solar power generation, and how different power influence coefficients interact with this decay. It should be noted that under different power influence coefficients, the attenuation curve will be adjusted accordingly. For example, under persistently poor weather conditions, the actual efficiency of the solar panel may be lower than the expected attenuation curve shows.

[0045] Step S54: obtaining a second average power based on the power attenuation correction factor and the first average power.

[0046] Specifically, in this technical solution, the server obtains the second average power based on the power attenuation correction factor and the first average power, that is, the second average power = power attenuation correction factor × the first average power.

[0047] Step S6: When the second power level is greater than the preset power threshold, the power of the solar-powered street lights in the preset area is adjusted based on the regional situation information, the first average power level and the second average power level in the current time period and the future time period.

[0048] Specifically, in the present technical solution, when the second power level is greater than the preset power threshold, it indicates that the predicted power generation of the solar-powered street lamps in the future time period is sufficient. Therefore, the server needs to reasonably adjust the power of the solar-powered street lamps in the preset area based on the regional situation information, the first average power level and the second average power level to meet the lighting needs of different areas.

[0049] Among them, the preset power threshold needs to be set specifically based on the actual situation; regional situation information includes street light distribution, geographical location, traffic flow and population density.

[0050] The following embodiment will describe in detail a method for adjusting the power of solar-powered street lights in a preset area based on regional situation information, a first average power consumption, and a second average power consumption during a current time period and a future time period.

[0051] In one possible implementation, refer to Figure 3 , which shows the third flow chart of a smart energy management method provided in an embodiment of the present application. Step S6 specifically includes steps S61-S65: Step S61: Determine the geographical location influence coefficient based on the geographical location.

[0052] Specifically, in this technical solution, the server determines the geographical location influence coefficient based on the geographical location of a preset area.

[0053] First, the server needs to divide the city into different areas based on geographical location, such as commercial areas, residential areas, industrial areas, parks, etc., and analyze the specific characteristics and needs of each area. For example, commercial areas may need brighter lighting at night to attract customers, while residential areas may pay more attention to reducing light pollution. Therefore, an impact coefficient needs to be assigned to the importance of the lighting needs corresponding to each type of area.

[0054] Step S62: Calculate the regional lighting demand coefficient corresponding to the preset area based on traffic flow, population density and geographical location influence coefficient.

[0055] Specifically, in this technical solution, the server calculates the regional lighting demand coefficient corresponding to the preset area based on traffic flow, population density and geographical location influence coefficient. The higher the regional lighting demand coefficient corresponding to the preset area, the higher the street light power required for the preset area, and the lower the regional lighting demand coefficient corresponding to the preset area, the lower the street light power required for the preset area.

[0056] The following embodiment will explain in detail how to calculate the regional lighting demand coefficient corresponding to a preset area based on traffic flow, population density and geographical location influence coefficient.

[0057] In a possible implementation, step S62 specifically includes the following steps: Get the maximum traffic flow and maximum population density corresponding to the preset area.

[0058] Specifically, in this technical solution, the server will obtain data on the highest traffic flow and maximum population density in each area from the urban planning department or the transportation management bureau.

[0059] Based on the maximum traffic flow, maximum population density, traffic flow, population density and geographical location influence coefficient, the regional lighting demand coefficient corresponding to the preset area is calculated.

[0060] Specifically, in the present technical solution, the server analyzes the relative differences between traffic flow and maximum traffic flow, population density and maximum population density, and their possible impacts on lighting demand based on maximum traffic flow, maximum population density, traffic flow and population density.

[0061] In a possible implementation, the regional lighting demand coefficient is calculated by the following formula: Among them, C is the regional lighting demand coefficient, k is the geographical location influence coefficient, F is the traffic flow, R is the population density, and F max is the maximum traffic flow, R max is the maximum population density.

[0062] Step S63: Based on the regional lighting demand coefficient and the street lamp distribution, determine the first standard power corresponding to the preset area.

[0063] Specifically, in this technical solution, the server determines the first standard power corresponding to the preset area based on the regional lighting demand coefficient and street light distribution. The street light distribution includes the number, type and distribution density of street lights. The professional management personnel of this solution will determine an ideal power based on the number, type and distribution density of different street lights, and then fine-tune the ideal power based on the regional lighting demand coefficient to obtain the first standard power.

[0064] Step S64: During the current time period, the power of the solar-powered street lights in the preset area is adjusted based on the first standard power and the first average power.

[0065] Specifically, in the technical solution, in the current time period, the server adjusts the power of the solar-powered street lamps in the preset area based on the first standard power and the first average power. That is, the server will determine whether the first average power can meet the continuous output of the first standard power in the current time period. If it does, the power of the solar-powered street lamp will be adjusted to the first standard power; if it does not meet the requirements, the power of the solar-powered street lamp will be adjusted to be lower than the first standard power to ensure that the first average power can be continuously output in the current time period.

[0066] Step S65: In a future time period, based on the first standard power and the second average power, the power of the solar-powered street lights in the preset area is adjusted.

[0067] Specifically, in this technical solution, in the future time period, the server adjusts the power of the solar-powered street lamps in the preset area based on the first standard power and the second average power. That is, the server will determine whether the second average power can meet the continuous output of the first standard power in the future time period. If it does, the power of the solar-powered street lamp will be adjusted to the first standard power; if it does not meet the requirements, the power of the solar-powered street lamp will be adjusted to be lower than the first standard power to ensure that the second average power can be continuously output in the future time period.

[0068] Step S7: When the second power level is not greater than the preset power threshold, the power of the solar-powered street lights in the preset area is adjusted based on the regional condition information, the first weather data, the second weather data, the first average power level and the second power level in the current time period and the future time period.

[0069] Specifically, in the present technical solution, when the second power level is not greater than the preset power threshold, it indicates that the predicted power generation of the solar-powered street lamps in the future time period is insufficient. Therefore, the server needs to reasonably adjust the power of the solar-powered street lamps in the preset area based on the regional situation information, the first weather data, the second weather data, the first average power level and the second power level to meet the lighting needs of different areas when the power generation of the solar-powered street lamps is insufficient.

[0070] Among them, the regional situation information also includes important regional identification points and regional priority coefficients.

[0071] The following embodiment will explain in detail the method for adjusting the power of solar-powered street lights in a preset area based on regional condition information, first weather data, second weather data, first average power and second power in the current time period and future time period.

[0072] In one possible implementation, refer to Figure 4 , which shows a fourth flow chart of an intelligent energy management method provided in an embodiment of the present application. Step S7 specifically includes steps S71-S77: Step S71: Divide the preset area based on the important area identification points to obtain key preset areas and general preset areas.

[0073] Specifically, in this technical solution, the server will divide the preset areas based on the important area identification points to obtain key preset areas and general preset areas. Among them, the important area identification points are identification points obtained after classification according to the importance of each area, such as safety needs, crowd density and the importance of social and economic activities. These identification points cover areas such as commercial areas, residential areas, hospitals, schools, government agencies, and important transportation hubs. The server will then divide the areas containing important area identification points by using geographic information system tools. The areas containing important area identification points are key preset areas, and the areas that do not contain important area identification points are general preset areas.

[0074] Step S72: Based on the area priority coefficients, determine the key area priority coefficients corresponding to the key preset areas and the general area priority coefficients corresponding to the general preset areas.

[0075] Specifically, in this technical solution, the server determines the key area priority coefficient corresponding to the key preset area and the general area priority coefficient corresponding to the general preset area based on the area priority coefficient. First, the server needs to evaluate the characteristics of each area, such as population density, economic activities, security needs, etc., to determine its importance in urban operations, and assign appropriate priority coefficients to different types of key preset areas and general preset areas to reflect their importance in lighting needs and power distribution.

[0076] Step S73: Determine the second standard power corresponding to the key preset area based on the key area priority coefficient.

[0077] Specifically, in this technical solution, the server determines the second standard power corresponding to the key preset area based on the key area priority coefficient. The professional management personnel of this solution will determine the second standard power according to the key area priority coefficients corresponding to different key areas. The second standard power should be able to meet the basic lighting needs of the key area even when the power is limited.

[0078] Step S74: Determine the third standard power corresponding to the general preset area based on the general area priority coefficient.

[0079] Specifically, in this technical solution, the server determines the third standard power corresponding to the general preset area based on the general area priority coefficient. The professional management personnel of this solution will determine the third standard power according to the general area priority coefficients corresponding to different general areas. The third standard power should be able to meet the minimum lighting needs of the general area even when the power is limited.

[0080] Step S75: Determine a first weather influence coefficient based on the first weather data, and determine a second weather influence coefficient based on the second weather data.

[0081] Specifically, in the present technical solution, the server determines the first weather influence coefficient based on the first weather data, and determines the second weather influence coefficient based on the second weather data.

[0082] Similarly, the first weather data includes a first sunshine duration, a first temperature, and a first cloud cover; the second weather data includes a second sunshine duration, a second temperature, and a second cloud cover.

[0083] The calculation method for the first weather impact coefficient for the current time period is: U1 = αF(S1) + βG(T1) + γH(C1). Among them, U1 is the first weather impact coefficient. α, β, γ are the impact weight factors corresponding to sunshine duration, temperature and cloud cover respectively. F(S1) is a function used to convert the first sunshine duration S1 into a standardized value to reflect the impact on power generation and lighting. G(T1) is a function used to convert the first temperature T1 into a standardized value to reflect the impact of temperature on solar power generation efficiency and lighting demand. H(C1) is a function used to convert the first cloud cover C1 into a standardized value to reflect the impact of cloud cover on light intensity. Similarly, the calculation method for the second weather impact coefficient for the future time period is: U2 = αF(S2) + βG(T2) + γH(C2).

[0084] Step S76: In the current time period, the power of the solar-powered street lights in the key preset area is adjusted based on the second standard power and the first weather impact coefficient, and the power of the solar-powered street lights in the general preset area is adjusted based on the third standard power, the first average power and the first weather impact coefficient.

[0085] Specifically, in this technical solution, the server multiplies the second standard power by the first weather impact coefficient to obtain the first adjusted power corresponding to the key preset area, and adjusts the power of the solar-powered street lights in the key preset area in the current time period with the first adjusted power. The server multiplies the third standard power by the first weather impact coefficient to obtain the second adjusted power corresponding to the general preset area, and determines whether the first average power can meet the continuous output of the first adjusted power and the second adjusted power in the current time period. If it does, the power of the solar-powered street lights in the general preset area is adjusted to the second adjusted power in the previous time period; if it does not meet the requirements, the power of the solar-powered street lights in the general preset area is adjusted to be lower than the second adjusted power in the previous time period to ensure that the first average power can meet the continuous output in the current time period.

[0086] Step S77: In the future time period, the power of the solar-powered street lights in the key preset area is adjusted based on the second standard power and the second weather impact coefficient, and the power of the solar-powered street lights in the general preset area is adjusted based on the third standard power, the second average power and the second weather impact coefficient.

[0087] Specifically, in this technical solution, the server multiplies the second standard power by the second weather impact coefficient to obtain the third adjusted power corresponding to the key preset area, and adjusts the power of the solar-powered street lights in the key preset area in the future time period with the third adjusted power. The server multiplies the third standard power by the second weather impact coefficient to obtain the fourth adjusted power corresponding to the general preset area, and determines whether the second average power can meet the continuous output of the third adjusted power and the fourth adjusted power in the future time period. If it does, the power of the solar-powered street lights in the general preset area is adjusted to the fourth adjusted power in the future time period; if it does not meet, the power of the solar-powered street lights in the general preset area is adjusted to be lower than the fourth adjusted power in the future time period to ensure that the second average power can meet the continuous output in the future time period.

[0088] Reference Figure 5 , which shows a structural schematic diagram of an intelligent energy management system provided by an embodiment of the present application, the system includes an acquisition module 1, a processing module 2 and a power regulation module 3; the acquisition module 1 is used to obtain regional situation information corresponding to a preset area; the acquisition module 1 is also used to obtain the first weather data of the current time period and the historical weather data of the preset historical time period; the processing module 2 is used to predict the weather data of the future time period based on the first weather data and the historical weather data to obtain the second weather data; the acquisition module 1 is also used to obtain the first average power of the solar-powered street lamps in the preset area during the current time period; the processing module 2 is also used to obtain the first average power, the first weather data, ... The power regulating module 3 is used to regulate the power of the solar-powered street lamps in the preset area based on the regional situation information, the first weather data, the second weather data, the first average power and the second average power when the second power is greater than the preset power threshold value in the current time period and the future time period; the power regulating module 3 is also used to regulate the power of the solar-powered street lamps in the preset area based on the regional situation information, the first weather data, the second weather data, the first average power and the second power in the current time period and the future time period when the second power is not greater than the preset power threshold value.

[0089] In a possible implementation, the acquisition module 1 is also used to obtain the maximum sunshine duration and the ideal temperature; the processing module 2 is also used to calculate the power impact coefficient based on the first sunshine duration, the first temperature, the first cloud cover, the second sunshine duration, the second temperature, the second cloud cover, the maximum sunshine duration and the ideal temperature; the processing module 2 is also used to obtain the corresponding power attenuation correction factor based on the preset power attenuation correction curve and the power influence coefficient; the processing module 2 is also used to obtain the second average power based on the power attenuation correction factor and the first average power.

[0090] In a possible implementation manner, the processing module 2 is further configured to calculate the power impact coefficient using the following formula: Among them, E is the power impact coefficient, S1 is the first sunshine duration, S2 is the second sunshine duration, T1 is the first temperature, T2 is the second temperature, C1 is the first cloud cover, C2 is the second cloud cover, S m is the maximum sunshine duration, T b is the ideal temperature, w1 is the first power generation influence weight, w2 is the second power generation influence weight, and w3 is the third power generation influence weight.

[0091] In a possible implementation, the power regulation module 3 is further used to determine the geographical location influence coefficient based on the geographical location; the power regulation module 3 is further used to calculate the regional lighting demand coefficient corresponding to the preset area based on the traffic flow, population density and the geographical location influence coefficient; the power regulation module 3 is further used to determine the first standard power corresponding to the preset area based on the regional lighting demand coefficient and the street light distribution; the power regulation module 3 is further used to adjust the power of the solar-powered street lights in the preset area based on the first standard power and the first average power in the current time period; the power regulation module 3 is further used to adjust the power of the solar-powered street lights in the preset area based on the first standard power and the second average power in the future time period.

[0092] In a possible implementation, the acquisition module 1 is also used to obtain the maximum traffic flow and maximum population density corresponding to the preset area; the power regulation module 3 is also used to calculate the regional lighting demand coefficient corresponding to the preset area based on the maximum traffic flow, maximum population density, traffic flow, population density and geographical location influence coefficient.

[0093] In a possible implementation manner, the power regulation module 3 is further configured to calculate the regional lighting demand coefficient using the following formula: Among them, C is the regional lighting demand coefficient, k is the geographical location influence coefficient, F is the traffic flow, R is the population density, and F max is the maximum traffic flow, R max is the maximum population density.

[0094] In a possible implementation, the power regulation module 3 is also used to divide the preset area based on the important area identification points to obtain the key preset area and the general preset area; the power regulation module 3 is also used to determine the key area priority coefficient corresponding to the key preset area and the general area priority coefficient corresponding to the general preset area based on the area priority coefficient; the power regulation module 3 is also used to determine the second standard power corresponding to the key preset area based on the key area priority coefficient; the power regulation module 3 is also used to determine the third standard power corresponding to the general preset area based on the general area priority coefficient; the power regulation module 3 is also used to determine the first weather impact coefficient based on the first weather data, and based on the second weather data , determine the second weather impact coefficient; the power adjustment module 3 is also used to adjust the power of the solar-powered street lights in the key preset area based on the second standard power and the first weather impact coefficient in the current time period, and to adjust the power of the solar-powered street lights in the general preset area based on the third standard power, the first average power and the first weather impact coefficient; the power adjustment module 3 is also used to adjust the power of the solar-powered street lights in the key preset area based on the second standard power and the second weather impact coefficient in the future time period, and to adjust the power of the solar-powered street lights in the general preset area based on the third standard power, the second average power and the second weather impact coefficient.

[0095] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0096] The present application also discloses an electronic device. Figure 6 , Figure 6 The electronic device 600 may include: at least one processor 601 , at least one network interface 604 , a user interface 603 , a memory 605 , and at least one communication bus 602 .

[0097] The communication bus 602 is used to realize the connection and communication between these components.

[0098] The user interface 603 may include a display screen (Display) and a camera (Camera), and the optional user interface 603 may also include a standard wired interface and a wireless interface.

[0099] The network interface 604 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0100] Among them, the processor 601 may include one or more processing cores. The processor 601 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 605, and calling data stored in the memory 605. Optionally, the processor 601 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 601 can integrate one or more combinations of a central processing unit (Central Processing Unit, CPU), a graphics processor (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 601, and it can be implemented by a single chip.

[0101] Among them, the memory 605 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 605 includes a non-transitory computer-readable storage medium. The memory 605 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 605 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area may store data involved in the above-mentioned method embodiments, etc. The memory 605 may optionally be at least one storage device located away from the aforementioned processor 601. Refer to Figure 6 , the memory 605 as a computer-readable storage medium may include an operating system, a network communication module, a user interface module and an application program.

[0102] exist Figure 6In the electronic device 600 shown, the user interface 603 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 601 can be used to call an application stored in the memory 605, and when executed by one or more processors 601, the electronic device 600 executes one or more methods in the above-mentioned embodiments. It should be noted that for the aforementioned method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should know that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0103] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0104] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0105] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0106] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0107] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0108] The above are only exemplary embodiments of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, those skilled in the art will easily think of other embodiments of the present disclosure.

[0109] This application is intended to cover any variation, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art not described in the present disclosure. The description and examples are to be regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. An intelligent energy management method, characterized in that: The method comprises: Obtain regional situation information corresponding to a preset area; Get the first weather data of the current time period and the historical weather data of the preset historical time period; Predicting weather data for a future time period based on the first weather data and the historical weather data to obtain second weather data; Acquire a first average power consumption of solar-powered street lamps in the preset area during the current time period; Based on the first average power, the first weather data and the second weather data, obtaining a second average power of the solar-powered street lights in the preset area during the future time period; When the second power level is greater than a preset power threshold, the power of the solar-powered street lights in the preset area is adjusted based on the area situation information, the first average power level, and the second average power level during the current time period and the future time period; When the second power level is not greater than a preset power threshold, the power of the solar-powered street lights in the preset area is adjusted based on the regional condition information, the first weather data, the second weather data, the first average power level and the second power level during the current time period and the future time period.

2. The method according to claim 1, characterized in that: The first weather data includes a first sunshine duration, a first temperature, and a first cloud cover; the second weather data includes a second sunshine duration, a second temperature, and a second cloud cover; the second average power of the solar-powered street lamps in the preset area during the future time period is obtained based on the first average power, the first weather data, and the second weather data, specifically including: Get the maximum sunshine duration and ideal temperature; Calculate the power impact coefficient based on the first sunshine duration, the first temperature, the first cloud cover, the second sunshine duration, the second temperature, the second cloud cover, the maximum sunshine duration and the ideal temperature; Based on the preset power attenuation correction curve and the power influence coefficient, a corresponding power attenuation correction factor is obtained; The second average power is obtained based on the power attenuation correction factor and the first average power.

3. The method according to claim 2, characterized in that The calculating the power impact coefficient based on the first sunshine duration, the first temperature, the first cloud cover, the second sunshine duration, the second temperature, the second cloud cover, the maximum sunshine duration and the ideal temperature specifically includes: The power impact coefficient is calculated by the following formula: Wherein, E is the power impact coefficient, S1 is the first sunshine duration, S2 is the second sunshine duration, T1 is the first temperature, T2 is the second temperature, C1 is the first cloud cover, C2 is the second cloud cover, S m is the maximum sunshine duration, T b is the ideal temperature, w1 is the first power generation influence weight, w2 is the second power generation influence weight, and w3 is the third power generation influence weight.

4. The method according to claim 1, characterized in that The regional situation information includes street lamp distribution, geographical location, traffic flow and population density; in the current time period and the future time period, based on the regional situation information, the first average power and the second average power, the power of the solar-powered street lamps in the preset area is adjusted, specifically including: Based on the geographical location, determining a geographical location influence coefficient; Calculating a regional lighting demand coefficient corresponding to the preset area based on the traffic flow, the population density and the geographical location influence coefficient; Determining a first standard power corresponding to the preset area based on the regional lighting demand coefficient and the street lamp distribution; During the current time period, based on the first standard power and the first average power, the power of the solar-powered street lights in the preset area is adjusted; In the future time period, the power of the solar-powered street lights in the preset area is adjusted based on the first standard power and the second average power.

5. The method according to claim 4, characterized in that The calculating the regional lighting demand coefficient corresponding to the preset area based on the traffic flow, the population density and the geographical location influence coefficient specifically includes: Obtaining the maximum traffic flow and maximum population density corresponding to the preset area; Based on the maximum traffic flow, the maximum population density, the traffic flow, the population density and the geographical location influence coefficient, the regional lighting demand coefficient corresponding to the preset area is calculated.

6. The method according to claim 5, characterized in that The calculating the regional lighting demand coefficient corresponding to the preset area based on the maximum traffic flow, the maximum population density, the traffic flow, the population density and the geographical location influence coefficient specifically includes: The lighting demand coefficient of the area is calculated by the following formula: Wherein, C is the regional lighting demand coefficient, k is the geographical location influence coefficient, F is the traffic flow, R is the population density, and F max is the maximum traffic flow, R max is the maximum population density.

7. The method according to claim 1, characterized in that The regional situation information also includes important regional identification points and regional priority coefficients; the power of the solar-powered street lights in the preset area is adjusted based on the regional situation information, the first weather data, the second weather data, the first average power, and the second power in the current time period and the future time period, specifically including: Dividing the preset area based on the important area identification points to obtain key preset areas and general preset areas; Based on the area priority coefficient, determining a key area priority coefficient corresponding to the key preset area and a general area priority coefficient corresponding to the general preset area; Based on the key area priority coefficient, determining a second standard power corresponding to the key preset area; Determining a third standard power corresponding to the general preset area based on the general area priority coefficient; Determine a first weather influence coefficient based on the first weather data, and determine a second weather influence coefficient based on the second weather data; In the current time period, based on the second standard power and the first weather impact coefficient, the power of the solar-powered street lamps in the key preset area is adjusted, and based on the third standard power, the first average power and the first weather impact coefficient, the power of the solar-powered street lamps in the general preset area is adjusted; During the future time period, the power of the solar-powered street lights in the key preset area is adjusted based on the second standard power and the second weather impact coefficient, and the power of the solar-powered street lights in the general preset area is adjusted based on the third standard power, the second average power and the second weather impact coefficient.

8. An intelligent energy management system, characterized in that: The system includes an acquisition module, a processing module and a power regulation module; The acquisition module is used to acquire the regional situation information corresponding to the preset area; The acquisition module is further used to acquire the first weather data of the current time period and the historical weather data of the preset historical time period; the processing module is used to predict the weather data of the future time period based on the first weather data and the historical weather data to obtain the second weather data; The acquisition module is further used to acquire a first average power of the solar-powered street lights in the preset area during the current time period; The processing module is further used to obtain a second average power of the solar-powered street lamps in the preset area during the future time period based on the first average power, the first weather data and the second weather data; The power regulating module is configured to regulate the power of the solar-powered street lamps in the preset area based on the regional situation information, the first average power and the second average power in the current time period and the future time period when the second power is greater than a preset power threshold; The power regulation module is also used to regulate the power of the solar-powered street lights in the preset area based on the regional condition information, the first weather data, the second weather data, the first average power and the second power during the current time period and the future time period when the second power is not greater than a preset power threshold.

9. An electronic device, characterized in that: The electronic device (600) comprises a processor (601), a memory (605), a user interface (603) and a network interface (604), wherein the memory (605) is used to store instructions, the user interface (603) and the network interface (604) are used to communicate with other devices, and the processor (601) is used to execute the instructions stored in the memory (605) so that the electronic device (600) executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is executed.

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