Design Support System

Abstract

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

Description

[Technical field]

[0001] The present disclosure relates to a design support system for zoning planning of a building having a plurality of spaces each of which is selectable by a plurality of users. [Background technology]

[0002] Patent Document 1 describes an office planning support system that includes 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 mimics the behavior of a user. The subjective survey system collects subjective survey data, and the objective survey system collects objective survey data. The objective survey data includes inter-organizational proximity, which is a total proximity requirement. The planning requirement extraction unit has a planning requirement generation unit. The planning requirement generation unit calculates a required area based on the subjective survey data and the objective survey data, and performs a stacking process that allocates floors to place each organization based on the inter-organizational proximity and the required area.

[0003] Patent Document 2 describes a design support device that supports the selection of office workspace layout candidates. The design support device includes an execution unit that simulates user behavior, a calculation unit that calculates an index related to the satisfaction of the work environment for each user, a selection unit that selects layout candidates using satisfaction information, and a generation unit that generates various information. The satisfaction level includes an index of physiological comfort. The selection unit presents office layouts that are optimal for the user who feels physiological comfort as selection candidates.

[0004] Patent Document 3 describes an air-conditioning control system suitable for free address offices. The air-conditioning control system includes a database that stores workers' preference data regarding thermal sensation and workers' scheduled attendance data on the day of air-conditioning control, and a setting means that sets an air-conditioning temperature distribution in the office space based on the preference data and the scheduled attendance data. The air-conditioning control system further includes a control means and a notification means. The control means controls the air-conditioning in the office space based on the air-conditioning temperature distribution, and the notification means notifies the workers of the air-conditioning temperature distribution. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Patent No. 6111238 [Patent Document 2] Patent Publication No. 2021-56811 [Patent Document 3] JP 2019-219097 A Summary of the Invention [Problem to be solved by the invention]

[0006] Meanwhile, in workplaces where multiple users work, free address systems are increasingly being introduced, allowing each user to choose the space they prefer. In such workplaces, it is necessary to provide appropriate diversity in the space and increase spatial selectivity, which is the property that allows users to freely select the space in which to work. Increasing spatial selectivity increases users' self-efficacy, leading to improved intellectual productivity and satisfaction.

[0007] An object of the present disclosure is to provide a design support system that can provide appropriate diversity in space and enhance spatial selectivity. [Means for solving the problem]

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

[0009] This design support system is used when making a zoning plan for a building having a plurality of spaces that can be selected by each of a plurality of users. In the design support system, a work style data collection unit collects work style data of a plurality of users, and a preference data collection unit collects preference data of the plurality of users for spaces. A space selection behavior model, which is a model showing which space each user will select, is created from the work style data, preference data, and space value data, which is data of value set for each space, and a plurality of spaces are evaluated using the space selection behavior model. Thus, by evaluating a plurality of spaces based on the space selection behavior model created from the user's preferences, the user's actual work style, and the value of the space itself, the plurality of spaces can be appropriately evaluated from information regarding which space the user will select at what time. Therefore, optimal space zoning according to the respective situations of a plurality of users is possible, and space selectivity can be increased while providing appropriate diversity to the space. As a result, the user's sense of self-efficacy can be increased, and the user's intellectual productivity and satisfaction can be increased.

[0010] (2) In the above (1), the preference data may include thermal preference data indicating the user's thermal preference, and the space value data may include the suitability of the space for the thermal preference data. In this case, the space selection behavior model is created taking into account the thermal preference data, making it possible to zone the space taking into account the user's thermal preference. Therefore, the space selectivity can be further improved.

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

[0012] (4) In the above (3), the design support system may include a comfort evaluation unit that evaluates the thermal comfort of the user from the energy simulation model. In this case, since the thermal comfort of the user is evaluated from the energy simulation model, it is possible to improve comfort based on the thermal environment of the building.

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

[0014] (6) In any of the above (1) to (5), the zoning plan may include zoning plans for air conditioning systems installed in multiple spaces. In this case, optimal zoning of the air conditioning system according to the respective situations of multiple users is possible. Effect of the Invention

[0015] According to the present disclosure, it is possible to provide appropriate diversity in space and improve spatial selectivity. [Brief description of the drawings]

[0016] [Figure 1] FIG. 1 is a diagram showing an example of a zoning plan. [Diagram 2] FIG. 2 is a block diagram showing a functional configuration of the design support system according to the embodiment. [Diagram 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. [Diagram 5] FIG. 5 is a diagram showing an example of a zoning plan. [Figure 6] FIG. 6 is a flowchart showing an example of steps of a design support method according to the embodiment. [Figure 7] FIG. 7 is a flowchart showing an example of steps of a design support method according to the modified example. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0017] Hereinafter, an embodiment of the 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 embodiment, but is indicated 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 given the same reference numerals, and duplicated descriptions are omitted as appropriate. The drawings may be partially simplified or exaggerated for ease of understanding, and the dimensional ratios and the like are not limited to those shown in the drawings.

[0018] For example, in an office plan, the spatial zoning within a building is determined by the designer. A "building" refers to something that is built for people to work or study. A building has multiple spaces. A "space" refers to a location in a building where a user performs an activity. A "space" refers to, for example, a room or a section separated by a partition or the like. A "user" refers to a person who uses a building.

[0019] "Zoning" refers to what kind of space is to be arranged where and with what area in a building. "Zoning plan" refers to a plan for zoning. As shown in FIG. 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 move a boundary B between multiple spaces S to change the area of ​​the space S. The zoning plan may include a zoning plan for an air conditioning system to be installed in the multiple spaces S.

[0020] In the past, zoning involved analyzing the results of surveys on users' working styles, and then designing the space while sorting out the requirements based on the designer's own experience and thinking. However, with this method, the relationship between the input data on working styles and the output plan requirements and specific zoning layouts was not necessarily clear logically or quantitatively, and it was unclear whether the design was optimal for the user's working styles.

[0021] Particularly in recent years, flexible workplaces have become more widespread. Flexible workplaces aim to provide a work style in which users can choose the most suitable place to work according to their activities (e.g., work) and their preferences. An activity refers to a user's activities, such as document creation, meetings, and breaks. In particular, input data such as data on working styles is considered to be increasingly important in the design of flexible workplaces.

[0022] In light of the above demands, there is a need for a method to numerically optimize zoning plans using data on users' work styles as input. In a flexible workplace, users must choose a space. At this time, it is important that a space that matches the user's activities and preferences exists within a certain distance and is available (e.g., there is 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 select the space in which to work.

[0023] The usage status of each space affects the energy consumption of the building, so a method of optimizing the energy consumption from the viewpoint of minimizing the energy consumption is required. The design support system according to the present embodiment minimizes the air conditioning energy, which accounts for a large proportion of the energy consumption during the operation of the building, by taking into account the thermal preference of the user, which is the preference for the thermal environment, and the space selection behavior based on the thermal preference. For example, in a flexible workplace, by gathering users with similar thermal preferences in one air conditioning zone, the thermal comfort of the users can be improved and energy consumption can be suppressed. In the present embodiment, by focusing on the selection behavior of the users and providing appropriate diversity in the space to increase the space selectivity, the user's self-efficacy can be increased, and intellectual productivity and satisfaction can be improved.

[0024] Fig. 2 is a block diagram showing a functional configuration of a design support system 1 as an example of this embodiment. The design support system 1 supports a zoning plan for a building having a plurality of spaces that can be selected by each of a plurality of users. As shown in Fig. 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 that is installed in the terminal T and can be operated by a user. The type of the application is not particularly limited.

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

[0026] Terminal T includes a processor (e.g., a CPU) that executes an operating system and software (applications), a main memory unit configured with ROM and RAM, an auxiliary memory unit configured with flash memory or the like, a communication control unit configured with a wireless communication module or the like, an input device such as a button, and an output device 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 a memory unit.

[0027] In the terminal T, a design support program 10 is executed as an application. The design support program 10 is, for example, an application executed in the terminal T. However, at least a part of the functions of the design support program 10 may be executed by a server external to the terminal T. The design support program 10 may be downloaded from the server.

[0028] Each function of the design support system 1 is realized by reading a design support program 10 into a processor or main memory and executing the design support program 10. The processor operates the communication control unit, input device, or output device described above in accordance with the design support program 10, and reads and writes data in the memory. Data used for processing by the terminal T is stored in the memory.

[0029] The design support system 1 may be a distributed processing system composed of a plurality of computers, or may be a client-server system or a cloud system. The design support program 10 includes, for example, a main module, a data acquisition module, a judgment module, and an output module. Each functional element of the design support program 10 functions by executing the data acquisition module, the judgment module, and the output module. The design support program 10 may be provided by being fixedly recorded on a tangible storage medium such as a CD-ROM, a DVD-ROM, or a semiconductor memory, for example. The design support program 10 may 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 space selection behavior model generation unit 13, a space 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 memory 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 the terminal T. The display control unit 19 displays various screens of the design support program 10 on the display of the terminal T in accordance with, for example, commands from functions other than the display control unit 19 of the design support program 10. For example, the display control unit 19 is a function that manages screen display on the display of the terminal T. The memory unit 20 is a function that stores data input / output to / from the terminal T by the design support program 10.

[0032] The work style data collection unit 11 collects work style data of multiple users. Hereinafter, "work style data" may be referred to as "work style data." The work style data collection unit 11 obtains work style data of multiple users by, for example, collecting the results of a questionnaire survey of multiple users. The user work style data includes, for example, the ratio of users inside a building, and data on where in the building the user is performing what activity and for how long. In this case, the user work style data includes what kind of work the user performed in what space and for how long.

[0033] The user's work style data may include, for example, at least one of the following (on an average day): work start time, work end time, activity time ratio, and activity duration. The user's work style data may also include data on the user's daily activities (what time they came to work, what activities they did with whom and where, and what time they left work) within a certain period (for example, about one week to one month).

[0034] The working style data collection unit 11 collects the user's working style data, for example, by a subjective survey. However, the working style data collection unit 11 may collect the user's working style data by an objective survey. The working style data collection unit 11 may collect the working style data by acquiring the user's position and activity inside the building for each space and each time by at least one of a beacon and a camera, for example. In this way, the working style data collection unit 11 can collect the user's working style data in various ways.

[0035] The preference data collection unit 12 collects preference data of a plurality of users with respect to a space. The preference data includes, for example, thermal preference data indicating the thermal preferences of the users. Hereinafter, the "preference data" may be referred to as "preference data." The preference data collection unit 12 obtains the preference data of the plurality of users by, for example, collecting the results of a questionnaire given to the plurality of users.

[0036] The preference data includes, for example, data on a space inside a building that the user likes. The thermal preference data includes data on the user's preference for thermal environments. For example, as shown in FIG. 3, the thermal preference data includes data indicating whether a warm environment or a cool environment is preferred. The thermal preference data may be an average value or range of a temperature that the user likes (for example, 23° C.). However, the thermal preference data is not limited to this, and may include data on whether the user likes or dislikes the environment, obtained under an environment where a physical environmental measurement is performed.

[0037] The preference data may include data indicating whether a closed space or an open space is preferred. The preference data may include data indicating whether a window side or a corridor side is preferred. The preference data may include data indicating whether a narrow space or a wide space is preferred. The preference data may include data indicating whether a bright space or a dark space is preferred. The preference data may include data indicating whether a lively space or a quiet space is preferred. The preference data may include data indicating preferences for each activity. The preference data collection unit 12 collects the user's preference data by, for example, a subjective survey. However, the preference data collection unit 12 may also collect the user's preference data by an objective survey.

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

[0039] Table 1 below shows examples of space types and their compatibility with activities. Routine, focus, creative, collaborative, discussion, coordination, online group, recharge, and lunch in Table 1 are examples of activities. The higher the relationship in Table 1, the higher the compatibility between the space type and the activity. For example, when the activity is "focus," it has the highest compatibility with quiet spaces ("1") and the lowest compatibility with closed meeting spaces and semi-closed meeting spaces ("0"). When the activity is "coordination," it has the highest compatibility with closed meeting spaces ("1") and the lowest compatibility with quiet spaces, semi-quiet spaces, and recharge spaces ("0"). [Table 1]

[0040] The space value data includes, for example, a travel distance. The travel distance is, for example, a distance from an entrance / exit of a building. When the space value data includes the travel distance, zoning that takes into account the user's travel distance becomes possible. The space value data may include, for example, a congestion degree. The congestion degree indicates, for example, the rate at which a space is congested. The congestion degree may also be an average value of the ratio of the actual number of users to the capacity of the space. When the space value data includes the congestion degree, zoning that takes into account the degree of congestion in the space becomes possible.

[0041] The space value data may include a thermal environment. The thermal environment is, for example, room temperature (indoor air temperature). However, the thermal environment does not have to be room temperature, and may be something that affects the thermal sensation felt by the user when using the space, or a thermal preference. Furthermore, the thermal environment may be the surface temperatures, radiant temperature and operative temperature of the walls, floors and ceilings, as well as SET* (Standard Effective Temperature) or PMV (Predicted Mean Thermal Sensation) which are comprehensive thermal evaluation indices. It may also be the operational settings of each space (for example, cool zone, warm zone, etc.).

[0042] The space selection behavior model generation unit 13 generates a space selection behavior model that is a model that simulates which space each of a plurality of users selects from the work style data, the preference data, and the space value data. The space selection behavior model may be, for example, a model that indicates space selectivity. Space selectivity indicates the property that a user can freely select a space to work in. Higher space selectivity indicates that a user can freely select a space, and lower space selectivity indicates that a user cannot freely select a space. Space selectivity may be quantified.

[0043] The spatial choice behavior model may be a conditional logit model. When the spatial choice behavior model is a conditional logit model, any factor that affects the spatial choice behavior can be added.

[0044] As an example, the space selection behavior model may calculate the value of each space for each user, and calculate a numerical value obtained by adding up the maximum space value that the user can select as an objective function indicating space selectivity. For example, the space selection behavior model may be given the suitability of the activity and the space, the degree of congestion, the travel distance, and the thermal environment as factors. The space selection behavior model generation unit 13 may use, for example, the objective function shown in the following formula (1). Formula (1) shows the objective function for maximizing the space value data.

number

[0045] In this way, the space selection behavior model generating unit 13 may generate a space selection behavior model using the suitability of the activity and the space, the movement distance, the congestion degree, and the thermal environment as objective functions. Furthermore, the space selection behavior model generating unit 13 may generate an agent model composed of an activity model and a space selection behavior model that are the results of a time series simulation of the activity.

[0046] The space evaluation unit 14 evaluates the zoning plan for the multiple spaces from the space selection behavior model. For example, the space evaluation unit 14 parameterizes the zoning plan from the type and area of ​​each space, and sets them as design variables. In the example of FIG. 1, the inside of a building M is divided into multiple spaces S, a type is set for each space S, and, for example, the space evaluation unit 14 changes the areas 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 can be used that manipulates the two variables of the type and area of ​​the space S, 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 generate, for example, the amount of energy consumed by equipment installed in the building and a time series simulation of the thermal environment in the building as the energy simulation model. The "equipment installed in the building" is, for example, electrical equipment including air conditioning, lighting, and information equipment.

[0048] The energy simulation model generating unit 15 may generate a model for performing a time series simulation of the energy consumption of the electrical appliances and the thermal environment over a year. The objective function for the energy consumption is to minimize the energy consumption of the building. For example, the objective function for the energy consumption is to minimize the total value of the annually integrated power consumption required by the electrical appliances.

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

[0050] The energy simulation model generation unit 15 may generate an energy simulation model from the number of users of each space obtained from the agent model and the operation schedule of the electrical equipment. In this case, the energy simulation model generation unit 15 may change the operation schedule of the electrical equipment and the usage rate of the electrical equipment depending on the number of users of the space. In this case, it is possible to perform a simulation close to the actual operating situation of the building.

[0051] The energy efficiency evaluation unit 16 evaluates the energy efficiency of the building based on the energy simulation model and the space selection behavior model. The energy efficiency evaluation unit 16 may generate a graph showing the relationship between energy efficiency and space selectivity, as shown in FIG. 4, for example.

[0052] The comfort evaluation unit 17 evaluates the thermal comfort of the user from the energy simulation model. Thermal comfort is, for example, a state of mind that indicates satisfaction with a 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 user who uses the space. The above-mentioned time-series simulation data includes, for example, air temperature, radiant temperature, and humidity calculated every predetermined time (for example, every hour). The objective function of thermal comfort, for example, maximizes the thermal comfort of the user taking into account the thermal preferences. For example, the objective function of thermal comfort may maximize the ratio of users who felt comfortable to the total number of occupants in all spaces over a year.

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

[0054] For example, as shown in Figures 4 and 5, the search unit 18 may search for and display the layout of a building based on the relationship between spatial selectivity and energy efficiency. Figures 4 and 5 show an example in which the layout of a building M searched for by the search unit 18 is displayed on the display of a terminal T at point A on a graph showing the relationship between spatial selectivity and energy efficiency.

[0055] The search unit 18 determines how many spaces of each type are to be allocated to the building M, taking into account the relationship between space selectivity and energy efficiency, for example. FIG. 5 shows an example in which the first space, the second space, and the fifth space are allocated to the second floor of the building M, and the second space, the third space, and the fourth space are allocated to the third floor of the 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, FIG. 5 is merely an example, and the search for the layout of the building M by the search unit 18 is not limited to the above example.

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

[0057] The agent model described above is composed of, for example, an activity model that performs a time series simulation of activities, and a spatial selection behavior model that simulates spatial selection behavior based on activities at each calculation step. The activity model may be a Markov chain model shown in Wang et al. (2011). In this case, a state transition probability matrix can be calculated only from the data on the time ratio and duration of activities, making it possible to stochastically 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 shown in Cha et al. (2017) may be used. In this case, any factors that affect spatial choice behavior can be added. For example, suitability of the activity and space, congestion, travel distance, and thermal environment are given as factors. For the suitability of the activity and space, as shown in Table 1 above, it is assumed what activity each space is designed for and how it is used based on the design intention of the designer and the operational intention of the building owner / manager. For the thermal environment above, weights for selecting cool / normal / warm spaces for each preference may be assumed, as shown in Table 2 below. [Table 2]

[0059] In order to determine the parameters of the agent model, the working style data collection unit 11 may collect the user's working style data by at least one of a subjective survey and an objective survey, and the preference data collection unit 12 may collect the user's preference data by at least one of a subjective survey and an objective survey. As described above, the working style data may be collected by a subjective survey, for example, the start time of work, the end time of work, the time ratio of major activities, and the duration in an average day. When collecting more accurate data to improve the prediction accuracy of the model, the working style data collection unit 11 may collect data such as specific daily activities (what time did you come to work, what kind of activity did you do with whom and where, and what time did you leave work) for a period of about one week to one month. When the working style data collection unit 11 collects the working style data by an objective survey, by using at least one of the technologies of an AI camera and a beacon, it is possible to accurately track when and where the user was.

[0060] The preference data collection unit 12 collects information on preferences for thermal environments (whether one likes to work in a cool space or a warm space, etc.) through a subjective survey, for example. Based on this data, when simulating with the agent model, the selection probability can be changed based on the thermal environment of each space. The preference data collection unit 12 may also collect information on the office space, environment, or fixtures, such as whether one prefers a closed / open space, whether one prefers a window seat, etc. In this case, the collected information can be considered as a parameter of the agent model.

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

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

[0063] In step S3, for example, the space selection behavior model generation unit 13 simulates the usage of multiple spaces in the space selection behavior model for each layout to generate usage data and evaluate space selectivity. At this time, the space selection behavior model generation unit 13 combines the layout with an agent model and simulates the behavior of each user during a certain evaluation period. At this time, by using the above-mentioned agent model, the user's space selection behavior changes depending on the settings of the layout, area, and thermal environment of each type of each layout, and the number of people in each space and the usage data change. At this time, the space 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 the energy consumption in the energy simulation model based on the calculated usage data in all zones. The "zone" indicates, for example, a space. For example, the energy simulation model generation unit 15 performs an energy thermal environment simulation by providing the data on the number of people in each zone obtained by the agent model to the energy simulation model. At this time, the energy simulation model generation unit 15 may change the operation schedule and the usage rate of air conditioning, lighting, outlets, etc. according to the number of people in the room. In this case, a simulation closer to the actual operation situation of the building can be performed. In addition, when determining the control setting value (for example, the indoor air temperature setting value) regarding the thermal environment of each zone, the control value may be determined in the calculation step by taking into account the thermal environment preference (thermal preference) of the person in the target zone. In this case, it is possible to easily improve thermal comfort as a result of the space selection behavior based on the thermal preference.

[0065] For example, the energy efficiency evaluation unit 16 evaluates thermal comfort and energy consumption from the results of simulation using the above inputs. For thermal comfort, the comfort of each person is evaluated based on the time-series simulation data (e.g., air temperature, radiant temperature, humidity, etc., every hour) regarding the thermal environment of each zone and the thermal environment preferences of the people in the zone at each calculation step. As described above, the objective function regarding thermal comfort may be, for example, maximizing the ratio of people who felt comfortable to the total number of people in all zones over the year. The objective function regarding energy consumption may be, for example, minimizing the total value of the annual accumulated power consumption required 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 the layout to be passed on to the next step (next generation) of optimization, the layout to be mutated, etc. Then, the search unit 18 performs a convergence judgment. If it is judged that the layout has converged, a series of steps of the design support method is completed. On the other hand, if it is judged that the layout has not converged, step S2 is executed again. In step S2, the search unit 18 may generate a new parameter set when changing the generation. Thereafter, steps S3 to S5 are executed, and steps S2 to S5 are repeated as necessary, so that the generation is updated and a layout with a good objective function value can be searched for. 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 judgment becomes YES, and a series of steps of the design support method is completed.

[0067] Next, the steps of the design support method according to the modified example will be described with reference to Fig. 7. The design support method according to the modified example differs from the above-described design support method in that it has step S11 and provides steps S12 and S13 instead of step S4. Steps S11 to S13 will be described below.

[0068] In step S11, for example, the space selection behavior model generation unit 13 assigns air conditioning zones to the layout. The space 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 space function zoning is the same as the air conditioning zoning (completely one-to-one correspondence), but it does not have to be the same. One space function zone may include multiple air conditioning zones, and one air conditioning zone may include multiple space function zones. In addition, the space selection behavior model generation unit 13 can support space selection behavior based on the user's 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 the usage data and determines the capacity of the air conditioning equipment for each air conditioning zone. The air conditioning load calculation may be performed using, for example, the above-mentioned energy simulation model.

[0070] In step S13, for example, the energy efficiency evaluation unit 16 evaluates the thermal environment and energy consumption with an energy simulation model based on the above-mentioned usage data and the air conditioning system. As described above, the design support method according to the modified example can provide air conditioning zoning with an appropriate distribution corresponding to the thermal environment desired by the user, and can further improve the comfort of the user. In addition, it is possible to prevent over-designing the capacity of the air conditioning equipment (oversizing), optimize the capacity, and reduce energy consumption.

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

[0072] A space selection behavior model, which is a model showing which space S each user will select, is created from data on work styles, data on preferences, and space value data, which is data on values ​​set for each space S, and multiple spaces S are evaluated using the space selection behavior model. Thus, by evaluating multiple spaces S based on the space selection behavior model created from the user's preferences, the user's actual work style, and the value of the space S itself, multiple spaces S can be appropriately evaluated from information regarding when and which space the user will select. Therefore, optimal zoning of the space S according to the respective situations of multiple users is possible, and it is possible to increase space selectivity while providing appropriate diversity to the space S. As a result, it is possible to increase the user's self-efficacy and increase the user's intellectual productivity and satisfaction.

[0073] As described above, the preference data may include thermal preference data indicating the user's thermal preference, and the space value data may include the suitability of the space S to the thermal preference data. In this case, the space selection behavior model is created taking into account the thermal preference data, making it possible to zone the space S taking into account the user's thermal preference. Therefore, the space selectivity can be further improved.

[0074] As described 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 of the building M and the energy consumption of the building M, and an energy efficiency evaluation unit 16 that evaluates the energy efficiency of the building M from the energy simulation model and the space selection behavior model. In this case, the energy efficiency of the building M is evaluated from the energy simulation model and the space selection behavior model that predict the thermal environment of the building M and the energy consumption of the building M. Therefore, the energy consumption of the building M can be reduced.

[0075] As described above, the design support system 1 may include a comfort evaluation unit 17 that evaluates the thermal comfort of the user from the energy simulation model. In this case, since the thermal comfort of the user is evaluated from the energy simulation model, it is possible to improve the comfort based on the thermal environment of the building.

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

[0077] As mentioned above, the zoning plan may include a zoning plan for an air conditioning system to be installed in multiple spaces S. In this case, it becomes possible to optimally zone the air conditioning system according to the respective situations of multiple users. More specifically, by simultaneously performing air conditioning zoning in addition to 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, and to further improve user comfort. In addition, it is possible to prevent over-designing the capacity of air conditioning equipment (oversizing), optimize capacity, and reduce energy consumption.

[0078] The above describes the embodiments and modifications of the design support system and design support method according to the present disclosure. However, the present disclosure is not limited to the above-described embodiments or modifications. In other words, it is easily recognized by those skilled in the art that the present invention can be modified and changed in various ways within the scope of the gist of the claims. In other words, the functions of the components of the design support system and the contents and order of the steps of the design support method can be modified as appropriate within the scope of the above gist. [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...search unit, 19...display control unit, 20...memory unit, A...point, B...boundary, M...building, S...space, T...terminal.

Claims

1. A design support system for supporting a zoning plan for a building having a plurality of spaces selectable by each of a plurality of users, comprising: A work style data collection unit that collects work style data of a plurality of users; A preference data collection unit that collects preference data of a plurality of users with respect to the space; a space selection behavior model generation unit that generates a space selection behavior model that is a model that simulates which space each of the plurality of users will select from the work style data, the preference data, and space value data that is value data calculated for each of the plurality of spaces; and a space evaluation unit that evaluates zoning plans for a plurality of the spaces based on the space choice behavior model; Equipped with Design support system.

2. the preference data includes thermal preference data indicative of thermal preferences of the user; the space value data includes a fit of the space to the thermal preference data; The design support system according to claim 1 .

3. an energy simulation model generation unit that 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 based on the energy simulation model and the space selection behavior model; Equipped with The design support system according to claim 1 or 2.

4. A comfort evaluation unit that evaluates the thermal comfort of a user from the energy simulation model. The design support system according to claim 3.

5. a search unit that parameterizes a plurality of the spaces and searches for a layout that has a high spatial evaluation, a high thermal comfort evaluation, and an energy evaluation; Equipped with The design support system according to claim 1 or 2.

6. The zoning plan includes zoning plans for air conditioning systems to be installed in the plurality of spaces, The design support system according to claim 1 or 2.

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