An energy-saving strategy optimization method for air conditioning and lighting systems of existing buildings

Abstract

The application discloses an energy-saving strategy optimization method for an air conditioning and lighting system of an existing building, and belongs to the technical field of energy-saving optimization. According to the temperature and light intensity parameters set according to the indoor environment requirements of the building, the operation data of each air conditioning and lighting subsystem are stored; a mode switching time axis of a daily use cycle is constructed, and an air conditioning-lighting collaborative operation segment is marked; the operation time length and total energy consumption of each segment in the cycle are counted, and mode labels are added to the data; a collaborative operation feature map is constructed, and the mode switching state value and energy-saving gain value of each segment are evaluated; an energy-saving optimization response range is constructed based on the gain value, and the operation parameters of the subsystem are fed back and adjusted; the application realizes collaborative energy saving of air conditioning and lighting, improves scene adaptability and energy-saving effect stability, solves the problems of poor collaboration, quantification difficulty and feedback loss of the existing scheme, and is suitable for energy-saving reconstruction of air conditioning and lighting systems of various existing buildings, and has low implementation cost and remarkable effect.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy-saving optimization, in particular to an energy-saving strategy optimization method for air conditioning and lighting systems of existing buildings. BACKGROUND

[0002] In the long-term operation of existing buildings, air conditioning and lighting systems are the two types of equipment with the highest energy consumption proportion, accounting for more than 60% of the total building energy consumption, and their energy-saving level directly determines the overall energy efficiency of the building.

[0003] The existing scheme mostly adopts the mode of independent control of air conditioning and lighting systems, such as fixed temperature threshold operation of air conditioning (26℃ in summer and 20℃ in winter) and fixed brightness operation of lighting (500 lux in office scenes), without considering the synergistic energy-saving potential of the two in different use scenarios, for example, in the lunch break period of office buildings, the personnel activity is reduced, only the air conditioning load is reduced while the lighting brightness is maintained, or only the lighting is dimmed while the air conditioning load is maintained, which all causes energy waste.

[0004] At the same time, most energy-saving schemes do not combine the environmental demand changes of the building daily use cycle, adopt the fixed operation mode of "one size fits all", and have no real-time feedback and dynamic optimization. For example, in the office building, the personnel density and activity intensity are significantly different in the morning (8:00-12:00), lunch break (12:00-13:00) and afternoon (13:00-18:00), and the demand for temperature and light intensity is different, but the existing scheme does not adjust the operation parameters for different time periods, resulting in the phenomenon of "overcooling / overheating" and "overbright / dim", which not only affects the use comfort, but also increases the invalid energy consumption. When the system energy consumption fluctuates due to seasonal changes (high temperature in summer and low temperature in winter), the parameters cannot be adjusted according to the actual operation state, and when the energy consumption rises due to the aging of the subsystem, it cannot be identified and optimized in time, so the energy-saving effect is difficult to maintain for a long time. SUMMARY

[0005] The purpose of the present application is to provide an energy-saving strategy optimization method for air conditioning and lighting systems of existing buildings to solve the problems raised in the background.

[0006] In order to solve the above technical problems, the present application provides the following technical scheme:

[0007] An energy-saving strategy optimization method for air conditioning and lighting systems of existing buildings, the method comprising the following steps:

[0008] Step S1: According to the environmental demand of the indoor environment of the existing building, set the control parameter range of indoor temperature and light intensity to form an indoor environment mode, and store the corresponding indoor environment mode data of each air conditioning and lighting subsystem, which records the operation parameters of the system;

[0009] Step S2: constructing a mode switching time axis in a daily building use cycle, determining a scale of the time axis and a mode switching node, and marking an indoor environment mode switching segment of air conditioning and lighting coordination operation between adjacent nodes;

[0010] Step S3: taking the daily building use cycle as a cycle period, adding mode labels to the indoor environment mode data, and simultaneously counting indoor environment mode data clusters of the air conditioning and lighting subsystems in each mode switching segment, wherein the clusters record running time lengths of the air conditioning and lighting subsystems and subsystem energy consumptions;

[0011] Step S4: constructing an air conditioning-lighting coordination operation feature map, dividing the feature map into shape regions corresponding to the mode switching segments, and calculating mode switching state values corresponding to the shape regions, wherein the shape regions include triangular regions and sector regions;

[0012] Step S5: based on comparison and analysis of the shape regions, evaluating energy saving gain values of the air conditioning and lighting subsystems;

[0013] Step S6: determining an energy saving optimization range and a real-time energy saving feedback range based on all the energy saving gain values, to form an energy saving optimization response range, and feeding back and adjusting indoor environment mode data of each air conditioning and lighting subsystem according to the energy saving optimization response range, to realize system energy saving optimization.

[0014] As a preferred scheme of the present application, the specific implementation process of step S1 comprises:

[0015] Based on environment demands of an existing building indoor environment, parameter domains of building indoor temperature and light intensity are initialized and set to be combined to constitute an indoor environment mode, wherein the building indoor temperature parameter domain is controlled to be reached by an air conditioning system, and the building indoor light intensity parameter domain is controlled to be reached by a lighting system;

[0016] An indoor environment mode data cluster is stored, taking each air conditioning and lighting subsystem as a data source, wherein the indoor environment mode data cluster records mode running parameters, the mode running parameters include refrigeration / heating capacity of the air conditioning system, air conditioning energy consumption, and rated power of the lighting system, and lighting energy consumption, wherein one environment demand mode corresponds to one indoor environment mode data cluster.

[0017] As a preferred scheme of the present application, the specific implementation process of step S2 comprises:

[0018] A mode switching time axis is constructed, wherein a starting point of the mode switching time axis is a daily building use starting time, a scale t of the mode switching time axis is initialized, and based on the scale t, a mode switching node with any label y is recorded as ;

[0019] Based on the mode switching time axis, a switching time segment composed of any two adjacent mode switching nodes is obtained, and an indoor environment mode switching segment label for air conditioner-lighting cooperative operation is performed, denoted as , wherein, denotes the mode switching node with label y+1.

[0020] As a preferred scheme of the present application, the specific implementation process of step S3 comprises:

[0021] With the daily use cycle of the building as the mode cycle period, the indoor environment mode data cluster is additionally marked with a mode label, and based on the indoor environment mode switching segment labeled by the mode switching time axis, the running time of the air conditioner-lighting subsystem formed in the indoor environment mode switching segment is accumulated and counted, and the subsystem energy consumption is the sum of the air conditioner energy consumption and the lighting energy consumption;

[0022] The indoor environment mode data cluster additionally marked with the mode label is denoted as , , wherein, denotes the indoor environment mode data cluster corresponding to the air conditioner-lighting subsystem with number i, denotes the mode running parameter of the air conditioner-lighting subsystem with number i in the environment mode switching segment , denotes the subsystem running time, denotes the subsystem energy consumption, and k is the label of the mode switching node.

[0023] As a preferred scheme of the present application, the specific implementation process of step S4 comprises:

[0024] The air conditioner-lighting cooperative operation feature map is constructed, which is circular, with the center point as the fixed point and the radius S, and S is the standard energy consumption of the air conditioner-lighting subsystem in the scale t range initialized and configured;

[0025] In the air conditioner-lighting cooperative operation feature map, the circle is divided into k equal sectors with the center point as the center, wherein one radius of the sector corresponds to one indoor environment mode switching segment;

[0026] In the air conditioner-lighting cooperative operation feature map corresponding to the air conditioner-lighting subsystem with number i, the indoor environment mode switching segment corresponding sector radius is denoted as , and denotes the mode switching state value of the air conditioner-lighting cooperative operation behavior, and , if , it indicates that the indoor environment mode switching segment If the interior air conditioning and lighting subsystem is not running, then .

[0027] As a preferred scheme of the present application, the implementation process of step S5 includes:

[0028] In the air conditioning-lighting collaborative operation feature map corresponding to the air conditioning and lighting subsystem numbered i, the circle center is taken as the vertex, and the straight line is connected between the radius and the end of the radius , to form a collaborative operation feature triangle, denoted as , wherein represents the mode switching state value corresponding to the air conditioning and lighting subsystem numbered i;

[0029] In the air conditioning-lighting collaborative operation feature map corresponding to the air conditioning and lighting subsystem numbered i, the circle center is taken as the vertex, and the sector area between the radius and the radius is obtained, denoted as ;

[0030] The energy saving gain value of the air conditioning and lighting subsystem numbered i is evaluated as , wherein represents the area of the collaborative operation feature triangle .

[0031] As a preferred scheme of the present application, the implementation process of step S6 includes:

[0032] Based on the energy saving gain value, an energy saving optimization range is constructed as , wherein is the mean value of the energy saving gain value, and , is the variance of the energy saving gain value, and ;

[0033] Based on the energy saving gain value, a real-time energy saving feedback range is constructed as ;

[0034] Based on the energy saving optimization range and the real-time energy saving feedback range, an energy saving optimization response range is generated as , wherein max{} and min{} are maximum and minimum value functions, respectively;

[0035] Taking the energy saving optimization response range as the energy saving optimization target, the indoor environment mode data cluster of the air conditioning and lighting subsystem numbered i is fed back when the air conditioning system and the lighting system control the building indoor temperature parameter domain and the light intensity parameter domain, respectively, to meet the energy saving optimization response range.

[0036] The application discloses an energy-saving strategy optimization system for air conditioning and lighting systems of existing buildings, which comprises a storage and a processor, wherein the storage is used for storing a program of an energy-saving strategy optimization method for air conditioning and lighting systems of existing buildings; the processor is used for executing the program of the energy-saving strategy optimization method for air conditioning and lighting systems of existing buildings; and the processor is further integrated with core function modules, wherein the core function modules comprise an environmental parameter and mode data management module, a time axis and switching segment processing module, an operation data statistical module, a collaborative feature analysis module, an energy-saving gain evaluation module and an energy-saving optimization feedback module.

[0037] The environmental parameter and mode data management module and the time axis and switching segment processing module jointly constitute a basic data processing unit of the system.

[0038] The environmental parameter and mode data management module is used for setting a control parameter range of indoor temperature and light intensity to form an indoor environment mode according to indoor environment requirements of the existing building, and simultaneously storing indoor environment mode data corresponding to each air conditioning and lighting subsystem, so as to ensure that the data record is complete and corresponds to the subsystem one by one; and the time axis and switching segment processing module is used for constructing a mode switching time axis based on a daily use cycle of the building, determining a time axis scale and a mode switching node, marking an air conditioning-lighting collaborative operation switching segment between adjacent nodes, and realizing accurate matching between the switching segment and an actual use scene.

[0039] As a preferred scheme of the application, the operation data statistical module, the collaborative feature analysis module, the energy-saving gain evaluation module and the energy-saving optimization feedback module jointly constitute an energy-saving analysis and optimization unit of the system.

[0040] The operation data statistical module is used for adding a mode mark to the indoor environment mode data based on a daily use cycle of the building as a cycle period, and statistically calculating a running time and a total energy consumption of the air conditioning and lighting subsystem in each switching segment, so as to ensure the timeliness and accuracy of data statistics; the collaborative feature analysis module is used for constructing an air conditioning-lighting collaborative operation feature map for each air conditioning and lighting subsystem, dividing a sector region corresponding to the switching segment, calculating a mode switching state value of each region, and converting abstract operation data into intuitive graphical features; the energy-saving gain evaluation module is used for constructing a collaborative operation feature triangle corresponding to adjacent state values in the collaborative operation feature map, calculating a ratio of a triangle area to a corresponding sector area, obtaining an energy-saving gain value, and realizing quantitative evaluation of an energy-saving effect; and the energy-saving optimization feedback module is used for constructing an energy-saving optimization range, a real-time energy-saving feedback range and an energy-saving optimization response range of intersection processing of the two ranges based on a mean value and a variance of the energy-saving gain value, feeding back and adjusting indoor environment mode data of the subsystem, and ensuring realization of an energy-saving optimization target.

[0041] As a preferred scheme of the present application, the energy-saving strategy optimization system for the air conditioning and lighting system of existing buildings is connected with the air conditioning and lighting system of existing buildings to realize the energy-saving strategy optimization method for the air conditioning and lighting system of existing buildings.

[0042] Compared with the prior art, the present application has the following beneficial effects:

[0043] (1) Through the synergistic feature analysis and gain evaluation, the synergistic energy-saving space of air conditioning and lighting in different scenes is mined to break through the limitation of independent control. For example, in the lunch break period, the air conditioning load (temperature is raised by 1-2℃) and the lighting brightness (light intensity is reduced by 50%-60%) are simultaneously reduced, which can reduce the period energy consumption compared with the independent control scheme, and the comprehensive building energy consumption is also reduced.

[0044] (2) Based on the time axis and switching segment design of the daily use cycle, the environmental requirements of different periods are adapted. For example, in the morning / afternoon office period of an office building, a higher comfort level (temperature is 24-26℃, light intensity is 300-500 lux) is maintained, and in the lunch break period, the energy consumption is reduced (temperature is 26-27℃, light intensity is 150-200 lux).

[0045] (3) Through the operation data statistics and energy-saving gain value analysis, the quantitative evaluation of energy-saving potential and effect is realized to effectively control the gain value error, accurately identify the high energy consumption subsystem, avoid the blindness of experience adjustment, and improve the optimization efficiency.

[0046] (4) Based on the optimization range design of the mean and variance, the system operation fluctuation (such as seasonal change and subsystem aging) can be responded in real time to realize long-term stable energy saving (for example, the upper limit of the air conditioning temperature parameter domain is automatically reduced in the summer high temperature, and the lower limit of the temperature parameter domain is appropriately reduced in the winter low temperature). BRIEF DESCRIPTION OF DRAWINGS

[0047] The accompanying drawings are included to provide a further understanding of the present application, and constitute a part of the specification, which together with the embodiments of the present application, serve to explain the present application, and do not constitute a limitation of the present application.

[0048] Figure 1 is a step schematic diagram of the energy-saving strategy optimization method for the air conditioning and lighting system of existing buildings. DETAILED DESCRIPTION

[0049] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0050] Reference is made to Figure 1 In this embodiment one, an energy saving strategy optimization method for air conditioning and lighting systems of existing buildings is provided, taking an office existing building (8 floors above ground, total building area 5000 square meters) built for 10 years in a city as the implementation scene; the air conditioning system is a centralized air conditioning (2 subsystems per floor, a total of 16 subsystems), with a refrigeration / heating power of 5-8 kW; the lighting system is LED lighting (4 subsystems per floor, a total of 32 subsystems), with a rated power of 10-15 W per lamp, and 30 lamps per floor.

[0051] The method comprises the following steps:

[0052] Step S1: According to the environmental requirements of the indoor environment of the existing building, the control parameter range of indoor temperature and light intensity is set to form the indoor environment mode, and the indoor environment mode data corresponding to each air conditioning and lighting subsystem is stored, which records the operating parameters of the system;

[0053] It should be noted that the temperature and light intensity parameter domain is set based on the indoor environmental requirements (comfort, functional requirements) of the building, and a "demand-parameter" corresponding relationship is established, and the operating data of each subsystem is stored to provide basic data support for subsequent analysis, avoiding that the parameter setting deviates from the actual demand.

[0054] Exemplarily, based on the environmental requirements of the indoor environment of the existing building, the parameter domain of the indoor temperature and light intensity of the building is initialized and set to form the indoor environment mode, and the indoor temperature parameter domain is controlled by the air conditioning system, and the indoor light intensity parameter domain is controlled by the lighting system;

[0055] The indoor environment mode data cluster with each air conditioning and lighting subsystem as the data source is stored, and the mode operating parameters are recorded in the indoor environment mode data cluster, including the refrigeration / heating capacity of the air conditioning system, the air conditioning energy consumption, and the rated power of the lighting system, the lighting energy consumption, wherein one environment demand mode corresponds to one indoor environment mode data cluster;

[0056] For example, according to the office comfort standard (GB / T50785-2012 "Evaluation standard for indoor thermal and humid environment of civil buildings"), the summer temperature parameter domain is set to 24-26℃, and the winter temperature parameter domain is set to 18-22℃; the light intensity during office hours (8:00-12:00, 13:00-18:00) is 300-500 lux, and the light intensity during lunch break (12:00-13:00) is 150-200 lux; the refrigeration / heating capacity of each air conditioning subsystem (5-6 kW in summer) and the hourly energy consumption (1.2-1.5 kWh) are recorded, and the rated power of each lighting subsystem (450 W per floor) and the hourly energy consumption (0.3-0.4 kWh) are recorded.

[0057] Step S2: Constructing a mode switching time axis in a daily building use cycle, determining the scale of the time axis and the mode switching nodes, and marking the indoor environment mode switching segments of the air conditioning and lighting coordination operation between adjacent nodes;

[0058] It should be noted that the mode switching time axis is constructed in combination with the daily use cycle of the building, and the coordinated operation segments of different time periods are marked, which binds the energy saving optimization with the actual use scenarios (such as office, lunch break, and off work), solves the problem that the fixed mode cannot adapt to dynamic demand, and realizes accurate matching of “time period-parameter”.

[0059] Exemplarily, the mode switching time axis is constructed, the starting point of the mode switching time axis is the starting time of the daily building use, the scale t of the mode switching time axis is initialized, and based on the scale t, the mode switching nodes are sequentially labeled on the mode switching time axis, and any mode switching node with a label y is denoted as ;

[0060] Based on the mode switching time axis, the switching time segment composed of any two adjacent mode switching nodes is obtained, and the indoor environment mode switching segment of the air conditioning-lighting coordination operation is marked, denoted as , wherein, denotes the mode switching node with a label y+1;

[0061] For example, taking 8:00 as the starting point and 18:00 as the ending point, the time axis scale is set to 1 hour; according to the work and rest, three nodes are determined: 8:00 (work), 12:00 (lunch break), 13:00 (work break), and 18:00 (work), and three switching segments are marked: 8:00→12:00 (morning office), 12:00→13:00 (lunch break), and 13:00→18:00 (afternoon office).

[0062] Step S3: Taking the daily use cycle of the building as the cycle period, adding mode labels to the indoor environment mode data, and simultaneously counting the indoor environment mode data clusters of the air conditioning and lighting subsystems in each mode switching segment, and recording the running time and subsystem energy consumption of the air conditioning and lighting subsystems in the cluster;

[0063] It should be noted that the running time and total energy consumption of each switching segment are counted according to the daily cycle, the system running state is converted into quantifiable data, and then objective basis is provided for energy saving effect evaluation, so as to avoid the subjectivity of experience judgment.

[0064] Exemplarily, the indoor environment mode data cluster is additionally labeled with modes based on the mode switching time axis, and based on the indoor environment mode switching segments marked by the mode switching time axis, the indoor environment mode data clusters in the indoor environment mode switching segments The runtime length of the indoor air-conditioning lighting subsystem and the subsystem energy consumption, which is the cumulative sum of the air-conditioning energy consumption and the lighting energy consumption;

[0065] The indoor environment mode data cluster marked with the additional mode is recorded as , wherein, represents the indoor environment mode data cluster corresponding to the air-conditioning lighting subsystem numbered i, represents the mode running parameter of the air-conditioning lighting subsystem numbered i in the environment mode switching segment , represents the subsystem runtime length, represents the subsystem energy consumption, and k is the label of the mode switching node;

[0066] For example, the runtime length (4 hours in the morning, 1 hour for lunch break, and 5 hours in the afternoon) and the total energy consumption (air-conditioning + lighting) of each segment are counted daily; and the data cluster is marked with "season-period" (such as "summer-morning office" and "summer-lunch break").

[0067] Step S4: constructing an air-conditioning-lighting collaborative running feature map, dividing the feature map into shape regions corresponding to the mode switching segments, and calculating the mode switching state values corresponding to each shape region, wherein the shape regions include triangular regions and sector regions;

[0068] It should be noted that through the circular collaborative running feature map, the abstract energy consumption and runtime length data are converted into intuitive graphical features (sector regions and radius lengths), and geometric calculations (feature triangular areas) are combined to realize the visualization analysis of the running state, so as to reduce the complexity of energy-saving analysis and save algorithm resources.

[0069] Exemplarily, the air-conditioning-lighting collaborative running feature map is constructed, the air-conditioning-lighting collaborative running feature map is circular, the center point is a fixed point, the radius is S, and S is the standard energy consumption of the air-conditioning lighting subsystem within the scale t range initialized and configured;

[0070] In the air-conditioning-lighting collaborative running feature map, the circle is divided into k equal sectors with the center point as the center, wherein one radius of the sector corresponds to one indoor environment mode switching segment;

[0071] In the air-conditioning-lighting collaborative running feature map corresponding to the air-conditioning lighting subsystem numbered i, the indoor environment mode switching segment corresponding to the sector radius is recorded as , and represents the mode switching state value of the air-conditioning-lighting collaborative running behavior, and , if , it represents the indoor environment mode switching segment If the inner air conditioning and lighting subsystem is not running, then ;

[0072] For example, the radius of the circular feature map is set to 8 (corresponding to the standard energy consumption of 8 kWh / period), which is divided into 3 equal sectors (each 120°); the state value = (total energy consumption of the segment / running time) × scale (1 hour), the state value of the 8th floor east side No. 1 subsystem in the morning = 6.0 / 4×1=1.5, 1.15 / 1×1=1.15 at lunch break, and 7.5 / 5×1=1.5 in the afternoon.

[0073] Step S5: Based on the shape area comparison analysis, the energy saving gain value of the air conditioning and lighting subsystem is evaluated;

[0074] It should be noted that the "feature triangle area / sector area" is used as the energy saving gain value to quantify the energy saving potential of different switching segments and different subsystems to avoid blind adjustment.

[0075] Exemplarily, in the air conditioning and lighting collaborative operation feature map corresponding to the air conditioning and lighting subsystem numbered i, the center of the circle is taken as the vertex, and the ends of the radii and are connected by a straight line to form a collaborative operation feature triangle, denoted as , wherein represents the mode switching state value corresponding to the air conditioning and lighting subsystem numbered i;

[0076] In the air conditioning and lighting collaborative operation feature map corresponding to the air conditioning and lighting subsystem numbered i, the center of the circle is taken as the vertex, and the sector area between the radii and is obtained, denoted as ;

[0077] The energy saving gain value of the air conditioning and lighting subsystem numbered i is evaluated , wherein represents the area of the collaborative operation feature triangle ;

[0078] For example, the feature triangle area formed by the adjacent radii (such as 1.5 in the morning and 1.15 at lunch break) = 0.86, the sector area = (120 / 360)×π×8²≈67.02, and the gain value = 0.86 / 67.02≈0.0128; the average of the gain values of all subsystems in summer = 0.013, and the variance = 0.002.

[0079] Step S6: Based on all the energy saving gain values, the energy saving optimization range and the real-time energy saving feedback range are determined to form the energy saving optimization response range, and the indoor environment mode data of each air conditioning and lighting subsystem is adjusted according to the energy saving optimization response range feedback to realize system energy saving optimization;

[0080] It should be noted that the optimization range is constructed based on the mean and variance of the gain value, the intersection of "global optimization requirement" and "single system real-time state" is taken as the optimization target, the subsystem parameters are dynamically adjusted to ensure stable energy saving effect and meet the actual operation conditions, so as to form a closed loop of "evaluation-adjustment-re-evaluation".

[0081] Exemplarily, based on the energy saving gain value, an energy saving optimization range is constructed , wherein, is the mean of the energy saving gain value, and , is the variance of the energy saving gain value, and ;

[0082] Based on the energy saving gain value, a real-time energy saving feedback range is constructed ;

[0083] Based on the energy saving optimization range and the real-time energy saving feedback range, an energy saving optimization response range is generated , wherein, max{} and min{} are maximum and minimum value functions respectively;

[0084] The energy saving optimization response range is taken as the energy saving optimization target, the indoor environment mode data cluster of the air conditioning and lighting subsystem numbered i is fed back when the air conditioning system and the lighting system control the indoor temperature parameter domain and the light intensity parameter domain of the building respectively, to meet the energy saving optimization response range;

[0085] For example, the energy saving optimization range = 0.013 ± 0.002 (0.011-0.015), the real-time feedback range of the 8th floor west side No. 2 subsystem = 0.012 ± 0.002 (0.010-0.014), and the optimization response range = 0.011-0.014; If the air conditioning temperature parameter domain of this subsystem during the lunch break period is adjusted to 26-27℃, and the lighting light intensity parameter domain is adjusted to 150-180 lux, the energy saving optimization range is met.

[0086] In the first embodiment: a kind of energy saving strategy optimization system for existing building air conditioning and lighting system is provided, and existing building air conditioning and lighting system are connected to be applied to the above-mentioned embodiment one, the system includes: storage and processor, storage, for storing the program of a kind of energy saving strategy optimization method for existing building air conditioning and lighting system;Processor is used to execute the program of a kind of energy saving strategy optimization method for existing building air conditioning and lighting system;The processor also integrates core function module, and core function module includes environmental parameter and mode data management module, time axis and switching section processing module, operation data statistics module, collaborative feature analysis module, energy saving gain evaluation module and energy saving optimization feedback module;

[0087] The environmental parameter and mode data management module and the timeline and switching segment processing module jointly constitute a basic data processing unit of the system.

[0088] The environmental parameter and mode data management module is configured to set a control parameter range of indoor temperature and light intensity according to indoor environmental requirements of an existing building to form an indoor environmental mode, and store indoor environmental mode data corresponding to each air conditioning and lighting subsystem to ensure that the data is complete and corresponds to the subsystems one by one. The timeline and switching segment processing module is configured to construct a mode switching timeline based on a daily use cycle of the building, determine a timeline scale and a mode switching node, mark an air conditioning-lighting collaborative operation switching segment between adjacent nodes, and realize accurate matching of the switching segment and an actual use scenario.

[0089] The operation data statistical module, the collaborative feature analysis module, the energy saving gain evaluation module, and the energy saving optimization feedback module jointly constitute an energy saving analysis and optimization unit of the system.

[0090] The operation data statistical module is configured to add a mode mark to the indoor environmental mode data based on a daily use cycle of the building as a cycle period, and statistically determine a running time and total energy consumption of the air conditioning and lighting subsystems in each switching segment to ensure the timeliness and accuracy of the data statistics. The collaborative feature analysis module is configured to construct an air conditioning-lighting collaborative operation feature map for each air conditioning and lighting subsystem, divide a sector region corresponding to the switching segment, calculate a mode switching state value of each region, and convert abstract operation data into intuitive graphical features. The energy saving gain evaluation module is configured to construct a collaborative operation feature triangle corresponding to adjacent state values in the collaborative operation feature map, calculate a ratio of an area of the triangle to an area of the sector, obtain an energy saving gain value, and realize quantitative evaluation of an energy saving effect. The energy saving optimization feedback module is configured to construct an energy saving optimization range, a real-time energy saving feedback range, and an intersection processing energy saving optimization response range based on a mean value and a variance of the energy saving gain value, feed back indoor environmental mode data of the subsystems to ensure realization of an energy saving optimization target.

[0091] It should be noted that, in this text, relational terms such as first and second are used merely to distinguish one entity or action from another, without necessarily requiring or implying any such actual relationship or order between such entities or actions. Moreover, the terms "comprises", "comprising", or any other variant thereof are intended to cover non-exclusive inclusions, so that a process, method, article, or apparatus that includes a list of elements does not only include those elements, but also includes other elements not explicitly listed, or inherent to such a process, method, article, or apparatus.

[0092] Finally, it should be noted that the above only describes the preferred embodiments of the present application and is not intended to limit the present application, and although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent replacements to some technical features. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for optimizing energy-saving strategies for air conditioning and lighting systems in existing buildings, characterized in that, The method includes the following steps: Step S1: Based on the environmental requirements of the existing building, set the control parameter range of indoor temperature and light intensity to form an indoor environment mode, and store the indoor environment mode data corresponding to each air conditioning and lighting subsystem. The data records the system's operating parameters. Step S2: Construct a timeline for mode switching within the daily building usage cycle, determine the scale of the timeline and mode switching nodes, and mark the indoor environment mode switching segments where air conditioning and lighting operate in coordination between adjacent nodes. Step S3: Using the daily usage cycle of the building as the cycle period, add mode tags to the indoor environment mode data, and at the same time, count the indoor environment mode data clusters of the air conditioning and lighting subsystems in each mode switching segment. The clusters record the running time and energy consumption of the air conditioning and lighting subsystems. Step S4: Construct a feature map of air conditioning-lighting coordinated operation, divide the feature map into shape regions corresponding to mode switching segments, and calculate the mode switching state value corresponding to each shape region. The shape regions include triangular regions and fan-shaped regions. Step S5: Based on the comparative analysis of shape regions, evaluate the energy-saving gain value of the air conditioning and lighting subsystem; Step S6: Determine the energy-saving optimization range and real-time energy-saving feedback range based on all energy-saving gain values ​​to form an energy-saving optimization response range. Adjust the indoor environmental mode data of each air conditioning and lighting subsystem according to the feedback of the energy-saving optimization response range to achieve system energy-saving optimization.

2. The energy-saving strategy optimization method for existing building air conditioning and lighting systems according to claim 1, characterized in that, The specific implementation process of step S1 includes: Based on the existing indoor environmental requirements of the building, the parameter domains of indoor temperature and light intensity are initialized to form an indoor environment mode. The indoor temperature parameter domain is controlled by the air conditioning system, and the indoor light intensity parameter domain is controlled by the lighting system. The system stores indoor environment mode data clusters with each air conditioning and lighting subsystem as the data source. The indoor environment mode data clusters record mode operation parameters, including the cooling / heating capacity and air conditioning energy consumption of the air conditioning system, and the rated power and lighting energy consumption of the lighting system. Each environmental demand mode corresponds to one indoor environment mode data cluster.

3. The energy-saving strategy optimization method for existing building air conditioning and lighting systems according to claim 2, characterized in that, The specific implementation process of step S2 includes: A mode switching timeline is constructed, starting from the daily building usage start time. The scale 't' of the timeline is initialized, and based on scale 't', mode switching nodes are sequentially labeled on the timeline. Any mode switching node labeled 'y' is denoted as... ; Based on the mode switching time axis, the switching time segment between any two adjacent mode switching nodes is obtained, and the indoor environment mode switching segment for coordinated operation of air conditioning and lighting is marked as follows: ,in, This indicates the mode switching node with the label y+1.

4. The energy-saving strategy optimization method for existing building air conditioning and lighting systems according to claim 3, characterized in that, The specific implementation process of step S3 includes: Using the daily usage cycle of the building as the pattern cycle, pattern tags are added to the indoor environment pattern data clusters, and based on the indoor environment pattern switching segments marked by the pattern switching time axis, the data are accumulated and statistically analyzed within the indoor environment pattern switching segments. The running time of the air conditioning and lighting subsystem formed within the system, and the energy consumption of the subsystem, wherein the energy consumption of the subsystem is the sum of the energy consumption of air conditioning and the energy consumption of lighting; The indoor environmental model data cluster with additional pattern tags is denoted as... ,in, This represents the indoor environment pattern data cluster corresponding to the air conditioning and lighting subsystem numbered i. This indicates a segment where the environment mode is switched. Operating parameters for the air conditioning and lighting subsystem with internal number i. Indicates the subsystem runtime. This represents the energy consumption of the subsystem, and k is the label of the mode switching node.

5. The energy-saving strategy optimization method for existing building air conditioning and lighting systems according to claim 4, characterized in that, The specific implementation process of step S4 includes: Construct a characteristic map of air conditioning-lighting coordinated operation. The characteristic map of air conditioning-lighting coordinated operation is circular, with a fixed center point and a radius of S. S is the standard energy consumption of the air conditioning and lighting subsystem within the scale t range of the initial configuration. In the air conditioning-lighting coordinated operation feature diagram, the circle is divided into k equal sectors with the center point as the center point, and one radius of the sector corresponds to an indoor environment mode switching segment. In the characteristic diagram of coordinated operation of air conditioning and lighting corresponding to the air conditioning and lighting subsystem numbered i, the indoor environment mode switching segment is included. The corresponding sector radius is denoted as and use The mode switching state value indicates the coordinated operation behavior of air conditioning and lighting, and ,like This indicates a segment where the indoor environment mode is switched. If the interior air conditioning and lighting subsystem is not operating, then... .

6. The energy-saving strategy optimization method for existing building air conditioning and lighting systems according to claim 5, characterized in that, The specific implementation process of step S5 includes: In the characteristic diagram of the coordinated operation of air conditioning and lighting subsystem i, with the center of the circle as the vertex and the radii connected by straight lines, With radius The ends of the triangle form a cooperative operation characteristic triangle, denoted as... ,in, This represents the mode switching status value corresponding to the air conditioning and lighting subsystem numbered i; In the characteristic diagram of the coordinated operation of air conditioning and lighting subsystem i, with the center of the circle as the vertex, the radius is obtained. With radius The area of ​​the sector between them is denoted as ; The energy-saving gain value of the air conditioning and lighting subsystem with evaluation number i is evaluated. In the formula, Represents the characteristic triangle of cooperative operation The area.

7. The energy-saving strategy optimization method for existing building air conditioning and lighting systems according to claim 6, characterized in that, The specific implementation process of step S6 includes: Based on the energy-saving gain value, construct the energy-saving optimization range. ,in, This is the average value of the energy-saving gain, and , Let be the variance of the energy-saving gain value, and ; Construct a real-time energy-saving feedback range based on the energy-saving gain value. ; Based on the energy-saving optimization range and the real-time energy-saving feedback range, an energy-saving optimization response range is generated. In the formula, max{} and min{} are the maximum and minimum value functions, respectively; Optimize response range for energy saving To achieve energy-saving optimization, when the air conditioning system and lighting system control the indoor temperature parameter domain and light intensity parameter domain respectively, the indoor environmental pattern data cluster of the air conditioning and lighting subsystem numbered i is fed back. To meet the energy-saving optimization response range.

8. The energy-saving strategy optimization system for an energy-saving strategy optimization method for existing building air conditioning and lighting systems according to claim 1, characterized in that, The energy-saving strategy optimization method for existing building air conditioning and lighting systems is integrated into a storage device in the form of a program. The storage device is built into the energy-saving strategy optimization system, which also includes a processor for executing the program of the energy-saving strategy optimization method for existing building air conditioning and lighting systems. The processor also integrates core functional modules, including an environmental parameter and mode data management module, a time axis and switching segment processing module, an operation data statistics module, a collaborative feature analysis module, an energy-saving gain evaluation module, and an energy-saving optimization feedback module. The environmental parameter and mode data management module, the time axis and switching segment processing module together constitute the basic data processing unit of the system. The environmental parameter and mode data management module is used to set the control parameter range of indoor temperature and light intensity according to the existing building's indoor environment requirements to form an indoor environment mode. At the same time, it stores the indoor environment mode data corresponding to each air conditioning and lighting subsystem to ensure that the data records are complete and correspond one-to-one with the subsystems. The time axis and switching segment processing module is used to construct a mode switching time axis based on the building's daily usage cycle, determine the time axis scale and mode switching nodes, and mark the air conditioning-lighting coordinated operation switching segments between adjacent nodes to achieve accurate matching between switching segments and actual usage scenarios.

9. The energy-saving strategy optimization system according to claim 8, characterized in that, The operation data statistics module, collaborative feature analysis module, energy-saving gain evaluation module, and energy-saving optimization feedback module together constitute the energy-saving analysis and optimization unit of the system. The system comprises several modules: Operational Data Statistics Module, which adds pattern markers to indoor environmental mode data based on the building's daily usage cycle, and calculates the runtime and total energy consumption of the air conditioning and lighting subsystems within each switching segment, ensuring the timeliness and accuracy of data statistics; Collaborative Feature Analysis Module, which constructs an air conditioning-lighting collaborative operation feature map for each subsystem, divides the data into sector regions corresponding to the switching segments, calculates the mode switching state values ​​for each region, and transforms abstract operational data into intuitive graphical features; Energy Saving Gain Assessment Module, which constructs collaborative operation feature triangles corresponding to adjacent state values ​​in the collaborative operation feature map, calculates the ratio of the triangle area to the corresponding sector area to obtain the energy saving gain value, and achieves a quantitative assessment of energy saving effects; and Energy Saving Optimization Feedback Module, which constructs the energy saving optimization range, the real-time energy saving feedback range, and the energy saving optimization response range (the intersection of the two) based on the mean and variance of the energy saving gain value, and provides feedback to adjust the indoor environmental mode data of the subsystems to ensure the achievement of energy saving optimization goals.

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