Design support system

Abstract

We provide a design support system that enhances spatial selectivity by incorporating appropriate diversity into the space. [Solution] One embodiment of the design support system is a design support system 1 that supports zoning planning for a building having multiple spaces that can be selected by each of multiple users. The design support system 1 includes a work style data collection unit 11 that collects data on the work styles of multiple users, a preference data collection unit 12 that collects data on the preferences of multiple users for spaces, a space selection behavior model generation unit 13 that generates a space selection behavior model, which is a model that simulates which space each of the multiple users will select from the work style data, preference data, and space value data, which is data on the value calculated for each of the multiple spaces, and a space evaluation unit 14 that evaluates the zoning plan of the multiple spaces from the space selection behavior model.

Description

Technical Field

[0001] The present disclosure relates to a design support system for zoning plans of buildings having a plurality of spaces that can be selected by each of a plurality of users.

Background Art

[0002] Patent Document 1 describes an office planning support system including a subjective survey system, an objective survey system, a simulator, a planning requirement extraction system, a storage unit, a basic data input system, and a data output system. The simulator performs a simulation that simulates the behavior of users. The subjective survey system collects subjective survey data, and the objective survey system collects objective survey data. The objective survey data includes the proximity between organizations, which is the overall proximity requirement. The planning requirement extraction unit has a planning requirement generation unit. The planning requirement generation unit calculates the required area based on the subjective survey data and the objective survey data, and performs a stacking process of allocating the floors for arranging each organization based on the proximity between organizations and the required area.

[0003] Patent Document 2 describes a design support device that provides support when selecting candidates for the layout of a workspace in an office. The design support device includes an execution unit that simulates the behavior of users, a calculation unit that calculates an index related to the satisfaction of the work environment for each user, a selection unit that selects candidates for the layout using the satisfaction information, and a generation unit that generates various types of information. The above-mentioned satisfaction includes an index of physiological comfort. The selection unit presents the optimal office layout as a selection candidate for users who feel physiologically comfortable.

[0004] Patent Document 3 describes an air conditioning control system for a free-address office. The air conditioning control system includes a database that stores employee preference data regarding temperature and working conditions and employee attendance schedule data for air conditioning control days, and setting means that sets the air conditioning temperature distribution in the workspace based on the preference data and attendance schedule data. The air conditioning control system further includes control means and notification means. The control means controls the air conditioning in the workspace based on the air conditioning temperature distribution, and the notification means notifies the employee of the air conditioning temperature distribution. [Prior art documents] [Patent Documents]

[0005] [Patent Document 1] Patent No. 6111238 [Patent Document 2] Japanese Patent Publication No. 2021-56811 [Patent Document 3] Japanese Patent Publication No. 2019-219097 [Overview of the project] [Problems that the invention aims to solve]

[0006] Incidentally, in workplaces where multiple users work, free addressing, where each user can choose their preferred workspace, is becoming increasingly common. In such workplaces, it is necessary to enhance spatial selectivity—the ability for users to freely choose their workspace—by providing appropriate diversity in the space. Enhancing spatial selectivity leads to increased user self-efficacy and improves user intellectual productivity and satisfaction.

[0007] This disclosure aims to provide a design support system that can enhance spatial selectivity by providing appropriate diversity in space. [Means for solving the problem]

[0008] (1) The design support system relating to this disclosure is a design support system that supports zoning planning for a building having multiple spaces that can be selected by each of multiple users. The design support system comprises a work style data collection unit that collects data on the work styles of multiple users, a preference data collection unit that collects data on the preferences of multiple users for spaces, a space selection behavior model generation unit that generates a space selection behavior model, which is a model that simulates which space each of the multiple users will select from the work style data, preference data, and space value data, which is data on the value calculated for each of the multiple spaces, and a space evaluation unit that evaluates the zoning plan of the multiple spaces from the space selection behavior model.

[0009] This design support system is used when planning the zoning of a building that has multiple spaces that can be selected by multiple users. In the design support system, a work style data collection unit collects data on the work styles of multiple users, and a preference data collection unit collects data on the preferences of multiple users for different spaces. From the work style data, preference data, and spatial value data (data on the value assigned to each space), a spatial selection behavior model is created that shows which space each user will choose, and multiple spaces are evaluated using the spatial selection behavior model. Therefore, by evaluating multiple spaces based on the spatial selection behavior model created from user preferences, actual work styles, and the value of the space itself, it is possible to appropriately evaluate multiple spaces based on information about when and which space a user will choose. Consequently, it becomes possible to create optimal spatial zoning according to the circumstances of each of the multiple users, thereby increasing spatial selectivity while providing appropriate diversity in the space. As a result, it is possible to increase users' self-efficacy and improve their intellectual productivity and satisfaction.

[0010] (2) In (1) above, the preference data may include thermal preference data that indicates the user's thermal preferences, and the spatial value data may include the degree of spatial fit to the thermal preference data. In this case, by creating a spatial selection behavior model that takes into account the thermal preference data, it becomes possible to zone spaces that take into account the user's thermal preferences. Therefore, spatial selectivity can be further enhanced.

[0011] (3) In (1) or (2) above, the design support system may include an energy simulation model generation unit that generates an energy simulation model that simulates the thermal environment and energy consumption of the building, and an energy efficiency evaluation unit that evaluates the energy efficiency of the building from the energy simulation model and the spatial selection behavior model. In this case, the energy efficiency of the building is evaluated from the energy simulation model that predicts the thermal environment and energy consumption of the building and the spatial selection behavior model. Therefore, the energy consumption of the building can be reduced.

[0012] (4) In (3) above, the design support system may include a comfort evaluation unit that evaluates the user's thermal comfort from an energy simulation model. In this case, since the user's thermal comfort is evaluated from an energy simulation model, the comfort based on the building's thermal environment can be improved.

[0013] (5) In any of (1) to (4) above, the design support system may include a search unit that parameterizes multiple spaces and searches for a layout in which at least one of the spatial evaluation, thermal comfort, and energy evaluation is high. In this case, the search unit can search for a layout in which at least one of the spatial evaluation, thermal comfort, and energy evaluation is high.

[0014] (6) In any of (1) to (5) above, the zoning plan may include a zoning plan for an air conditioning system provided in a plurality of spaces. In this case, it becomes possible to zone the air conditioning system optimally according to the respective situations of a plurality of users.

Advantages of the Invention

[0015] According to the present disclosure, it is possible to enhance spatial selectivity by providing appropriate diversity to the space.

Brief Description of the Drawings

[0016] [Figure 1] FIG. 1 is a diagram showing an example of a zoning plan. [Figure 2] FIG. 2 is a block diagram showing the functional configuration of a design support system according to an embodiment. [Figure 3] FIG. 3 is a diagram showing an example of thermal preference data. [Figure 4] FIG. 4 is a diagram showing an example of the relationship between spatial selectivity and energy efficiency. [Figure 5] FIG. 5 is a diagram showing an example of a zoning plan. [Figure 6] FIG. 6 is a flowchart showing an example of the steps of a design support method according to an embodiment. [Figure 7] FIG. 7 is a flowchart showing an example of the steps of a design support method according to a modified example.

Modes for Carrying Out the Invention

[0017] Hereinafter, embodiments of a design support system according to the present disclosure will be described with reference to the drawings. The design support system according to the present disclosure is not limited to the following embodiments, but is defined by the claims, and is intended to include all modifications within the scope equivalent to the claims. In the description of the drawings, the same or corresponding elements are denoted by the same reference numerals, and redundant descriptions are omitted as appropriate. The drawings may be drawn with some parts simplified or exaggerated for ease of understanding, and dimensional ratios and the like are not limited to those described in the drawings.

[0018] For example, in office planning, the spatial zoning within the building is determined by the designer. "Building" refers to something constructed for people to work or conduct research. A building has multiple spaces. "Space" refers to a location within the building where a user performs an activity. "Space" can refer to a room, or a section separated by partitions, etc. "User" refers to a person who uses the building.

[0019] "Zoning" refers to the arrangement of different spaces within a building, specifying where and for what area. "Zoning plan" refers to the plan for zoning. As shown in Figure 1, the design support system according to this embodiment evaluates the zoning plan for multiple spaces S in a building M. For example, the design support system according to this embodiment evaluates the zoning plan for multiple spaces S from a space selection behavior model described later. The design support system according to this embodiment may change the area of ​​the spaces S by moving the boundaries B between the multiple spaces S. The zoning plan may also include the zoning plan for air conditioning systems installed in the multiple spaces S.

[0020] Traditionally, zoning involved analyzing the results of surveys conducted among users regarding their work styles, with designers organizing requirements based on their own experience and thinking. However, with this method, the relationship between the input data on work styles and the output planning requirements and specific zoning layouts was not always logically or quantitatively clear, making it uncertain whether the design was optimally suited to the users' work styles.

[0021] In recent years, flexible workplaces have become increasingly popular. Flexible workplaces aim to provide a work style where users can choose the optimal location based on their work activities and preferences. Activities refer to user tasks such as document creation, meetings, and breaks. In particular, input data related to work styles is considered increasingly important in the design of flexible workplaces.

[0022] Given the demands described above, there is a need for a method to numerically optimize zoning plans using data on user work styles as input. In a flexible workplace, users need to choose their workspace. At this time, it is important that a space that suits the user's activities and preferences exists within a certain distance and is available (for example, has an empty seat). In other words, there is a need for a method that can optimize from the perspective of spatial selectivity, which is the property that allows users to freely choose the space in which they work.

[0023] Since the usage of each space affects the energy consumption of a building, methods for optimizing energy consumption from the perspective of minimizing it are required. The design support system according to this embodiment minimizes air conditioning energy, which accounts for a large proportion of energy consumption during building operation, by taking into account users' thermal preferences for the thermal environment and their space selection behavior based on those preferences. For example, in a flexible workspace, by gathering users with similar thermal preferences into one air conditioning zone, it is possible to enhance users' thermal comfort while suppressing energy consumption. In this embodiment, by focusing on users' selection behavior and providing appropriate diversity in spaces to enhance space selectivity, it is possible to increase users' self-efficacy and improve intellectual productivity and satisfaction.

[0024] Figure 2 is a block diagram showing the functional configuration of a design support system 1 as an example of this embodiment. The design support system 1 assists in zoning planning of a building having multiple spaces that can be selected by multiple users. As shown in Figure 2, the design support system 1 as an example includes a terminal T and a design support program 10. The terminal T includes, for example, a computer. The design support program 10 may be, for example, an application installed on the terminal T and operable by the user. The type of application is not particularly limited.

[0025] Terminal T is, for example, a device capable of executing the functions of design support system 1 and design support program 10. Terminal T may be a portable terminal. A portable terminal refers to a portable device such as a mobile phone including a smartphone, a tablet, a camera, or a laptop computer. Terminal T may also be a device other than a portable terminal, such as a personal computer.

[0026] Terminal T comprises a processor (e.g., CPU) that runs an operating system and software (applications), a main memory unit composed of ROM and RAM, an auxiliary memory unit composed of flash memory, a communication control unit composed of a wireless communication module, input devices such as buttons, and output devices such as a display. However, the configuration of terminal T is not limited to the above and can be changed as appropriate. Hereinafter, the main memory unit and the auxiliary memory unit may be collectively referred to as the memory unit.

[0027] On terminal T, the design support program 10 is executed as an application. The design support program 10 is, for example, an application executed on terminal T. However, at least some of the functions of the design support program 10 may be executed by a server outside of terminal T. The design support program 10 may also be downloaded from such a server.

[0028] Each function of the design support system 1 is realized by loading the design support program 10 into the processor or main memory and executing the design support program 10. The processor operates the aforementioned communication control unit, input device, or output device according to the design support program 10, and reads and writes data to the memory unit. The data used for processing terminal T is stored in the memory unit.

[0029] The design support system 1 may be a distributed processing system composed of multiple computers, a client-server system, or a cloud system. The design support program 10 includes, for example, a main module, a data acquisition module, a decision module, and an output module. Each functional element of the design support program 10 functions when the data acquisition module, decision module, and output module are executed. The design support program 10 may be provided, for example, by being permanently recorded on a tangible storage medium such as a CD-ROM, DVD-ROM, or semiconductor memory. The design support program 10 may also be provided via a communication network as a data signal superimposed on a carrier wave.

[0030] For example, the design support program 10 includes, as functional components, a work style data collection unit 11, a preference data collection unit 12, a spatial selection behavior model generation unit 13, a spatial evaluation unit 14, an energy simulation model generation unit 15, an energy efficiency evaluation unit 16, a comfort evaluation unit 17, a search unit 18, a display control unit 19, and a storage unit 20.

[0031] The display control unit 19 displays, for example, an operation screen for operating the functions of the design support program 10 on the display of terminal T. The display control unit 19 displays various screens of the design support program 10 on the display of terminal T according to commands from functions of the design support program 10 other than the display control unit 19. For example, the display control unit 19 is a function that controls the display of screens on the display of terminal T. The storage unit 20 is a function that stores data input and output to terminal T by the design support program 10.

[0032] The work style data collection unit 11 collects work style data from multiple users. "Work style data" may be referred to as "work style data" below. The work style data collection unit 11 obtains work style data from multiple users, for example, by collecting the results of surveys conducted with multiple users. User work style data includes, for example, the percentage of time a user spends inside a building, and data on where in the building they perform what activities and for how long. In this case, user work style data includes what kind of work a user performed in what space and for how long.

[0033] User work style data may include, for example, at least one of the following: (on an average day) start time, end time, percentage of time spent on activities, and duration of activities. Additionally, user work style data may include data on the user's daily activities over a certain period (e.g., one week to one month) (what time they arrived at work, what activities they did, with whom and where, and what time they left work).

[0034] The work style data collection unit 11 collects user work style data, for example, through subjective surveys. However, the work style data collection unit 11 may also collect user work style data through objective surveys. The work style data collection unit 11 may also collect work style data by, for example, acquiring the user's location and activity within a building on a spatial and temporal basis using at least one of beacons and cameras. Thus, the work style data collection unit 11 can collect user work style data in a variety of ways.

[0035] The preference data collection unit 12 collects preference data of multiple users regarding a space. This preference data includes, for example, thermal preference data that indicates a user's thermal preference. "Preference data" may be referred to as "preference data" below. The preference data collection unit 12 obtains preference data of multiple users, for example, by collecting the results of surveys conducted with multiple users.

[0036] Preference data includes, for example, data on the user's favorite spaces within a building. Thermal preference data includes data on the user's preferences for the thermal environment. For example, thermal preference data includes data indicating whether the user prefers a warm or cool environment, as shown in Figure 3. Thermal preference data may also be the average value or range of the user's preferred temperature (for example, 23°C). However, thermal preference data is not limited to this and may also include data on whether the user likes or dislikes an environment obtained under conditions where physical environmental measurements have been taken.

[0037] Preference data may include data indicating whether the user prefers enclosed or open spaces. Preference data may include data indicating whether the user prefers a window side or a corridor side. Preference data may include data indicating whether the user prefers a narrow or spacious space. Preference data may include data indicating whether the user prefers a bright or dark space. Preference data may include data indicating whether the user prefers a lively or quiet space. Preference data may include data indicating preferences for each activity. The preference data collection unit 12 collects user preference data, for example, through subjective surveys. However, the preference data collection unit 12 may also collect user preference data through objective surveys.

[0038] The spatial selection behavior model generation unit 13 acquires spatial value data, which is data on the value calculated for each of a plurality of spaces. The spatial value data is stored in the storage unit 20 in advance, for example. The spatial value data includes, for example, the degree of fit between the type of space and the activity. The type of space indicates the category of space. The types of spaces include, for example, at least one of quiet spaces, semi-quiet spaces, open meeting spaces, semi-closed meeting spaces, closed meeting spaces, and recharge spaces.

[0039] Table 1 below shows examples of the degree of suitability between space types and activities. Routine, Focus, Creative, Collaborative, Discussion, Coordinate, Online Group, Recharge, and Lunch in Table 1 are examples of activities. A higher number in Table 1 indicates a higher degree of suitability between the space type and the activity. For example, when the activity is "Focus," the suitability with quiet spaces is highest ("1"), and the suitability with closed and semi-closed meeting spaces is lowest ("0"). When the activity is "Coordinate," the suitability with closed meeting spaces is highest ("1"), and the suitability with quiet spaces, semi-quiet spaces, and recharge spaces is lowest ("0"). [Table 1]

[0040] Spatial value data may include, for example, travel distance. Travel distance is, for example, the distance from the building's entrance. When spatial value data includes travel distance, zoning that takes into account the user's travel distance becomes possible. Spatial value data may also include, for example, congestion level. Congestion level indicates, for example, the proportion of time a space is congested. Alternatively, congestion level may be the average ratio of the actual number of users to the space's capacity. When spatial value data includes congestion level, zoning that takes into account the degree of congestion in the space becomes possible.

[0041] Spatial value data may include the thermal environment. The thermal environment is, for example, room temperature (indoor air temperature). However, the thermal environment does not have to be room temperature; it may be something that affects the thermal sensation a user feels when using the space, or a thermal preference. Furthermore, the thermal environment may include the surface temperatures of walls, floors, and ceilings, radiant temperatures and action temperatures, as well as a comprehensive thermal evaluation index such as SET* (Standard Effective Temperature) or PMV (Predicted Mean Thermal Value). It may also include operational settings for each space (e.g., cool zones and warm zones).

[0042] The spatial selection behavior model generation unit 13 generates a spatial selection behavior model from work style data, preference data, and spatial value data, which simulates which space each of multiple users will choose. The spatial selection behavior model may, for example, be a model that shows spatial selectivity. Spatial selectivity indicates the property that users can freely choose the space in which they work. The higher the spatial selectivity, the more freely users can choose a space, and the lower the spatial selectivity, the less freely users can choose a space. Spatial selectivity may also be quantified.

[0043] The spatial choice behavior model may be a conditional logit model. If the spatial choice behavior model is a conditional logit model, any factors that influence spatial choice behavior can be added.

[0044] As an example, the spatial selection behavior model may calculate the value of each space for each user, and the sum of the maximum spatial values ​​that the user can choose may be calculated as the objective function indicating spatial selectivity. For example, the spatial selection behavior model may be given factors such as the suitability of the activity and space, the degree of congestion, the distance traveled, and the thermal environment. The spatial selection behavior model generation unit 13 may use, for example, the objective function shown in equation (1) below. Equation (1) shows the objective function for maximizing the spatial value data.

number

[0045] Thus, the spatial selection behavior model generation unit 13 may generate a spatial selection behavior model using the suitability of the activity to the space, the distance traveled, the degree of congestion, and the thermal environment as objective functions. Furthermore, the spatial selection behavior model generation unit 13 may generate an agent model composed of an activity model, which is the result of a time-series simulation of the activity, and the spatial selection behavior model.

[0046] The spatial evaluation unit 14 evaluates the zoning plan of multiple spaces from a spatial selection behavior model. For example, the spatial evaluation unit 14 parameterizes the zoning plan from the type and area of ​​each space and uses these as design variables. In the example in Figure 1, the interior of building M is divided into multiple spaces S, a type is assigned to each space S, and for example, the spatial evaluation unit 14 changes the area of ​​the multiple spaces S by moving the boundary B between the multiple spaces S. However, this is just one example of parameterization, and any method of manipulating the two variables of space S, the type and area, is acceptable, and the method is not limited to the above.

[0047] The energy simulation model generation unit 15 generates an energy simulation model that simulates the thermal environment of the building and the energy consumption of the building. The energy efficiency evaluation unit 16 may, for example, generate an energy simulation model of the amount of energy consumed by equipment installed in the building and a time-series simulation of the thermal environment in the building. "Equipment installed in the building" refers to electrical equipment, such as air conditioning, lighting, and information equipment.

[0048] The energy simulation model generation unit 15 may create a model that performs time-series simulations of the energy consumption of electrical equipment and the thermal environment over a year. The objective function for energy consumption minimizes the energy consumption of the building. For example, the objective function for energy consumption minimizes the total amount of electricity consumed by electrical equipment over a year.

[0049] The energy simulation model generation unit 15 may use simulation tools such as EnergyPlus provided by the U.S. Department of Energy. The energy simulation model generation unit 15 may also input information about the building geometry, the thermal properties of the walls constituting the building, and the air conditioning system in advance, and create an energy simulation model based on that information.

[0050] Furthermore, the energy simulation model generation unit 15 may generate an energy simulation model from the number of users in each space and the operating schedule of electrical equipment, which are obtained from the agent model. In this case, the energy simulation model generation unit 15 may change the operating schedule of electrical equipment and the usage rate of electrical equipment according to the number of users in the space. In this case, it becomes possible to perform a simulation that is closer to the actual operating conditions of the building.

[0051] The energy efficiency evaluation unit 16 evaluates the energy efficiency of a building from an energy simulation model and a spatial selection behavior model. The energy efficiency evaluation unit 16 may also generate a graph showing the relationship between energy efficiency and spatial selectivity, for example, as shown in Figure 4.

[0052] The comfort evaluation unit 17 evaluates the user's thermal comfort from an energy simulation model. Thermal comfort is, for example, a mental state indicating satisfaction with the thermal environment. The comfort evaluation unit 17 evaluates the comfort of each user from, for example, time-series simulation data regarding the thermal environment of each space and the thermal preferences of the users using that space. The above time-series simulation data includes, for example, air temperature, radiant temperature, and humidity calculated at predetermined time intervals (e.g., every hour). The objective function for thermal comfort is, for example, to maximize the user's thermal comfort taking thermal preferences into account. The objective function for thermal comfort may, for example, be to maximize the percentage of users who were comfortable relative to the total number of occupants in all spaces over the year.

[0053] The search unit 18 parameterizes multiple spaces and searches for a layout in which at least one of the following is high: spatial evaluation, thermal comfort, and energy evaluation. "Spatial evaluation" is, for example, spatial selectivity. "Layout" refers to the arrangement of multiple spaces in a building. The search unit 18 evaluates the building layout based on the value of the objective function for maximizing spatial value data, the value of the objective function for maximizing thermal comfort, and the value of the objective function for minimizing the building's energy consumption. In other words, the search unit 18 evaluates the layout by taking into account the maximization of spatial value, the maximization of thermal comfort, and the minimization of the building's energy consumption assigned to each of the multiple spaces.

[0054] For example, as shown in Figures 4 and 5, the search unit 18 may search for and display building layouts based on the relationship between spatial selectivity and energy efficiency. Figures 4 and 5 show an example where the layout of building M, searched by the search unit 18, is displayed on the terminal T's display at point A on the graph showing the relationship between spatial selectivity and energy efficiency.

[0055] The search unit 18 determines, for example, which types of spaces to allocate to building M and to what extent, taking into account the relationship between spatial selectivity and energy efficiency. Figure 5 shows an example in which the first, second, and fifth spaces are allocated to the second floor of building M, and the second, third, and fourth spaces are allocated to the third floor of building M. The first space is a quiet space, the second space is a semi-quiet space, the third space is an open meeting space, the fourth space is a semi-closed meeting space, and the fifth space is a recharge space. However, Figure 5 is merely an example, and the search unit 18's exploration of the building M layout is not limited to the above example.

[0056] Next, with reference to Figure 6, an example of a design support method for evaluating the spatial zoning plan of a building using the design support system 1 will be described. The flowchart in Figure 6 shows an example of the steps of the design support method according to this embodiment. First, parameters of the spatial selection behavior model are determined based on pre-investigated data, and an energy simulation model of the building is created (step S1).

[0057] The aforementioned agent model consists, for example, an activity model that performs a time-series simulation of activities and a spatial choice behavior model that simulates spatial choice behavior based on activities at each computation step. As the activity model, the Markov chain model shown in Wang et al. (2011) may be used. In this case, the state transition probability matrix can be calculated from only the time proportion and duration data of the activities, making it possible to probabilistically determine the state of the current step from the state of the previous step.

[0058] As a spatial choice behavior model, the conditional logit model presented by Cha et al. (2017) may be used. In this case, any factors that influence spatial choice behavior can be added. For example, activity and space suitability, congestion level, travel distance, and thermal environment can be given as factors. Regarding activity and space suitability, as shown in Table 1 above, assumptions are made about what activities each space is designed for and how it will be used, based on the designer's design intent, the building owner / manager's operational intent, etc. Regarding the thermal environment mentioned above, as shown in Table 2 below, weights for selecting cool / normal / warm spaces for each preference may be assumed. [Table 2]

[0059] To determine the parameters of the agent model, the work style data collection unit 11 may collect user work style data through at least one of subjective and objective surveys, and the preference data collection unit 12 may collect user preference data through at least one of subjective and objective surveys. As mentioned above, for work style data, for example, the average start time of work, end time of work, percentage of time spent on major activities, and duration of work on a typical day may be collected through subjective surveys. To collect more accurate data to improve the prediction accuracy of the model, the work style data collection unit 11 may collect data on specific daily activities (what time the user arrives at work, what activities they do, with whom and where, and what time they leave work) over a period of about one week to one month. When the work style data collection unit 11 collects work style data through objective surveys, it is possible to accurately track when and where the user was by using at least one of the technologies of an AI camera and a beacon.

[0060] The preference data collection unit 12 collects information, for example, on preferences regarding the thermal environment (e.g., whether one prefers to work in a cool space or a warm space) through subjective surveys. Based on this data, the selection probability can be changed based on the thermal environment of each space when simulating with the agent model. The preference data collection unit 12 may also collect information on office spaces, environments, or furniture, such as whether one prefers enclosed or open spaces, or whether one prefers a window side. In this case, the collected information can be considered as parameters for the agent model.

[0061] In step S1, for example, the energy simulation model generation unit 15 may create a model that performs time-series simulations of energy consumption for air conditioning, lighting, and outlets, as well as the indoor thermal environment, over the course of a year. In this case, a simulation tool such as EnergyPlus provided by the U.S. Department of Energy may be used. The energy simulation model generation unit 15 may also create a model in advance by inputting information on the building geometry, the thermal properties of the walls, and the air conditioning system. Furthermore, the energy simulation model generation unit 15 may be configured to receive the number of occupants in each space and the operating schedules for air conditioning, lighting, and outlets based on the simulation results of the agent model.

[0062] In step S2, for example, the search unit 18 generates multiple layouts using an optimization algorithm. At this time, the search unit 18 may also generate multiple parameter sets related to the layouts using metaheuristics. The metaheuristics may be, for example, a genetic algorithm.

[0063] In step S3, for example, the spatial selection behavior model generation unit 13 simulates how multiple spaces are used in the spatial selection behavior model for each layout, generates usage data, and evaluates spatial selectivity. At this time, the spatial selection behavior model generation unit 13 combines the layout and the agent model to simulate the behavior of each individual user over a certain period of time, which is the evaluation period. At this time, by using the aforementioned agent model, the user's spatial selection behavior changes depending on the arrangement, area, and thermal environment settings of each type of space in each layout, and the number of people in each space and the usage data change. At this time, the spatial selectivity, which is the first objective function, is evaluated using the agent model.

[0064] In step S4, for example, the energy efficiency evaluation unit 16 evaluates the thermal environment and energy consumption using an energy simulation model based on the calculated usage data for all zones. A "zone" refers to, for example, a space. For example, the energy simulation model generation unit 15 provides the energy simulation model with the data on the number of occupants in each zone obtained by the agent model and performs an energy thermal environment simulation. At this time, the energy simulation model generation unit 15 may change the operating schedule and usage rate of air conditioning, lighting, and outlets, etc., according to the number of occupants. In this case, a simulation closer to the actual operating conditions of the building can be performed. Furthermore, when determining the control set values ​​for the thermal environment of each zone (for example, indoor air temperature set values), the thermal environment preferences (thermal preferences) of people occupying the target zone may be taken into consideration in the calculation step. In this case, it becomes easier to improve thermal comfort as a result of space selection behavior based on thermal preferences.

[0065] For example, the energy efficiency evaluation unit 16 evaluates thermal comfort and energy consumption based on the results of the simulation after receiving the above inputs. For thermal comfort, the comfort level of each person is evaluated based on time-series simulation data regarding the thermal environment of each zone (e.g., air temperature, radiant temperature, humidity, etc., at one-hour intervals) and the thermal environment preferences of the people in that zone at each calculation step. As mentioned above, the objective function for thermal comfort is to maximize the proportion of people who were comfortable relative to the total number of people in all zones over the year. For the objective function for energy consumption, it is to minimize the total amount of electricity consumed annually for air conditioning, lighting, and outlets.

[0066] In step S5, for example, the search unit 18 evaluates the layout based on the values ​​of the three objective functions obtained in step S4, and determines which layouts to carry over to the next optimization step (next generation) and which layouts to modify. Then, the search unit 18 performs a convergence check. If it determines that convergence has occurred, the series of steps of the design support method is completed. On the other hand, if it determines that convergence has not occurred, step S2 is executed again. In step S2, the search unit 18 may generate a new parameter set when performing a generation change. After that, steps S3 to S5 are executed, and steps S2 to S5 are repeated as needed, thereby updating the generations and searching for a layout with good objective function values. For example, when a predetermined number of generations is reached, or when the change in the objective function value becomes sufficiently small, the generation update is terminated, the convergence check becomes YES, and the series of steps of the design support method is completed.

[0067] Next, the steps of the modified design support method will be explained with reference to Figure 7. The modified design support method differs from the previously described design support method in that it has step S11, and steps S12 and S13 are provided instead of step S4. Steps S11 to S13 will be explained below.

[0068] In step S11, for example, the spatial selection behavior model generation unit 13 assigns air conditioning zones to the layout. The spatial selection behavior model generation unit 13 assigns air conditioning zones, which are control units of the air conditioning system, to the layout (spatial function zoning) generated by the optimization algorithm. For example, the spatial function zoning is identical to the air conditioning zoning (they correspond exactly one-to-one), but they do not have to be identical. One spatial function zone may contain multiple air conditioning zones, and one air conditioning zone may contain multiple spatial function zones. Furthermore, the spatial selection behavior model generation unit 13 can support the user's spatial selection behavior based on their thermal preferences by providing thermal environment settings (Cool / Neutral / Warm) to the assigned air conditioning zones.

[0069] In step S12, for example, the energy simulation model generation unit 15 performs an air conditioning load calculation based on usage data and determines the capacity of the air conditioning equipment for each air conditioning zone. The air conditioning load calculation may be performed, for example, using the energy simulation model described above.

[0070] In step S13, for example, the energy efficiency evaluation unit 16 evaluates the thermal environment and energy consumption using an energy simulation model based on the usage data and air conditioning system described above. In summary, the design support method according to the modified example can provide air conditioning zoning with an appropriate distribution that corresponds to the thermal environment desired by the user, thereby further enhancing user comfort. In addition, it can suppress the oversizing of air conditioning equipment, thereby optimizing capacity and reducing energy consumption.

[0071] Next, the effects and benefits obtained from the design support system 1 according to this embodiment will be described in more detail. As shown in Figures 1 and 2, the design support system 1 is used when planning the zoning of a building M having multiple spaces S that can be selected by multiple users. In the design support system 1, the work style data collection unit 11 collects data on the work styles of multiple users, and the preference data collection unit 12 collects data on the preferences of multiple users for the spaces S.

[0072] A spatial choice behavior model is created from data on work styles, preferences, and spatial value data (data on the value assigned to each space S), which shows which space S each user will choose. Multiple spaces S are then evaluated using this spatial choice behavior model. Therefore, by evaluating multiple spaces S based on the spatial choice behavior model created from user preferences, actual work styles, and the value of the spaces S themselves, it is possible to appropriately evaluate multiple spaces S based on information about when and which space a user chooses. Consequently, it becomes possible to zone the spaces S optimally according to the individual circumstances of multiple users, thereby increasing spatial selectivity while providing appropriate diversity to the spaces S. As a result, it is possible to increase users' self-efficacy and improve their intellectual productivity and satisfaction.

[0073] As mentioned above, preference data may include thermal preference data indicating the user's thermal preferences, and spatial value data may include the degree of fit of space S to the thermal preference data. In this case, by creating a spatial selection behavior model that takes thermal preference data into account, it becomes possible to zone space S in a way that takes the user's thermal preferences into account. Therefore, spatial selectivity can be further enhanced.

[0074] As mentioned above, the design support system 1 may include an energy simulation model generation unit 15 that generates an energy simulation model that simulates the thermal environment and energy consumption of building M, and an energy efficiency evaluation unit 16 that evaluates the energy efficiency of building M from the energy simulation model and the spatial selection behavior model. In this case, the energy efficiency of building M is evaluated from the energy simulation model that predicts the thermal environment and energy consumption of building M, and the spatial selection behavior model. Therefore, the energy consumption of building M can be reduced.

[0075] As mentioned above, the design support system 1 may include a comfort evaluation unit 17 that evaluates the user's thermal comfort from an energy simulation model. In this case, since the user's thermal comfort is evaluated from the energy simulation model, the comfort level based on the building's thermal environment can be improved.

[0076] As mentioned above, the design support system 1 may include a search unit 18 that parameterizes multiple spaces S and searches for a layout in which at least one of the spatial evaluation, thermal comfort, and energy evaluation is high. In this case, the search unit 18 can search for a layout in which at least one of the spatial evaluation, thermal comfort, and energy evaluation is high.

[0077] As mentioned above, the zoning plan may include a zoning plan for air conditioning systems installed in multiple spaces S. In this case, it becomes possible to zone the air conditioning system optimally according to the specific circumstances of each of the multiple users. More specifically, by performing air conditioning zoning simultaneously with spatial functional zoning in the optimization process, it is possible to provide air conditioning zoning with an appropriate distribution that corresponds to the thermal environment desired by the user, thereby further enhancing user comfort. In addition, it is possible to suppress the oversizing of air conditioning equipment, thereby optimizing capacity and reducing energy consumption.

[0078] The embodiments and modifications of the design support system and design support method relating to this disclosure have been described above. However, this disclosure is not limited to the embodiments or modifications described above. That is, it will be readily apparent to those skilled in the art that the present invention can be modified and changed in various ways within the scope of the gist described in the claims. In other words, the functions of each component of the design support system, as well as the content and sequence of the steps of the design support method, can be changed as appropriate within the scope of the gist described above. [Explanation of symbols]

[0079] 1...Design support system, 10...Design support program, 11...Work style data collection unit, 12...Preference data collection unit, 13...Spatial selection behavior model generation unit, 14...Spatial evaluation unit, 15...Energy simulation model generation unit, 16...Energy efficiency evaluation unit, 17...Comfort evaluation unit, 18...Exploration unit, 19...Display control unit, 20...Storage unit, A...Point, B...Boundary, M...Building, S...Space, T...Terminal.

Claims

1. A design support system that assists in zoning planning for a building having multiple spaces that can be selected by each of multiple users, A work style data collection unit that collects data on the work styles of multiple users, A preference data collection unit that collects preference data for the space of multiple users, A spatial selection behavior model generation unit generates a spatial selection behavior model, which is a model that simulates which space each of the multiple users will choose, based on the aforementioned work style data, the aforementioned preference data, and spatial value data, which is value data calculated for each of the multiple spaces. A spatial evaluation unit that evaluates zoning plans for multiple spaces from the spatial selection behavior model, Equipped with, Design support system.

2. The aforementioned preference data includes thermal preference data indicating the user's thermal preferences. The spatial value data includes the degree of fit of the space to the thermal preference data, The design support system according to claim 1.

3. An energy simulation model generation unit generates an energy simulation model that simulates the thermal environment of the building and the energy consumption of the building, An energy efficiency evaluation unit that evaluates the energy efficiency of the building from the energy simulation model and the spatial selection behavior model, Equipped with, A design support system according to claim 1 or claim 2.

4. The system includes a comfort evaluation unit that evaluates the user's thermal comfort from the aforementioned energy simulation model. The design support system according to claim 3.

5. A search unit that parameters multiple spaces and searches for a layout in which at least one of the spatial evaluation, thermal comfort, and energy evaluation is high, Equipped with, A design support system according to claim 1 or claim 2.

6. The zoning plan includes a zoning plan for air conditioning systems installed in multiple spaces. A design support system according to claim 1 or claim 2.

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