Machine learning based building dynamic shading and energy optimization collaborative control system

Abstract

This invention discloses a machine learning-based collaborative control system for building dynamic shading and energy optimization, belonging to the field of collaborative control. It addresses the problems of insufficient building intelligence and high energy consumption in existing systems. The system includes a data acquisition module for acquiring illumination and building information; a dynamic shading module for calculating the building's illumination range, acquiring the building's usable space, and measuring the illuminance of the usable space; and a dynamic shading operation based on the usable space, illumination range, and illuminance; an energy judgment module for acquiring the energy consumption of electrical appliances; measuring the energy consumption of electrical appliances under shading operation and making energy judgments based on different energy consumption levels; and an energy optimization module for adjusting the use of electrical appliances based on the energy judgment results and optimizing energy consumption. This invention effectively improves building comfort and reduces energy loss.

Description

Technical Field

[0001] This invention belongs to the field of collaborative control and involves machine learning technology, specifically a collaborative control system for building dynamic shading and energy optimization based on machine learning. Background Technology

[0002] Existing building dynamic shading and energy optimization collaborative control systems have the following specific defects during operation:

[0003] 1. Existing shading control mainly relies on manual experience or timed switches, which are disconnected from environmental data and make it difficult to achieve precise control. At the same time, in pursuit of energy conservation, shading devices often need to be completely closed, resulting in insufficient indoor lighting, limited visibility, and affecting comfort.

[0004] 2. Insufficient overall perspective: It fails to comprehensively and effectively manage the energy usage of the entire building, typically relying on assessments and judgments of the energy consumption of representative equipment. This leads to compromises on overall energy management goals during localized optimization processes. For example, adjusting shading devices to reduce the energy consumption of the air conditioning system may increase the energy consumption of the lighting system, thus failing to achieve a true reduction in overall energy consumption.

[0005] 3. Lack of detailed consideration and dynamic adjustment of actual energy consumption; using fixed values ​​to represent energy consumption in a general way cannot accurately reflect the actual energy consumption of buildings under different environmental conditions and usage states, and cannot provide precise control basis for collaborative control systems.

[0006] To address this, we propose a collaborative control system for building dynamic shading and energy optimization based on machine learning. Summary of the Invention

[0007] To address the shortcomings of existing technologies, the purpose of this invention is to provide a collaborative control system for building dynamic shading and energy optimization based on machine learning. This invention aims to improve building comfort and reduce energy consumption.

[0008] To achieve the above objectives, the present invention adopts the following technical solution: a machine learning-based building dynamic shading and energy optimization collaborative control system, comprising:

[0009] Data acquisition module: measures the angle of sunlight at different times to obtain illumination information; acquires spatial information of the building and operational information of electrical appliances within the building to form building information;

[0010] Dynamic shading module: Based on building information, obtain the building's spatial information, combine it with illumination information, calculate the building's illumination range, obtain the building's usable space, and measure the illuminance of the usable space; based on the usable space, illumination range, and illuminance, determine and perform dynamic shading operation on the building.

[0011] Energy assessment module: Acquires the operating information of electrical appliances in the building and obtains the energy consumption of the appliances; measures the energy consumption of the appliances under shading operation and makes energy assessment of the shading operation based on the energy consumption of the appliances under different operations.

[0012] Energy optimization module: Based on the energy assessment results, the use of electrical appliances is adjusted, and energy is optimized by combining the energy consumption of electrical appliances.

[0013] Furthermore, the irradiation range is calculated as follows:

[0014] Based on the building's spatial information, the window length and interior depth of the building are obtained, with the window length denoted as ck and the interior depth as sn; based on the illumination information, the angle of sunlight is obtained, with the angle of sunlight denoted as zj.

[0015] Based on the building's window length ck and sunlight angle zj, combined with the building's interior depth sn, the farthest distance of sunlight inside the building is calculated to obtain the illumination distance yj.

[0016]

[0017] Based on the irradiation distance, the irradiation range interval zsf is obtained; zsf = [0, yj];

[0018] The usable space of the building is obtained, and the direct sunlight range is calculated based on the usable space and the range of illumination.

[0019] Furthermore, the range of direct sunlight is calculated as follows:

[0020] Using the building's windows as a reference, the distance between the building's usable space and the building's windows is obtained. Based on the distance between the building's usable space and the building's windows, the building's usable space is reduced in dimensionality. The usable space is represented by the distance, resulting in the usable range interval sy, where sy = [zsy, ysy].

[0021] Based on the usage range interval sy and the irradiation range interval zsf, the direct radiation range interval cdf is obtained, cdf = [zcd, ycd];

[0022]

[0023] Where: 0, yj, zsy, ysy are interval parameters, zsf = [0, yj], sy = [zsy, ysy];

[0024] The decision is made by dynamically shading the building based on the range of direct sunlight.

[0025] Furthermore, the decision is made by dynamically shading the building based on the range of direct sunlight, as detailed below:

[0026] Based on the direct range interval cdf=[zcd,ycd], the direct range is obtained as ycd-zcd;

[0027] When ycd-zcd>0, it indicates that there is direct sunlight within the building's usable area, and shading is required.

[0028] When ycd-zcd=0, it indicates that there is no direct sunlight within the building's usable area. The illuminance of the usable space is obtained, and a comprehensive judgment is made based on the illuminance of the usable space.

[0029] The standard illuminance range of the building is obtained and denoted as bzd;

[0030] The illuminance of the space is measured at n points within a range using a lux meter, resulting in measured illuminance values ​​czd(1), czd(2), ..., czd(n). These measured illuminance values ​​are then compared with standard illuminance ranges.

[0031] If the measured illuminance is higher than the standard illuminance range, then shading should be applied.

[0032] The sunshade operation is carried out by selecting sunshade curtains of different lengths.

[0033] Furthermore, sunshade curtains of different lengths were selected for sunshade operations, as detailed below:

[0034] The initial length of the sunshade curtain, csc, is calculated based on the angle of sunlight zj and the range of use sy.

[0035] csc = ck - zsy × tan(zj);

[0036] Where: ck is the window length, and zsy is the interval parameter of the range sy used;

[0037] After using a sunshade curtain of length csc for shading, the illuminance inside the building is measured. If the illuminance is lower than the maximum value of the standard illuminance range, a sunshade curtain of length csc is selected for shading. If the illuminance is higher than the standard illuminance range, the initial length csc of the sunshade curtain is increased. The illuminance measurement of the used space is repeated until the illuminance is lower than the maximum value of the standard illuminance range.

[0038] Furthermore, the energy level of the shading operation is assessed, as follows:

[0039] Based on the operating information of electrical appliances in the building, the types of electrical appliances and their energy consumption in the building under shading are obtained, and the energy consumption of the building under shading is calculated; the types of electrical appliances and their energy consumption in the building without shading are also obtained, and the energy consumption of the building without shading is calculated; by comparing the energy consumption of the building under shading with that of the building without shading, the energy change of shading operation is determined; and shading operation is selected based on the energy change.

[0040] Furthermore, the energy consumption of the building without shading is calculated as follows:

[0041] Obtain the types of electrical appliances operating in the building without shading (wzl); statistically analyze the energy consumption of each type of electrical appliance to obtain the energy consumption nxh of the electrical appliances operating without shading over a continuous period of time. Divide the time into t time nodes, and construct a time curve xsq for energy consumption without shading based on the time nodes and the energy consumption without shading; analyze the time curve for energy consumption without shading and calculate the rate of change before and after different time nodes; denote the rate of change before the time node without shading as qbh, and the rate of change after the time node without shading as hbh.

[0042]

[0043] Where: Δt represents the small change in time; qbh(i) represents the rate of change of the i-th node before the time node under the condition of no shading; hbh(i) represents the rate of change of the i-th node after the time node under the condition of no shading; and nxh(i) represents the energy consumption of the i-th node under the condition of no shading.

[0044] When |qbh(i)|>hbh(i)=0, this time node is extracted to obtain the time segmentation node fg for fluctuation consumption and stable consumption under unshaded conditions;

[0045] Based on the time segmentation node fg of fluctuation consumption and stable consumption under unshaded conditions, the average change of the first fg time nodes is calculated to obtain the average fluctuation value wbj under unshaded conditions.

[0046]

[0047] Based on the mean fluctuation value wbj under unshaded conditions, an unshaded fluctuation function y1 is constructed, and the energy consumption is obtained through the unshaded fluctuation function.

[0048] Furthermore, the energy consumption is calculated using the unshaded fluctuation function, as follows:

[0049] Based on the time curve of the segment node fg under no shading and the energy consumption under no shading xsq, the total amount of fluctuating energy consumption under no shading is calculated to obtain the fluctuating energy consumption bdx under no shading.

[0050]

[0051] Where: xsq(t) represents the time curve of energy consumption as a function of t; d(t) indicates that t is the integral variable;

[0052] Based on the mean fluctuation value wbj under unshaded conditions, construct the unshaded fluctuation function y1;

[0053] y1 = wbj × x1 + b1;

[0054] Where: y1, x1, and b1 are the construction parameters; y1 represents the instantaneous power;

[0055] b1 is obtained by using the segment node fg under unshaded conditions and the fluctuating energy consumption bdx under unshaded conditions:

[0056]

[0057] The stable energy consumption per unit time under unshaded conditions is obtained and denoted as wdx;

[0058] Based on the unshaded fluctuation function y1 and the stable energy consumption wdx under unshaded conditions, the electrical energy consumption zxh under unshaded conditions is obtained;

[0059] Where: bdx represents the fluctuating energy consumption under no shading; x1 represents the time of energy consumption by electrical appliances;

[0060] Based on the types of electrical appliances operating without shading (wzl), the energy consumption of electrical appliances under unshaded conditions (zxh(1), zxh(2), ..., zxh(wzl)) is obtained. The building energy consumption (wjx) under unshaded conditions is then calculated based on the energy consumption of electrical appliances under unshaded conditions (zxh(1) to zxh(wzl)).

[0061] wjx=zxh(1)+zxh(2)+…+zxh(wzl).

[0062] Furthermore, the energy consumption of the building under shading is calculated as follows:

[0063] Obtain the types of electrical appliances operating within the building under shading conditions; and statistically analyze the energy consumption of each type of appliance, as detailed below:

[0064] Obtain the energy consumption znxh of electrical appliances operating under shading over a continuous period of time. Divide the time into t time nodes. Based on the time nodes and the energy consumption under shading, construct the time curve zxsq of energy consumption under shading. Analyze the time curve of energy consumption under shading and calculate the rate of change before and after different time nodes. Denote the rate of change before the time node under shading as zqbh and the rate of change after the time node under shading as zhbh.

[0065]

[0066] Where: Δt represents the small change in time; zqbh(i) represents the rate of change of the i-th node before the time node under shading; zhbh(i) represents the rate of change of the i-th node after the time node under shading; and znxh(i) represents the energy consumption of the i-th node under shading.

[0067] When |zqbh(i)|>zhbh(i)=0, the time node is extracted to obtain the time segmentation node zfg for fluctuation consumption and stable consumption under shading;

[0068] Based on the time segmentation node zfg of fluctuation consumption and stable consumption under shading, the average change of the first zfg time nodes is calculated to obtain the average fluctuation value zwbj under shading.

[0069]

[0070] Based on the average fluctuation value zwbj under shading, a shading fluctuation function y2 is constructed, and the energy consumption is obtained through the shading fluctuation function.

[0071] Furthermore, the energy consumption is calculated using the shading fluctuation function, as follows:

[0072] Based on the time curve of energy consumption between the segment node zfg under shading and zxsq, the total energy consumption under shading is calculated to obtain the energy consumption under shading zbdx.

[0073]

[0074] Where: zxsq(t) represents the time curve of energy consumption under shading as a function of t; d(t) indicates that t is the integral variable;

[0075] Based on the mean fluctuation value zwbj under shading, construct the shading fluctuation function y2;

[0076] y2 = zwbj × x2 + b2;

[0077] Where: y2, x2, and b2 are the construction parameters; y2 represents instantaneous power, and x2 represents time;

[0078] b2 is obtained by using the segment node zfg under shading and the fluctuating energy consumption zbdx under shading:

[0079]

[0080] The stable energy consumption per unit time under shading is obtained and denoted as zwdx;

[0081] Based on the shading fluctuation function y2 and the stable energy consumption under shading zwdx, the electrical energy consumption under shading zzxh is obtained;

[0082]

[0083] Where: zbdx represents the fluctuating energy consumption under no shading; x2 represents the energy consumption time of electrical appliances;

[0084] Based on the types of electrical appliances operating under the shading system (zzl), the energy consumption of these appliances (zzxh(1), zzxh(2), ..., zzxh(zzl)) is obtained. Then, the building energy consumption (zjx) under the shading system is calculated based on these energy consumption values ​​(zzxh(1) to zzxh(zzl)).

[0085] zjx=zzxh(1)+zzxh(2)+……+zzxh(zzl).

[0086] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0087] 1. This invention measures light data and calculates the direct sunlight range by light angle, optimizing shading control so that the shading device can accurately block direct sunlight. The specific parameters of the shading device are accurately calculated by using the sunlight angle and indoor illuminance, which reduces direct sunlight while enhancing indoor lighting and improving comfort.

[0088] 2. Conduct a comprehensive analysis of the building's operating devices to ensure the accuracy and comprehensiveness of energy consumption data, and implement comprehensive and effective management of the building's overall energy usage; compare building energy consumption under different shading conditions to ensure effective reduction of energy consumption;

[0089] 3. Conduct a detailed analysis of the energy consumption of individual devices. By analyzing the changes in energy consumption of the devices, construct a function to represent them. Adjust the function by adjusting the overall energy consumption to ensure the accuracy of the function in displaying changes in energy consumption. Attached Figure Description

[0090] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0091] Figure 1 This is an overall system block diagram of the present invention;

[0092] Figure 2 This is a schematic diagram of sunlight exposure in this invention;

[0093] Figure 3 This is a schematic diagram of the direct-light zone in this invention;

[0094] Figure 4 This is a schematic diagram of the energy consumption curve in this invention. Detailed Implementation

[0095] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0096] Example 1

[0097] Please see Figure 1 The present invention provides a technical solution: a collaborative control system for building dynamic shading and energy optimization based on machine learning, comprising a data acquisition module, a dynamic shading module, a collaborative control module, an energy optimization module and a server, wherein the data acquisition module, the dynamic shading module, the collaborative control module and the energy optimization module are respectively connected to the server, and the server controls the data acquisition module, the dynamic shading module, the collaborative control module and the energy optimization module respectively;

[0098] Data acquisition module: measures the angle of sunlight at different times to obtain illumination information; acquires spatial information of the building and operational information of electrical appliances within the building to form building information;

[0099] Dynamic shading module: Based on building information, obtain the building's spatial information, combine it with illumination information, calculate the building's illumination range, obtain the building's usable space, and measure the illuminance of the usable space; based on the usable space, illumination range, and illuminance, determine and perform dynamic shading operation on the building.

[0100] The specific workflow of the dynamic shading module is as follows:

[0101] Please see Figure 2Based on the building's spatial information, the window length and interior depth of the building are obtained, with the window length denoted as ck and the interior depth as sn; based on the illumination information, the angle of sunlight is obtained, with the angle of sunlight denoted as zj.

[0102] Based on the building's window length ck and sunlight angle zj, combined with the building's interior depth sn, the farthest distance of sunlight inside the building is calculated to obtain the illumination distance yj.

[0103]

[0104] It should be noted that: the illumination distance refers to the horizontal distance between the farthest point of sunlight and the window, and its maximum value does not exceed the interior depth of the building; the maximum value of the illumination distance and the interior depth of the building is taken by the max function.

[0105] Based on the irradiation distance, the irradiation range interval zsf is obtained; zsf = [0, yj];

[0106] It should be noted that the illumination range refers to the distance range within the building interior that sunlight illuminates, with the window position as the base point.

[0107] The usable space of the building is acquired, and the direct sunlight range is calculated based on the usable space and the area of ​​illumination; the details are as follows:

[0108] Using the building's windows as a reference, the distance between the building's usable space and the building's windows is obtained. Based on the distance between the building's usable space and the building's windows, the building's usable space is reduced in dimensionality. The usable space is represented by the distance, resulting in the usable range interval sy, where sy = [zsy, ysy].

[0109] Please see Figure 3 Based on the usage range interval sy and the irradiation range interval zsf, the direct radiation range interval cdf is obtained, cdf = [zcd, ycd];

[0110]

[0111] Where: 0, yj, zsy, ysy are interval parameters, zsf = [0, yj], sy = [zsy, ysy];

[0112] It should be noted that: max means to take the maximum value, and min means to take the minimum value; zcd takes the minimum value of yj and max(0, zsj) to avoid useless values ​​when the usage range and the irradiation range do not overlap; if the usage range and the irradiation range do not overlap, then zcd and ycd are equal.

[0113] The decision is made by dynamically shading the building based on the range of direct sunlight; the details are as follows:

[0114] Based on the direct range interval cdf=[zcd,ycd], the direct range is obtained as ycd-zcd;

[0115] When ycd-zcd>0, it indicates that there is direct sunlight within the building's usable area, and shading is required.

[0116] When ycd-zcd=0, it indicates that there is no direct sunlight within the building's usable area. The illuminance of the usable space is obtained, and a comprehensive judgment is made based on the illuminance of the usable space.

[0117] According to the "Standard for Lighting Design of Buildings", the standard illuminance range of the building is obtained and denoted as bzd;

[0118] It should be noted that the "Standard for Lighting Design of Buildings" is an important document that regulates the design of building lighting, covering the indoor lighting requirements for newly built, expanded, renovated and decorated civil and industrial buildings.

[0119] The illuminance of the space is measured at n points within a range using a lux meter to obtain the measured illuminance czd(1), czd(2), ..., czd(n); and the measured illuminance czd(1), czd(2), ..., czd(n) is processed using Scikit-learn.

[0120] It should be noted that machine learning is used to process the measured illuminance, thereby reducing measurement errors caused by measuring instruments and measurement behavior.

[0121] Scikit-learn is an open-source machine learning library based on Python, focusing on the implementation and optimization of traditional machine learning algorithms. It provides a complete workflow from data preprocessing and feature engineering to model training and evaluation, and is one of the standard tools for both academic research and industrial application.

[0122] Compare the measured illuminance with the standard illuminance range.

[0123] If the measured illuminance is higher than the standard illuminance range, then shading should be applied.

[0124] Sunshade operations are performed by selecting sunshades of different lengths; details are as follows:

[0125] The initial length of the sunshade curtain, csc, is calculated based on the angle of sunlight zj and the range of use sy.

[0126] csc = ck - zsy × tan(zj);

[0127] Where: ck is the window length, and zsy is the interval parameter of the range sy used;

[0128] It should be noted that: after using a sunshade with a length of csc to block the sun, there is no area in the space where the sun shines directly.

[0129] After using a sunshade curtain of length csc for shading, the illuminance inside the building is measured. If the illuminance is lower than the maximum value of the standard illuminance range, a sunshade curtain of length csc is selected for shading. If the illuminance is higher than the standard illuminance range, the initial sunshade curtain length csc is increased through machine learning. The illuminance measurement of the used space is repeated until the illuminance is lower than the maximum value of the standard illuminance range.

[0130] It should be noted that machine learning is a branch of artificial intelligence (AI) that enables computer systems to automatically learn and improve their performance using data and algorithms.

[0131] Energy assessment module: Based on the operating information of electrical appliances in the building, it acquires the energy consumption of the appliances; it measures the energy consumption of the appliances under shading operation, and makes an energy assessment of the shading operation based on the energy consumption of the appliances.

[0132] Based on the operating information of electrical appliances in the building, the types of electrical appliances and their energy consumption in the building under shading are obtained, and the energy consumption of the building under shading is calculated; the types of electrical appliances and their energy consumption in the building without shading are also obtained, and the energy consumption of the building without shading is calculated; by comparing the energy consumption of the building under shading with that of the building without shading, the energy change of shading operation is determined; and shading operation is selected based on the energy change.

[0133] Obtain the types of electrical appliances operating inside the building without sunshade (wzl); and statistically analyze the energy consumption of each type of electrical appliance, as detailed below:

[0134] Please see Figure 4 Obtain the energy consumption nxh of electrical appliances operating without shading over a continuous period of time. Divide the time into t time nodes. Based on the time nodes and the energy consumption without shading, construct the time curve xsq of energy consumption without shading. Analyze the time curve of energy consumption without shading and calculate the rate of change before and after different time nodes. Denote the rate of change before the time node without shading as qbh and the rate of change after the time node without shading as hbh.

[0135]

[0136] Where: Δt represents the small change in time; qbh(i) represents the rate of change of the i-th node before the time node under the condition of no shading; hbh(i) represents the rate of change of the i-th node after the time node under the condition of no shading; and nxh(i) represents the energy consumption of the i-th node under the condition of no shading.

[0137] When |qbh(i)|>hbh(i)=0, this time node is extracted to obtain the time segmentation node fg for fluctuation consumption and stable consumption under unshaded conditions;

[0138] Based on the time segmentation node fg of fluctuation consumption and stable consumption under unshaded conditions, the average change of the first fg time nodes is calculated to obtain the average fluctuation value wbj under unshaded conditions.

[0139]

[0140] Based on the time curve of the segment node fg under no shading and the energy consumption under no shading xsq, the total amount of fluctuating energy consumption under no shading is calculated to obtain the fluctuating energy consumption bdx under no shading.

[0141]

[0142] Where: xsq(t) represents the time curve of energy consumption as a function of t; d(t) indicates that t is the integral variable;

[0143] Based on the mean fluctuation value wbj under unshaded conditions, construct the unshaded fluctuation function y1;

[0144] y1 = wbj × x1 + b1;

[0145] Where: y1, x1, b1 are construction parameters; y1 represents instantaneous power, and x1 represents time;

[0146] b1 is obtained by using the segment node fg under unshaded conditions and the fluctuating energy consumption bdx under unshaded conditions:

[0147]

[0148] It should be noted that the energy consumed by the function constructed using the fluctuation mean wbj at time node fg should be consistent with the fluctuation energy consumption bdx under no shading. b1 should be calculated based on their consistency.

[0149] The stable energy consumption per unit time under unshaded conditions is obtained and denoted as wdx;

[0150] Based on the unshaded fluctuation function y1 and the stable energy consumption wdx under unshaded conditions, the electrical energy consumption zxh under unshaded conditions is obtained;

[0151]

[0152] Where: bdx represents the fluctuating energy consumption under no shading; x1 represents the time of electrical energy consumption.

[0153] Based on the types of electrical appliances operating without shading (wzl), the energy consumption of these appliances under unshaded conditions (zxh(1), zxh(2), ..., zxh(wzl)) is obtained. Then, the building energy consumption (wjx) under unshaded conditions is calculated based on these energy consumption values.

[0154] wjx=zxh(1)+zxh(2)+…+zxh(wzl).

[0155] Obtain the types of electrical appliances operating within the building under shading conditions; and statistically analyze the energy consumption of each type of appliance, as detailed below:

[0156] Obtain the energy consumption znxh of electrical appliances operating under shading over a continuous period of time. Divide the time into t time nodes. Based on the time nodes and the energy consumption under shading, construct the time curve zxsq of energy consumption under shading. Analyze the time curve of energy consumption under shading and calculate the rate of change before and after different time nodes. Denote the rate of change before the time node under shading as zqbh and the rate of change after the time node under shading as zhbh.

[0157]

[0158] Where: Δt represents the small change in time; zqbh(i) represents the rate of change of the i-th node before the time node under shading; zhbh(i) represents the rate of change of the i-th node after the time node under shading; and znxh(i) represents the energy consumption of the i-th node under shading.

[0159] When |zqbh(i)|>zhbh(i)=0, the time node is extracted to obtain the time segmentation node zfg for fluctuation consumption and stable consumption under shading;

[0160] Based on the time segmentation node zfg of fluctuation consumption and stable consumption under shading, the average change of the first zfg time nodes is calculated to obtain the average fluctuation value zwbj under shading.

[0161]

[0162] Based on the time curve of energy consumption between the segment node zfg under shading and zxsq, the total energy consumption under shading is calculated to obtain the energy consumption under shading zbdx.

[0163]

[0164] Where: zxsq(t) represents the time curve of energy consumption under shading as a function of t; d(t) indicates that t is the integral variable;

[0165] Based on the mean fluctuation value zwbj under shading, construct the shading fluctuation function y2;

[0166] y2 = zwbj × x2 + b2;

[0167] Where: y2, x2, and b2 are the construction parameters; y2 represents instantaneous power, and x2 represents time;

[0168] b2 is obtained by using the segment node zfg under shading and the fluctuating energy consumption zbdx under shading:

[0169]

[0170] It should be noted that the energy consumed by the function constructed using the fluctuation mean zwbj at the zfg time node should be consistent with the fluctuation energy consumption zbdx under shading, and b2 should be calculated based on their consistency.

[0171] The stable energy consumption per unit time under shading is obtained and denoted as zwdx;

[0172] Based on the shading fluctuation function y2 and the stable energy consumption under shading zwdx, the electrical energy consumption under shading zzxh is obtained;

[0173]

[0174] Where: zbdx represents the fluctuating energy consumption under no shading; x2 represents the energy consumption time of electrical appliances;

[0175] Based on the types of electrical appliances operating under the shading system (zzl), the energy consumption of these appliances (zzxh(1), zzxh(2), ..., zzxh(zzl)) is obtained. Then, the building energy consumption (zjx) under the shading system is calculated based on these energy consumption values.

[0176] zjx=zzxh(1)+zzxh(2)+……+zzxh(zzl).

[0177] Energy optimization module: Based on the energy assessment results, adjust the use of electrical appliances and optimize energy consumption in combination with the energy consumption of electrical appliances;

[0178] Based on the energy judgment results, obtain the building energy consumption wjx under no shading and the building energy consumption zjx under shading. When the shading operation is a shading request in the non-dynamic shading module, compare the building energy consumption wjx under no shading and the building energy consumption zjx under shading, and perform shading control according to the building status with low energy consumption.

[0179] Introducing new energy sources into shading control involves adding solar energy receiving devices to the sun-facing surface of the electric sunshade curtain, which then prioritize power supply for the operation of the electric sunshade curtain.

[0180] It should be noted that the shading control of motorized sunshades allows them to face the sun directly, effectively capturing solar energy and reducing the building's energy consumption.

[0181] In this application, if a corresponding calculation formula appears, the above calculation formula is a dimensionless calculation. The weighting coefficient, proportional coefficient and other coefficients in the formula are set to quantify each parameter to obtain a result value. The size of the weighting coefficient and proportional coefficient is only required to not affect the proportional relationship between the parameter and the result value.

[0182] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A machine learning based building dynamic shading and energy optimization collaborative control system, characterized in that, include: Data acquisition module: measures the angle of sunlight at different times to obtain illumination information; Building information is formed by acquiring spatial information of buildings and operational information of electrical appliances within them. Dynamic shading module: Based on building information, obtain the building's spatial information, combine it with illumination information, calculate the building's illumination range, obtain the building's usable space, and measure the illuminance of the usable space; based on the usable space, illumination range, and illuminance, determine and perform dynamic shading operation on the building. Energy assessment module: Acquires operating information of electrical appliances in the building and obtains the energy consumption of the appliances; measures the energy consumption of appliances under shading operation and makes energy assessment of the shading operation based on the energy consumption of appliances under different operations. The energy level of the shading operation is assessed as follows: Based on the operating information of electrical appliances in the building, the types of electrical appliances and their energy consumption in the building under shading are obtained, and the energy consumption of the building under shading is calculated; the types of electrical appliances and their energy consumption in the building without shading are also obtained, and the energy consumption of the building without shading is calculated; the energy consumption of the building under shading is compared with that of the building without shading to determine the energy change of shading operation; and the shading operation is selected based on the energy change. The energy consumption of a building without shading is calculated as follows: Obtain the types of electrical appliances operating in the building without shading (wzl); statistically analyze the energy consumption of each type of electrical appliance to obtain the energy consumption nxh of the electrical appliances operating without shading over a continuous period of time. Divide the time into t time nodes, and construct a time curve xsq for energy consumption without shading based on the time nodes and the energy consumption without shading; analyze the time curve for energy consumption without shading and calculate the rate of change before and after different time nodes; denote the rate of change before the time node without shading as qbh, and the rate of change after the time node without shading as hbh. ； ； Where: Δt represents the small change in time; qbh(i) represents the rate of change of the i-th node before the time node under the condition of no shading; hbh(i) represents the rate of change of the i-th node after the time node under the condition of no shading; and nxh(i) represents the energy consumption of the i-th node under the condition of no shading. When |qbh(i)|>hbh(i)=0, the time node is extracted to obtain the time segmentation node fg of fluctuation consumption and stable consumption under unshaded conditions; Based on the time segmentation node fg of fluctuation consumption and stable consumption under unshaded conditions, the average change of the first fg time nodes is calculated to obtain the average fluctuation value wbj under unshaded conditions. ； Based on the mean fluctuation value wbj under unshaded conditions, an unshaded fluctuation function y1 is constructed, and the energy consumption is obtained through the unshaded fluctuation function; Energy optimization module: Based on the energy assessment results, the use of electrical appliances is adjusted, and energy is optimized by combining the energy consumption of electrical appliances.

2. The machine learning-based building dynamic shading and energy optimization collaborative control system according to claim 1, characterized in that, The irradiation range is calculated as follows: Based on the building's spatial information, the window length and interior depth of the building are obtained, with the window length denoted as ck and the interior depth as sn; based on the illumination information, the angle of sunlight is obtained, with the angle of sunlight denoted as zj. Based on the building's window length ck and sunlight angle zj, combined with the building's interior depth sn, the farthest distance of sunlight inside the building is calculated to obtain the illumination distance yj. ； Based on the irradiation distance, the irradiation range interval zsf is obtained; zsf = [0, yj]; The usable space of the building is obtained, and the direct sunlight range is calculated based on the usable space and the range of illumination.

3. The machine learning-based building dynamic shading and energy optimization collaborative control system according to claim 2, characterized in that, The calculation of the area directly exposed to sunlight is as follows: Using the building's windows as a reference, the distance between the building's usable space and the building's windows is obtained. Based on the distance between the building's usable space and the building's windows, the building's usable space is reduced in dimensionality. The usable space is represented by the distance, resulting in the usable range interval sy, where sy = [zsy, ysy]. Based on the usage range interval sy and the irradiation range interval zsf, the direct radiation range interval cdf is obtained, cdf = [zcd, ycd]; ； Where: 0, yj, zsy, ysy are interval parameters, zsf = [0, yj], sy = [zsy, ysy]; The decision is made by dynamically shading the building based on the range of direct sunlight.

4. The machine learning-based building dynamic shading and energy optimization collaborative control system according to claim 3, characterized in that, The decision is made by dynamically shading the building based on the range of direct sunlight, as detailed below: Based on the direct range interval cdf=[zcd,ycd], the direct range is obtained as ycd-zcd; When ycd-zcd>0, it indicates that there is direct sunlight within the building's usable area, and shading is required. When ycd-zcd=0, it indicates that there is no direct sunlight within the building's usable area. The illuminance of the usable space is obtained, and a comprehensive judgment is made based on the illuminance of the usable space. The standard illuminance range of the building is obtained and denoted as bzd; The illuminance of the space is measured at n points within a range using a lux meter, resulting in measured illuminance values ​​czd(1), czd(2), ..., czd(n). The measured illuminance values ​​are then compared with the standard illuminance range. If the measured illuminance is higher than the standard illuminance range, then shading should be applied. The sunshade operation is carried out by selecting sunshade curtains of different lengths.

5. The machine learning-based building dynamic shading and energy optimization collaborative control system according to claim 4, characterized in that, Select sunshade curtains of different lengths for sun shading operations, as detailed below: The initial length of the sunshade curtain, csc, is calculated based on the angle of sunlight zj and the range of use sy. ； Where: ck is the window length, and zsy is the interval parameter of the range sy used; After using a sunshade curtain of length csc for shading, the illuminance inside the building is measured. If the illuminance is lower than the maximum value of the standard illuminance range, a sunshade curtain of length csc is selected for shading. If the illuminance is higher than the standard illuminance range, the initial length csc of the sunshade curtain is increased. The illuminance measurement of the used space is repeated until the illuminance is lower than the maximum value of the standard illuminance range.

6. The machine learning-based building dynamic shading and energy optimization collaborative control system according to claim 1, characterized in that, Energy consumption is calculated using the unshaded fluctuation function, as follows: Based on the time curve of the segment node fg under no shading and the energy consumption under no shading xsq, the total amount of fluctuating energy consumption under no shading is calculated to obtain the fluctuating energy consumption bdx under no shading. ； Where: xsq(t) represents the time curve of energy consumption as a function of t; d(t) indicates that t is the integral variable; Based on the mean fluctuation value wbj under unshaded conditions, construct the unshaded fluctuation function y1; ； Where: y1, x1, and b1 are the construction parameters; y1 represents the instantaneous power; b1 is obtained by using the segment node fg under unshaded conditions and the fluctuating energy consumption bdx under unshaded conditions: The stable energy consumption per unit time under unshaded conditions is obtained and denoted as wdx; Based on the unshaded fluctuation function y1 and the stable energy consumption wdx under unshaded conditions, the electrical energy consumption zxh under unshaded conditions is obtained; ； Where: bdx represents the fluctuating energy consumption under no shading; x1 represents the time of energy consumption by electrical appliances; Based on the types of electrical appliances operating without shading (wzl), the energy consumption of electrical appliances under unshaded conditions (zxh(1), zxh(2), ..., zxh(wzl)) is obtained. The building energy consumption (wjx) under unshaded conditions is calculated based on the energy consumption of electrical appliances under unshaded conditions (zxh(1) to zxh(wzl)). 。 7. The machine learning-based building dynamic shading and energy optimization collaborative control system according to claim 1, characterized in that, The energy consumption of a building under shading is calculated as follows: Obtain the types of electrical appliances operating within the building under shading conditions; and statistically analyze the energy consumption of each type of appliance, as detailed below: Obtain the energy consumption znxh of electrical appliances operating under shading over a continuous period of time. Divide the time into t time nodes. Based on the time nodes and the energy consumption under shading, construct the time curve zxsq of energy consumption under shading. Analyze the time curve of energy consumption under shading and calculate the rate of change before and after different time nodes. Denote the rate of change before the time node under shading as zqbh and the rate of change after the time node under shading as zhbh. ； ； Where: Δt represents the small change in time; zqbh(i) represents the rate of change of the i-th node before the time node under shading, zhbh(i) represents the rate of change of the i-th node after the time node under shading, and znxh(i) represents the energy consumption of the i-th node under shading. When |zqbh(i)|>zhbh(i)=0, the time node is extracted to obtain the time segmentation node zfg for fluctuation consumption and stable consumption under shading; Based on the time segmentation node zfg of fluctuation consumption and stable consumption under shading, the average change of the first zfg time nodes is calculated to obtain the average fluctuation value zwbj under shading. ； Based on the average fluctuation value zwbj under shading, a shading fluctuation function y2 is constructed, and the energy consumption is obtained through the shading fluctuation function.

8. The machine learning-based building dynamic shading and energy optimization collaborative control system according to claim 7, characterized in that, Energy consumption is calculated using the shading fluctuation function, as follows: Based on the time curve of energy consumption between the segment node zfg under shading and zxsq, the total energy consumption under shading is calculated to obtain the energy consumption under shading zbdx. ； Where: zxsq(t) represents the time curve of energy consumption under shading as a function of t; d(t) indicates that t is the integral variable; Based on the mean fluctuation value zwbj under shading, construct the shading fluctuation function y2; ； Where: y2, x2, and b2 are the construction parameters; y2 represents instantaneous power, and x2 represents time; b2 is obtained by using the segment node zfg under shading and the fluctuating energy consumption zbdx under shading: The stable energy consumption per unit time under shading is obtained and denoted as zwdx; Based on the shading fluctuation function y2 and the stable energy consumption under shading zwdx, the electrical energy consumption under shading zzxh is obtained; Where: zbdx represents the fluctuating energy consumption under no shading; x2 represents the energy consumption time of electrical appliances; Based on the types of electrical appliances operating under the shading system (zzl), the energy consumption of electrical appliances under the shading system (zzxh(1), zzxh(2), ..., zzxh(zzl)) is obtained. The building energy consumption under the shading system (zjx) is calculated based on the energy consumption of electrical appliances under the shading system (zzxh(1) to zzxh(zzl)). 。

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