Public place illumination intelligent regulation and control method capable of distinguishing multiple environments

Abstract

The invention relates to the technical field of illumination control, in particular to a public place illumination intelligent regulation and control method capable of distinguishing multiple environments. The method comprises the following steps: firstly, classifying public places, analyzing activity and personnel behavior characteristics of the public places, determining an illumination function and influence variables, and defining a target model; secondly, establishing an analytic hierarchy structure, and constructing a judgment matrix to calculate a weight vector and check consistency by taking an illumination function as a target layer, relevant factors as a criterion layer and public places as a scheme layer, and distributing regulation and control weights; and finally, determining lighting functions and a target model thereof according to the priority, setting an initial value, adjusting variables, solving a current value, judging whether the current value meets a threshold value or not, and regulating and controlling in sequence until all lighting functions are met. According to the method, the requirements of different places can be accurately met, the regulation and control weight is scientifically determined, multi-target regulation and control are efficiently realized, and a flexible regulation and control strategy is also provided.

Description

Technical Field

[0001] The present invention relates to the technical field of lighting control, and in particular to a method for intelligently controlling lighting in public places with multi-environment differentiation. Background Art

[0002] With the development of society and the continuous improvement of people's requirements for quality of life, lighting design in public places has become increasingly important. Public places cover many types of spaces, such as shopping malls, office buildings, schools, hospitals, hotels, etc., and the lighting requirements of these places are complex and diverse.

[0003] In traditional lighting systems, a single lighting setting is often used, which cannot fully take into account the special needs of different areas and different activity scenes. For example, in a shopping mall, the product display area may require bright light with a specific color temperature to highlight the characteristics of the product, while the channel area pays more attention to the uniformity and guidance of the light, and the rest area needs to create a comfortable and soft atmosphere lighting. However, traditional lighting systems are usually unable to make intelligent adjustments based on these different needs, resulting in either the overall lighting being too bright, causing energy waste, or insufficient lighting in certain areas affecting the user experience.

[0004] In addition, energy consumption is also an important problem faced by traditional lighting systems. Since lighting parameters cannot be adjusted intelligently according to actual needs, a large amount of energy is wasted on unnecessary lighting, which not only increases operating costs but also does not conform to the concept of sustainable development. Therefore, it is of great practical significance to develop a method that can distinguish and intelligently optimize lighting according to different environments. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention proposes a multi-environment differentiated public place lighting intelligent control method.

[0006] The technical solution of the present invention is as follows:

[0007] A method for intelligently controlling lighting in public places with multiple environments, comprising:

[0008] By classifying public places and analyzing their activities and personnel behavior characteristics, the lighting functions and variables affecting the lighting functions are determined, and the target model related to the lighting function variables is defined;

[0009] Taking lighting function as the target layer, variables affecting lighting function as the criteria layer factors, and different types of public places as the scheme layer, a hierarchical analysis structure is established; by constructing a judgment matrix, calculating weight vectors and consistency tests, the weights of each lighting function and its internal factors are allocated;

[0010] First, the target model corresponding to the lighting function with the highest priority in public places is regulated. The initial variables of the target model are all rated values. The variable size of the target model is adjusted, and the current value of the target model is solved until the current value meets the set threshold; the next lighting function is regulated in order of lighting function priority from high to low until all lighting function controls are met.

[0011] The determination of lighting function energy saving function, illumination uniformity and user comfort;

[0012] The energy-saving function influencing variables include energy consumption, the number of lamps, the power of the lamps and the working time of the lamps in the statistical time period;

[0013] The variables affecting illumination uniformity include illumination uniformity index, the number of measurement sub-areas divided into lighting areas, illumination value at the center of measurement sub-areas, average illumination and standard deviation of illumination value;

[0014] The variables influencing user comfort include user satisfaction index, the number of users participating in the survey, the user's evaluation score on the evaluation index, and the number of evaluation indicators.

[0015] The energy-saving function target model calculation formula is:

[0016]

[0017] E is the energy consumption of the energy-saving function target model, T is the time period for determining statistics, n is the number of lighting systems of lamps, P i is the power of each lamp i, t i is the known working time of each lamp i;

[0018] The calculation formula of the illumination uniformity target model is:

[0019]

[0020] in,

[0021] Among them, U is the illumination uniformity index, is the average illumination; σ E is the standard deviation of the illuminance value; m is the number of measurement sub-areas divided into the lighting area; E j is the illumination value at the center of the j-th sub-region, j=1, 2, ..., m;

[0022] The calculation formula of the user comfort target model is:

[0023]

[0024] Among them, S is the user satisfaction index, k is the number of users surveyed, and xij is the evaluation score of each user for l evaluation indicators.

[0025] The hierarchical analysis structure takes the lighting function of the public place lighting system as the target layer, including energy-saving function, illumination uniformity and user comfort; for the energy-saving function, energy consumption, number of lamps, lamp power and lamp working time are taken as criterion layer factors; for illumination uniformity, illumination uniformity index, number of measurement sub-areas, illumination value of the center of the sub-area, average illumination and illumination standard deviation are taken as criterion layer factors; for user comfort, user satisfaction index, number of users participating in the survey, user evaluation scores of evaluation indicators and number of evaluation indicators are taken as criterion layer factors; the conditions of different types of public places are taken as the solution layer.

[0026] The method for constructing a judgment matrix comprises:

[0027] Assume the judgment matrix is ​​A=(a ij ), where a ij Indicates the relative importance of the i-th factor relative to the j-th factor; for the judgment matrix between lighting functions, the energy-saving function is F1, the illumination uniformity is F2, and the user comfort is F3, then a 12 Indicates the importance of energy saving function relative to illumination uniformity, and so on;

[0028] For the judgment matrix of internal factors of each lighting function, for the energy-saving function, let the energy consumption be E1, the number of lamps be E2, the lamp power be E3, and the lamp working time be E4, then a 12 Indicates the importance of energy consumption relative to the number of lamps; the values ​​of the judgment matrix elements are based on expert scores, using a 1-9 scale, with 1 representing equal importance and 9 representing extremely important.

[0029] The method for calculating the weight vector comprises:

[0030] For the weight calculation between lighting functions:

[0031] First, calculate the product of each row element of the judgment matrix A n is the matrix order;

[0032] Then calculate M i The nth root of

[0033] Last pair After normalization, we get the weight vector ω=(ω1,ω2,...,ω n ),in

[0034]

[0035] The weight calculation of the internal factors of each lighting function is similar. For the internal factors of the energy-saving function, the weight vector of factors such as energy consumption and the number of lamps relative to the energy-saving function is calculated according to the above method;

[0036] The consistency checking method comprises:

[0037] Calculate the maximum eigenvalue λ of the judgment matrix A max , calculated by the formula Where (Aω) i represents the i-th element of the vector Aω;

[0038] Calculate consistency index For the lighting function judgment matrix n = 3, then

[0039]

[0040] Find the corresponding average random consistency index RI (for n=3, RI=0.58);

[0041] Calculating the consistency ratio If CR is less than 0.1, the judgment matrix is ​​reasonable and the weight vector is valid; if CR is greater than 0.1, the judgment matrix needs to be reconstructed;

[0042] The weight allocation method comprises:

[0043] Assume that the lighting function weight vector is W = (ω F1 ,ω F2 ,ω F3 ), the energy-saving function target model is E, the illumination uniformity target model is U, and the user comfort target model is S;

[0044] Then the energy-saving function target model control weight ω E =ω F1 , illumination uniformity target model control weight ω U =ω F2 , user comfort target model control weight ω S =ω F3 .

[0045] The initial variables of the target model are all rated values, including the energy consumption, number of lamps, lamp power and lamp working time of the energy-saving function target model are set to rated values; the illumination uniformity index, number of measurement sub-areas, illumination value of the center of the sub-area, average illumination and illumination standard deviation of the illumination uniformity target model are set to rated values; the user satisfaction index, number of users participating in the survey, user evaluation scores of the evaluation indicators and the number of evaluation indicators of the user comfort target model are set to initial values.

[0046] The variable size of the target model is adjusted, and the current value of the target model is solved. For the energy-saving function target model, the variable of the lamp working time is adjusted and the current value is calculated; for the illumination uniformity target model, the variable of the number of measurement sub-areas divided by the lighting area or the illumination value at the center of the sub-area is adjusted and the current value is calculated; for the user comfort target model, the variable of the user's evaluation score for the evaluation index is adjusted and the current value is calculated.

[0047] Whether the current value meets the threshold is judged. For the energy-saving function target model, the calculated current value of energy consumption is compared with the set energy consumption threshold; for the illumination uniformity target model, the calculated current value of illumination uniformity index is compared with the set illumination uniformity threshold; for the user comfort target model, the calculated current value of user satisfaction index is compared with the set user satisfaction threshold

[0048] The beneficial effect of the present invention is that by carefully classifying public places, such as office places, commercial places, cultural and educational places, medical and health places, transportation hubs, etc., and analyzing the activities and behavioral characteristics of people in various places, the lighting functions required for different places can be accurately determined. For example, office places require uniform and sufficient lighting to avoid eye fatigue, and commercial places need to highlight the display effect of goods. This targeted analysis ensures that the lighting system can better adapt to various environments and meet the specific needs of different places.

[0049] The analytical framework is constructed using the hierarchical analysis method. With lighting functions as the target layer, relevant influencing factors as the criterion layer, and different public places as the solution layer, the relative importance of each factor is determined by constructing a judgment matrix, the weight vector is calculated and consistency is tested, and finally the control weight is allocated according to the weight. This method scientifically and rationally determines the weights of each lighting function and its influencing factors, avoids subjective arbitrariness, makes the allocation of control weights more objective and accurate, and helps to achieve the optimal control of the lighting system.

[0050] Lighting functions are regulated in order of priority. First, the lighting function with the highest priority and its target model are determined, and the initial value of the variable is set. Then, the variable is dynamically adjusted according to the actual situation and the current value is solved to determine whether the threshold is met. If it is met, the next lighting function regulation is entered according to the priority until all lighting functions are met. This method can efficiently and accurately realize the multi-objective regulation of the lighting system, while taking into account multiple goals such as energy saving function, illumination uniformity and user comfort, and meet the diverse lighting needs of public places.

[0051] During the control process, for different lighting function target models, such as the energy-saving function target model, the lamp working time variable can be adjusted according to the actual situation; the illumination uniformity target model can adjust the number of sub-areas or the illumination value variable at the center of the sub-area; the user comfort target model can adjust the user's evaluation score variable for the evaluation index. This flexible control strategy can better adapt to the ever-changing environment and personnel needs of public places. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 Schematic diagram of the overall process of the intelligent control method for public place lighting with multiple environments

[0053] Figure 2 Detailed flow chart of the S100 method for intelligent control of public lighting in multiple environments

[0054] Figure 3 Detailed flow chart of the steps of the intelligent control method S200 for public place lighting with multiple environment distinctions

[0055] Figure 4 Detailed flow chart of the steps of the intelligent control method S300 for public place lighting with multiple environments DETAILED DESCRIPTION

[0057] 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.

[0058] See also Figure 1 , which shows a method for intelligently controlling lighting in public places with multiple environments provided by an embodiment of the present invention, including:

[0059] S100: Determine lighting functions and variables that affect lighting functions by classifying public places and analyzing their activities and personnel behavior characteristics, and define a target model related to lighting function variables.

[0060] S200: Taking lighting function as the target layer, variables affecting lighting function as the criterion layer factors, and different types of public places as the scheme layer, a hierarchical analysis structure is established; by constructing a judgment matrix, calculating weight vectors and consistency tests, the weights of each lighting function and its internal factors are allocated.

[0061] S300: First, the target model corresponding to the lighting function with the highest priority in the public place is regulated. The initial variables of the target model are all rated values. The variable size of the target model is adjusted, and the current value of the target model is solved until the current value meets the set threshold. The next lighting function is regulated in descending order of lighting function priority until all lighting function controls are met.

[0062] S100 involves basic analysis of public place lighting systems. First, public places are classified, and the activities and behavioral characteristics of people in different places are analyzed to determine the lighting functions, including energy saving, illumination uniformity and user comfort. At the same time, the variables that affect these functions are determined, and finally the target model related to the lighting function variables is defined. Through the detailed classification and analysis of public places, the actual needs of different places can be fully considered, and accurate basic data and direction can be provided for subsequent lighting control, ensuring that the lighting system can better adapt to various environments.

[0063] Please refer to Figure 2 , which shows a flowchart of an exemplary multi-environment differentiated public place lighting intelligent control method S100 of the present application, and its contents include:

[0064] S110: Determine the lighting function of the public place lighting system.

[0065] First, public places can be classified into office places, commercial places, cultural and educational places, medical and health places, and transportation hubs.

[0066] For different types of places, analyze the main activities and behavioral characteristics of the places. For example, office places are where office workers carry out activities such as document processing and conference exchanges. They need to work attentively for a long time in a fixed position, and the lighting should be uniform and sufficient to avoid eye fatigue. Commercial places are mainly used for product display and sales, and customers browse and select randomly. The lighting must highlight the products and ensure safe and comfortable walking in the store. Cultural and educational places cover teaching, reading, display and other activities. Different areas have different requirements for light, which must meet the needs of learning, viewing and cultural relics protection. Medical and health places include diagnosis, nursing, and rehabilitation activities. Different areas vary according to their functions. The lighting must meet the requirements of accurate observation, surgical safety and patient comfort. Transportation hubs are places where people and vehicles gather and flow, and they carry out activities such as waiting for buses and flights. The lighting should be bright, directional, energy-saving and reliable.

[0067] Determine the required lighting functions based on activity and behavior characteristics. Lighting functions include energy saving, illumination uniformity, and user comfort.

[0068] S120: Determine variables that affect lighting functions.

[0069] The variables affecting the energy-saving function include energy consumption, the number of lamps, the power of the lamps and the working time of the lamps in the statistical time period.

[0070] The variables affecting illumination uniformity include illumination uniformity index, the number of measurement sub-areas divided into lighting areas, illumination value at the center of measurement sub-areas, average illumination and standard deviation of illumination value.

[0071] The variables influencing user comfort include user satisfaction index, the number of users participating in the survey, the user's evaluation score on the evaluation index, and the number of evaluation indicators.

[0072] S130: Define a target model including variables related to lighting functions.

[0073] The calculation formula of the energy-saving function target model is:

[0074]

[0075] E is the energy consumption of the energy-saving function target model, T is the time period for determining statistics, n is the number of lighting systems of lamps, P i is the power of each lamp i, t i is the known working time of each lamp i.

[0076] The calculation formula of the illumination uniformity target model is:

[0077]

[0078] in,

[0079] Among them, U is the illumination uniformity index, is the average illumination; σ E is the standard deviation of the illuminance value; m is the number of measurement sub-areas divided into the lighting area; E j is the illumination value at the center of the j-th sub-region, j=1, 2, ..., m.

[0080] The calculation formula of the user comfort target model is:

[0081]

[0082] Among them, S is the user satisfaction index, k is the number of users surveyed, and x ij is the evaluation score of each user for l evaluation indicators.

[0083] S200 builds an analysis framework based on S100. A hierarchical analysis structure is established with lighting functions as the target layer, related influencing factors as the criterion layer, and different public places as the solution layer. Then a judgment matrix is ​​constructed to determine the relative importance of each factor, the weight vector is calculated and consistency is tested, and finally the control weight is allocated according to the weight. The hierarchical analysis method is used to scientifically and reasonably determine the weights of each lighting function and its influencing factors, making the allocation of control weights more objective and accurate, which helps to achieve the optimal control of the lighting system.

[0084] Please refer to Figure 3 , which shows a flowchart of an exemplary multi-environment differentiated public place lighting intelligent control method S200 of the present application, and its contents include:

[0085] S210: Establish a hierarchical analysis structure.

[0086] The lighting functions of public place lighting systems are taken as the target layer, including energy-saving function, illumination uniformity and user comfort.

[0087] For energy-saving function, energy consumption, number of lamps, lamp power and lamp working time are used as criterion layer factors; for illumination uniformity, illumination uniformity index, number of measurement sub-areas, illumination value of sub-area center, average illumination and illumination standard deviation are used as criterion layer factors; for user comfort, user satisfaction index, number of users participating in the survey, user evaluation scores of evaluation indicators and number of evaluation indicators are used as criterion layer factors.

[0088] The specific conditions of different types of public places (office places, commercial places, etc.) are taken as the solution layer.

[0089] S220: Construct a judgment matrix.

[0090] Assume the judgment matrix is ​​A=(a ij ), where a ij Indicates the relative importance of the i-th factor relative to the j-th factor. For the judgment matrix between lighting functions, the energy-saving function is F1, the illumination uniformity is F2, and the user comfort is F3, then a 12 Indicates the importance of energy saving function relative to illumination uniformity, and so on.

[0091] For the judgment matrix of internal factors of each lighting function, for the energy-saving function, let the energy consumption be E1, the number of lamps be E2, the lamp power be E3, and the lamp working time be E4, then a 12 Indicates the importance of energy consumption relative to the number of lamps. The values ​​of the elements of the judgment matrix are based on the expert scores, using a 1-9 scale, with 1 indicating equal importance and 9 indicating extremely important.

[0092] S230: Calculate a weight vector.

[0093] For the weight calculation between lighting functions:

[0094] First, calculate the product of each row element of the judgment matrix A n is the matrix order.

[0095] Then calculate M i The nth root of

[0096] Last pair After normalization, we get the weight vector ω=(ω1,ω2,...,ω n ),in

[0097]

[0098] The weight calculation of the internal factors of each lighting function is similar. For the internal factors of the energy-saving function, the weight vector of factors such as energy consumption and the number of lamps relative to the energy-saving function is calculated according to the above method.

[0099] S240: Perform consistency check.

[0100] Calculate the maximum eigenvalue λ of the judgment matrix A max , calculated by the formula Where (Aω) i Represents the i-th element of the vector Aω.

[0101] Calculate consistency index For the lighting function judgment matrix n = 3, then

[0102]

[0103] Find the corresponding average random consistency index RI (for n=3, RI=0.58).

[0104] Calculating the consistency ratio If CR is less than 0.1, the judgment matrix is ​​reasonable and the weight vector is valid; if CR is greater than 0.1, the judgment matrix needs to be reconstructed.

[0105] S250: adjusting the weight according to the weight distribution.

[0106] Assume that the lighting function weight vector is W = (ω F1 ,ω F2 ,ω F3 ), the energy-saving function target model is E, the illumination uniformity target model is U, and the user comfort target model is S.

[0107] Then the energy-saving function target model control weight ω E =ω F1, illumination uniformity target model control weight ω U =ω F2 , user comfort target model control weight ω S =ω F3 .

[0108] S300 controls lighting functions based on the results of S200. Determine the lighting function with the highest priority and its target model, set the initial value of the variable, adjust the variable according to the actual situation and solve the current value, determine whether the threshold is met, and if so, enter the next lighting function control according to the priority until all lighting functions are met. Control the lighting functions in order of priority and dynamically adjust the variables according to the actual situation, which can efficiently and accurately realize the multi-target control of the lighting system and meet the diverse lighting needs of public places.

[0109] Please refer to Figure 4 , which shows a flowchart of an exemplary multi-environment differentiated public place lighting intelligent control method S300 of the present application, and its contents include:

[0110] S310: Determine the lighting function with the highest priority and its target model.

[0111] According to the lighting function priority ranking results obtained in S200 and its sub-steps, the lighting function with the highest priority in the current public place is determined.

[0112] Find the target model corresponding to the lighting function, such as the energy-saving function corresponds to the energy-saving function target model, the illumination uniformity corresponds to the illumination uniformity target model, and the user comfort corresponds to the user comfort target model.

[0113] S320: Set the initial value of the target model variable to the rated value.

[0114] For the energy-saving function target model, the energy consumption, the number of lamps, the lamp power and the lamp working time are set to the rated values. For example, the lamp power is the power value marked on the lamp product manual, and the number of lamps is the number of designed installations, etc.

[0115] For the illumination uniformity target model, the variables such as illumination uniformity index, number of measurement sub-areas, illumination value at the center of the sub-area, average illumination and illumination standard deviation are set to rated values. The number of measurement sub-areas can be determined according to the rules for dividing the lighting areas of the venue, and the initial values ​​of other variables can be set with reference to the lighting design standards.

[0116] For the user comfort target model, the user satisfaction index, the number of users participating in the survey, the user's evaluation score for the evaluation index, and the number of evaluation indicators are set as initial values. The user satisfaction index can be initially set to an intermediate value (such as 5 points out of 10 points), the number of users participating in the survey can be set to an estimated reasonable value, and the evaluation score and the number of evaluation indicators can be set according to the relevant survey template.

[0117] S330: Adjust the target model variables and solve the current values.

[0118] For energy saving function target model:

[0119] The lamp working time variable is appropriately adjusted according to the actual situation.

[0120] Calculation formula using energy-saving function target model Calculate the current value.

[0121] For the illumination uniformity target model:

[0122] The number of measurement sub-areas divided into the lighting area or the variable of the illumination value at the center of the sub-area is adjusted. Exemplarily, the division method of the measurement sub-areas is adjusted according to the layout of the venue.

[0123] Calculation formula using illumination uniformity target model Calculate the current value.

[0124] For the user comfort target model:

[0125] The user's evaluation score variable for the evaluation indicator is adjusted, and new evaluation scores are collected through user feedback.

[0126] Calculation formula using user comfort target model Calculate the current value.

[0127] S340: Determine whether the current value meets the threshold.

[0128] For the energy-saving function target model, the calculated current value of energy consumption is compared with the set energy consumption threshold. If the current value is less than or equal to the threshold, the requirement is met; if the current value is greater than the threshold, the variable continues to be adjusted.

[0129] For the illumination uniformity target model, compare the calculated illumination uniformity index current value with the set illumination uniformity threshold. If the current value is greater than or equal to the threshold, the requirement is met; if the current value is less than the threshold, continue to adjust the variable.

[0130] For the user comfort target model, compare the calculated current value of the user satisfaction index with the set user satisfaction threshold. If the current value is greater than or equal to the threshold, the requirement is met; if the current value is less than the threshold, continue to adjust the variable.

[0131] S350: Enter the next lighting function control according to the priority order.

[0132] If the current value of the target model of the current lighting function meets the threshold requirement, the next lighting function is regulated in descending order of lighting function priority. Steps S310 to S340 are repeated until all lighting functions are regulated.

[0133] The basic principles of the present application are described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, effects, etc. mentioned in the present application are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. are required by each embodiment of the present application. In addition, the specific details disclosed above are only for the purpose of illustration and ease of understanding, not for limitation, and the above details do not limit the present application to being implemented by adopting the above specific details.

[0134] The block diagrams of the devices, apparatuses, equipment, and systems involved in this application are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagram. As will be appreciated by those skilled in the art, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open words, referring to "including but not limited to", and can be used interchangeably with them. The words "or" and "and" used here refer to the words "and / or" and can be used interchangeably with them, unless the context clearly indicates otherwise. The words "such as" used here refer to the phrase "such as but not limited to", and can be used interchangeably with them.

[0135] It should also be noted that in the apparatus, device and method of the present application, each component or each step can be decomposed and / or recombined. Such decomposition and / or recombination should be regarded as equivalent solutions of the present application.

[0136] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present application. Therefore, the present application is not intended to be limited to the aspects shown herein, but rather to the widest scope consistent with the principles and novel features of the present invention.

[0137] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for intelligently controlling lighting in public places with multiple environments, characterized in that: include: By classifying public places and analyzing their activities and personnel behavior characteristics, the lighting functions and variables affecting the lighting functions are determined, and the target model related to the lighting function variables is defined; Taking lighting function as the target layer, variables affecting lighting function as the criteria layer factors, and different types of public places as the scheme layer, a hierarchical analysis structure is established; by constructing a judgment matrix, calculating weight vectors and consistency tests, the weights of each lighting function and its internal factors are allocated; First, the target model corresponding to the lighting function with the highest priority in public places is regulated. The initial variables of the target model are all rated values. The variable size of the target model is adjusted, and the current value of the target model is solved until the current value meets the set threshold; the next lighting function is regulated in order of lighting function priority from high to low until all lighting function controls are met.

2. According to the method of intelligent control of public place lighting with multiple environments differentiated according to claim 1, it is characterized in that: The determination of lighting function energy saving function, illumination uniformity and user comfort; The energy-saving function influencing variables include energy consumption, the number of lamps, the power of the lamps and the working time of the lamps in the statistical time period; The variables affecting illumination uniformity include illumination uniformity index, the number of measurement sub-areas divided into lighting areas, illumination value at the center of measurement sub-areas, average illumination and standard deviation of illumination value; The variables influencing user comfort include user satisfaction index, the number of users participating in the survey, the user's evaluation score on the evaluation index, and the number of evaluation indicators.

3. The method for intelligently controlling lighting in public places with multiple environments according to claim 2 is characterized in that: The energy-saving function target model calculation formula is: E is the energy consumption of the energy-saving function target model, T is the time period for determining statistics, n is the number of lighting systems of lamps, P i is the power of each lamp i, t i is the known working time of each lamp i; The calculation formula of the illumination uniformity target model is: in, Among them, U is the illumination uniformity index, E is the average illumination; σ E is the standard deviation of the illuminance value; m is the number of measurement sub-areas divided into the lighting area; E j is the illumination value at the center of the j-th sub-region, j=1, 2, ..., m; The calculation formula of the user comfort target model is: Among them, S is the user satisfaction index, k is the number of users surveyed, and x ij is the evaluation score of each user for l evaluation indicators.

4. The method for intelligently controlling lighting in public places with multiple environments according to claim 1 is characterized in that: The hierarchical analysis structure takes the lighting function of the public place lighting system as the target layer, including energy-saving function, illumination uniformity and user comfort; for the energy-saving function, energy consumption, number of lamps, lamp power and lamp working time are taken as criterion layer factors; for illumination uniformity, illumination uniformity index, number of measurement sub-areas, illumination value of the center of the sub-area, average illumination and illumination standard deviation are taken as criterion layer factors; for user comfort, user satisfaction index, number of users participating in the survey, user evaluation scores of evaluation indicators and number of evaluation indicators are taken as criterion layer factors; the conditions of different types of public places are taken as the solution layer.

5. The method for intelligently controlling lighting in public places with multiple environments according to claim 1 is characterized in that: The method for constructing a judgment matrix comprises: Assume the judgment matrix is ​​A=(a ij ), where a ij Indicates the relative importance of the i-th factor relative to the j-th factor; for the judgment matrix between lighting functions, the energy-saving function is F1, the illumination uniformity is F2, and the user comfort is F3, then a 12 Indicates the importance of energy saving function relative to illumination uniformity, and so on; For the judgment matrix of internal factors of each lighting function, for the energy-saving function, let the energy consumption be E1, the number of lamps be E2, the lamp power be E3, and the lamp working time be E4, then a 12 Indicates the importance of energy consumption relative to the number of lamps; the values ​​of the judgment matrix elements are based on expert scores, using a 1-9 scale, with 1 representing equal importance and 9 representing extremely important. The method for calculating the weight vector comprises: For the weight calculation between lighting functions: First, calculate the product of each row element of the judgment matrix A n is the matrix order; Then calculate M i The nth root of Last pair After normalization, we get the weight vector ω=(ω1,ω2,...,ω n ),in The weight calculation of the internal factors of each lighting function is similar. For the internal factors of the energy-saving function, the weight vector of factors such as energy consumption and the number of lamps relative to the energy-saving function is calculated according to the above method; The consistency checking method comprises: Calculate the maximum eigenvalue λ of the judgment matrix A max , calculated by the formula Where (Aω) i represents the i-th element of the vector Aω; Calculate consistency index For the lighting function judgment matrix n = 3, then Find the corresponding average random consistency index RI (for n=3, RI=0.58); Calculating the consistency ratio If CR is less than 0.1, the judgment matrix is ​​reasonable and the weight vector is valid; if CR is greater than 0.1, the judgment matrix needs to be reconstructed; The weight allocation method comprises: Assume that the lighting function weight vector is W = (ω F1 ,ω F2 ,ω F3 ), the energy-saving function target model is E, the illumination uniformity target model is U, and the user comfort target model is S; Then the energy-saving function target model control weight ω E =ω F1 , illumination uniformity target model control weight ω U =ω F2 , user comfort target model control weight ω S =ω F3 .

6. The method for intelligently controlling lighting in public places with multiple environments according to claim 1 is characterized in that: The initial variables of the target model are all rated values, including the energy consumption, number of lamps, lamp power and lamp working time of the energy-saving function target model are set to rated values; the illumination uniformity index, number of measurement sub-areas, illumination value of the center of the sub-area, average illumination and illumination standard deviation of the illumination uniformity target model are set to rated values; the user satisfaction index, number of users participating in the survey, user evaluation scores of the evaluation indicators and the number of evaluation indicators of the user comfort target model are set to initial values.

7. The method for intelligently controlling lighting in public places with multiple environments according to claim 1 is characterized in that: The variable size of the target model is adjusted, and the current value of the target model is solved. For the energy-saving function target model, the variable of the lamp working time is adjusted and the current value is calculated; for the illumination uniformity target model, the variable of the number of measurement sub-areas divided by the lighting area or the illumination value at the center of the sub-area is adjusted and the current value is calculated; for the user comfort target model, the variable of the user's evaluation score for the evaluation index is adjusted and the current value is calculated.

8. The method for intelligently controlling lighting in public places with multiple environments according to claim 1 is characterized in that: Whether the current value meets the threshold is judged. For the energy-saving function target model, the calculated current value of energy consumption is compared with the set energy consumption threshold; for the illumination uniformity target model, the calculated current value of the illumination uniformity index is compared with the set illumination uniformity threshold; for the user comfort target model, the calculated current value of the user satisfaction index is compared with the set user satisfaction threshold.

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