Automatic snow removal method for photovoltaic panel, electronic equipment and program product

Abstract

The invention discloses an automatic snow removal method for a photovoltaic panel, electronic equipment and a program product, and the method comprises the steps: evaluating the total value of energy required to be consumed for melting accumulated snow in each snow removal time in a plurality of different snow removal time durations through an energy consumption evaluation model, and directly comparing the total values of energy required to be consumed for snow removal in different time durations; a snow removal scheme with the lowest energy consumption can be rapidly determined, energy waste in the snow removal process is reduced, in addition, the total energy consumption value comprises electric energy consumed by heat generated by the photovoltaic panel and an electric energy value lost in the electric energy conversion stopping process, direct electric energy loss and indirect electric energy loss of the photovoltaic panel in the snow removal process are both considered, and the snow removal efficiency is improved. The comprehensiveness and accuracy of the energy loss value are improved, and the evaluation accuracy of the energy consumption evaluation model is further improved.

Description

Technical Field

[0001] The present application relates to the technical field of photovoltaic panel snow removal, and specifically to an automatic photovoltaic panel snow removal method, electronic equipment and program product. Background Art

[0002] Photovoltaic panels are highly efficient energy utilization devices that can convert solar energy into electrical energy. They have been widely used due to their outstanding performance in energy conversion. Since photovoltaic panels need to utilize solar energy in the process of energy conversion and are usually installed outdoors, it is easy for snow to accumulate on photovoltaic panels after snowfall in winter. If the snow on the photovoltaic panels is not removed in time, the power generation efficiency and service life of the photovoltaic panels will be affected. The existing snow removal methods have high energy consumption and cost.

[0003] Therefore, how to remove snow from photovoltaic panels with lower energy consumption and cost is a technical problem that needs to be solved urgently by technicians in this field. Summary of the invention

[0004] In view of this, an embodiment of the present application provides a method for automatic snow removal of photovoltaic panels, which uses an energy consumption evaluation model to evaluate the total energy required to achieve snow removal in different time lengths, so as to accurately determine the snow removal plan with the lowest total energy consumption.

[0005] In a first aspect, an embodiment of the present application provides a method for automatic snow removal of photovoltaic panels, the method comprising: obtaining the thickness and density of the current snow on the photovoltaic panels; determining the thickness of the snow that actually needs to be melted based on the thickness of the current snow and the equilibrium thickness, wherein the equilibrium thickness is the thickness of the snow that at least needs to be melted to make the current snow slide off the photovoltaic panel; determining the mass of the snow that actually needs to be melted based on the thickness and density of the snow that actually needs to be melted; and evaluating the total energy consumed by melting the mass of snow in each snow removal time in multiple different snow removal time lengths through an energy consumption evaluation model, wherein, The total energy consumed includes a first energy consumption value and a second energy consumption value. The first energy consumption value is the electric energy consumed for generating heat to melt snow, and the second energy consumption value is the electric energy lost by stopping electric energy conversion. The energy consumption evaluation model is used to evaluate the first energy consumption value and the second energy consumption value within different snow removal time lengths; compare the total energy consumed for melting the snow of the actual mass required to be melted within multiple different snow removal time lengths, and take the heating power corresponding to the first energy consumption value in the smallest total energy value as the optimal heating power; and remove snow from the photovoltaic panels based on the optimal heating power and the corresponding snow removal time length.

[0006] In certain embodiments of the present application, evaluating the total energy consumed to melt a mass of snow in each snow removal time among multiple different snow removal time lengths through an energy consumption evaluation model includes: evaluating a first energy consumption value consumed to melt a mass of snow in multiple different snow removal time lengths through a first evaluation function, wherein the first evaluation function includes a functional relationship between the snow removal time length and the corresponding required heating power; evaluating a second energy consumption value lost to melt a mass of snow in multiple different snow removal time lengths through a second evaluation function, wherein the second evaluation function includes a functional relationship between the snow removal time length and the corresponding convertible electrical energy value; adding the first energy consumption value and the second energy consumption value in each snow removal time length among multiple different snow removal time lengths to obtain the total energy consumption value in each snow removal time length.

[0007] In some embodiments of the present application, the first energy consumption value consumed by melting a mass of snow within a plurality of different snow removal time lengths is evaluated by the first evaluation function, including: according to the total heat Q required to melt the mass of snow m all , the amount of heat provided by light Q s And the length of snow removal time t, the heating power P required for snow removal is determined based on the following formula:

[0008]

[0009] Among them, Q all =m[C p (0-T e )+h],C p is the specific heat capacity, T e is the current ambient temperature, h is the melting latent heat of the current snow, which can be set to 334 kj / kg based on experience, and the heat provided by sunlight is Q s It can be obtained by t×(1-Al)×G, where Al is the albedo and G is the solar radiation.

[0010] In certain embodiments of the present application, determining the actual thickness of snow that needs to be melted based on the current snow thickness and the equilibrium thickness includes: comparing the current snow thickness with the equilibrium thickness; when the current snow thickness is greater than the equilibrium thickness, the actual thickness of snow that needs to be melted is the equilibrium thickness; when the current snow thickness is not greater than the equilibrium thickness, the actual thickness of snow that needs to be melted is the current snow thickness.

[0011] In certain embodiments of the present application, before evaluating the total energy consumed to melt a mass of snow in each snow removal time among multiple different snow removal time lengths through an energy consumption assessment model, it also includes: determining a suitable snow removal time length interval based on the thickness of the snow that actually needs to be melted; selecting a suitable number of key points within the suitable snow removal time length interval as the starting and end points of multiple different snow removal time lengths, and the suitable number of key points includes at least two key points.

[0012] In certain embodiments of the present application, snow removal for photovoltaic panels based on optimal heating power and corresponding snow removal time length includes: determining the voltage required for snow removal according to the optimal heating power; applying voltage in reverse to both ends of the photovoltaic panel within the snow removal time length corresponding to the optimal heating power, so that the photovoltaic panel generates corresponding heat to melt the snow that actually needs to be melted.

[0013] In certain embodiments of the present application, the method further includes: during the snow removal process, adjusting the tilt angle of the photovoltaic panel to the maximum tilt angle to which the photovoltaic panel can be adjusted; after the snow removal is completed, restoring the tilt angle of the photovoltaic panel to the tilt angle corresponding to the current season.

[0014] In certain embodiments of the present application, it also includes: when the current snow thickness is greater than a preset threshold, executing an automatic snow removal method.

[0015] In a second aspect, an embodiment of the present application provides an electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the automatic snow removal method for photovoltaic panels described in the first aspect.

[0016] In a third aspect, an embodiment of the present application provides a computer program product, including a computer program / instruction, which, when executed by a computer program / instruction processor, is used to implement the automatic snow removal method for photovoltaic panels described in the first aspect.

[0017] The embodiments of the present application provide a method, electronic device and program product for automatic snow removal from photovoltaic panels. The method uses an energy consumption assessment model to evaluate the total energy required to melt the mass of the accumulated snow within each of a plurality of different snow removal time lengths, directly compares the total energy required for snow removal at different times, and can quickly determine the snow removal plan with the lowest energy consumption, thereby reducing energy waste in the snow removal process. In addition, the total energy consumption includes the electrical energy required to generate heat by the photovoltaic panel itself and the electrical energy lost in the process of stopping the electrical energy conversion. The direct and indirect electrical energy losses of the photovoltaic panel during the snow removal process are taken into account, thereby improving the comprehensiveness and accuracy of the energy loss value, and further improving the accuracy of the energy consumption assessment model evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0019] Figure 1 It is a structural schematic diagram of the automatic snow removal system for photovoltaic panels provided in some embodiments of the present application.

[0020] Figure 2 What is shown is a flow chart of a method for automatic snow removal of low-power photovoltaic panels provided in some embodiments of the present application.

[0021] Figure 3 It is a flow chart of the energy consumption assessment model provided in some embodiments of the present application for assessing snow removal energy consumption.

[0022] Figure 4 This is a system module diagram of an automatic snow removal device provided in some embodiments of the present application.

[0023] Figure 5 It is a schematic diagram of the structure of an electronic device provided in some embodiments of the present application. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0025] Application Overview

[0026] After the photovoltaic panels are covered with snow, if the snow is not cleared in time, it will affect the power generation efficiency of the photovoltaic cells, cause energy waste, and even have an adverse effect on the life of the photovoltaic panels.

[0027] Based on the above problems, in the related art, the snow removal operation of photovoltaic panels mainly includes the following methods:

[0028] First, a heating device is installed on the photovoltaic panel to provide a certain amount of heat energy to the photovoltaic panel to melt the snow on the photovoltaic panel array. However, the additional heating device will increase the cost of the snow removal process.

[0029] Second, self-heating snow removal by photovoltaic panels, by utilizing the pn characteristics of photovoltaic panels, applying rated voltage to the photovoltaic panels to energize them, and reversely converting electrical energy into heat energy to melt the snow on the photovoltaic panels. However, if this method is used for snow removal during the day, it will affect the efficiency of electrical energy conversion because the photovoltaic panels' electrical energy conversion process needs to be stopped. If snow removal is done at night, due to the lower temperature, more thermal energy needs to be provided during the snow melting process, which consumes more electrical energy, thereby increasing the energy consumption of snow removal. Snow melting can only be done by relying on experience or using a larger heating power, and it is difficult to determine an accurate, low-power snow removal solution.

[0030] In response to the above problems, the embodiment of the present application creatively proposes an energy consumption assessment model, which is used to evaluate the total energy required to achieve snow removal in different time lengths, so as to accurately determine the snow removal plan with the lowest total energy consumption.

[0031] Various non-limiting embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0032] Exemplary photovoltaic panel automatic snow removal system

[0033] The photovoltaic panel automatic snow removal method provided in the present application can be applied to a photovoltaic panel automatic snow removal system, which can evaluate the power consumption required for melting snow within different time lengths and use the snow removal technical solution with the lowest power consumption to remove snow from the photovoltaic panel.

[0034] Figure 1 It is a structural schematic diagram of the automatic snow removal system for photovoltaic panels provided in some embodiments of the present application.

[0035] like Figure 1 As shown, the photovoltaic panel automatic snow removal system 100 in the present application may include a photovoltaic panel array 110, a sensor assembly 120, a controller 130, a memory 140, an inverter 150 and a power grid 160. The photovoltaic panel array 110 may include a plurality of photovoltaic panels, each photovoltaic panel includes a plurality of photovoltaic units 111, and the present application does not specifically limit the number of photovoltaic units 111.

[0036] In some embodiments, the sensor assembly 120 is disposed on the photovoltaic panel array 110 and can be used to obtain sensor data related to snow accumulation on the photovoltaic panel array 110 and sensor data related to the environment. For example, the sensor assembly 120 may include a pressure sensor, a snow thickness sensor, a temperature sensor, and the like.

[0037] In some embodiments, the controller 130 may be configured to be connected to the sensor 120 and the inverter 150 respectively to control the power conversion process of the photovoltaic unit 111 to achieve reasonable distribution and use of power.

[0038] In some embodiments, the inverter 150 is connected between the power grid 160 and the photovoltaic panel array 110. The controller 130 can also change the output state of the current by controlling the inverter to be in the energy storage state or the inversion state, that is, the output is AC or DC.

[0039] Specifically, when the sun rises during the day, the multiple photovoltaic cells 111 in the photovoltaic panel array 110 can absorb light energy, and the light energy excites the electrons in the photovoltaic cells (also called photovoltaic cells) to undergo transitions to generate electron-hole pairs, forming a current flowing from the P-type region to the N-type region, thereby generating direct current. At this time, the controller 130 can convert the direct current generated by the photovoltaic panel array 120 into alternating current by controlling the inverter 150 and output it to the power grid 160.

[0040] After the controller 130 receives the snow removal signal, it can control the inverter 150 to convert AC power into DC output, apply a forward voltage across the photovoltaic panel array 110, so that the photovoltaic panel array 110 generates a certain amount of heat to melt the snow on the photovoltaic panel array 110.

[0041] In some embodiments, the inverter 150 can be a combination of one or more of a grid-connected bidirectional inverter, a centralized inverter, and a string inverter, and can be flexibly set according to the number of photovoltaic units included in the photovoltaic panel array 110, and is not specifically limited here.

[0042] In some embodiments, the memory 140 may be used to store data and / or instructions. The memory 140 may include one or more storage components, each of which may be an independent device or part of another device. In some embodiments, the memory 140 may include a random access memory (RAM), a read-only memory (ROM), a mass storage device, etc., or any combination thereof. Exemplarily, the mass storage device may include a magnetic disk, an optical disk, a solid-state disk, etc.

[0043] In some embodiments, the memory 140 may be configured to store a computer program related to the photovoltaic panel automatic snow removal method shown in the present application. When the computer program is executed (such as called by the controller 130), the low-power photovoltaic panel automatic snow removal method shown in the embodiment of the present application may be implemented.

[0044] In some embodiments, the controller 130 can determine the heating power used in the snow removal process according to the sensor data about snow accumulation and the sensor data of the environment obtained from the sensor assembly 120 through the energy consumption evaluation model in the memory 140. The specific determination process can be seen in Figure 2 and its related description.

[0045] Exemplary photovoltaic panel automatic snow removal method

[0046] Corresponding to the above system, the present application provides a low-power photovoltaic panel automatic snow removal method for the above system. Figure 2 What is shown is a flow chart of a method for automatic snow removal of low-power photovoltaic panels provided in some embodiments of the present application.

[0047] In some embodiments, Figure 2 The exemplary process shown may be executed by controller 130 .

[0048] like Figure 2 As shown, the method may include the following steps:

[0049] S210: Obtain the thickness and density of the current snow accumulation on the photovoltaic panel.

[0050] Due to the different positions of the photovoltaic units in the photovoltaic panel and the influence of the environment, the thickness of the snow covering the photovoltaic panel may be different. Therefore, sensors can be set at several key positions on the photovoltaic panel to obtain the sensor data of the corresponding photovoltaic units. Exemplarily, the thickness of the snow on the photovoltaic units at the four corners of the photovoltaic panel and the center of the photovoltaic panel can be obtained respectively to improve the reliability of the detection data. In another embodiment, the thickness of the snow at the four corners of the photovoltaic array and the center of the photovoltaic panel array can also be obtained respectively to improve the reliability of the detection data and reduce the hardware cost.

[0051] In some embodiments, the thickness of the snow on the photovoltaic units at the several key positions obtained above with the largest thickness value can be used as the current snow thickness to ensure that the heat energy to be provided can be calculated with the maximum amount of snow in the subsequent snow removal process, avoiding the situation where the snow on the photovoltaic units is not completely cleared; the average value of the thickness of the snow on the photovoltaic units at the several key positions obtained above can also be calculated, and the average value can be used as the current snow thickness, which is not specifically limited here.

[0052] In some embodiments, the thickness of snow accumulated on each photovoltaic unit in the current photovoltaic panel can be obtained by a snow thickness sensor or a snow depth sensor. For example, the snow thickness sensor or the snow depth sensor can be a laser sensor or an ultrasonic sensor.

[0053] In some embodiments, the density of snow can be measured on-site by a density measuring device, or a snow layer density measurement system can be added to obtain the density of snow, which is not specifically limited here.

[0054] S220: Determine the actual thickness of snow that needs to be melted according to the current thickness of snow and the equilibrium thickness.

[0055] S230: Determine the mass of the snow that actually needs to be melted according to the thickness and density of the snow that actually needs to be melted.

[0056] The equilibrium thickness may be the thickness of the snow that is at least required to melt in order for the current snow to slide off the photovoltaic panel.

[0057] Taking into account that in the actual snow removal process, when the snow on the photovoltaic panel reaches a certain thickness, the snow water formed after melting a certain mass of snow close to the surface of the photovoltaic panel will act as a "lubricant". At the same time, the downward force brought by the tilt of the photovoltaic panel will cause the remaining snow on the photovoltaic panel to slide off. Therefore, this application determines the actual thickness of the snow that needs to be melted by comparing the current thickness of the snow on the photovoltaic panel obtained with the thickness of the snow that needs to be melted at least to cause an "avalanche" to cause the remaining snow to slide off (equilibrium thickness), so as to ensure the reliability and accuracy of the data.

[0058] Specifically, the actual thickness of the snow that needs to be melted can be determined based on the comparison result between the current snow thickness and the equilibrium thickness obtained in the aforementioned S210: when the current snow thickness is greater than the equilibrium thickness, it means that the current snow thickness meets the conditions for causing an "avalanche", that is, only snow of the equilibrium thickness needs to be melted, and the remaining snow can slide down with the help of snow water formed after the snow melts and the downward sliding force of the photovoltaic panels. The actual thickness of the snow that needs to be melted is the equilibrium thickness; when the current snow thickness is not greater than the equilibrium thickness, it means that the current snow thickness does not meet the conditions for causing an "avalanche", and all the current snow needs to be melted at this time. The actual thickness of the snow that needs to be melted is the current snow thickness.

[0059] In some embodiments, the balance thickness may be set according to an empirical value or may be adjusted according to actual conditions.

[0060] When working, the photovoltaic panel will be adjusted to the tilt angle corresponding to the current season to improve power generation efficiency. In some embodiments, during the snow removal process, the tilt angle of the photovoltaic panel can be adjusted to the maximum angle that the photovoltaic panel can be adjusted to, for example, close to 90°, without affecting the heat energy provided by the sun to the photovoltaic panel, so as to strengthen the sliding force of the snow on the photovoltaic panel, so as to minimize the thickness of the snow that needs to be melted, and further reduce the power consumption during the snow melting process. After the snow removal is completed, the tilt angle of the photovoltaic panel is restored to the tilt angle corresponding to the current season.

[0061] S240, evaluating the total energy consumed to melt the mass of snow in each snow removal time among multiple different snow removal time lengths through an energy consumption evaluation model.

[0062] The total energy value may be a total electrical energy loss value in a process of melting a corresponding mass of snow within a certain length of time.

[0063] Considering that the photovoltaic panel self-heating method is used for snow removal, that is, in the process of reversely energizing the photovoltaic panel to generate heat, the photovoltaic panel's power conversion process needs to be stopped, which in turn affects the photovoltaic panel's power conversion efficiency. Therefore, in this application, the total energy consumed in the snow removal process is divided into two parts, the first energy consumption value and the second energy consumption value, wherein the first energy consumption value is the actual power consumed for generating heat to melt snow, and the second energy consumption value is the power lost by stopping the photovoltaic panel's power conversion process. Therefore, by taking into account both the direct power loss of the photovoltaic panel's own heat energy and the indirect power loss caused by the inability to perform photovoltaic conversion, the comprehensiveness and accuracy of the energy loss value are improved.

[0064] In some embodiments, the mass of snow that actually needs to be melted can be obtained by multiplying the thickness of the snow that actually needs to be melted determined in S220 by the density of the snow.

[0065] In some embodiments, the energy consumption evaluation model can be used to evaluate the first energy consumption value and the second energy consumption value required to melt the corresponding mass of snow within different snow removal time lengths. The specific evaluation process can be referred to Figure 3 and its related description.

[0066] In some embodiments, the appropriate snow removal time interval can be determined according to the actual thickness of the snow that needs to be melted. For example, the snow removal time interval can be determined based on experience. For example, if the thickness of the snow that needs to be melted is 4 cm, it generally takes about 90 minutes to melt 4 cm of snow, and the snow removal time interval can be set to 70 minutes-110 minutes. The snow removal time interval can also be determined by experiment. For example, the time taken to melt 4 cm-8 cm of snow under the same temperature and heating power can be recorded, and the snow removal time required for each increase of 1 cm of snow thickness can be calculated. When the thickness of the snow that needs to be melted is greater than 4 cm, the approximate time length T for melting the current thickness of snow can be calculated based on the time required for each increase of 1 cm of snow obtained from the experiment. The snow removal time interval can be a floating range of 20% above and below the time length T, which is (1-20%)T-(1+20%)T. In the appropriate snow removal time interval, a suitable number of key points are selected as the starting point and end point of the multiple different snow removal time lengths, and the suitable number of key points includes at least two key points. The number and interval of the selected key points can be adjusted according to the actual snow removal situation within the corresponding time.

[0067] S250, comparing the total energy values ​​consumed by the mass of snow that actually needs to be melted corresponding to a plurality of different snow removal time lengths, and taking the heating power corresponding to the first energy consumption value in the smallest total energy value as the optimal heating power.

[0068] In some embodiments, the technical solution with the lowest energy consumption can be selected to heat the photovoltaic panels. Specifically, the total energy values ​​required to melt the corresponding mass of snow in multiple different snow removal times obtained in the aforementioned S240 are compared, and the heating power corresponding to the first energy consumption value in the smallest total energy value is used as the heating power used in the final snow removal process, so as to minimize the energy consumption in the snow removal process.

[0069] S260: Remove snow from the photovoltaic panel based on the optimal heating power and the corresponding snow removal time length.

[0070] In some embodiments, the corresponding current and voltage can be calculated first through the optimal power determined by the aforementioned S250, and then the photovoltaic panel can be used as a load, and within the snow removal time length corresponding to the optimal heating power, the corresponding voltage is applied to both ends of the photovoltaic panel to generate corresponding heat on the surface of the photovoltaic panel to achieve snow removal.

[0071] Considering that the photoelectric conversion efficiency of photovoltaic panels will be affected only when the snow reaches a certain thickness, if snow removal is performed when snow is detected, it may cause energy waste and violate the original intention of "low power consumption". Therefore, a preset threshold can be set, and snow removal will be started when the thickness of snow is greater than the preset threshold.

[0072] In some embodiments, the preset threshold value can be determined according to the functional relationship between the thickness of the snow and the photoelectric conversion efficiency of the corresponding photovoltaic panel. For example, the functional relationship between the photoelectric conversion efficiency η and the thickness of the snow h is η(h) = η0×e -k×h , where η0 is the photoelectric conversion efficiency of the photovoltaic cell when there is no snow, and k is the influence coefficient of the snow thickness on the photoelectric conversion efficiency. Assuming that the photoelectric conversion efficiency is 23% when there is no snow, the preset threshold can be 20%, that is, the current actual photoelectric conversion efficiency is more than 3% lower than the normal photovoltaic conversion efficiency. It is considered that the current amount of snow has affected the photoelectric conversion efficiency, and the snow removal operation is started to execute the automatic snow removal method for photovoltaic panels.

[0073] Therefore, based on the aforementioned automatic snow removal method of photovoltaic panels, the total energy value required to melt the mass of the snow in each snow removal time among multiple different snow removal time lengths can be evaluated through the energy consumption assessment model. The total energy value required for snow removal at different times can be directly compared, and the snow removal plan with the lowest energy consumption can be quickly determined to reduce energy waste in the snow removal process. At the same time, the total energy consumption includes the electrical energy required for the photovoltaic panel to generate heat itself and the electrical energy value lost in the process of stopping the electrical energy conversion. The direct and indirect electrical energy losses of the photovoltaic panel during the snow removal process are taken into account, which improves the comprehensiveness and accuracy of the energy loss value and further improves the accuracy of the energy consumption assessment model.

[0074] Example performance evaluation model determines the power consumption process

[0075] In order to further illustrate the specific process of the energy consumption evaluation model in S240 evaluating the total energy required for different snow removal times, the present application provides a flow chart of the energy consumption evaluation model evaluating the snow removal energy consumption ( Figure 3 ). In some embodiments, Figure 3 The exemplary process shown may be executed by controller 130 .

[0076] like Figure 3 As shown, the method may include the following steps:

[0077] S310. Evaluate a first energy consumption value consumed for melting the mass of snow within a plurality of different snow removal time lengths using a first evaluation function.

[0078] The first evaluation function may be a function for evaluating the electric energy value (first energy consumption value) actually required to be consumed by the photovoltaic panel itself during the snow removal process. The function may include a functional relationship between the snow removal time length t and the heating power P required for snow removal.

[0079] Considering that sunlight will also generate some heat when snow is removed during the day, the heat generated by the light can also be added to the process of calculating the energy consumption. Specifically, the evaluation of the first energy consumption value can be achieved through the following steps:

[0080] According to the current ambient temperature T e , the current latent heat of melting h and specific heat C of the snow p The total heat Q required to melt m mass of snow can be obtained all =m[C p (0-T e )+h), where h can be a constant according to experience, for example, it can be set to 334 kj / kg; through the albedo Al, the solar radiation G can be used to obtain the heat Q that can be provided by the light s =t×(1-Al)×G, so the functional relationship between the snow removal time length t and the heating power P required for snow removal can be obtained as follows:

[0081]

[0082] Among them, the electric energy value (first energy consumption value) Q required for snow removal time length t e =P×t.

[0083] Considering that in the actual conversion process of electrical energy and thermal energy, there may be a loss value E loss , a time threshold can be set. When the snow removal time length t is less than the time threshold, the loss value E lossIt can be ignored. When the snow removal time length t is not less than the time threshold, a fixed value is set as the loss value E loss , add it to the evaluation process of the first energy consumption value, that is,

[0084] S320: Evaluate a second energy consumption value lost by melting the mass of snow within a plurality of different snow removal time lengths using a second evaluation function.

[0085] The second evaluation function may be a function for evaluating the electric energy loss value (second energy consumption value) caused by the photovoltaic panel stopping light energy conversion during the snow removal process. The function may include the snow removal time length t and the corresponding electric energy value E that can be converted. s The functional relationship between them.

[0086] For example, the amount of electrical energy E that can be converted by the photovoltaic panel within the snow removal time length t can be calculated based on the area S of the photovoltaic panel, the light intensity I, and the efficiency η of the photovoltaic panel. s (Second energy consumption value), namely E s =S×I×t×η; the amount of electrical energy E that can be converted by the photovoltaic panel per unit time can also be set based on past experience unit , then E s =E unit ×t, for the second energy consumption value E s The calculation method of is not specifically limited here.

[0087] S330, adding the first energy consumption value and the second energy consumption value in each snow removal time length among a plurality of different snow removal time lengths to obtain a total energy consumption value in each snow removal time length.

[0088] In some embodiments, the first energy consumption value and the second energy consumption value corresponding to the snow removal time length to be measured obtained in the above S310 and S320 can be added together to obtain the total energy consumption value within the snow removal time length to be measured, that is, the total energy consumption value E all =Q e +E s .

[0089] Exemplary Devices

[0090] Combination of the above Figures 1 to 3 , describes the method embodiment of the present application in detail, and the device embodiment of the present application is described in detail below. It should be understood that the description of the method embodiment corresponds to the description of the device embodiment, so the part not described in detail can refer to the previous method embodiment.

[0091] The present application also provides an automatic snow removal device, including a module for implementing the photovoltaic panel automatic snow removal method provided in the present application. Figure 4 As shown, Figure 4 This is a system module diagram of an automatic snow removal device 400 provided in some embodiments of the present application. The automatic snow removal device 400 provided in the present application may include a snow accumulation information acquisition module 410, a snow melting information determination module 420, an energy consumption assessment module 430, a power determination module 440 and a snow removal module 450.

[0092] The snow information acquisition module 410 is used to obtain the thickness and density of the current snow on the photovoltaic panel.

[0093] The snowmelt information determination module 420 is used to determine the thickness of the snow that actually needs to be melted based on the current snow thickness and the equilibrium thickness, wherein the equilibrium thickness is the thickness of the snow that needs to be melted at least to allow the current snow to slide off the photovoltaic panel. The snowmelt information determination module is also used to determine the mass of the snow that actually needs to be melted based on the thickness and density of the snow that actually needs to be melted.

[0094] The energy consumption assessment module 430 is used to evaluate the total energy consumed to melt the mass of snow within multiple different snow removal time lengths through an energy consumption assessment model, wherein the total energy consumed includes a first energy consumption value and a second energy consumption value, the first energy consumption value is the electric energy consumed for generating heat to melt snow, and the second energy consumption value is the electric energy lost by stopping electric energy conversion, and the energy consumption assessment model 430 is also used to evaluate the first energy consumption value and the second energy consumption value within different snow removal time lengths.

[0095] The power determination module 440 is used to compare the total energy consumed by the mass of current snow that actually needs to be melted within multiple different snow removal time lengths, and take the heating power corresponding to the first energy consumption value in the smallest total energy value as the optimal heating power.

[0096] The snow removal module 450 is used to remove snow from the photovoltaic panel based on the optimal heating power and the corresponding snow removal time length.

[0097] For the specific definition of the automatic snow removal device, please refer to the definition of the method for the low-power automatic snow removal device mentioned above, which will not be repeated here. Each module in the above-mentioned automatic snow removal device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0098] Exemplary electronic devices and program products

[0099] The present application also provides an electronic device, such as Figure 5The electronic device 500 provided in the present application includes a memory 510, a processor 520, and an input / output interface 530. The memory 510, the processor 520, and the input / output interface 530 are connected through an internal connection path, the memory 510 is used to store instructions, and the processor 520 is used to execute the instructions stored in the memory 510 to control the input / output interface 530 to receive input data and information, and output data such as operation results.

[0100] It should be understood that in the embodiment of the present application, the processor 520 can adopt a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits to execute relevant programs to implement the technical solution provided in the embodiment of the present application.

[0101] The memory 510 may include a read-only memory and a random access memory, and provides instructions and data to the processor 520. A portion of the processor 520 may also include a nonvolatile random access memory. For example, the processor 520 may also store information on the device type.

[0102] During the implementation process, each step of the above method can be completed by the hardware integrated logic circuit in the processor 520 or the instruction in the form of software. The vehicle auxiliary braking method disclosed in the embodiment of the present application can be directly embodied as a hardware processor for execution, or it can be executed by a combination of hardware and software modules in the processor. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 510, and the processor 520 reads the information in the memory 510 and completes the steps of the above method in combination with its hardware. To avoid repetition, it is not described in detail here. The present application also provides a computer program product, including a computer program / instruction. When the computer program / instruction processor in the computer program product provided by the present application is executed, the automatic snow removal method for photovoltaic panels provided by the present application can be implemented.

[0103] It should be noted that, in the description of this application, the terms "first", "second", "third", etc. are used for descriptive purposes only and cannot be understood as indicating or implying relative importance. In addition, in the description of this application, unless otherwise specified, the meaning of "plurality" is two or more.

[0104] It should be understood that the term "and / or" in this article is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0105] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0106] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units 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 interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0107] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. The above description is for the purpose of illustrating and describing the technical solution of the present application. In addition, this description is not intended to limit the embodiments of the present application to the scope of the above-disclosed forms. Although multiple exemplary aspects and embodiments have been discussed in the above content, those skilled in the art can easily obtain other variations, modifications, changes, additions and sub-combinations based on the above content.

[0108] 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.

[0109] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, a network device, a user device, a core network device, an operation and maintenance management (operation administration and maintenance, OAM) or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber Line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that can be read by a computer or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a digital video disc (DVD)), or a semiconductor medium (e.g., a solid state disk (SSD)), etc. The computer-readable storage medium may be a volatile or non-volatile storage medium, or may include both volatile and non-volatile types of storage media.

[0110] The above are only preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent substitutions, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A method for automatic snow removal of photovoltaic panels, characterized in that: include: Get the current thickness and density of snow on the photovoltaic panels; Determining the actual thickness of snow that needs to be melted according to the current thickness of snow and the equilibrium thickness, wherein the equilibrium thickness is the thickness of snow that needs to be melted at least to enable the current snow to slide off the photovoltaic panel; Determining the mass of the snow that actually needs to be melted according to the thickness and density of the snow that actually needs to be melted; The total energy consumed to melt the mass of snow in each snow removal time in a plurality of different snow removal time lengths is evaluated by an energy consumption evaluation model, wherein the total energy consumed includes a first energy consumption value and a second energy consumption value, the first energy consumption value is the electric energy value consumed for generating heat to melt snow, and the second energy consumption value is the electric energy value lost by stopping electric energy conversion, and the energy consumption evaluation model is used to evaluate the first energy consumption value and the second energy consumption value in different snow removal time lengths; Comparing the total energy values ​​actually consumed to melt the mass of snow corresponding to the multiple different snow removal time lengths, and taking the heating power corresponding to the first energy consumption value in the smallest total energy value as the optimal heating power; Snow is removed from the photovoltaic panel based on the optimal heating power and the corresponding snow removal time length.

2. The automatic snow removal method for photovoltaic panels according to claim 1, characterized in that: The total energy consumed to melt the mass of snow in each snow removal time in a plurality of different snow removal time lengths is evaluated by the energy consumption evaluation model, and includes: Evaluating the first energy consumption value consumed for melting the mass of snow within a plurality of different snow removal time lengths by a first evaluation function, wherein the first evaluation function includes a functional relationship between the snow removal time length and the corresponding required heating power; Evaluate the second energy consumption value lost by melting the mass of snow within a plurality of different snow removal time lengths by using a second evaluation function, wherein the second evaluation function includes a functional relationship between the snow removal time length and the corresponding convertible electrical energy value; The first energy consumption value and the second energy consumption value in each snow removal time length of the multiple different snow removal time lengths are added together to obtain the total energy consumption value in each snow removal time length.

3. The automatic snow removal method for photovoltaic panels according to claim 2, characterized in that: The first energy consumption value consumed for melting the mass of snow within a plurality of different snow removal time lengths is evaluated by the first evaluation function, comprising: According to the total heat Q_all required to melt the snow mass m, the heat Q_s provided by the light and the length of the snow removal time t, the heating power P required for snow removal is determined based on the following formula: P=(Q_all-Q_s) / t=(m[C_p(0-T_e)+h]-Q_s) / t Among them, Q_all=m[C_p(0-T_e)+h], C_p is the specific heat capacity, T_e is the current ambient temperature, h is the latent heat of melting of the current snow, and according to experience, h can be set to 334 kj / kg. The heat Q_s provided by the illumination can be obtained by t×(1-Al)×G, Al is the albedo, and G is the solar radiation.

4. The automatic snow removal method for photovoltaic panels according to claim 1, characterized in that: Determining the actual thickness of snow that needs to be melted according to the current thickness of snow and the equilibrium thickness includes: comparing the current snow thickness with the equilibrium thickness; When the current snow thickness is greater than the equilibrium thickness, the actual thickness of the snow that needs to be melted is the equilibrium thickness; When the current snow thickness is not greater than the equilibrium thickness, the actual thickness of the snow that needs to be melted is the current snow thickness.

5. The photovoltaic panel automatic snow removal method according to claim 1, characterized in that: Before evaluating the total value of energy consumed to melt the mass of snow in each snow removal time in a plurality of different snow removal time lengths through an energy consumption evaluation model, the method further includes: Determining a suitable snow removal time interval according to the thickness of the snow that actually needs to be melted; An appropriate number of key points are selected within the appropriate snow removal time interval as starting points and end points of the multiple different snow removal time lengths, and the appropriate number of key points includes at least two key points.

6. The automatic snow removal method for photovoltaic panels according to claim 1, characterized in that: The snow removal from the photovoltaic panel based on the optimal heating power and the corresponding snow removal time length comprises: determining the voltage required for snow removal according to the optimal heating power; The voltage is reversely applied to both ends of the photovoltaic panel within the snow removal time length corresponding to the optimal heating power, so that the photovoltaic panel generates corresponding heat to melt the snow that actually needs to be melted.

7. The method for automatic snow removal of photovoltaic panels according to claim 1, characterized in that: Also includes: During snow removal, the tilt angle of the photovoltaic panel is adjusted to the maximum tilt angle to which the photovoltaic panel can be adjusted; After snow removal is completed, the tilt angle of the photovoltaic panel is restored to the tilt angle corresponding to the current season.

8. The method for automatic snow removal of photovoltaic panels according to claim 1, characterized in that: Also includes: When the current snow thickness is greater than a preset threshold, the photovoltaic panel automatic snow removal method is executed.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can perform the photovoltaic panel automatic snow removal method according to any one of claims 1-8.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction processor is executed, it is used to implement the automatic snow removal method for photovoltaic panels according to any one of claims 1-8.

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