A building energy-saving control method based on new energy

Abstract

The present invention discloses a building energy-saving control method based on new energy, which relates to the field of clean energy technology, including: collecting meteorological data and coupled power generation device operation data, and pre-processing the data; obtaining a wind power generation model according to historical meteorological data and coupled power generation device operation data; determining the shadow distribution and adjustment scheme of wind power generation, and establishing a solar power generation model based on this; obtaining the ideal power generation through the wind power generation model and the solar power generation model, calculating the offset value between the ideal power generation and the actual power generation, determining the configuration scheme of the coupled power generation device according to the offset value, and supplying clean energy for the building. The present invention comprehensively utilizes a variety of new energy technologies, reduces the difficulty of combination, and improves the power generation efficiency of multiple energy coupled power generation devices. Then determine the configuration scheme of the coupled power generation device, gradually improve the parameters of the wind power generation equipment and solar power generation equipment in the power generation system, so that the structural configuration of the power generation system is gradually optimized and formed.

Description

Technical Field

[0001] The present invention relates to the field of clean energy technology, and more specifically to a building energy-saving control method based on new energy. Background Art

[0002] With the development of economy and the progress of society, people have put forward higher and higher requirements on energy. There are three main sources of traditional electric energy, namely thermal power, hydropower and nuclear power. Among them, thermal power and nuclear power cause pollution to the environment, and hydropower will flood a large amount of land, which may cause damage to the ecological environment.

[0003] Similarly, in the field of building energy conservation control, the use of clean energy instead of traditional thermal power energy can significantly reduce carbon emissions, reduce the urban heat island effect, and improve user comfort while reducing economic costs. Based on this, finding new energy has become an urgent issue facing mankind. In the existing technology, people are looking for new energy functions including wind energy and solar energy. However, different energy sources have different production methods and the technology is not mature. There are many technical difficulties in combining multiple energy sources for energy supply. Some new energy sources require greater geographical advantages, such as geothermal tides, etc. Similarly, the production methods of multiple energy sources combined will conflict.

[0004] Therefore, how to propose a building energy-saving control method based on new energy, comprehensively utilize multiple new energy technologies, reduce the difficulty of combination, improve the power generation efficiency of multiple energy coupling power generation devices, and realize energy-saving control of buildings is an urgent problem that technical personnel in this field need to solve. Summary of the invention

[0005] In view of this, the present invention provides a building energy-saving control method based on new energy, which comprehensively utilizes multiple new energy technologies, reduces the difficulty of combination, improves the power generation efficiency of multiple energy coupling power generation devices, and realizes energy-saving control of buildings. In order to achieve the above purpose, the present invention adopts the following technical solutions:

[0006] A building energy-saving control method based on new energy, comprising:

[0007] Collect meteorological data and coupled power generation device operation data, and pre-process the data;

[0008] A wind power generation model is obtained based on historical meteorological data and coupled power generation device operation data;

[0009] Determine the shadow distribution and regulation scheme of wind power generation and use it to establish a solar power generation model;

[0010] The ideal power generation is obtained through the wind power generation model and the solar power generation model, the offset value between the ideal power generation and the actual power generation is calculated, the configuration scheme of the coupled power generation device is determined according to the offset value, and clean energy is supplied to the building according to the configuration scheme.

[0011] Optionally, the collected meteorological data and coupled power generation device operation data include: collecting wind speed, wind direction, wind force, air density, light intensity, light incident angle, altitude, temperature, annual average light intensity, solar daily trajectory, wind power generation and solar power generation. The coupled power generation device is a solar and wind energy collection device installed around the building.

[0012] Optionally, the preprocessing of the data includes: performing data cleaning, noise reduction and feature transformation, and normalizing the data to a unit norm.

[0013] Optionally, obtaining the wind power generation model includes:

[0014] Collect historical meteorological data and coupled power generation device operation data;

[0015] Divide wind direction and air density into regions, and classify the collected data according to the divided regions;

[0016] According to the classified data, the wind speed and the wind turbine power are fitted to obtain the wind speed function of the wind turbine under different wind directions and air densities, which characterizes the wind turbine power function;

[0017] The meteorological forecast results of the wind turbine are processed to find the corresponding wind direction and air density, and the predicted wind speed is substituted into the power function to obtain the predicted power.

[0018] Optionally, the shadow distribution includes:

[0019] Collect the sunshine time to determine the solar altitude angle, solar azimuth angle and the steering angle of the wind turbine;

[0020] Calculate the shadow shielding time at each position under the steering angle of each wind turbine in the area, and draw the shadow impact distribution map of the area.

[0021] Optionally, the determining of the adjustment scheme for wind power generation includes:

[0022] Obtain the wind energy generation before adjustment, obtain the wind strength in different areas according to the wind speed function, control the wind turbine to face the maximum wind strength, and obtain the wind energy generation after adjustment according to the power function;

[0023] The wind energy generation offset value before and after the adjustment is calculated and compared with the solar energy generation offset value before and after the adjustment. If it is greater than a first threshold, the wind turbine blade direction is offset.

[0024] Optionally, the establishing of a solar power generation model includes:

[0025] Q san =(S all-S zd )sinθP-S gs μ, where Q san is the ideal solar power generation, S all is the total area of ​​solar panels, S zd is the shadow distribution, θ is the incident angle of light, P is the power generation of the solar panel per unit area, S gs is the interference area formed by wind power generation equipment on the solar panel, μ represents the influence factor, μ=0.13sinμ.

[0026] Optionally, the calculation of the offset value between the ideal power generation and the actual power generation includes: Among them, Q py is the energy deviation between wind power generation and solar power generation, Q win is the ideal wind power generation, Q san is the ideal solar power generation, Q sj is the actual value of wind power generation and solar power generation, For energy loss.

[0027] Optionally, the method of determining the configuration scheme of the coupled power generation device according to the offset value includes: continuously acquiring the calculated offset value, setting an offset value threshold, wherein the offset value threshold is less than a first threshold, selecting a group with the highest theoretical value of power generation of the coupled power generation device within the offset value threshold range, and determining the configuration parameters of the wind power generation equipment and the solar power generation equipment; wherein the configuration parameters include the total area of ​​the solar panels, the shadow distribution, the steering angle of the wind turbine, the incident angle of light, the interference area formed by the wind power generation equipment on the solar panels, the number of wind power generation equipment and the power generation power of the solar panels.

[0028] It can be seen from the above technical solutions that, compared with the prior art, the present invention discloses a building energy-saving control method based on new energy, which has the following beneficial effects:

[0029] The present invention includes: collecting meteorological data and coupled power generation device operation data, and pre-processing the data; obtaining a wind power generation model according to historical meteorological data and coupled power generation device operation data; determining the shadow distribution and adjustment scheme of wind power generation, and establishing a solar power generation model based on this; obtaining the ideal power generation through the wind power generation model and the solar power generation model, calculating the offset value between the ideal power generation and the actual power generation, determining the configuration scheme of the coupled power generation device according to the offset value, and supplying clean energy for the building according to the configuration scheme. Wind power generation and solar power generation are combined, the wind power generation offset value before and after the adjustment and the solar power generation offset value before and after the adjustment are calculated and compared, and if they are greater than a first threshold, the wind turbine blade direction is offset. According to the offset value obtained by continuous acquisition and calculation, an offset value threshold is set. If the offset value threshold is less than the first threshold, a group with the highest theoretical value of the power generation of the coupled power generation device is selected within the offset value threshold range, and the configuration parameters of the wind power generation equipment and the solar power generation equipment are determined to achieve the most efficient power generation of the solar and wind coupled power generation devices. A variety of new energy technologies are comprehensively utilized to reduce the difficulty of combination and improve the power generation efficiency of multiple energy coupled power generation devices. Then, the configuration plan of the coupled power generation device is determined, and clean energy is supplied to the building according to the configuration plan. The parameters of the wind power generation equipment and solar power generation equipment in the power generation system are gradually improved, so that the structural configuration of the power generation system is gradually optimized and energy-saving control of the building is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0031] Figure 1 A schematic flow chart of a building energy-saving control method based on new energy provided by the present invention. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] The embodiment of the present invention discloses a building energy-saving control method based on new energy, comprising:

[0034] Collect meteorological data and coupled power generation device operation data, and pre-process the data;

[0035] A wind power generation model is obtained based on historical meteorological data and coupled power generation device operation data;

[0036] Determine the shadow distribution and regulation scheme of wind power generation and use it to establish a solar power generation model;

[0037] The ideal power generation is obtained through the wind power generation model and the solar power generation model, the offset value between the ideal power generation and the actual power generation is calculated, the configuration scheme of the coupled power generation device is determined according to the offset value, and clean energy is supplied to the building according to the configuration scheme.

[0038] Furthermore, the collected meteorological data and coupled power generation device operation data include: collecting wind speed, wind direction, wind force, air density, light intensity, light incident angle, altitude, temperature, annual average light intensity, solar daily trajectory, wind power generation and solar power generation. The coupled power generation device is a solar and wind energy collection device installed around the building.

[0039] Furthermore, the data preprocessing includes: data cleaning, noise reduction and feature transformation, and data normalization to unit norm. The data vector is divided by its norm so that the norm of the data vector is 1. Assume that there is a data vector x = [x1, x2, ..., x n ], whose norm is ||x||, then the normalized data vector is For each data x i , the normalized value is Eliminate the dimension effect of data to make different features comparable.

[0040] Furthermore, obtaining the wind power generation model includes:

[0041] Collect historical meteorological data and coupled power generation device operation data;

[0042] Divide wind direction and air density into regions, and classify the collected data according to the divided regions;

[0043] According to the data obtained through classification, the wind speed and the wind turbine power are fitted to obtain the wind speed function of the wind turbine under different wind directions and air densities, and to characterize the wind turbine power function;

[0044] The meteorological forecast results of the wind turbine are processed to find the corresponding wind direction and air density, and the predicted wind speed is substituted into the power function to obtain the predicted power.

[0045] In a specific implementation, the specific steps of obtaining the wind power generation model include:

[0046] Obtain historical data of each wind turbine in the wind farm, including the time series of wind speed, wind direction, air density, and wind power under normal operating conditions of the wind turbine;

[0047] The wind direction is divided into p grid areas, and the air density is increased from the minimum air density value at fixed intervals to the maximum air density. Assuming that the air density has v values, there are p×v combinations of wind direction and air density. The historical data of each wind turbine is classified according to the combination.

[0048] The classified data is fitted with a k-order polynomial f(x) of wind turbine power corresponding to wind speed x, and the obtained Among them, a i are the coefficients of the polynomial, then the scalar function D is: Among them, y t represents the actual power of the fan at wind speed x, It represents the power obtained by fitting the wind speed x of the wind turbine using the k-order polynomial f(x);

[0049] The obtained objective function is partially differentiated with respect to the coefficients and set to 0, that is, a linear equation system is obtained, the linear equation system is transformed into a matrix form, the linear equation system is numerically solved using the Gaussian elimination method, different k values ​​are selected to calculate the objective function value, and the high-order polynomial corresponding to the minimum value of the objective function value is selected as the best approximation polynomial;

[0050] The above operation is iterated for each wind turbine to obtain the high-order function of wind speed of each wind turbine under different wind direction ranges and air density conditions, that is, the power approximate function; the steering angle of the wind turbine is changed, the rotation angle range is divided according to the rotation angle, and the above process is iterated to obtain the wind power generation model under different rotation angle ranges.

[0051] Process the real-time weather forecast data to find the corresponding wind direction, air density conditions and steering angle of the wind turbine, and obtain the predicted power Q of the wind power generation model. win .

[0052] The functional relationship between wind turbine power and meteorological variables is found through historical data, and the predicted power is directly obtained through the predicted value of meteorological data. At the same time, the deviation between the actual output power and the predicted power calculated by the function can also be used to assist in checking whether the wind turbine is operating normally.

[0053] Furthermore, the shadow distribution includes:

[0054] Collect the sunshine time to determine the solar altitude angle, solar azimuth angle and the steering angle of the wind turbine;

[0055] Calculate the shadow shielding time at each position under the steering angle of each wind turbine in the area, and draw the shadow impact distribution map of the area.

[0056] In a specific implementation, the specific steps of the shadow distribution are:

[0057] Collect the illumination time to obtain the sunrise time, sunset time, time zone, and longitude and latitude;

[0058] Determine the sun's altitude angle based on collected data and the solar azimuth σ;

[0059] Calculate the number of hours any location is shadowed by a wind turbine;

[0060] Set the wind turbine's position coordinates to (x0, y0, z0) and its hub height to h g , the blade radius is r, and the solar altitude angle at time z is When the maximum shadow length l is max It is expressed as:

[0061]

[0062] The shadow impact area of ​​the wind turbine is within the range of radius r with (x1, y1, z1) as the center; The plane distance l from any position (x, y, z) at time z to the center point of the shadow (x1, y1, z1) z It is expressed as: At time z, if l is satisfied z ≤l, the shadow of the wind turbine will block the position, and the time t at time z is when the position is blocked by the shadow z Satisfy t z =1; otherwise t z =0.

[0063] The shadow distribution is: performing shadow shading judgment on all unit area positions of the solar panel, summarizing the total shadow shading area of ​​the solar panel at each moment, that is, obtaining the real-time shadow distribution in the solar power generation model at each moment.

[0064] Among them, the light incident angle θ is the angle between the sunlight and the vertical ground.

[0065] Solar altitude angle The angle between the sun's rays and the horizontal ground.

[0066] Solar azimuth σ: the angle between the projection of the sun's rays on the horizontal plane and the south direction.

[0067] The relationship between these three can be expressed by the following formula:

[0068] In a specific implementation, a shadow impact distribution map of the planned area can also be drawn according to the shadow blocking time, including: taking the calculation step length as 5 minutes, the number of hours T that the location is blocked by the shadow of the wind turbine i Expressed as: T i =1 / 12(t1+t2+...+t N ), where N is the number of minutes; assuming that there are F wind turbines in a wind farm, the total number of hours T at any location in a year that is shaded by wind turbines in the wind farm is expressed as: T = T1 + T2 + ... + T F The shadow impact time at any position in the solar power generation area is calculated over a long time span, and a shadow impact distribution map of the power generation area is drawn. The shadow shading judgment is performed on all unit area positions of the solar panels, and the shadow shading judgment of multiple wind turbines is performed on the same unit area position of the solar panels. The net shadow shading area of ​​the solar power generation area is obtained by superimposing F wind turbines at any time, and the average shadow distribution at any time is obtained. The real-time shadow distribution and the average shadow distribution are weighted to obtain the shadow distribution.

[0069] Furthermore, the adjustment scheme for determining wind power generation includes:

[0070] Obtain the wind energy generation before adjustment, obtain the wind strength in different areas according to the wind speed function, control the wind turbine to face the maximum wind strength, and obtain the wind energy generation after adjustment according to the power function;

[0071] The wind energy generation offset value before and after the adjustment is calculated and compared with the solar energy generation offset value before and after the adjustment. If it is greater than a first threshold, the wind turbine blade direction is offset.

[0072] In a specific implementation, a building energy-saving control method based on new energy further includes determining the first threshold:

[0073] Build a prediction model based on convolutional neural network;

[0074] The wind power generation before and after the adjustment, the fluctuation impact of the power generation change on the power grid and the energy demand data of the power grid are used as input values, and the first threshold value is the output value;

[0075] Perform preprocessing, including cropping, scaling, normalization, and other operations, and divide the data into training and test sets;

[0076] Use the training set for training, select appropriate optimizers, loss functions, hyperparameters such as learning rate, and set appropriate parameters such as the number of training epochs and batch size;

[0077] Use the test set to evaluate and optimize the model, and evaluate the performance of the model by calculating indicators such as the accuracy, precision, and recall rate of the model;

[0078] A first threshold is obtained according to the optimized prediction model.

[0079] Furthermore, the establishment of a solar power generation model includes:

[0080] Q san =(S all -S zd )sinθP-S gs μ, where Q san is the ideal solar power generation, S all is the total area of ​​solar panels, S zd is the shadow distribution, θ is the incident angle of light, P is the power generation of the solar panel per unit area, S gs is the interference area formed by wind power generation equipment on the solar panel, μ represents the influence factor, μ=0.13sinμ.

[0081] Furthermore, the calculation of the offset value between the ideal power generation and the actual power generation includes: Among them, Q py is the energy deviation between wind power generation and solar power generation, Q win is the ideal wind power generation, Q san is the ideal solar power generation, Q sj is the actual value of wind power generation and solar power generation, For energy loss.

[0082] Furthermore, the configuration scheme of the coupled power generation device determined according to the offset value includes: continuously obtaining the calculated offset value, setting an offset value threshold, and if the offset value threshold is less than a first threshold, selecting a group of coupled power generation devices with the highest theoretical value of power generation within the offset value threshold range, determining the configuration parameters of the wind power generation equipment and the solar power generation equipment, and realizing the most efficient power generation of the solar and wind coupled power generation device; wherein the configuration parameters include the total area of ​​the solar panel, the shadow distribution, the steering angle of the wind turbine, the incident angle of light, the interference area formed by the wind power generation equipment on the solar panel, the number of solar power generation equipment, the number of wind power generation equipment and the power generation of the solar panel.

[0083] In a specific implementation, a building energy-saving control system based on new energy includes:

[0084] Acquisition module: used to collect meteorological data and coupled power generation device operation data, and pre-process the data;

[0085] Wind power generation model building module: used to obtain a wind power generation model based on historical meteorological data and coupled power generation device operation data;

[0086] Solar power generation model building module: used to determine the shadow distribution and adjustment scheme of wind power generation, and to build a solar power generation model based on this;

[0087] Configuration module: used to obtain the ideal power generation through wind power generation model and solar power generation model, calculate the offset value between the ideal power generation and the actual power generation, determine the configuration scheme of the coupled power generation device according to the offset value, and supply clean energy to the building according to the configuration scheme.

[0088] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0089] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A building energy-saving control method based on new energy, characterized in that: include: Collect meteorological data and coupled power generation device operation data, and pre-process the data; A wind power generation model is obtained based on historical meteorological data and coupled power generation device operation data; The wind power generation model is obtained by: Collect historical meteorological data and coupled power generation device operation data; Divide wind direction and air density into regions, and classify the collected data according to the divided regions; According to the classified data, the wind speed and wind turbine power are fitted to obtain the wind speed function of the wind turbine under different wind directions and air densities, which characterizes the wind turbine power function; Process the meteorological forecast results of the wind turbine, find the corresponding wind direction and air density, substitute the predicted wind speed into the power function, and get the predicted power; The above operation is iterated for each wind turbine to obtain the wind speed function, i.e., the power function, of each wind turbine under different wind direction intervals and air density conditions; the steering angle of the wind turbine is changed, the rotation angle interval is divided according to the rotation angle, and the above process is iterated to obtain the wind power generation model under different rotation angle intervals; Process the real-time weather forecast data to find the corresponding wind direction, air density conditions and steering angle of the wind turbine, and obtain the predicted power Q of the wind power generation model. win ; The functional relationship between wind turbine power and meteorological variables is found through historical data, and the predicted power is directly obtained through the predicted value of meteorological data. At the same time, the deviation between the actual output power and the predicted power calculated by the function is used to assist in checking whether the wind turbine is operating normally. Determine the shadow distribution and regulation scheme of wind power generation and use it to establish a solar power generation model; The shadow distribution includes: Collect the sunshine time to determine the solar altitude angle, solar azimuth angle and the steering angle of the wind turbine; Calculate the shadow shielding time at each position under each wind turbine steering angle and draw a shadow impact distribution map; The adjustment scheme for determining wind power generation includes: Obtain wind power generation before adjustment, obtain wind strength in different areas according to wind speed function, control wind turbines to face maximum wind strength, and obtain wind power generation after adjustment according to power function; Calculate the wind energy generation offset value before and after the adjustment and compare it with the solar energy generation offset value before and after the adjustment. If the offset value is greater than a first threshold, offset the direction of the wind turbine blades. Determine the first threshold: Build a prediction model based on convolutional neural network; The wind power generation before and after the adjustment, the fluctuation impact of the power generation change on the power grid and the energy demand data of the power grid are used as input values, and the first threshold value is the output value; Perform preprocessing, including cropping, scaling, normalization, and division into training and test sets; Use the training set for training, select the optimizer, loss function and learning rate, and set the number of training rounds and batch size; use the test set to evaluate and optimize the model, and evaluate the performance of the model by calculating the accuracy, precision and recall rate of the model; Obtaining a first threshold value according to the optimized prediction model; The ideal power generation is obtained through the wind power generation model and the solar power generation model, the offset value between the ideal power generation and the actual power generation is calculated, the configuration scheme of the coupled power generation device is determined according to the offset value, and clean energy is supplied to the building according to the configuration scheme.

2. A building energy-saving control method based on new energy according to claim 1, characterized in that: The collected meteorological data and coupled power generation device operation data include: collecting wind speed, wind direction, wind force, air density, light intensity, light incident angle, altitude, temperature, annual average light intensity, solar daily trajectory, wind power generation and solar power generation. The coupled power generation device is a solar and wind energy collection device set up around the building.

3. A building energy-saving control method based on new energy according to claim 1, characterized in that: The data preprocessing includes: data cleaning, noise reduction and feature transformation, and data normalization to unit norm.

4. A building energy-saving control method based on new energy according to claim 1, characterized in that: The solar power generation model is established including: Q san =(S all -S zd )sinθP-S gs μ, where Q san is the ideal solar power generation, S all is the total area of ​​solar panels, S zd is the shadow distribution, θ is the incident angle of light, P is the power generation of the solar panel per unit area, S gs is the interference area formed by wind power generation equipment on the solar panel, μ represents the influence factor, μ=0.13sinμ.

5. A building energy-saving control method based on new energy according to claim 1, characterized in that: The calculation of the offset value between the ideal power generation and the actual power generation includes: Among them, Q py is the energy deviation between wind power generation and solar power generation, Q win is the ideal wind power generation, Q san is the ideal solar power generation, Q sj is the actual value of wind power generation and solar power generation, For energy loss.

6. A building energy-saving control method based on new energy according to claim 1, characterized in that: The method for determining the configuration scheme of the coupled power generation device according to the offset value includes: continuously obtaining the calculated offset value, setting an offset value threshold, wherein the offset value threshold is less than a first threshold, selecting a group with the highest theoretical value of power generation of the coupled power generation device within the offset value threshold range, and determining the configuration parameters of the coupled power generation device; the configuration parameters include the total area of ​​the solar panel, the shadow distribution, the steering angle of the wind turbine, the incident angle of light, the interference area formed by the wind power generation equipment on the solar panel, the number of wind power generation equipment and the power generation power of the solar panel.

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