JP5421847B2 - Prediction display server and prediction display system - Google Patents

Description

  The present invention relates to a prediction display server and a prediction display system.

  Conventionally, a management system that encourages users to reduce energy consumption by measuring energy consumption such as electricity, gas, and water inside buildings such as office buildings and factories and displaying the measurement results on the screen. Is known (see, for example, Patent Document 1).

  Furthermore, in order to encourage the user to reduce energy consumption, it is desirable not only to measure and display energy consumption, but also to estimate future energy consumption and energy creation.

  For example, Patent Document 2 describes that the solar radiation intensity for each geographical location is predicted based on the average time-dependent solar radiation intensity for each weather condition and the weather condition forecast stored in a database.

  Patent Document 3 describes that the amount of photovoltaic power generation on the next day is estimated by estimating the sunshine hours based on conditions such as weather forecasts and seasons.

JP 2007-133469 A JP 2005-318901 A JP 2010-16999 A

  However, the configurations of Patent Documents 1 to 3 described above do not present a specific action pattern to the user. For this reason, even if the energy consumption predicted value and the energy creation predicted value are calculated, there is a problem that it is difficult to understand what action the user should take based on this value.

  Therefore, an object of the present invention is to provide a predictive display server in which a user can easily take a specific action, and a predictive display system including the predictive display server.

  In order to achieve the above object, the prediction display server of the present invention is a prediction display server that predicts and displays energy consumption in a building, and includes past weather information and energy consumption corresponding to the past weather information. A storage unit that stores actual values; an analysis mechanism that analyzes past behavior patterns of users based on the actual energy consumption values; and corresponding to future weather information based on the analyzed past behavior patterns A prediction mechanism that predicts a plurality of future behavior patterns of the user, an energy prediction unit that has a consumption prediction mechanism that predicts an energy consumption prediction value corresponding to each of the plurality of future behavior patterns, and Is provided.

  In addition, the storage unit further stores an energy creation performance value corresponding to the past weather information, and the energy prediction unit further includes a creation prediction mechanism that predicts an energy creation prediction value corresponding to future weather information. Can have.

  Furthermore, the energy prediction unit further includes a balance prediction mechanism that calculates a future energy balance prediction value corresponding to each of the plurality of future behavior patterns based on the energy consumption prediction value and the energy creation prediction value. be able to.

  And the said analysis mechanism of the said action prediction part can estimate the presence or absence of the user for every divided time slot | zone based on the said energy consumption performance value.

  In addition, a mode switching unit that selects the plurality of future behavior patterns according to a specific behavior mode selected by the user can be further provided.

  Furthermore, the mode switching unit can have, as the behavior mode, an economic mode that prioritizes cost suppression, a comfort mode that prioritizes comfort, and a normal mode that harmonizes cost suppression and comfort.

  The mode switching unit may include an account setting mechanism that can change the setting of the behavior mode for each individual user.

  In addition, the analysis mechanism of the energy prediction unit can analyze the past behavior pattern of the user individual based on the movement locus of the identification tag possessed by the user individual.

  The energy prediction unit may further include an essential condition setting mechanism that sets an indispensable condition that cannot be changed in common for all behavior patterns.

  Further, the storage unit stores past behavior patterns for each room, the behavior prediction unit predicts a plurality of future behavior patterns for each room, and the energy prediction unit stores a plurality of future energy consumption prediction values for each room. Can be predicted for each.

  The predictive display system of the present invention is a predictive display system for displaying energy consumption in a building on a display means, measuring means for measuring the energy consumption of equipment arranged in the building, and the vicinity of the building Weather forecasting means for forecasting future weather information, communication means for obtaining the weather information from the weather forecasting means, any of the prediction display servers described above, and the forecasted for each of the plurality of future behavior patterns Display means for displaying a predicted energy balance.

  Thus, the prediction display server of the present invention is a prediction display server that predicts and displays energy consumption in a building, and includes past weather information and an energy consumption actual value corresponding to the past weather information. A storage unit for storing; an analysis mechanism for analyzing a user's past behavior pattern based on an actual energy consumption value; and a plurality of future user information corresponding to future weather information based on the analyzed past behavior pattern A behavior prediction unit that predicts a behavior pattern, and an energy prediction unit that has a consumption prediction mechanism that predicts an energy consumption prediction value corresponding to each of a plurality of future behavior patterns.

  For this reason, the user can know a plurality of future behavior patterns and predicted energy consumption values corresponding to the future behavior patterns according to future weather information. You can choose.

  In addition, the storage unit further stores the energy creation performance value corresponding to the past weather information, and the energy prediction unit further includes a creation prediction mechanism that predicts the energy creation prediction value corresponding to the future weather information. Since the energy creation predicted value can be known according to the weather information, a specific action pattern can be selected in consideration of the energy creation predicted value.

  Furthermore, the energy prediction unit may further include a balance prediction mechanism that calculates a future energy balance prediction value corresponding to each of a plurality of future behavior patterns based on the energy consumption prediction value and the energy creation prediction value.

  For this reason, the user can know a plurality of future behavior patterns and corresponding energy balance predicted values according to future weather information. You can choose.

  And the analysis mechanism of an action prediction part can presume a user's action pattern by a simple method by estimating the presence or absence of a user for every divided time slot based on an energy consumption performance value.

  In addition, by further including a mode switching unit that selects a plurality of future behavior patterns according to a specific behavior mode selected by the user, a behavior pattern adapted to the user's preference can be predicted.

  Further, the mode switching unit has, as the behavior mode, an economic mode that prioritizes cost control, a comfort mode that prioritizes comfort, and a normal mode that harmonizes cost control and comfort, so that each user's preference Can be classified and presented from an easy-to-understand viewpoint.

  Since the mode switching unit has an account setting mechanism that can change the setting of the behavior mode for each individual user, the behavior pattern can be selected on an individual basis, so that the behavior pattern adapted to the user's preference can be predicted.

  In addition, the analysis mechanism of the energy prediction unit can capture the user's individual behavior pattern reliably and easily by analyzing the user's past behavior pattern based on the movement trajectory of the identification tag possessed by the user.

  In addition, since the energy predicting unit further has an indispensable condition setting mechanism for setting an indispensable condition that cannot be changed in common for all action patterns, it is possible to set the indispensable condition regardless of a specific action mode. Predict behavior patterns that suit your preferences.

  Furthermore, the storage unit stores past behavior patterns for each room, the behavior prediction unit predicts a plurality of future behavior patterns for each room, and the energy prediction unit predicts a plurality of predicted future energy consumption values for each room. By doing so, it is possible to predict the predicted energy consumption more accurately.

  The predictive display system of the present invention is a predictive display system for displaying energy consumption in a building on a display means, a measuring means for measuring energy consumption of equipment arranged in the building, and a future in the vicinity of the building. Displays weather forecasting means for forecasting weather information, communication means for obtaining weather information from the weather forecasting means, one of the above-described forecast display servers, and energy balance forecast values predicted for each of a plurality of future behavior patterns Display means.

  For this reason, the user can know a plurality of future behavior patterns and corresponding energy balance predicted values according to future weather information, and therefore selects a favorite behavior pattern in consideration of the energy balance predicted values. be able to.

It is a block diagram explaining the structure of the prediction display server of this invention. It is explanatory drawing explaining the whole structure of a prediction display system. It is a block diagram explaining the detail of the structure by the side of the building of a prediction display system. It is a flowchart explaining the whole flow of a prediction display process. It is a flowchart explaining the flow of an action analysis process. It is a flowchart explaining the flow of an action prediction process. It is an image figure explaining the result of a prediction display process. It is an image figure explaining the result of the prediction display process at the time of changing a setting for every room.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

(overall structure)
First, the whole structure of the prediction display system S of this invention is demonstrated using FIG.

  The prediction display system S includes a plurality of houses H1-HX as a building, a weather information server 2 as a weather prediction unit that predicts weather information, a prediction display server 3 that predicts and displays energy consumption in the building, And a communication network N for connecting them to each other.

  The weather information server 2 predicts future weather information in the vicinity of the building based on ground weather, marine weather, high-rise weather, radar, weather satellites, etc., and predicts the predicted weather information via the communication network N on the user side. Delivered to the display server 3 and the house H1-HX.

  The distributed weather information includes precipitation, temperature, sunshine duration, wind direction and wind speed, snow cover, cloud cover, weather, solar radiation, humidity, etc. predicted every hour or three hours. The weather is classified into clear, clear, light clouds, cloudy, rain, snow, etc. according to the cloud coverage ratio.

  Moreover, as shown in FIG. 1, the house H1-HX as a building includes an energy consumption measuring means 11 as a measuring means, a router 15 and a gateway 16 as communication means, a display monitor 20 as a display means, Etc. are mainly provided.

(Device configuration)
Hereinafter, a specific configuration of the device installed on the house H side as the building will be described in detail with reference to FIG.

  Electricity is supplied to the house H through the grid power network E, and the amount of power is measured by the power meter E1. Similarly, gas and water are supplied to the house H through gas pipes and water pipes of the grid infrastructure network G, and the amount of gas and the amount of water are measured by the gas / water meter G1.

  Further, the house H includes a solar power generation device 50 as a distributed power generation device, and a storage battery 60 as a power storage device that temporarily stores electric power.

  In the house H, various energy consuming devices 7A-7E are installed. For example, as a power load device, there are an air conditioner (7A), a lighting device (7B), and a home appliance (7C). Moreover, there exist a cooking load (7D) and a hot water supply load (7E) as a gas load apparatus. The hot water supply load (7E) is also a water load device that consumes water.

  And the energy consumption measuring means 11 is attached to the electric power load apparatus (7A-7C) as these energy consuming apparatuses in order to measure an electric power consumption for every apparatus.

  As this energy consumption measuring means 11, there can be used one that is plugged into a power outlet provided on the wall of the house H, or one that is plugged into a ceiling light or pendant light attached to the ceiling. The energy consumption measuring means 11 measures a current value every 10 seconds, temperature, humidity, gas usage, water usage, etc. as energy consumption.

  Furthermore, the distribution board measuring device 12 is connected to the distribution board 120 as the energy consumption measuring means of the core part. The distribution board measuring device 12 measures a main current value, main voltage value, solar current value, branch circuit current value, etc. every 10 seconds.

  Although not shown in the figure, the distribution board measuring device 12 includes an external measuring instrument for measuring the amount of power of the main trunk 120a, and an output measuring instrument installed in accordance with the number of branch trunks 120b,. And a measuring instrument for measuring the electric energy of each of the auxiliary wirings 120c and 120d.

  In addition, although not shown, in the house H of the present embodiment, a thermohygrometer for measuring temperature and humidity is installed for each room in order to measure comfort. It is preferable to install at least one thermohygrometer on the upper side and the lower side in the room so that the temperature unevenness in the room can be measured.

  And the measured value measured by the energy consumption measuring means 11,... And the distribution board measuring device 12 as measuring means for measuring the energy consumption of the equipment arranged in the building, and measured by the thermohygrometer. The measured temperature / humidity value is transmitted to the totalization management device 13 via a communication means in a wireless or wired house.

  The aggregation management device 13 includes a communication unit that transmits and receives data, a data storage unit that records data such as received measurement values, and a control unit that controls these.

  On the other hand, the gas and water consumption of the house H is measured by the gas / water measuring device 14. The gas / water measuring device 14 is connected to a gas meter (G1) or a gas meter connected to a gas pipe separately from the gas meter. This gas meter is equipped with a measuring instrument for measuring a pulse count generated according to the amount of gas used.

  Further, the gas / water measuring device 14 is also connected to a water meter (G1) or a water meter connected to a water pipe separately. This water meter is equipped with a measuring instrument for measuring a pulse count generated according to the amount of water used. And the measured value measured with the gas and water measuring device 14 is transmitted to the totalization management device 13 via the communication means in a wireless or wired house.

  Further, the storage amount control device 62 connected to the power conditioner 61 of the storage battery 60 shown in FIG. 3 measures the storage amount of the storage battery 60, and the measured value is transmitted via a communication means in a wireless or wired house. It is transmitted to the aggregation management device 13.

  Further, the tabulation management apparatus 13 is connected to a communication network N such as the Internet via a router 15 and a gateway 16. Note that the router 15 and the gateway 16 may be a single device having both functions. Then, transmission / reception of data such as measurement values and prediction values, transmission / reception of control signals, and the like are performed with the external prediction display server 3 also connected to the communication network N.

  Further, the display monitor 20 serving as a display unit connected to the router 15 in the house H transmits and receives data to and from the totalization management device 13 via a wireless or wired communication unit in the house. Then, the display monitor 20 displays the energy consumption predicted value, the energy creation predicted value, and the energy balance predicted value for each of a plurality of future behavior patterns predicted by the predicted display server 3 (see FIGS. 7 and 8).

  Note that a personal computer monitor owned by the user can be used as the display monitor 20, but it is preferable to prepare a dedicated monitor for energy display in consideration of user convenience.

(Configuration of prediction display server)
Next, the configuration of the prediction display server 3 of the present embodiment will be described with reference to FIG. The prediction display server 3 includes a storage unit 31 that stores past weather information 31a and an energy consumption performance value 31b corresponding to the past weather information 31a, a control unit 32 that includes an action prediction unit 33 and an energy prediction unit 34. , A mode switching unit 35 for selecting an action pattern, and a communication means 36 for communicating with the house H via the communication network N (see FIG. 2).

  Note that the storage unit 31, the control unit 32, the mode switching unit 35, and the communication unit 36 described below are all executed as functional blocks using a general-purpose microcomputer including a CPU, a memory, an HDD, an SSD, and the like. The

  The storage unit 31 stores past weather information 31a, an energy consumption record value 31b corresponding to the past weather information 31a, an energy creation record value 31c corresponding to the past weather information 31a, and the date and time.

  The past meteorological information 31a includes precipitation, temperature, sunshine duration, wind direction and wind speed, snow cover, cloud cover, weather, solar radiation, humidity and the like for every predetermined time (1 hour or 3 hours) in the past five years. The weather is classified into clear, clear, cloudy, rain, etc. based on the amount of clouds.

  The actual energy consumption value 31b includes the amount of electric power used, the amount of gas used, the amount of water used per predetermined time, and the electricity rate, gas rate, water rate, etc., converted into charges. Furthermore, as the corresponding energy creation achievement value 31c, there is a power generation amount every hour or every three hours.

  And the control part 32 of a present Example has the behavior prediction part 33 which has the analysis mechanism 33a and the prediction mechanism 33b, the consumption prediction mechanism 34a, the creation prediction mechanism 34b, the balance prediction mechanism 34c, and the essential condition setting mechanism 34d. An energy predicting unit 34.

  Among these, the analysis mechanism 33a of the behavior prediction unit 33 analyzes a user's past behavior pattern based on the actual energy consumption value 31b and stores it in the storage unit 31 together with weather information. The user behavior patterns include “present” or “absent” of the user in each time zone divided every hour or every three hours.

  The “present” or “absent” is estimated based on the past energy consumption result value 31b of the user. Specifically, when the power consumption of the living room is smaller than the threshold during the daytime, it is estimated as “absent”, and when the power consumption is greater than the threshold, it is estimated as “present”. This threshold value can be calculated based on the actual energy consumption value 31b or can be calculated by experiment.

  In addition, as a determination method of “present” or “absent”, a method based on manual input by a user, a method based on a detection means such as a human sensor, or the like, or a method based on these methods and the actual energy consumption value 31b may be used. May be used in combination.

  When a human sensor is installed, the number of persons in each room and the position of a person in the room can be detected in addition to the distinction between “present” and “absent” as the behavior pattern. Further, it can be estimated whether the user is sleeping or waking up.

  Here, it is preferable to give the user an individual identification tag in order to capture an individual-unit behavior pattern rather than a single behavior pattern of the entire user home. Then, the movement trajectory of the identification tag possessed by the individual user is captured and tracked by a reader placed at each point that is a key indoor place such as the entrance and entrance of the room. As such an identification tag, a dedicated IC tag, a mobile phone, a card key, or the like can be used.

  Moreover, the capture of the behavior pattern of the individual unit can be performed only in the initial stage, and it can be estimated from the actual energy consumption value in a reverse calculation based on the captured behavior pattern of the individual unit after the initial stage. For example, if the mother is the only person using the washing machine from the data acquired in the initial stage, it can be estimated that the mother has used the machine after that.

  In order to calculate the energy consumption predicted value in more detail, in addition to the above-mentioned distinction of “present” or “absent”, ON / OFF of the operation of the air conditioner (7A) as an action pattern, ON of the lighting device (7B) Alternatively, it is possible to detect OFF, ON or OFF of a home appliance (7C) such as a washing machine.

  Further, when the user owns a car, by installing a car detection means for detecting the “present” or “absence” of the car, it can be recognized as an action pattern that the user has gone out of the car.

  In addition, the prediction mechanism 33b of the behavior prediction unit 33 predicts a plurality of future behavior patterns of the user corresponding to future weather information based on the analyzed past behavior patterns.

  That is, the prediction mechanism 33b searches the weather information 31a stored in the storage unit 31 for the same season classification, the same time zone, and the same weather as the future weather information.

  Then, all the behavior patterns on the date and time satisfying the three conditions are extracted as predicted values, and the occurrence probability of each behavior pattern is calculated. For example, on a sunny holiday in spring, the behavior pattern is predicted that the probability of being absent in the afternoon is 60%, the probability that only the grandmother is at home is 10%, and the others are 30%.

  In addition, the prediction mechanism 33b is provided with the behavior pattern of ON / OFF of the operation of the air conditioner (7A), ON / OFF of the lighting device (7B), the washing machine, in addition to the above-described distinction between “present” and “absent” It is also possible to predict ON / OFF of the home appliance (7C) such as whether the user is sleeping or waking up.

  And the prediction mechanism 33b of the action prediction part 33 of a present Example is based on the user's action pattern in the other house H2 ... HX connected via the communication network N of the said house H1 used as a prediction object. It is also possible to predict user behavior patterns.

  That is, the prediction mechanism 33b searches the weather information 31a stored in the storage unit 31 for the same season division, the same time zone, and the same weather as the future weather information.

  Then, from the behavior patterns of the users in other houses H2... HX linked via the communication network N, all the behavior patterns on the date and time satisfying the three conditions are extracted as predicted values, and each behavior pattern The occurrence probability is calculated.

  This behavior pattern is extracted from the other houses H2... HX of the houses H2... HX having facility information of the same or similar building as the house H1 to be predicted and family structure information. It is preferable to carry out from inside.

  Here, building facility information includes building building material information, building floor plan information, building equipment information, building location information, building performance information, and the like. Family composition information includes father, mother, brother, brother, grandfather, grandmother and other attributes, physical characteristics such as age, height, and weight, past consumption history combined with operational information for each individual, family There are the total number of people.

  Further, the consumption prediction mechanism 34a of the energy prediction unit 34 predicts an energy consumption prediction value corresponding to each of a plurality of future behavior patterns. As this energy consumption prediction value, for example, an average value of several power consumption amounts classified into the same action pattern is calculated.

  In addition, the creation prediction mechanism 34b of the energy prediction unit 34 predicts an energy creation prediction value corresponding to future weather information. In other words, the creation prediction mechanism 34 b searches the weather information 31 a stored in the storage unit 31 for the same season division, the same time zone, and the same weather. And the average value of some electric power generation amounts of the date which satisfies three conditions is used as an energy creation prediction value.

  Furthermore, the balance prediction mechanism 34c of the energy prediction unit 34 calculates a future energy balance prediction value corresponding to each of a plurality of future behavior patterns based on the energy consumption prediction value and the energy creation prediction value. Specifically, the energy balance predicted value is calculated by subtracting the energy consumption predicted value from the energy creation predicted value for each behavior pattern.

  In addition, the essential condition setting mechanism 34d of the energy predicting unit 34 sets essential conditions that cannot be changed in common for all action patterns. Indispensable conditions include the presence or absence of a specific user, setting a behavior mode of a specific room, and the like.

  And in the prediction display server 3 of a present Example, the memory | storage part 31 memorize | stores the past action pattern for every room, the action prediction part 33 estimates several future action patterns for every room, and the energy prediction part 34 Predict multiple future energy consumption predictions for each room.

  Furthermore, the mode switching unit 35 selects a plurality of behavior patterns predicted by the prediction mechanism 33b of the behavior prediction unit 33 from the viewpoint of a specific behavior mode selected by the user.

  Action modes include an economic mode that prioritizes cost control, a comfort mode that prioritizes comfort, and a normal mode that harmonizes cost control and comfort.

  The economic mode is an action mode that preferentially extracts an action pattern having a small energy balance prediction value.

  The comfort mode is an action mode that preferentially extracts an action pattern in which the room temperature, humidity, temperature unevenness, and the like in the building are reduced regardless of the predicted energy balance.

  The normal mode is an action mode that is intermediate between the economic mode and the comfort mode. It is an action mode that preferentially extracts action patterns with small predicted energy balance and low room temperature, humidity, temperature unevenness, etc. in the building. It is.

  In addition, the “extraction” of the behavior pattern for each behavior mode described above is to select only a specific behavior pattern that matches the behavior mode from all the behavior patterns, and to make all the behavior patterns a priority for each behavior mode. Sorting based on, performing both the selection and sorting described above, and the like.

  In addition, it is preferable that the mode switching unit 35 has a performance priority mode for extracting only action patterns having a probability of occurring in the past action patterns higher than a predetermined value. Furthermore, it can also comprise so that the action pattern which everyone who goes out of the action pattern by which cost is naturally estimated to become the minimum goes out can be excluded.

  In addition, the mode switching unit 35 has an account setting mechanism 35a that can change the setting of the behavior mode for each user as well as the behavior mode for each user's home. This account setting mechanism 35a makes it possible to select an action mode on an individual basis when the user's home consists of a plurality of people.

  When one of the behavior modes is selected by the user, all the behavior patterns are ranked and rearranged based on the viewpoint that each behavior mode has priority. Therefore, for example, when the economic mode is selected, the action pattern with the lowest cost is arranged at the top, and thereafter, the action patterns are arranged and displayed in an order that gradually increases the cost.

  Moreover, the communication means 36 acquires weather information from the weather information server 2 as a weather prediction means. The acquired weather information is stored in the storage unit 31 of the prediction display server 3. Furthermore, the communication means 36 distributes prediction information such as an action pattern, an energy consumption prediction value, an energy creation prediction value, and an energy balance prediction value to the house H side.

(Prediction display process flow)
Subsequently, the flow of the prediction display process executed in the prediction display server 3 of the present embodiment will be described with reference to FIGS.

  First, the overall flow of the prediction display process will be described with reference to FIG. The predictive display process described below is started by clicking a predictive display button on the home page that the user is browsing. At that time, the target prediction date (for example, the next day) is designated.

  First, as a prior process, the analysis mechanism 33a of the behavior prediction unit 33 analyzes the user's behavior pattern and stores it in the storage unit together with the weather information 31a (step S1). The behavior analysis process by the analysis mechanism 33a will be described later.

  In the predictive display process, when there are a plurality of users in the target building, the behavior setting is set for each user by the account setting mechanism 35a of the mode switching unit 35 (steps S2 and S3). For example, both Mr. A and Mr. B select the economic mode, and Mr. C selects the comfort mode.

  When the selection of the behavior mode is completed, the essential condition that cannot be changed in common for all the behavior patterns is set by the essential condition setting mechanism 34d (step S4). For example, it can be set that Mr. C is always at home.

  Then, the memory | storage part 31 acquires the weather information of an estimated date for every time slot | zone from the weather information server 2 (step S5). The acquired predicted date and time and weather information are classified into a plurality of items that can determine the user's behavior pattern. For example, the forecast date season is classified into “Spring”, “Summer”, “Autumn”, “Winter”, and the weather is classified into “Sunny”, “Cloudy”, “Rain” by time zone, and by time zone The temperature is classified into “low”, “medium”, and “high” (step S6).

  The prediction mechanism 33b of the behavior prediction unit 33 predicts a plurality of behavior patterns that the user can take using the behavior pattern analyzed in advance and the acquired weather information (step S7). The behavior prediction process by the prediction mechanism 33b will be described later.

  When a plurality of behavior patterns are predicted, the consumption prediction mechanism 34a predicts an energy consumption prediction value corresponding to each behavior pattern (step S8). For example, an average value of a plurality of power consumption amounts classified into the same action pattern is calculated and used as an energy consumption predicted value of each action pattern.

  Then, the creation prediction mechanism 34b predicts the energy creation prediction value based on the weather information on the prediction date acquired from the weather information server 2 (step S9). Specifically, the same season classification, the same time zone, and the same weather as the weather information on the predicted date are searched from the weather information 31a stored in the storage unit 31. And the average value of the some generated electric energy of the date and time applicable as an energy creation prediction value is calculated, and it is set as the energy creation prediction value of a prediction day.

  When the energy consumption predicted value and the energy creation predicted value are calculated in this way, the balance prediction mechanism 34c subtracts them to calculate the energy balance predicted value. In this case, a plurality of predicted energy consumption values are calculated for each behavior pattern, and only one energy creation prediction value is calculated. Therefore, the energy balance predicted value is calculated for each behavior pattern.

  Finally, the display monitor 20 as a display means displays all the predicted income / loss values calculated for each of the plurality of behavior patterns at once on the screen. The contents of the image displayed on the screen will be described later.

  Next, the flow of the behavior analysis process executed as a prior process will be described with reference to FIG.

  In this behavior analysis process, the analysis mechanism 33a extracts all past energy consumption performance values belonging to a certain category from the weather information 31a stored in the storage unit 31 (step S101). This classification is based on the items of season, weather, and temperature.

  Since the extracted actual energy consumption value is a continuous value, it is divided into time zones of a predetermined width (1 hour or 3 hours) so that the processing is easy (step S102).

  Then, “present” or “absent” is estimated based on the actual energy consumption value for each time period (step S103). For example, when the power consumption is smaller than the threshold, it is estimated as “absent”, and when the power consumption is larger than the threshold, it is estimated as “present”. Whether the “present” or “absent” as the estimated behavior pattern is stored in the storage unit 31.

  Next, the flow of the behavior prediction process executed in the prediction display process will be described with reference to FIG.

  In this behavior prediction process, the prediction mechanism 33b extracts all past behavior patterns having date and time and weather information belonging to the same classification as the weather information on the prediction date from the weather information 31a stored in the storage unit 31 ( Step S701). Conditions include season, weather, and temperature.

  Occurrence probabilities of the plurality of extracted past behavior patterns are calculated (step S702). That is, the probability of occurrence of each behavior pattern is calculated by dividing the number of occurrences of each behavior pattern by the total number of occurrences of all behavior patterns belonging to the same classification.

  When the occurrence probability is calculated, action patterns having a lower occurrence probability than a predetermined probability are excluded, and only action patterns having a higher occurrence probability are extracted (step S703). The extraction may be performed by extracting a predetermined number of behavior patterns in descending order of occurrence probability.

  Subsequently, an image diagram of a result of the above-described prediction display process will be described with reference to FIGS. In this example, it is assumed that there are three persons A, B, and C as individuals in the user's building.

  First, the image diagram of FIG. 7 will be described. On this result display screen, tomorrow's weather, which is the forecast date, and tomorrow's forecast power generation amount are displayed in the upper row, personal settings, which are account settings, and essential condition settings are displayed in the middle row, and recommended behavior patterns are shown in the lower row. The behavior patterns 1 to 3 are displayed. Note that more action patterns can be displayed by scrolling the screen.

  The weather displayed in the upper row is classified and displayed tomorrow's weather, and the weather downloaded from the weather information server 2 is displayed. The predicted power generation amount displays the power generation amount predicted by the creation prediction mechanism 34b. Note that the power generation amount may be converted into a charge and displayed.

  The personal setting displayed in the middle row displays the action mode selected for each user. For example, assume that Mr. A and Mr. B have selected the economic mode. Note that Mr. C who is not displayed is considered to have selected the normal mode.

  In addition, the essential condition setting displayed in the middle row indicates that Mr. C is at home at all times as an action pattern as an essential condition set by the essential condition setting mechanism 34d.

  The behavior pattern displayed in the lower row displays a plurality of user behavior patterns predicted by the behavior prediction unit 33 and the utility bill predicted by the energy prediction unit 34 corresponding to each behavior pattern.

  For example, as behavior pattern 1, both Mr. A and Mr. B are at home ("home") from 9:00 to 12:00, and both Mr. A and Mr. B are out ("outing") from 12:00 to 18:00. From 18:00 to 21:00, the utility bill is displayed when Mr. A is at home and Mr. B is out. In addition, as behavior pattern 2, from 9 o'clock to 12 o'clock, both A and B are at home ("home"), and from 12 o'clock to 18 o'clock, both A and B are out ("outing") From 18:00 to 21:00, the utility bill is displayed when both Mr. A and Mr. B are out.

  In addition, an action mode can be set for each room as shown in the image diagram of FIG. In the setting for each room, the storage unit 31 stores past behavior patterns for each room, the behavior prediction unit 33 predicts a plurality of future behavior patterns for each room, and the energy prediction unit 34 uses a plurality of future energy consumptions. Predict the predicted value for each room.

  In addition, on the right side of each action pattern in FIG. 8, the utility bill of each action pattern is displayed as a bar graph with “+” or “−” for each time zone for easy understanding.

  Next, the operation of the prediction display server 3 and the prediction display system S of this embodiment will be described.

  (1) Thus, the prediction display server 3 of a present Example is the prediction display server 3 which estimates and displays the energy consumption in a building. The prediction display server 3 stores the past weather information 31a and the energy consumption result value 31b corresponding to the past weather information 31a, and the storage unit 31 that stores the energy consumption result value 31b. Behavior prediction having an analysis mechanism 33a for analyzing past behavior patterns and a prediction mechanism 33b for predicting a plurality of future behavior patterns of the user corresponding to future weather information based on the analyzed past behavior patterns And an energy prediction unit 34 having a consumption prediction mechanism 34a that predicts an energy consumption prediction value corresponding to each of a plurality of future behavior patterns.

  For this reason, the user can know a plurality of future behavior patterns and predicted energy consumption values corresponding to the future behavior patterns according to future weather information. You can choose.

  In other words, the user's behavior pattern is greatly influenced by future weather conditions, so by predicting an appropriate behavior pattern considering this and calculating the energy consumption prediction value, the energy consumption prediction value can be calculated more accurately. It can be calculated.

  In addition, since the behavior pattern is presented to the user in a format that can be compared with the predicted energy consumption value, it can be used as a reference when determining the future behavior pattern in consideration of the environment.

  (2) In addition, the storage unit 31 further stores an energy creation result value 31c corresponding to past weather information 31a, and the energy prediction unit 34 predicts an energy creation prediction value corresponding to future weather information. By further including 34b, it is possible to know the energy creation predicted value according to future weather information, and therefore it is possible to select a specific action pattern in consideration of the energy creation predicted value.

  (3) Furthermore, the energy prediction unit 34 further includes a balance prediction mechanism 34c that calculates a future energy balance prediction value corresponding to each of a plurality of future behavior patterns based on the energy consumption prediction value and the energy creation prediction value. Can have.

  For this reason, the user can know a plurality of future behavior patterns and corresponding energy balance predicted values according to future weather information. You can choose.

  (4) Then, the analysis mechanism 33a of the behavior predicting unit 33 estimates the presence or absence of the user for each divided time zone based on the actual energy consumption value 31b, so that the behavior pattern of the user can be obtained by a simple method. Can be estimated.

  In addition, when a human sensor is installed, in addition to the distinction of “present” or “absent” as an action pattern, the number of people in each room and the position of a person in the room can also be detected.

  (5) Furthermore, by further including a mode switching unit 35 that selects a plurality of future behavior patterns according to a specific behavior mode selected by the user, a behavior pattern adapted to the user's preference can be predicted.

  That is, since the preference of energy consumption varies from user to user, by considering this, it is possible to increase the satisfaction of the user by presenting an action pattern of energy consumption that is more adapted to the user's preference.

  (6) Furthermore, the mode switching unit 35 has, as the behavior mode, an economic mode that prioritizes cost suppression, a comfort mode that prioritizes comfort, and a normal mode that harmonizes cost suppression and comfort. It is possible to classify the difference in preference between users from an easy-to-understand viewpoint.

  (7) Since the mode switching unit 35 has the account setting mechanism 35a that can change the setting of the behavior mode for each user, the behavior pattern can be selected on an individual basis. Can be predicted.

  In other words, when a plurality of individuals belong to the user side, a behavior pattern adapted to the user's personal preference can be predicted if a behavior mode that determines the preference of the behavior pattern on an individual basis can be set.

  (8) The analysis mechanism 33a of the energy prediction unit 33 reliably and easily captures the user's individual behavior pattern by analyzing the user's past behavior pattern based on the movement trajectory of the identification tag possessed by the user. it can.

  In this case, the behavior pattern of the individual unit is captured only in the initial stage, and thereafter the user pattern is estimated backward from the energy consumption performance value based on the captured behavior pattern of the individual unit. The troublesomeness of holding the identification tag for a long time can be reduced.

  (9) In addition, the energy predicting unit 34 can further set an essential condition regardless of a specific action mode by further including an indispensable condition setting mechanism 34d that sets an indispensable condition that cannot be changed in common for all action patterns. Therefore, it is possible to predict a behavior pattern adapted to the user's preference.

  For example, if there is an elderly person in the user's building, specify that the elderly person is always at home, or if the child is born, the mother and child are always at home regardless of the actual value. Can be specified.

  (10) Furthermore, the storage unit 31 stores past behavior patterns for each room, the behavior prediction unit 33 predicts a plurality of future behavior patterns for each room, and the energy prediction unit 34 predicts a plurality of future energy consumptions. By predicting the value for each room, the predicted energy consumption value can be predicted more accurately.

  (11) The predictive display system S of the present embodiment is a predictive display system S that displays energy consumption in a building on a display monitor 20 as a display means, and measures the energy consumption of equipment arranged in the building. An energy consumption measuring means 11, a distribution board measuring device 12, a gas / water measuring device 14 as a measuring means, a weather information server 2 as a weather predicting means for predicting future weather information in the vicinity of the building, a weather The communication means 36 which acquires weather information from a prediction means, one of the above-mentioned prediction display servers 3, and the display monitor 20 which displays the energy balance estimated value estimated for every some future action pattern are provided. Yes.

  For this reason, the user can know a plurality of future behavior patterns and corresponding energy balance predicted values according to future weather information, and therefore selects a favorite behavior pattern in consideration of the energy balance predicted values. be able to.

  Moreover, it becomes easy to compare for every action pattern by arranging and displaying the energy balance predicted value for every some future action pattern on the display monitor 20 as a display means.

  The embodiment of the present invention has been described in detail with reference to the drawings, but the specific configuration is not limited to this embodiment, and design changes that do not depart from the gist of the present invention are not limited to the present invention. included.

  For example, in the embodiment, the user's behavior pattern is not divided into weekdays and holidays, but is not limited to this, and the behavior prediction unit 33 analyzes the behavior patterns into weekdays and holidays. In addition, the behavior pattern may be predicted separately for weekdays and holidays.

  Moreover, although not demonstrated in the said Example, the display means 20 gives priority to several future action patterns and the energy balance estimated value calculated corresponding to each action pattern according to action mode. It is preferable to have a priority display mechanism for displaying the images with a priority.

  Furthermore, although the said Example demonstrated the case where the weather information server 2 as a weather prediction means was connected via the communication network N without arrange | positioning at the user side, it is not limited to this, A weather prediction The means may be executed inside the prediction display server 3.

  And in the said Example, although the case where it had a storage battery was not demonstrated, when it has a storage battery, the balance prediction mechanism 34c can also consider the electrical storage amount. In this case, a secondary storage battery mounted on a hybrid car or an electric vehicle can also be used as the storage battery.

  Moreover, in the said Example, although the prediction mechanism 33b of the action prediction part 33 calculated occurrence probability of each action pattern in the middle of a prediction display process, it is not limited to this, generation | occurrence | production of each action pattern in advance Probabilities may be calculated.

S Predictive display system 2 Weather information server 3 Predictive display server 31 Storage unit 31a Meteorological information 31b Actual energy consumption value 32 Control unit 33 Behavior prediction unit 33a Analysis mechanism 33b Prediction mechanism 34 Energy prediction unit 34a Consumption prediction mechanism 34b Creation prediction mechanism 34c Prediction mechanism 35 Mode switching unit 36 Communication means 11 Energy consumption measuring means (measuring means)
12 Distribution board measuring means (measuring means)
14 Gas and water meter (measuring means)
20 Display monitor (display means)

Claims (11)

A prediction display server that predicts and displays energy consumption in a building,
A storage unit for storing past weather information and an actual energy consumption value corresponding to the past weather information;
An analysis mechanism for analyzing a user's past behavior pattern based on the actual energy consumption value, and predicting a plurality of future behavior patterns of the user corresponding to future weather information based on the analyzed past behavior pattern A behavior prediction unit having a prediction mechanism;
An energy prediction unit having a consumption prediction mechanism that predicts an energy consumption prediction value corresponding to each of the plurality of future behavior patterns.   The storage unit further stores an energy creation performance value corresponding to the past weather information, and the energy prediction unit further includes a creation prediction mechanism that predicts an energy creation prediction value corresponding to future weather information. The prediction display server according to claim 1.   The energy prediction unit further includes a balance prediction mechanism that calculates a future energy balance prediction value corresponding to each of the plurality of future behavior patterns based on the energy consumption prediction value and the energy creation prediction value. The prediction display server according to claim 2, wherein the prediction display server is characterized in that:   The said analysis mechanism of the said action prediction part estimates the presence or absence of the user for every divided time slot | zone based on the said energy consumption performance value, The any one of Claim 1 thru | or 3 characterized by the above-mentioned. The prediction display server described in.   5. The prediction display according to claim 1, further comprising a mode switching unit that selects the plurality of future behavior patterns according to a specific behavior mode selected by a user. server   The mode switching unit includes, as the behavior mode, an economic mode that prioritizes cost control, a comfort mode that prioritizes comfort, and a normal mode that harmonizes cost control and comfort. 5. The prediction display server according to 5.   The prediction display server according to claim 5, wherein the mode switching unit includes an account setting mechanism that can change the setting of the behavior mode for each user.   The said analysis mechanism of the said energy estimation part analyzes the user's individual past action pattern based on the movement locus | trajectory of the identification tag which a user individual possesses, The any one of Claims 1 thru | or 7 characterized by the above-mentioned. The prediction display server described in.   The prediction display according to any one of claims 1 to 8, wherein the energy prediction unit further includes an essential condition setting mechanism for setting an indispensable condition that cannot be changed in common for all action patterns. server.   The storage unit stores past behavior patterns for each room, the behavior prediction unit predicts a plurality of future behavior patterns for each room, and the energy prediction unit calculates a plurality of future energy consumption predicted values for each room. The prediction display server according to any one of claims 1 to 9, wherein prediction is performed. A prediction display system for displaying energy consumption in a building on a display means,
Measuring means for measuring the energy consumption of the equipment arranged in the building;
Weather prediction means for predicting future weather information in the vicinity of the building;
Communication means for obtaining the weather information from the weather prediction means;
The prediction display server according to any one of claims 3 to 10,
And a display means for displaying the predicted energy balance predicted for each of the plurality of future behavior patterns.

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