METHOD FOR DETERMINING THE ACTIVATION MOMENT OF A BUILDING HEATING SYSTEM

Abstract

Method for determining an activation time for the heating system (11) of a building (10) and comprising recording indoor temperature measurements and meteorological values; selecting at least one restart sequence comprising indoor temperature measurements and meteorological values ​​associated with past times, each restart sequence comprising a plurality of successive times at which the measurements satisfy at least one predefined criterion; determining, for each selected time, a variation in indoor temperature relative to an initial time of the restart sequence and a plurality of variables; calculating a coefficient associated with each variable allowing maximizing, for all selected times, the equality between the variation in indoor temperature and the sum of the variables associated with their own coefficients;and to estimate the indoor temperature at a future time by applying the calculated coefficients to the plurality of variables determined at said future time. Figure to be published with the abbreviation: Fig. 1;

Description

Title of the invention: METHOD FOR DETERMINING THE ACTIVATION POINT OF A HEATING SYSTEM OF A BUILDING technical field

[0001] The present invention relates to the field of building thermal engineering and more specifically to the control of equipment designed to provide heat input to a building. The present invention also relates to the field of methods for estimating the evolution of the internal temperature of a building. STATE OF PRIOR ART

[0002] Time programming allows setting target temperatures to be reached over different predefined time periods. In a building, implementing such time programming requires activating or restarting a heating system before the start of a predefined time period in order to obtain the desired setpoint temperature at the beginning of said predefined time period.

[0003] Several methods have been developed to estimate the evolution of an indoor building's temperature in order to determine when to activate the heating system to ensure that the setpoint temperature is maintained while minimizing energy consumption related to the heating system. However, such methods are generally based on complex thermal models requiring significant computing power and / or precise data, which are not always easy to obtain.

[0004] Furthermore, weather conditions can significantly influence the evolution of the indoor temperature. Therefore, the methods may lose their accuracy when weather conditions vary.

[0005] It is therefore desirable to overcome these drawbacks of the prior art. In particular, it is desirable to provide a solution that allows for the rapid and accurate estimation of changes in indoor temperature, while requiring limited computing power, in order to determine the activation time of the heating system. Furthermore, it is desirable to provide a solution that takes into account variations in weather conditions. Description of the invention

[0006] An object of the present invention is to provide a method for determining the activation time of a building's heating system. The method is implemented by a control unit connected to the heating system, the system of heating heats the building when said heating system is activated. The method comprises: recording measurements of the building's internal temperature, referred to as the internal temperature, and the temperature outside the building, referred to as the external temperature, and forecast meteorological values, each measurement being associated with a measurement time, each forecast meteorological value being associated with a forecast time; selecting at least one restart sequence comprising internal and external temperature measurements and forecast meteorological values ​​associated with past measurement or forecast times, each restart sequence being defined, from an initial time, by a plurality of successive times, referred to as selected times, at which the internal temperature measurements satisfy at least one predefined criterion;determine, for each selected instant of each selected restart sequence, a variation in indoor temperature between said selected instant and the initial instant of the restart sequence, as well as a plurality of variables, determined at said selected instant and in relation to said initial instant, said variables influencing the variation in indoor temperature, at least one variable being a function of the indoor temperature and at least one variable being a function of forecast meteorological values;and to calculate, by multiple linear regression, a coefficient associated with each variable, the coefficients allowing to maximize, for all the selected instants, the equality between the variation of indoor temperature and the sum of the variables associated with their own coefficients. The method further comprises storing the coefficients calculated to activate the heating system at an instant of measurement of the indoor temperature as a function of an estimated variation of the indoor temperature between said instant of measurement and a future instant, said estimated variation of the indoor temperature being determined from said stored coefficients, applied to the plurality of variables determined using forecast meteorological values ​​and a measurement of the indoor temperature at said instant of measurement.

[0007] Thus, it is possible to estimate the evolution of the building's interior temperature quickly and without requiring significant computing power, since it is a simple thermal model with a plurality of defined variables, each associated with a coefficient, and which is solved simply by implementing a multiple linear regression. Furthermore, the data necessary for such an estimation are readily available, and the model takes into account variations in weather conditions. It is then possible to activate the heating system based on the evolution of the estimated interior temperature, thereby minimizing energy consumption.

[0008] According to a particular embodiment, selecting at least one restart sequence involves selecting a predefined minimum number of sequences of RELAUNCH.

[0009] According to a particular embodiment, selecting at least one restart sequence involves selecting all restart sequences over a period of predefined duration.

[0010] According to a particular embodiment, the control unit includes a time program comprising setpoint temperatures, each setpoint temperature being associated with a setpoint instant at which the setpoint temperature must be reached, and wherein at least one predefined criterion requires that the indoor temperature be increasing and the indoor temperature be less than a setpoint temperature associated with a setpoint instant of the time program occurring first after each of said selected instants, and wherein the heating system is further activated at each selected instant of each restart sequence.

[0011] Thus, it is possible to obtain a model allowing the estimation of the evolution of the indoor temperature under particular desired conditions adapted to a recovery period for which the activation of the heating makes it possible to reach a setpoint temperature.

[0012] According to a particular embodiment, the estimate of the interior temperature determined at the future time is determined at a setpoint time of the time programming, the method further comprising activating the heating system if the estimated interior temperature at said setpoint time is less than or equal to the setpoint temperature associated with said setpoint time.

[0013] Thus, it is possible to determine an activation time for the heating system precisely and quickly, taking into account variations in weather conditions, which makes it possible to ensure compliance with a setpoint temperature while minimizing energy consumption.

[0014] According to a particular embodiment, the estimation of the indoor temperature determined at the setpoint time is carried out when the heating system is inactive at the measurement time and when the measurement of the indoor temperature at said measurement time is lower than the setpoint temperature associated with said setpoint time.

[0015] Thus, the estimation of the indoor temperature is carried out only when necessary to determine an activation time for the heating system, which reduces the consumption related to the implementation of the process.

[0016] According to a particular embodiment, the forecast meteorological values ​​include values ​​of the outside temperature, and include values ​​of solar radiation, and in which the plurality of variables determined at a selected instant in relation to an initial instant includes a first variable equal to the difference between the indoor temperature at the initial time and the outdoor temperature at said selected time, a second variable equal to the cumulative solar radiation between the initial time and the selected time, and a third variable equal to the time difference between the selected time and the initial time.

[0017] Thus, it is possible to take into account the influence of external solar radiation on the evolution of the internal temperature while maintaining a fast and accurate process thanks to the selection of restart sequences according to a predefined criterion.

[0018] According to a particular embodiment, calculating, by multiple linear regression, a coefficient associated with each variable includes further calculating a coefficient associated with a constant equal to 1.

[0019] According to a particular embodiment, the calculated coefficients are obtained, in the form of a vector b comprising each of said coefficients, by solving the equation J1 y ■> ^ans la9ue Xa represents a matrix comprising, For each row, an explanatory vector is associated with a selected instant, each selected instant being associated with a row, each explanatory vector comprising the variables determined at the selected instant associated with and in relation to the initial instant of the restart sequence, in which Ya represents a vector containing, for each row, the variation in indoor temperature associated with a selected instant, equal to the variation in indoor temperature between said selected instant and the initial instant of the restart sequence, each selected instant being associated with a row in the same order as for the training matrix Xa, and in which Xa' is the transpose of Xa and y1 is the inverse matrix of XaXa-

[0020] The invention also relates to a management unit for managing the thermal performance of a building. The management unit is connected to a heating system, the heating system heating the building when said heating system is activated. The management unit comprises electronic circuitry configured to: record measurements of the building's interior temperature, referred to as the interior temperature, and the building's exterior temperature, referred to as the exterior temperature, and forecast weather values, each measurement being associated with a measurement time, each forecast weather value being associated with a forecast time;select at least one relaunch sequence comprising indoor and outdoor temperature measurements and forecast weather values ​​associated with past measurement or forecast times, each relaunch sequence being defined, from an initial time, by a plurality of successive times, called selected times, at which the indoor temperature measurements satisfy at least one predefined criterion; determine, for each selected time of each selected relaunch sequence, a variation in indoor temperature between said selected time and; the initial instant of the restart sequence and a plurality of variables, determined at said selected instant and in relation to said initial instant, said variables influencing the variation of indoor temperature, at least one variable being a function of the indoor temperature and at least one variable being a function of forecast meteorological values; calculate, by multiple linear regression, a coefficient associated with each variable, the coefficients allowing to maximize, for all the selected instants, the equality between the variation of indoor temperature and the sum of the variables associated with their own coefficients.The control unit further comprises electronic circuitry configured to store the coefficients calculated to activate the heating system at a given time of indoor temperature measurement based on an estimated variation in indoor temperature between said measurement time and a future time, said estimated variation in indoor temperature being determined from said stored coefficients, applied to the plurality of variables determined using forecast meteorological values ​​and a measurement of the indoor temperature at said measurement time.

[0021] A computer program product is also proposed, which can be stored on a medium and / or downloaded from a communication network, in order to be read by a processor. This computer program includes instructions for implementing the method mentioned above in any of its embodiments, when said computer program is executed by the processor. The invention also relates to an information storage medium storing such a computer program comprising instructions for implementing the method mentioned above in any of its embodiments when said computer program is read from said storage medium and executed by the processor. Brief description of the drawings

[0022] The features of the invention mentioned above, as well as others, will become clearer upon reading the following description of at least one exemplary embodiment, said description being made in relation to the accompanying drawings, among which:

[0023] [Fig. 1] schematically illustrates a building in which a method for determining the activation time of a building heating system is implemented;

[0024] [Fig.2] schematically illustrates a management unit implementing the process of termination of a moment of activation of the building's heating system;

[0025] [Fig.3] schematically illustrates a learning phase of the determination process mination of an instant activation of the building's heating system;

[0026] [Fig.4] schematically illustrates a phase of operation of the deter process mination of an instant activation of the building's heating system.

[0027] DETAILED DESCRIPTION OF IMPROVEMENTS

[0028] Fig. 1 thus schematically illustrates a building 10 in which is implemented a process for determining an activation time of a heating system 11 involving determining an estimate of the interior temperature of the building 10 at a future time.

[0029] Building 10 thus includes the heating system 11 which can be active, and then heats building 10 by providing a thermal input inside building 10, or inactive, and then provides no thermal input.

[0030] The building 10 further comprises at least one glazed wall 12 such as a window through which solar radiation 13 can be transmitted to the building 10 in the form of heat input.

[0031] The building 10 includes a first temperature sensor 14 configured to measure the indoor temperature of the building 10, called the indoor temperature Tint, and includes a second temperature sensor 15 configured to measure the outdoor temperature of the building 10, called the outdoor temperature Text.

[0032] The method for determining an activation time of the heating system 1 is implemented by a management unit 200.

[0033] In order to determine the indoor temperature Tint at a future time, the management unit 200 estimates a variation of the indoor temperature ATint between a current time and the future time on the basis of a model taking into account a plurality of variables, the variables being explanatory of the variation of the indoor temperature, in other words influencing the variation of the indoor temperature, and characterizing the thermal inputs supplied to the building 10 and the thermal losses escaping from the building 10.

[0034] According to one embodiment, a first variable represents the heat inputs provided by the heating system 11 and takes into account thermal insulation between the building 10 and the exterior of the building 10 resulting, for example, from the walls and windows of the building 10. A second variable characterizes the heat inputs that can be provided by solar radiation 13 through at least one glazed wall 12. A third variable characterizes the heat losses of the building 10 over time. The plurality of variables will be explained below, in step 304 of [Fig. 3].

[0035] The control unit 200 is connected to the first and second temperature sensors 14, 15, and can thus obtain measurements of the indoor temperature Tint and the outdoor temperature Text over time, each measurement being associated with a measurement instant. The indoor temperature Tint and the outdoor temperature Text are measured by the first temperature sensor 14, respectively by the second temperature sensor 15, with a predefined periodicity, for example every second. The unit The management unit 200 receives each indoor temperature measurement (Tint) and outdoor temperature measurement (Texl) at regular intervals, for example, every 5 to 6 minutes for the indoor temperature (Tint) via the first temperature sensor (14), and every 15 minutes for the outdoor temperature (Texl) via the second temperature sensor (15). The management unit 200 records the indoor temperature (Tint) and outdoor temperature measurements (T) as they are received. In one embodiment, the management unit 200 also receives an additional indoor temperature measurement (Tint) and outdoor temperature measurement (Texl) when the temperature change exceeds 0.5°C compared to the previously received temperature measurement.

[0036] Building 10 is associated with a time program comprising a plurality of setpoint temperatures Tcons, each setpoint temperature Tcons being associated with a predefined time range beginning with a specific time, called the setpoint time Tcons, at which the setpoint temperature Tcons must be reached. The control unit 200 contains the time program associated with building 10 and thus knows each setpoint temperature and its associated setpoint time.

[0037] The control unit 200 is connected to the heating system 11 and can thus determine the active or inactive state of the heating system 11 at any given time. The control unit 200 can also issue activation or deactivation instructions to the heating system 11.

[0038] The management unit 200 is further connected, via a communication network such as the internet, to a weather forecasting service 16. The management unit 200 can thus receive weather forecast values ​​for the outside temperature Text and solar radiation 13, denoted solar radiation Gh, as a function of time. According to one embodiment, the management unit 200 sends, at regular intervals, a request to the weather forecasting service 16 and receives in response a plurality of successive weather forecast values ​​for the outside temperature Text and a plurality of successive weather forecast values ​​for solar radiation Gh, each weather forecast value being associated with a forecast time.

[0039] The management unit 200 records and updates, upon each receipt of forecast meteorological values ​​representative of a given meteorological parameter such as outside temperature or solar radiation, a forecast vector of said meteorological parameter. This forecast vector includes, for each forecast instant, the most recently received associated forecast meteorological value. Furthermore, the management unit 200 constructs a historical vector for each meteorological parameter comprising a plurality of past instants and including, associated with each past instant, the forecast meteorological value. sionnelle associated with a forecast instant equal to said past instant which was received last, in other words received most recently.

[0040] The management unit 200 is configured to record all the measurements and forecast meteorological values ​​that it receives.

[0041] Figure 2 schematically illustrates an example of the unit's hardware architecture management unit 200. The management unit 200 then comprises, connected by a communication bus 210: a processor or CPU (“Central Processing Unit”) 201; a RAM (“Random Access Memory”) 202; a ROM (“Read Only Memory”) 203; a storage unit or a storage media reader, such as a HDD (“Hard Disk Drive”) 204; and an interface 205 allowing communication with the first and second temperature sensors 14, 15, with the heating system 11, and with a communication network allowing access to a service 16 for the provision of forecast weather data.

[0042] The processor 201 is capable of executing instructions loaded into RAM 202 from ROM 203, external memory (not shown), a storage medium, or a communication network. When the management unit 200 is powered on, the processor 201 is capable of reading instructions from RAM 202 and executing them. These instructions form a computer program causing the processor 203 to implement all or part of the algorithms and steps described below in relation to the management unit 200.

[0043] Thus, all or part of the algorithms and steps described below in relation to the management unit 200 can be implemented in software form by executing a set of instructions by a programmable machine, such as a DSP (Digital Signal Processor) or a microcontroller, or in hardware form by a dedicated machine or component, such as an FPGA (Field-Programmable Gate Array) or an ASIC (Application-Specific Integrated Circuit).

[0044] Fig. 3 schematically illustrates a learning phase of the process of determining an activation time of the heating system 11, implemented by the management unit 200.

[0045] In a first step 300, the management unit 200 waits for the learning phase to be triggered. For example, the management unit 200 performs the learning phase at regular intervals, and thus waits for the elapsed of a first predefined duration, counted from a previous implementation of the learning phase. The first predefined duration is, for example, 24 hours and can be between 12 hours and seven days. The start of the first implementation of the learning phase can be triggered manually by a user. Alternatively, the start of the first implementation of the learning phase is triggered by the activation of the heating system 11, for example after inactivity of the heating system 11 for more than several weeks, as may be the case at the end of the summer period.

[0046] In a subsequent step 302, the management unit 200 selects at least one restart sequence. Each restart sequence includes measurements of the indoor temperature Tint and the outdoor temperature Text, and forecast meteorological values ​​of solar radiation Gh associated with past measurement or forecast times. The measurements are taken from the first and second temperature sensors 14 and 15 and are recorded by the management unit 200. The forecast meteorological values ​​are taken from the forecast data supply service 16 and are recorded as historical vectors by the management unit 200.

[0047] Alternatively, each restart sequence includes forecast weather values ​​for the outside temperature. In one particular embodiment, each restart sequence also includes information representing the activation of the heating system 11. Furthermore, each restart sequence j begins with an initial time, denoted , and is defined by a plurality of successive times, called selected times, denoted fi (i and j being integers), for which the measurements and / or forecast weather values ​​and / or information representing the activation of the heating system 11 satisfy at least one predefined criterion. The management unit 200 thus selects, from recorded data, measurements or forecast weather data whose measurement or forecast times correspond to the selected times of each selected restart sequence j.

[0048] When a weather forecast measurement or value is not defined at said instant fi, said weather forecast measurement or value may be determined by linear interpolation between two weather forecast measurements or values ​​representative of the same parameter, one defined at an earlier instant and the other at a later instant than said instant fi of the restart sequence j-

[0049] Advantageously, the measurements and information representing the activation of the heating system 11 in each selected restart sequence cumulatively satisfy a first, second, and third predefined criterion. The first predefined criterion requires that the heating system 11 be active at each of the successive times fi. The second predefined criterion requires that the indoor temperature Tint be increasing. For example, the indoor temperature Tint must be higher at each of the successive times fi than at the previous time fi of the sequence of restart j, with a temperature variation over time greater than 0.2°C per hour. The third predefined criterion requires that the indoor temperature Tint measured at any instant of the restart sequence j be lower than a setpoint temperature Tcons of the time program that must be reached subsequently to that instant and associated with the first tcons setpoint time occurring after said instant

[0050] According to one embodiment, the management unit 200 selects all the restart sequences over a past period of a second predefined duration, the second predefined duration being, for example, between 7 days and 2 months. Thus, it is possible to select a large number of restart sequences, in other words, restart sequences obtained under sufficiently varied conditions, to obtain an accurate model. Furthermore, the variability related to differences between seasons is limited. For example, since the effect of solar radiation on the indoor temperature differs from one season to another due to the sun's path and the angle of the solar radiation relative to a glazed wall 12, the second predefined duration is sufficiently restricted so that the effect of solar radiation remains stable.

[0051] Alternatively, management unit 200 selects a predefined number of restart sequences.

[0052] According to another variant, the management unit 200 selects all relaunch sequences over a past period of a second predefined duration if the number of selected relaunch sequences is greater than a predefined minimum number, and selects the predefined minimum number of previous relaunch sequences otherwise, said relaunch sequences then extending over a past period greater than said second predefined duration.

[0053] According to one embodiment, the management unit 200 selects the restart sequences that also satisfy a fourth criterion. The fourth criterion requires that the difference in indoor temperature Tint between the initial time and a final time corresponding to the last time of the restart sequence j be greater than a predefined difference in indoor temperature equal, for example, to 1°C.

[0054] According to an example embodiment (not shown), the management unit 200 further determines whether at least one new restart sequence is selected compared to a previous implementation of the learning phase. If so, the management unit 200 proceeds to a subsequent step 304. Otherwise, the management unit 200 returns to step 300. Thus, the implementation of the learning phase is carried out only when new measurements and meteorological values ​​are taken into account. This reduces the computational energy consumption.

[0055] At step 304, the management unit 200 determines, for each selected instant of

[0056]

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[0060]

[0061] each selected restart sequence j, the plurality of variables at the selected instant and in relation to the initial instant of said restart sequence j. The first variable, representing the heat inputs provided by the heating system 11 and taking into account the thermal insulation between the building 10 and the exterior, is a function of the interior temperature Tint and the exterior temperature Texl. The first variable is defined by the difference between the interior temperature Tint at the initial time and the exterior temperature Text at the selected time. The second variable, representing the solar heat inputs transmitted to the building 10, is a function of the forecast meteorological values ​​of solar radiation Gh. The second variable is defined by the cumulative solar radiation Gh between the initial time d and the selected time, which can be written as [f _.. The third variable, re-' '0 The representative of heat losses over time is defined by the time difference between the selected instant / 1 and the initial instant. The management unit 200 further determines a fourth variable which is constant and equal to 1. This makes it possible to account for the influence of forecasted meteorological values, such as solar radiation, on the evolution of indoor temperature, while providing an accurate model through the selection of restart sequences based on predefined criteria. Furthermore, the use of solar radiation (Gh) meteorological values ​​allows for consideration of solar heat gains when estimating indoor temperature variations. This enables the adjustment of the duration for which the heating system (11) is activated before reaching a setpoint temperature, based on solar heat gains. Consequently, heating system energy consumption is reduced when solar radiation is high. According to an example implementation, the plurality of variables is grouped into a vector, called the explanatory vector of the evolution of the temperature X^' defined at a selected instant and in relation to an initial instant ^ of a restart sequence j, which can therefore be written: X(r / ) = The management unit 200 can construct a learning matrix, denoted Xa, for which each row is associated with a selected instant / 1 and corresponds to the explanatory vector of the temperature evolution X(tfy determined at said selected instant each selected instant / ï of the at least one selected restart sequence j being associated with a row, in a given order. In a subsequent step 306, the management unit 200 determines, for each instant selected fl of each selected restart sequence j, an internal temperature variation & between said selected instant fl and the initial instant of said restart sequence j. The variation in indoor temperature A constant equal to the difference between the indoor temperature Tint measured at the selected time and the indoor temperature Tint measured at time . Management unit 200 therefore calculates A T,„,(> / )= Tjti)-

[0062] According to one embodiment, the management unit 200 constructs a thermal evolution vector Ya which is a column vector for which each row, associated with a selected instant fl of the at least one selected restart sequence j, corresponds to the variation of internal temperature A determined at selected instant fi. Each selected instant fl of the at least one selected restart sequence j is associated with a line of said thermal evolution vector Ya in the same order as for the learning matrix Xa.

[0063] Steps 304 and 306 can alternatively be carried out in parallel. According to another example, step 306 is carried out before step 304.

[0064] In a subsequent step 308, the management unit 200 calculates, by multiple linear regression, a coefficient associated with each variable. The set of said coefficients is calculated so as to maximize the equality, for the set of selected instants fl, between the variation of indoor temperature A and the summation of the variables associated with their own coefficients.

[0065] According to an exemplary embodiment, the management unit 200 calculates a model vector b, comprising said coefficients, and allowing the minimization of the errors of the set of equations A Tint ( tj ) — tJ- ) b defined for all selected instants / ■' of the at least one selected restart sequence j. To do this, the management unit 200 calculates the model vector b by solving the following equation: y1 y , in which Xa' is the transpose of Xa and y J1 is 'a inverse matrix of XaXa-

[0066] Thus, the calculation of the model vector by multiple linear regression makes it possible to obtain an accurate model allowing the estimation of the indoor temperature while using a limited amount of data.

[0067] The management unit 200 then records the calculated coefficients or the obtained model vector b, and then returns to the initial step 300.

[0068] Fig. 4 schematically illustrates a phase of operation of the process for determining an activation time of the heating system 11, implemented by the management unit 200.

[0069]

[0070]

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[0077] In an initial step 400, the management unit 200 awaits a new measurement of the Tint indoor temperature from the first temperature sensor 14. In a subsequent step 402, the management unit 200 receives from the first temperature sensor 14 a new measurement of the internal temperature Tin^tm.), taken at a measurement instant tm. In a subsequent optional step 404, the management unit 200 obtains, for example upon request, the status of the heating system 11 at the measurement time tm, and determines whether, at the measurement time tm, the heating system 11 is inactive. If so, a step 406 is performed. Otherwise, the management unit 200 returns to the initial step 400. In the optional step 406, the control unit 200 determines whether the indoor temperature Tint measured at the measurement time tm is lower than a setpoint temperature Tcons that must be reached at a future setpoint time tcons. This future setpoint time tcons is the first time-scheduled event after the measurement time tm. The setpoint temperature Tcons must therefore be reached after the measurement time tm. If so, step 408 is performed. Otherwise, the control unit 200 returns to the initial step 400. In step 408, management unit 200 retrieves, in response to a request sent to service 16 for the provision of forecast meteorological data, forecast meteorological values ​​of outdoor temperature Text and solar radiation Gh, each associated with a future forecast time, and for future forecast times between the measurement time tm and a future time tf, at which an estimate of the indoor temperature is to be determined. In a subsequent step 410, the management unit 200 determines the plurality of variables described in step 304 defined at said future instant tfet in relation to the measurement instant tm. In other words, the management unit 200 determines the first variable, equal to the difference between the indoor temperature Tin^tm) at the measurement instant tm and the outdoor temperature Tex^tf) at the future instant tf, the second variable, equal to the cumulative solar radiation between the measurement instant tm and the future instant tf, the third variable, equal to the time difference between the future instant tjet and the measurement instant tm, and the fourth variable equal to 1. According to an example implementation, the plurality of variables forms an explanatory vector of the temperature evolution X(tf), defined at the future time tjet in relation to the measurement time tm, which can be written: In a subsequent step 412, management unit 200 determines an estimate of the indoor temperature Tint at the future time tf.

[0078] To this end, the management unit 200 calculates the estimated indoor temperature variation ATint_estim between the measurement time tm and the future time tj by applying the calculated coefficients to the plurality of variables determined in the preceding step 410. The management unit 200 uses the most recent calculated coefficients, obtained during step 308 of the most recent implementation of the learning phase.

[0079] According to one embodiment, the coefficients are applied by multiplying the model vector b by the explanatory vector of the temperature evolution X(tf) determined in the preceding step 410. In other words, the management unit 200 solves the equation A T in,Jstim =

[0080] The management unit 200 deduces an estimated indoor temperature Tint(tcons) at the future time tj by adding the indoor temperature measured at the measurement time tm to the estimated indoor temperature variation ATint_estim between the measurement time tm and the future time tf, i.e.: T. (tÀ—T (t 1 + * .• •

[0081] Advantageously, the management unit 200 further determines an activation time for the heating system 11. The management unit 200 implements for this purpose the optional steps 404 and 406 and implements steps 408, 410 and 412 taking as future time ^the future setpoint time tcons as defined in step 406. The control unit 200 then performs a step 414.

[0082] In step 414, the management unit 200 determines whether the estimated indoor temperature Tint(tcons) at the future setpoint time tcons is less than the setpoint temperature Tcons considered in step 406. If so, the management unit 200 performs step 416. Otherwise, the management unit 200 returns to the initial step 400.

[0083] At step 416, the management unit 200 activates the heating system 11.

[0084] It is thus possible to determine an activation time of the heating system of in a precise and rapid manner and taking into account variations in weather conditions, which makes it possible to ensure compliance with a set temperature while minimizing energy consumption.

[0085] Management unit 200 then returns to the initial step 400.

Claims

1. Demands Method for determining the activation time of a heating system (11) in a building (10), the method being implemented by a control unit (200) connected to the heating system (11), the heating system heating the building (10) when said heating system (11) is activated, the method comprising: - to record measurements of the building's internal temperature, referred to as the internal temperature, and the temperature outside the building, referred to as the external temperature, and forecast meteorological values ​​including external temperature values ​​and solar radiation values, each measurement being associated with a measurement time, each forecast value being associated with a forecast time, - select (302) at least one restart sequence comprising indoor and outdoor temperature measurements and forecast meteorological values ​​associated with past measurement or forecast times, each restart sequence being defined, from an initial time, by a plurality of successive times, called selected times, at which the indoor temperature measurements satisfy at least one predefined criterion, - determine (304, 306), for each selected instant of each selected restart sequence, a variation in indoor temperature between said selected instant and the initial instant of the restart sequence, as well as a plurality of variables determined at said selected instant and in relation to said initial instant, said variables influencing the variation in indoor temperature, a first variable being equal to the difference between the indoor temperature at the initial instant and the outdoor temperature at said selected instant, a second variable being equal to the cumulative solar radiation between the initial instant and the selected instant, and a third variable being equal to the time difference between the selected instant and the initial instant, - calculate (308), by multiple linear regression, a coefficient associated with each variable, the coefficients allowing to maximize, for all the selected instants, the equality between the variation of indoor temperature and the sum of the variables associated with their own coefficients, - to store (308) the coefficients calculated to activate the heating system (11) at a time of a new measurement of the indoor temperature as a function of an estimated variation of the indoor temperature between said time of the new measurement and a future time, said estimated variation of the indoor temperature being determined (412) from said stored coefficients, applied to the plurality of variables determined using forecast meteorological values ​​and a measurement of the indoor temperature at said time of the new measurement.

2. A method according to claim 1, wherein selecting at least one restart sequence involves selecting a predefined minimum number of restart sequences.

3. Method according to claim 1, wherein selecting at least one restart sequence involves selecting all restart sequences over a period of predefined duration.

4. A method according to any one of claims 1 to 3, wherein the control unit (200) includes a time program comprising setpoint temperatures, each setpoint temperature being associated with a setpoint instant at which the setpoint temperature must be reached, and wherein at least one predefined criterion requires that the indoor temperature be increasing, that the indoor temperature be lower than a setpoint temperature associated with a setpoint instant of the time program occurring first after each of said selected instants, and wherein the heating system (11) is further activated at each selected instant of each restart sequence.

5. A method according to claim 4, wherein the indoor temperature is estimated at the future time from the estimated variation of the indoor temperature between the time of the new measurement and the future time and the measurement of the indoor temperature at the time of the new measurement, wherein said future time corresponds to a setpoint time of the time programming, the method further comprising activating (416) the heating system if the estimated indoor temperature at said setpoint time is less than or equal to the setpoint temperature associated with said setpoint time.

6. A method according to claim 5, wherein the estimation of the indoor temperature determined at the setpoint time is performed when (404) the heating system is inactive at the measurement time and when (406) the measurement of the indoor temperature at said measurement time is less than the setpoint temperature associated with said setpoint time.

7. A method according to any one of claims 1 to 6, wherein the forecast weather values ​​include values ​​of outside temperature, and include values ​​of solar radiation, and wherein the plurality of variables determined at a selected instant in relation to an initial instant includes a first variable equal to the difference between the indoor temperature at the initial instant and the outdoor temperature at said selected instant, a second variable equal to the cumulative solar radiation between the initial instant and the selected instant, and a third variable equal to the time difference between the selected instant and the initial instant.

8. Method according to the preceding claim, wherein calculating (308), by multiple linear regression, a coefficient associated with each variable comprises further calculating a coefficient associated with a constant equal to 1.

9. A method according to any one of claims 1 to 8, wherein the calculated coefficients are obtained, in the form of a vector b comprising each of said coefficients, by solving the equation _ Çy' y y1 y-' y , in which Xa represents a matrix comprising, for each row, an explanatory vector associated with a selected instant, each selected instant being associated with a row, each explanatory vector comprising the variables determined at the selected instant associated with and in relation to the initial instant of the restart sequence, in which Ya represents a vector comprising, for each row, the variation in indoor temperature associated with a selected instant, equal to the variation in indoor temperature between said selected instant and the initial instant of the restart sequence, each selected instant being associated with a row in the same order as for the training matrix Xa,and in which Xa' is the transpose of Xa and (XX) is the inverse matrix of XaXa-,

10. A management unit (200) intended to manage the thermal performance of a building (10), the management unit (200) being connected to a heating system (11), the heating system heating the building (10) when said heating system (11) is activated, and the management unit (200) comprising electronic circuitry configured to: - record measurements of the building's interior temperature (10), referred to as the interior temperature, and the building's exterior temperature, referred to as the exterior temperature, and forecast meteorological values ​​including exterior temperature values ​​and solar radiation values, each measurement being associated with a measurement time, each forecast meteorological value being associated with a forecast time, - select at least one relaunch sequence comprising indoor and outdoor temperature measurements and forecast weather values ​​associated with past measurement or forecast times, each relaunch sequence being defined, from an initial time, by a plurality of successive times, called selected times, at which the indoor temperature measurements satisfy at least one predefined criterion, - determine, for each selected instant of each selected restart sequence, a variation in indoor temperature between said selected instant and the initial instant of the restart sequence, as well as a plurality of variables determined at said selected instant and in relation to said initial instant, said variables influencing the variation in indoor temperature, a first variable being equal to the difference between the indoor temperature at the initial instant and the outdoor temperature at said selected instant, a second variable being equal to the cumulative solar radiation between the initial instant and the selected instant, and a third variable being equal to the time difference between the selected instant and the initial instant, - calculate, by multiple linear regression, a coefficient associated with each variable, the coefficients allowing to maximize, for all the selected instants, the equality between the variation of indoor temperature and the sum of the variables associated with their own coefficients, - to store (308) the coefficients calculated to activate the heating system (11) at a time of a new measurement of the indoor temperature based on an estimated variation in the indoor temperature between said time of the new measurement and a future time, said estimated variation in the indoor temperature being determined (412) from said stored coefficients, applied to the plurality of variables determined using forecast meteorological values ​​and a measurement of the indoor temperature at said time of the new measure.

11. Product computer program that can be stored on a medium and / or downloaded from a communication network, in order to be read by a processor, and characterized in that it includes instructions to implement the method according to any one of claims 1 to 9, when said computer program is executed by the processor.

12. Information storage medium storing a computer program comprising instructions for implementing the method according to any one of claims 1 to 9 when said computer program is read from said storage medium and executed by the processor.

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