Method, apparatus and system for determining the amount of thermal energy delivered to a room in a building over a given period of time - Patents.com

Abstract

The invention relates to a method (100) for determining an amount of thermal energy to be supplied by a collective thermal management device (30) to a premises (20) in a building (2) over a given period of time, said determination being performed by one or more processors and comprising using a plurality of ambient temperature values ​​of the building, external temperature values ​​of the building (2), a volume of the premises (20) in the building and a heat loss coefficient, said method being characterized in that the heat loss coefficient is calculated (130) from a thermal simulation model (41) of the building, taking into account the shape of the premises and the configuration of the walls. The invention also relates to an allocator (10) for determining the amount of thermal energy to be supplied by the collective thermal management device (30) and to a system (1) for allocating heating costs, comprising an allocator (10) according to the invention.

Description

[Technical field]

[0001] The present invention relates to the field of buildings, in particular to the management of thermal energy in buildings. In particular, the present invention relates to a method for determining the amount of thermal energy to be supplied to premises in a building over a given period of time. Furthermore, the present invention relates to an apparatus and a system for determining the amount of thermal energy to be supplied to premises in a building, in particular for the allocation of energy costs. [Background technology]

[0002] The known prior art on which the present invention was developed is described below.

[0003] Building on the goals set out in the Paris Agreement, the European Union has set ambitious targets for the energy transition up to 2030 and 2050, with a focus on promoting the use of renewable energies, energy efficiency and reducing greenhouse gas emissions.

[0004] In 2016, buildings accounted for almost 40% of the European Union's final energy consumption. This sector therefore has a lot of room for progress in terms of energy efficiency, although there are large differences in the performance of buildings across countries. In particular, heating and cooling in the residential sector, services and industry account for around 50% of the EU's primary energy supply (European Commission - Information Sheet - 16 February 2016). In particular, the origin of primary energy for residential heating is mainly dependent on fossil fuels (82% in 2016), while 68% of total gas imports to Europe come from the heating and cooling sector.

[0005] Heating buildings is therefore a key objective for achieving the energy transition targets for 2030 and 2050.

[0006] Buildings have therefore been the subject of numerous studies and models aimed at characterizing their energy performance. For example, dynamic thermal simulations (DTS) of buildings have been proposed. These studies are mainly aimed at building owners and allow to simulate the energy performance of different envisaged technological solutions, such as CMV, heat generators or even artificial light management solutions compared. These studies based on dynamic thermal simulations of buildings are also implemented in construction project programs to analyse summer thermal comfort in the absence of air conditioning or to quantify the need for heating.

[0007] Such simulations have also been proposed to estimate the predicted consumption. However, buildings are complex and non-stationary energy systems. Therefore, important variations are observed between the simulated and measured consumption due to errors in the input data, the occupancy scenario or the environmental conditions. Moreover, these simulations are usually based on heavy software clients and are not used on embedded systems configured to perform the analysis in real time. Recently, it has been proposed to model buildings and their systems in order to optimize the energy management (Hugo Viot. Modelisation et instrumentation d'un batiment et de ses systemes pour optimiser sa gestion energetique. University of Bordeaux, 2016. In French. NNT:2016BORD0349; tel. +33 (0)1503037). In particular, since the DTS model is considered too heavy, it has been proposed to build a model with small dimensions so that it can be embedded in the controller to improve the energy management. Nevertheless, such simplified models have a performance that can be improved. Moreover, given that one building does not behave in the same way as another, the performance depends heavily on the learning base used and the model may require training for each new building.

[0008] Therefore, where this consumption cannot be efficiently predicted, monitoring is carried out, which, especially in the context of RT2012, requires a minimum monthly measurement of energy consumption per location and per energy type, but this is only monitoring and not a measure to promote the energy transition.

[0009] In this respect, in collective heating apartments, the division of heating costs is usually done according to the percentage of ownership or on the basis of the surface area of ​​the apartment. Such a division does not encourage thrift, since the heating costs are calculated according to the surface area of ​​the apartment or the percentage of ownership, even if the heating consumption differs from dwelling to dwelling.

[0010] Therefore, individualized heating bills are being implemented in France, not only to evaluate improvements in the energy performance of buildings, but also to hold residents accountable. Individualized heating bills (or allocations) allow each apartment to pay according to the amount it actually consumes. Residents are therefore encouraged to control their consumption and avoid energy waste. Individualized heating bills have achieved energy savings of around 15% on average and allowed a reduction in bills for residents who wish to regulate their consumption (ADEME, September 2019, ISBN979-10-297-1399-6).

[0011] To be able to know what each occupant has consumed, remotely readable measuring devices must be installed. Currently there are two main devices on the market: individual thermal energy meters (TEMs) and heat cost allocators (HCAs).

[0012] TEMs are installed at the entrance of each dwelling and display the actual heating consumption, allowing residents to monitor their own consumption. HCAs are installed when the installation of TEMs is technically impossible or not economical. HCAs use the measurement of the surface temperature of the heating element. They are placed at each radiator in the dwelling. "Traditional" HCAs have three main operating modes. These are defined by the standard NFEN834: i) single-probe measurement method (a probe that measures the surface temperature of the heating element or the temperature of the heat transfer fluid); ii) two-probe measurement method (one probe measures the surface temperature of the heating element or the temperature of the heat transfer fluid and the other probe measures the ambient temperature); iii) multi-probe measurement method (several probes to measure the average temperature of the heat transfer fluid and one probe for the ambient temperature).

[0013] The installation results of these solutions have fallen far short of expectations: more specifically, many buildings do not allow for individualized heating costs, mainly due to the complexity of installing these systems.

[0014] Moreover, these systems for allocating heating costs are unable to propose a reliable calculation of the energy consumed with regard to the location of the dwelling. More specifically, it is proposed to calculate heating costs based on a fixed portion of 30%, with the possibility of incorporating correction factors to take into account unfavourable thermal situations (houses located on the north side have less solar inflow, those on the top floor have greater heat losses, etc.). However, these measures are unable to accurately take into account the consumption of the house. Thus, strong inequities remain for residents depending on the location of the dwelling.

[0015] Moreover, these systems remain vulnerable to "heat theft": more specifically, dwellings with low heating capacity located in the center of a building will benefit from the heat transferred from adjacent hot dwellings. Thus, the inequities associated with the use of separate heat energy meters and the allocation of actual heating costs will also remain.

[0016] Therefore, there is a need for a solution that can effectively (e.g., in real time and accurately) determine residential thermal energy consumption, in particular the amount of thermal energy provided to the building premises by collective thermal management devices. Furthermore, such a solution should also allow for a more accurate calculation of heating costs, enhancing the fairness of heating cost payments in collective buildings. Summary of the Invention [Problem to be solved by the invention]

[0017] The present invention aims to remedy these drawbacks of the prior art. In particular, the invention aims to propose a method for determining the amount of thermal energy to be supplied to a premises in a building over a given period of time, which is capable of determining such an amount with precision and accuracy, and does so without the need for the installation of expensive dedicated equipment. Furthermore, taking into account the thermal simulation model of the building and the fact that the allocation can be carried out taking into account the ambient temperature, a compensation system can be introduced, which improves fairness between users and finally takes into account the level of thermal comfort rather than the level of energy consumption.

[0018] Furthermore, the invention aims to propose an allocator for determining the amount of thermal energy to be supplied to the premises of a building by a collective thermal management device, said allocator being able to operate on the basis of simple measurements of the building's ambient temperature and the outside air temperature in order to determine the amount of thermal energy to be supplied to the premises of the building by the collective thermal management device. [Means for solving the problem]

[0019] The present invention aims to overcome these drawbacks.

[0020] The present invention has as its object in particular to provide a method for allocating energy costs in a collective building comprising a number of individual premises and at least one collective thermal management device, the method being applicable to all the individual premises of the collective building and comprising the steps of: determining an amount of thermal energy provided by at least one collective thermal management device to at least one individual premises of the collective building over a given period of time; calculating at least one heat loss coefficient for the individual premises based on a thermal simulation model of the collective building; The determining may be performed by one or more processors and may include using: a thermal simulation model of an aggregate building, which represents the aggregate building virtually and takes into account, for each individual site, the shape of the individual sites, the configuration of the walls of the individual sites and the heat exchange between the various sites of the aggregate building; a plurality of ambient temperature values ​​for the collective building, the plurality of ambient temperature values ​​including a plurality of temperatures for individual premises and a plurality of temperatures for premises or common spaces of the collective building adjacent to the individual premises; One or more values ​​of temperature outside the collective building; The volume of each individual lot; and At least one heat loss coefficient for each individual premises.

[0021] The applicant has developed a method that allows to quickly calculate the amount of energy supplied to an individual premises, essentially based on internal and external ambient temperature data. In particular, in the context of the present invention, it allows the use of as many heat loss coefficients as there are premises. And, in a particular advantageous embodiment, several heat loss coefficients can be associated to the same individual premises as a function of the period considered. This method can be used in particular to calculate heating costs and to incorporate the concept of fairness between users of the same collective building.

[0022] According to other optional features of the method, said method may optionally include one or more of the following features, either alone or in combination:

[0023] If the individual sites are additionally defined by the fixture configuration, the thermal simulation model of the collective building is a model that further considers the fixture configuration. In this way, by directly incorporating the fixture configuration when constructing the thermal simulation model of the collective building, it is possible to improve performance without imposing a burden on the calculations.

[0024] The thermal simulation model of the multi-family building further takes into account data representing localized solar radiation over a period of time. In this way, by directly incorporating data representing solar radiation when constructing the thermal simulation model of the multi-family building, performance can be improved without incurring a computational burden.

[0025] The thermal simulation model of the complex is a dynamic thermal simulation model of the complex. The use of a dynamic thermal simulation model makes it possible to obtain an improved accuracy of the determined heat supply using the method according to the invention.

[0026] The heat loss coefficient for the individual premises is selected from at least two predefined heat loss coefficients, each of which corresponds to a period of time, so that it is possible to select a heat loss coefficient that allows a more accurate determination of the amount of thermal energy to be supplied, for example as a function of the season or month.

[0027] The determination of the amount of thermal energy supplied by at least one collective thermal management device to at least one individual premises of the collective building comprises the use of one or more adjustment factors, each of which is applied to an adjustment variable measured or calculated for a given period of time. Preferably, the adjustment factors are calculated based on a dynamic thermal simulation model of the collective building. It is thus possible to adjust the amount of energy supplied, determined as a function of additional parameters that best represent the use of the individual premises. This allows a more accurate determination of the amount of thermal energy supplied.

[0028] The adjustment variables are selected from: variables representing heat losses associated with window openings, variables representing the occupancy level of the individual premises, variables representing weather conditions (e.g. extreme weather conditions), and / or variables representing the use of auxiliary heating. This allows the incorporation of actual usage, either directly measured or modeled for each individual premises, without burdening the model, resulting in greater accuracy.

[0029] The adjustment variables are either measured directly at individual sites, modeled probabilistically based on statistics, or reconstructed based on measurements from machine learning algorithms.

[0030] For each adjustment factor, the method includes the step of calculating a number of adjustment factor values, each as a function of a period of the year, the value of the adjustment factor used to determine the amount of thermal energy to be delivered being a function of the given period of time, for example there are adjustment factor values ​​calculated for each month as a function of time, the value corresponding to the month under consideration being used.

[0031] The method includes a calibration step of the thermal simulation model of the collective building, which is preferably performed based on a first measurement period and a Bayesian calibration algorithm, so that the predictions of the consumption and internal temperature on an hourly basis of the thermal simulation model of the collective building reproduce the measured values ​​as accurately as possible.

[0032] The method includes a calibration step of the thermal simulation model of the collective building, which calibration step is preferably performed based on a first measurement period of ambient and external temperature values ​​and a Bayesian calibration algorithm, so that the temperatures calculated by the thermal simulation model of the collective building reproduce the measured temperature values ​​as accurately as possible.

[0033] The ambient temperature of an individual site corresponds to temperatures measured at multiple locations within the site. The various locations can correspond to different rooms.

[0034] The method includes calculating an individual heating cost for an individual premises as a function of the determined amount of thermal energy supplied to said individual premises by the collective thermal management device.

[0035] In the step of calculating the individual heating costs, the orientation and location characteristics of the individual premises in the collective building are taken into account, which makes it possible to correct disparities between premises and common spaces in the collective building. This introduces the principle of fairness into the allocation of heating costs and makes it possible to correct imbalances between premises and common spaces in the collective building (e.g. different orientations, different floors, etc.). Moreover, this allows tenants to pay for the part of the heating consumption for which they are actually responsible, i.e. the heating temperature.

[0036] The method comprises the step of calculating a confidence interval for the determined amount of thermal energy. Preferably, said calculation of the confidence interval comprises the use of at least one uncertainty value for one or more adjustment variables used during the determination of the amount of thermal energy to be delivered.

[0037] Calculating at least one heat loss coefficient for the individual sites based on the thermal simulation model of the collective building may include calculating, for the individual sites, at least one heat loss coefficient based on a plurality of simulations in which geometric values, wall configurations, and optionally fitting configurations of the individual sites are varied in a manner that incorporates uncertainties associated with the collective building.

[0038] Calculating at least one heat loss coefficient for the individual sites based on the thermal simulation model of the collective building may include calculating, for the individual sites, the at least one heat loss coefficient based on multiple simulations in which values ​​of the use and / or the weather conditions are further varied in a manner that incorporates uncertainties associated with the use and weather conditions.

[0039] According to a second object, the present invention relates to an allocator of energy costs in a collective building comprising a plurality of individual premises and at least one collective thermal management device, the method being applicable to all the individual premises of the collective building, comprising determining an amount of thermal energy to be supplied to at least one individual premises of the collective building by at least one collective thermal management device, said allocator comprising one or more processors configured to determine the amount of thermal energy to be supplied using: a thermal simulation model of an aggregate building, which represents the aggregate building virtually and takes into account, for each individual site, the shape of the individual sites, the configuration of the walls of the individual sites and the heat exchange between the various sites of the aggregate building; a plurality of ambient temperature values ​​for the collective building, the plurality of ambient temperature values ​​including a plurality of temperatures for individual premises and a plurality of temperatures for premises or common spaces of the collective building adjacent to the individual premises; One or more values ​​of temperature outside the collective building; The volume of each individual lot; and At least one heat loss coefficient for the individual premises, representing the percentage of the thermal energy supplied to the individual premises that is transferred to premises adjacent to the individual premises or to common spaces; The allocator is configured to calculate at least one heat loss coefficient for an individual site based on a thermal simulation model of the collective building.

[0040] In certain implementations, if the individual sites are further defined by fixture configurations, the allocator is characterized in that the thermal simulation model of the collective building further takes into account the fixture configurations.

[0041] Preferably, the allocator is such that the thermal simulation model of the collective building is a model that further takes into account data representative of local solar radiation over a given period of time.

[0042] As described below, an allocator has multiple heat loss coefficients, each dedicated to an individual site. Additionally, a site may be associated with multiple heat loss coefficients, each dedicated to a given time period.

[0043] According to a third object, the invention relates to a system for allocating heating costs, comprising an allocator according to the invention, in particular such an allocation system enabling tenants to pay for the part of the heating consumption for which they are actually responsible, i.e. the heating temperature.

[0044] Other characteristics and advantages of the invention will be better understood from the following description, given by way of example only and in no way limiting, with reference to the accompanying drawings, in which: [Brief description of the drawings]

[0045] [Figure 1] FIG. 2 illustrates a method according to one embodiment of the present invention. [Diagram 2] 1 illustrates a system for determining an amount of thermal energy provided by a collective thermal management device, according to one embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0046] For purposes of illustration, the figures are not necessarily drawn to scale, particularly in terms of thickness.

[0047] Aspects of the present invention are described with reference to flowchart illustrations and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the invention.

[0048] In the drawings, the flow diagrams and block diagrams illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flow diagrams or block diagrams may represent a system, device, module, or code, which is comprised of one or more executable instructions for implementing one or more specified logical functions. In certain implementations, the functions associated with the blocks may appear in a different order than shown in the figures. For example, two blocks shown in succession may in fact be executed substantially simultaneously or in the reverse order depending on the functionality involved. Each block of the block diagrams and / or flow diagrams, and combinations of blocks in the block diagrams and / or flow diagrams, may be implemented by a specialized hardware system, which performs the specified functions or actions, or executes a combination of specialized hardware and computer instructions.

[0049] Below, we provide an overview of the invention and related terms, then present the shortcomings of the prior art, and finally show in more detail how the present invention overcomes them.

[0050] The expression "heat loss coefficient", also called the total volumetric heat loss coefficient of a building, corresponds to the overall performance of the insulation in terms of heat loss per degree difference between the internal and external environment. The total volumetric heat loss coefficient of a building expresses the heat loss per unit heated volume. It is generally expressed in watts per cubic meter (Watts / m) for a change of one degree Celsius between the outdoor and indoor temperatures. 3 The coefficient G was introduced in the 1974 Thermal Regulation: "Order of April 10, 1974 on Thermal Insulation and Automatic Control of Heating Installations in Residential Buildings". It is generally between 0.5 and 3 watts / m 3 and °C.

[0051] In the remainder of the description, the expression "area within a building" corresponds to a part of a building consisting of one or more rooms. The area corresponds for example to an office or a residence. The expression "volume of the area" therefore corresponds to the volume of one or more rooms within a building.

[0052] The expression "individual heating costs" generally corresponds to heating costs calculated on the basis of the actual consumption of the premises within the building, which consumption is established on the basis of a device that determines the amount of heating or cooling consumed in each premises.

[0053] In the context of the present invention, the expression "thermal simulation model" may correspond to a model configured to virtually represent a building and to describe its behavior when faced with stresses related to the climate or the behavior of the users (these stresses are modeled probabilistically). In particular, the expression "dynamic thermal simulation of a building" may correspond to a model configured to calculate the evolution over time of the thermal state of a building. This notably makes it possible to determine, at every selected time of the simulation, the temperatures of a certain number of points of an element that constitutes the element and that evolve according to the different laws governing heat exchange (convection, conduction, radiation, change of state). The thermal simulation model thus makes it possible to estimate the thermal demand of the building, taking into account the building shell and its inertia, the different heat inputs, the behavior of the occupants and the local climate.

[0054] The expression "local solar radiation" in the context of the present invention can correspond to the amount of solar energy received per unit surface area, for example in watts per square meter (Watts / m 2 ) can be expressed as

[0055] The term "correlation model" or "algorithm" is to be understood within the meaning of the present invention as a finite sequence of operations or instructions that allows to calculate a value on the basis of one or more input values. The implementation of this finite sequence of operations makes it possible to attribute a value Y, such as, for example, a label Y, to an observation described by a sequence of features or parameters X used, thus implementing, for example, a function f that reproduces Y given the observed X. Y=f(X)+e During the ceremony: E: noise and measurement error.

[0056] The term "supervised machine learning model" should be understood within the meaning of the present invention to mean a correlation model that is automatically generated based on data called observations (which are labeled).

[0057] The term "unsupervised machine learning model" should be understood within the meaning of the present invention to mean a correlation model that is automatically generated based on data called observations (unlabeled).

[0058] Within the meaning of the present invention, the terms "processing", "calculating", "determining", "displaying", "converting", "extracting", "comparing" or more broadly "executable operations" are to be understood as actions performed by a device or processor, unless the context indicates otherwise. In this regard, operations relate to the operation and / or process of a data processing system, such as a computer system or an electronic computing device, which processes and transforms data represented as physical (electronic) quantities in the memory of a computer system or other storage device, and transmits or displays information. These operations can be based on applications or software.

[0059] The terms or expressions "application," "software," "program code," and "executable code" mean a representation, code, or notation of a sequence of instructions intended to cause data processing to perform a particular function directly or indirectly (e.g., after translation into another code). Examples of program code may include, but are not limited to, subprograms, functions, executable applications, source code, object code, libraries, and / or other sequences of instructions designed to execute on a computer system.

[0060] The term "processor" in the sense of the present invention is intended to mean at least one hardware circuit configured to execute operations according to instructions contained in a code. The hardware circuit may be an integrated circuit. Examples of processors include, but are not limited to, central processing units, graphic processors, application specific integrated circuits (ASICs), and programmable logic circuits.

[0061] The term "electronic device" is intended to mean any device comprising a processing unit or processor, for example in the form of a microcontroller cooperating with a data memory and, optionally, a program memory (which may be separable), the processing unit cooperating with said memory via an internal communication bus.

[0062] The term "coupled" in the context of the present invention shall mean directly or indirectly connected with one or more intermediate elements. Two elements may be mechanically or electrically coupled, or may be linked by a communication channel.

[0063] The terms "accurate" or "precision", "reliable" or "reliability", "highly accurate" or "precision" mean a reproducible and accurate measurement. Moreover, this means that the measurement is free of errors or at least that the error rate of the measurement is, for example, less than 5%, preferably less than 2%, most preferably less than 1%. Furthermore, the expression "improved precision" may correspond within the meaning of the present invention to a very accurate consumption value, which value has, for example, a precision of an error rate of less than 5%, preferably less than 2%, most preferably less than 1%.

[0064] Individual thermal energy meters (TEMs) exist, but these systems are expensive and complex to install (one meter is required for each hot water loop, and installation requires plumbing). Heat cost allocation tools (HCAs) also exist, which are based on measuring radiator surface temperatures. However, these systems are inaccurate and complex to install (especially since they need to be installed on each radiator). Neither TEMs nor HCAs establish fairness for building occupants.

[0065] The inventors have developed a solution that makes it possible to determine the amount of thermal energy delivered to a premises in a building over a given period of time without the installation of heavy electronic equipment.

[0066] In particular, the inventors have developed a determination solution that takes into account the heat loss coefficient of the site, calculated on the basis of a thermal simulation model of the building, taking into account the shape of the site and the configuration of the walls. Furthermore, if the site includes fittings, the thermal simulation model of the building can also take into account the configuration of this fitting. Furthermore, preferably, data representing local solar radiation over a given period of time can also be taken into account. Such a solution makes it possible to combine the accuracy of a solution using thermal simulation using large computational systems with the responsiveness and lightness of a solution based on heat loss coefficients. More specifically, attempts have been made to directly incorporate thermal simulation models into methods for determining the amount of thermal energy to be supplied to the site, but these solutions have not been accurate enough and are generally too heavy to implement.

[0067] Thus, according to a first aspect, the invention relates to a method 100 for determining the amount of thermal energy supplied to a premises 20 in a building 2, as shown according to the example of FIG.

[0068] The amount of thermal energy supplied to the premises 20 corresponds, for example, to the amount of energy supplied by the collective heat management device 30. The collective heat management device 30 generally corresponds to a collective gas boiler. Nevertheless, it can also correspond to another heating system (possibly electric), such as a heat pump or a heat network.

[0069] In particular, the determined amount of thermal energy to be supplied may be relative, although the determined amount of thermal energy to be supplied is preferably expressed in international measurement units of thermal energy, such as watt-hours. The amount of thermal energy to be supplied may correspond, for example, to an amount per month.

[0070] Preferably, the site 20 for which the amount of thermal energy to be delivered is determined corresponds to an individual site, more preferably to a dwelling. The site may be defined by a geometric shape. The geometric shape of the site may correspond to the dimensions of the walls forming said site. These dimensions may refer to the dimensions of the fittings and may include the orientation of the walls forming the site. Preferably, the geometric shape of the site 20 includes the surface area of ​​the walls and, optionally, the surface area of ​​the fittings, the position and orientation of the fittings in the building 2. Furthermore, the site is defined in particular by the configuration of the walls and, if necessary, by the configuration of the fittings. More specifically, as a function of the dimensions and properties of the materials used, the behavior of the site and therefore the amount of thermal energy to be delivered may vary.

[0071] The method 100 according to the present invention advantageously allows for calculating the amount of thermal energy delivered over a given period of time.

[0072] The predetermined period of time may for example correspond to a week, a month, a quarter, half a year or even a year. As will be explained in more detail below, the invention may take into account differential variations related to climatic conditions (e.g. solar radiation) and the predetermined period of time may preferably correspond to a period during which a single and same heat loss coefficient is used. Advantageously, the predetermined period of time is a calendar period and is preferably related to a season.

[0073] In the context of the present invention, determining the amount of thermal energy to be supplied to the site 20 of the building 2 includes using: a number of ambient temperature values ​​of the building, a value of the temperature outside the building 2, the volume of the building site 20, and the heat loss coefficient of the site.

[0074] The building ambient temperature values ​​can be provided by temperature sensors dedicated to the determination method or by temperature sensors integrated into a system already installed in the building. The ambient temperature sensors are preferably temperature sensors connected to a communication network (e.g. internet, wifi, sigfox, LoRa, LoRaWAN, Zigbee, Z-Wave, Enocean, 3G / 4G / 5G). The building ambient temperature values ​​preferably include a number of temperatures of the premises under investigation (in other words those for which the amount of thermal energy to be provided has to be determined), of premises adjacent to the premises under investigation or of common spaces adjacent to the premises under investigation.

[0075] The ambient temperature of the premises 20 may correspond to temperatures measured at least hourly in multiple locations (i.e., rooms) of the premises 20. The ambient temperature value used for the premises 20 may also correspond to an average or median value.

[0076] In particular, the determination may involve the use of at least two ambient temperature measurement locations on the premises 20, preferably a day zone and a night zone.

[0077] The determination method can use one or more values ​​of the temperature outside the building 2. The one or more temperatures outside the building can be provided by a temperature sensor dedicated to the determination method or by a temperature sensor integrated into a system already installed around or on the building. The external temperature sensor is preferably a temperature sensor connected to a communication network (e.g. internet, wifi, sigfox, LoRa, LoRaWAN, Zigbee, Z-Wave, Enocean, 3G / 4G / 5G). Alternatively, the temperature value outside the building can correspond to a local external temperature value measured or calculated for the geographical area in which the building 2 is located. The temperature value outside the building can also correspond to a local external temperature value estimated for the geographical area in which the building 2 is located.

[0078] The volume of the building site 20 generally corresponds to a known value or a value calculated taking into account, in particular, the geometric shape of the building and the site. In certain embodiments, the volume of the site can correspond to multiple volumes, each associated with one or more spaces of the site. For example, the determination of the amount of thermal energy to be provided to the site 20 can take into account a specific volume for each ambient temperature value of the site to be used. Hotter zones associated with a temperature value can be associated with a sub-volume of the site 20, while cooler zones will be associated with other temperature values ​​and with another sub-volume of the site 20.

[0079] In the context of the present invention, the determination of the amount of thermal energy to be supplied to the premises will be based on the heat loss coefficient of the premises calculated on the basis of a thermal simulation model 41 of the building 2 .

[0080] By calculating the site heat loss coefficient based on the thermal simulation model 41 of the building 2, a more precise and accurate site heat loss coefficient can be obtained than heat loss coefficients calculated or estimated with other biases.

[0081] Preferably, the thermal simulation model 41 of the building used to calculate the heat loss coefficient of the premises is a dynamic thermal simulation model of the building. More specifically, the dynamic thermal simulation model is based on an accurate description of the wall geometry and configuration. Furthermore, if the premises includes fittings, the thermal simulation model of the building can also take into account the configuration of this fitting. This allows the relevant physical phenomena (heat exchange by convection, conduction and radiation) to be taken into account, allowing an accurate calculation of the amount of thermal energy supplied to the premises.

[0082] There are other methods besides the 3CL method for calculating the consumption of conventional houses, used to generate the EPC. However, these methods are based on a more coarse description of the heat loss surface area and a more coarse modeling of the heat exchange. For example, the 3CL method does not incorporate the consideration of dynamic aspects, unlike the present invention, which is preferably based on a dynamic thermal simulation model of the building. It can only calculate the annual consumption of heating / cooling / DHW, but not, for example, the change in temperature over time. Moreover, it only applies to the analysis of the frame, without taking into account the use. In fact, it is less accurate compared to the method according to the present invention, which can preferably perform calculations with hourly time steps, both for consumption and internal temperature, while taking into account the use.

[0083] Thus, a thermal simulation model of a building advantageously takes into account the geometry of the site, the wall configuration (and optionally the composition of the fittings) and the stresses to which the building is subjected (preferably climate, use, etc.).

[0084] In the context of the present invention, a Dynamic Thermal Simulation model (DTS) makes it possible to calculate the evolution of the thermal state of a building over time, using a numerical model approximated to it, which makes it possible to obtain, at every selected time instant of the simulation, the temperatures of a certain number of points of the building, which vary according to the different laws governing heat exchange (convection, conduction, radiation, change of state).

[0085] Thus, a dynamic thermal simulation model in the context of the present invention is able to estimate the thermal demand (heating and cooling demand) and temperature of each zone of a building during operation. The model takes into account the building shell and its inertia (based on the description of the interior and exterior walls of the building), the heat exchange flows between the thermal zones, the different heat inputs, the occupant behavior and the local climate. Moreover, advantageously, when using the model to estimate the actual energy consumption, the calculations can also take into account the energy system (production system, type of emitters, etc.).

[0086] The thermal simulation model is preferably a multi-zone model, more preferably has a finite volume and is further preferably reduced by modal analysis. Such an arrangement allows a reduction in computation time by a factor of three. Furthermore, the model is arranged to determine, at each time step, the heating and cooling needs and / or temperatures of each zone of the building. Advantageously, the model is arranged to incorporate heat exchange between zones, e.g. between the sites 20. Furthermore, the model is arranged to take into account the thermal inertia in each wall.

[0087] In addition, in order to further improve the precision and accuracy of the determination according to the invention, the thermal simulation model 41 of the building 2 used can advantageously further take into account data representative of local solar radiation.

[0088] In particular, by considering data on local insolation per time period (eg, a given time period), the energy input from insolation, in whatever form it may be, direct or indirect, can be taken into account.

[0089] In particular, the local solar radiation data includes the global horizontal solar radiation and the diffuse horizontal solar radiation. These values ​​for a particular building 2 vary significantly as a function of the period considered. Also, in a particular period, the solar radiation impacts on two sites in different geographical situations (location, orientation, etc.) can be very different. It is therefore highly advantageous in the context of the present invention to use a thermal simulation model 41 of the building 2 that takes into account data of local solar radiation for the period (i.e. time period) studied or data representative of local solar radiation for the period studied.

[0090] The data for local solar radiation or data representative of local solar radiation may be constructed and preferably modeled on local historical data, more particularly when measurements of specific radiation values ​​need to be taken for each building under investigation, which measurements can be particularly expensive to obtain.

[0091] Alternatively, the data representative of local solar radiation is obtained from at least one equipment device or from a computer server that contains data relating to local solar radiation.

[0092] Various embodiments of the method according to the invention for determining the amount of thermal energy to be supplied to the premises 20 of a building 2 over a given period of time will now be described.

[0093] As shown in FIG. 1, the method according to the present invention may include a step 110 of generating a thermal simulation model of the building.

[0094] Many tools exist for generating 110 a thermal simulation model of a building. The thermal simulation model of a building 2 is preferably built on the basis of a computer solution that combines one or more libraries dedicated to the elements necessary for the description of a building, and a modeling module that allows to graphically describe the building 2 under study in 3D. It is thus possible to create a digital model of the building 2 that includes all information regarding materials, fittings, equipment and energy performance.

[0095] Beyond these aspects, it is possible to obtain better results by generating and using a dynamic thermal simulation model of the building, more specifically using modeling solutions that can further incorporate factors related to environmental impacts, especially light radiation.

[0096] The thermal simulation model 41 of the building 2 used in connection with the calculation of the heat loss coefficient of the site is preferably a dynamic thermal simulation model which may include the properties of the surrounding solar mask.

[0097] In particular, the thermal simulation model 41 of the building 2 used in connection with the calculation of the heat loss coefficient of the premises includes the characteristics of the wall composition and optionally the composition of the fittings. Advantageously, it can further include the characteristics of the air renewal flow rate and / or the distribution losses of the heating network.

[0098] Additionally, the thermal simulation model 41 of the building 2 is a dynamic thermal simulation model that includes characteristics related to the occupancy of the building, such as building occupancy times and / or occupancy levels, and may further include characteristics such as specific electrical applications, heating or air conditioning temperature settings, and / or heating or air conditioning schedules.

[0099] Advantageously, the thermal simulation model 41 of a building 2 is also a dynamic thermal simulation model configured to take into account the heat exchange between the sites 20, 20b of a given building 2.

[0100] As shown in figure 1, the determination method according to the invention can advantageously include a step 120 of calibrating the thermal simulation model of the building. Such a step can improve the accuracy of the method and therefore of the value of the determined amount of supplied thermal energy.

[0101] The calibration step 120 may be performed based on a first measurement period and a calibration algorithm, preferably a Bayesian calibration algorithm, which allows the predictions of consumption and internal temperature at each hourly time step of the thermal simulation model of the building to reproduce the measured values ​​more accurately.

[0102] The calibration step 120 makes it possible to increase the reliability of the thermal simulation model in such a way as to ensure that it reproduces as accurately as possible the real thermal behavior of the building 2. The aim of this step is to obtain a reliable and accurate representation of the real behavior of the building by calibrating the on-site measurements (based on ambient and external temperature data) and the output of the thermal simulation model (temperatures and consumptions simulated by the model).

[0103] This step therefore makes it possible, on the one hand, to incorporate measurements from the digital model generated by the thermal simulation model and, on the other hand, to calibrate the model taking into account sources of uncertainty and error that can explain the differences between the simulated data and the measurements. Advantageously, the estimation of the errors is based on the use of a Bayesian calibration algorithm.

[0104] This calibration step 120 may therefore result in modifications to the parameters of the thermal simulation model that will be reflected in the site heat loss coefficient values ​​generated for a given period of time.

[0105] In the context of the present invention, the thermal simulation model 41 of the building 2 has a thermal efficiency of at least 50 Wh / m 2 , e.g. at least 100Wh / m 2 It can be calibrated as a function of the period considered under varying sunlight conditions, with the outside temperature varying by at least 10° C., preferably by at least 30° C. Furthermore, it can be calibrated as a function of the period considered under conditions of an outside relative humidity varying by at least 15%. More specifically, the inventors have determined that these particular variables with these amplitude levels are most suitable in the context of the present invention in order to provide an amount of thermal energy that is determined as accurately as possible.

[0106] Furthermore, the method for determining the amount of thermal energy supplied to the premises 20 of the building 2 over a particular period of time may include a step of calculating an uncertainty score for the value of the determined amount of thermal energy supplied, particularly if a prior calibration step is included.

[0107] In particular, this uncertainty score can be calculated based on variables generated during the calibration procedure and representing the deviation between the consumption predictions and the internal temperatures at hourly time steps of the building's thermal simulation model and the measurements.

[0108] As shown in FIG. 1, the determination method according to the invention advantageously comprises a step 130 of calculating at least one heat loss coefficient of the building based on a thermal simulation model of the building.

[0109] The heat loss coefficient for each site 20 can therefore be calculated based on an uncalibrated or, preferably, calibrated thermal simulation model of the building. The heat loss coefficient thus estimated can advantageously correspond to the expected heat losses within the site 20 under the fluctuating operating conditions of the building 2. This calculation minimizes errors introduced in the estimation of the heat losses, which can be quite large if a purely statistical calculation is performed, which does not take into account the inertia of the building relative to the dynamic aspects of the stresses to which it is subjected (weather, use, etc.).

[0110] As mentioned before, ideally the calculation of the heat loss coefficient should take into account many factors such as the type (glazed or not), surface area and orientation of the various walls of the house, but also adjacent contacts, air renewal, various thermal bridges and even free inputs linked to the solar input and the use (metabolic heat, specific power). In this context, the use of calibrated thermal simulation models to estimate this heat loss coefficient is of great interest. The objective of the calculation of the heat loss coefficient of a site is to be able to estimate the value of the coefficient G of the site 20 while taking into account the various sources of uncertainty related to the building 2 and its environment (uncertainties related to the frame, systems, use, weather conditions).

[0111] An uncertainty analysis can be carried out with the aim of quantifying the variations in the outputs (particularly the consumption) of the calibrated thermal simulation model of the building caused by uncertainties in the model's input coefficients. According to one embodiment, to carry out this uncertainty analysis, each static parameter is defined on the one hand by a probability density function and on the other hand a variation model of the use and meteorological conditions is used. For example, based on these data, more than 500 simulations can be carried out, obtaining the variability of the consumption history of each premises 20, and based on these simulations, one or more heat loss coefficients G of the premises can be recalculated.

[0112] Therefore, calculating 130 at least one heat loss coefficient for an individual site based on a thermal simulation model of the collective building may preferably include calculating at least one heat loss coefficient for an individual site 20 based on multiple simulations in which the geometric values, wall configuration and optionally the fitting configuration of the individual site 20 are changed in a manner that incorporates uncertainties associated with the collective building 2.

[0113] More preferably, the calculation 130 of at least one heat loss coefficient for an individual site based on the thermal simulation model of the building may include calculating, for the site, at least one heat loss coefficient based on multiple simulations in which the values ​​of the use and / or the weather conditions (temperature and / or sunshine) are further modified in such a way as to incorporate uncertainties related to the use and the weather conditions. In these embodiments, the values ​​may be modified according to a probability density function and / or a variation model.

[0114] The use of uncertainty analysis to calculate the coefficient G allows the invention to provide greater accuracy compared to conventional methods, without burdening the operation of the invention.

[0115] Furthermore, the determination method according to the invention may include the use of a plurality of heat loss coefficients for a given premises 20, each calculated on the basis of a thermal simulation model of the building. Preferably, the determination method according to the invention includes the use of at least four heat loss coefficients. Advantageously, these heat loss coefficients are specific to a given period, for example a calendar period. More preferably, in the context of the method, the heat loss coefficients for the premises 20 are selected from at least two, preferably at least three, more preferably at least four heat loss coefficients, each heat loss coefficient corresponding to a period of a year. Even more preferably, the heat loss coefficients are selected from at least 12 heat loss coefficients (monthly coefficients) for a given premises 20.

[0116] The method of determination according to the invention may include a step 130 of calculating a number of heat loss coefficients based on a single and same thermal simulation model of the building or based on different thermal simulation models of the building.

[0117] The method according to the invention comprises determining the amount of thermal energy supplied to the premises 20 in the building 2 over a predetermined period of time.

[0118] As previously explained, the determination takes into account a number of ambient temperature values ​​for the building, one or more temperature values ​​outside the building 2, the volume of the building's site 20, and the heat loss coefficient of the site.

[0119] This determination can be compared to a calculation performed by a heating cost allocator using measurements of ambient temperature at the premises. In particular, a determination according to the invention can correspond to an estimation of the amount of energy that will be personally consumed at the premises before being subject to allocation, based on a number of ambient temperature values ​​and one or more temperature values ​​outside.

[0120] For example, a calculation might take the following form:

number

[0121] Example of a formula using tuning variables:

number

[0122] As discussed, the present invention may be implemented without tuning variables, with tuning variables, or with multiple tuning variables.

[0123] Advantageously, the determination may incorporate the use of one or more adjustment factors calculated based on a thermal simulation model of the building, which, when used in combination with adjustment variables representing environmental factors, may further improve the accuracy of the model.

[0124] Therefore, the method according to the invention advantageously comprises a step 140 of adjusting the amount of thermal energy supplied. Said adjustment step 140 comprises the use of one or more adjustment factors, each adjustment factor being applied to a adjustment variable.

[0125] The one or more adjustment variables may correspond to human or environmental factors that affect the thermal energy supplied to the premises. Thus, the adjustment variables may correspond to meteorological data such as atmospheric pressure or wind speed.

[0126] The adjustment variables may be measured directly within the site 20 of the building 2. Alternatively, the adjustment variables may be measured in the geographic area in which the building 2 is located. Another means of obtaining the adjustment variables is to model them probabilistically, for example based on statistics, or to generate them based on machine learning algorithms.

[0127] The adjustment variable is preferably calculated based on weekly, daily, or hourly data. These values ​​can be combined in a manner that produces a monthly value. In particular, if the heat loss coefficient is monthly, the adjustment variable will also be monthly.

[0128] For example, the determination of the amount of thermal energy supplied to the premises 20 may incorporate the use of adjustment variables selected from: variables representing heat losses associated with window openings and / or natural ventilation; and / or variables representing the use of auxiliary heating, allowing the incorporation of actual usage, either directly measured or modeled for each premises.

[0129] Preferably, the determination of the amount of thermal energy provided to the premises 20 incorporates the use of a regulation variable representing the premises' power consumption, including auxiliary heating.

[0130] This determination may also incorporate the use of an adjustment variable representing heat loss due to opening at least one window 24 in the building.

[0131] In this case and in a preferred manner, an adjustment variable representative of the heat loss associated with the window openings 24 may be calculated as a function of the changes in the ambient temperature of the premises and the humidity within the premises. In particular, time series of indoor and outdoor temperatures and humidity may be used. This therefore allows for an accurate estimation of the duration for which the windows are open, without the need to place sensors on each window.

[0132] The adjustment factor corresponds, for example, to a value that is used together with the adjustment variable value in determining the amount of thermal energy to be provided to the premises 20. In particular, the adjustment factor is used in a formula that determines the amount of thermal energy to be provided to the premises 20. The value of the adjustment factor is preferably calculated based on a thermal simulation model of the building 2.

[0133] The adjustment factor value may be updated, for example, every 3 months or less, preferably every 2 months or less, more preferably every month or less. It is thus possible to best take into account the value of the adjustment variable as a function of the season, and more generally, the usual climate for a particular period of time. Preferably, the method uses multiple predefined adjustment factor values ​​for the same adjustment factor as a function of predefined periods of time.

[0134] In connection with the method of the present invention for determining the amount of thermal energy to be delivered to the premises 20, a number of adjustment variable / adjustment factor pairs are advantageously used, which allows a more accurate calculation of the amount of thermal energy to be delivered compared to other systems.

[0135] In particular, the method according to the invention may include the use of a number of adjustment factors whose predetermined values ​​are selected as a function of a predetermined period of time. For example, an adjustment factor associated with an adjustment variable representing heat loss through the opening of at least one window 24 of a premises will not have the same value in July as in November. Preferably, the method according to the invention includes the use of at least two adjustment factors, more preferably at least three adjustment factors, even more preferably at least four adjustment factors for the same premises 20.

[0136] The use of adjustment variables and adjustment factors also allows the calculation of the thermal energy supply to be performed with a higher accuracy and with a reduced computational complexity, which in turn allows the generation of a large number of adjustment factor and heat loss coefficient values ​​for a site in a manner that is flexibly adapted to the annual study period, with a single use of the thermal simulation model.

[0137] As mentioned above, one of the advantages of the method according to the invention is that it allows to calculate a confidence interval for the determined amount of thermal energy delivered.

[0138] The calculation of this confidence interval may rely on the use of uncertainty values ​​of adjustment variables used during the determination of the amount of thermal energy delivered.

[0139] The uncertainty value of the adjustment variable can be a predefined value or a value calculated as a function of multiple adjustment values ​​of the variable for the same period (e.g., standard deviation). Alternatively, or in addition, the calculation of this confidence interval can depend on the calculated amount of thermal energy delivered and the calculation of the uncertainty value of the adjustment variable used.

[0140] The performance of the present invention is particularly illustrated by Table 1 below.

[0141] [Table 1]

[0142] Table 1 shows how the accuracy of the prediction is improved compared to conventional methods for determining the amount of thermal energy delivered to the premises 20 of a building 2 over a given period of time. In particular, if heat loss coefficients calculated based on a dynamic thermal simulation model are not used, the results are far from reality and do not allow for proper consideration of external factors such as radiation, window openings, auxiliary heating, etc.

[0143] Furthermore, Table 1 shows that taking radiation into account for the premises heat loss coefficient calculated based on the dynamic thermal simulation improves the accuracy, and even more so if the building is well insulated. Furthermore, Table 1 shows that taking into account window openings ("Openings") and the use of auxiliary heating ("Auxiliary Heating") as adjustment variables (together with the adjustment factor) improves the accuracy even further.

[0144] As mentioned above, the calculation of the heat loss coefficient for site G is preferably carried out through the propagation of uncertainties varying a number of parameters, which may include radiation and internal inputs (see application), making it possible to take into account the average influence (expectations) of these variables (radiation, internal inputs, etc.).

[0145] To further adjust the calculation of the consumption and bring it even closer to the real energy consumption, the solution according to the invention proposes to incorporate adjustment variables, which allow to adjust the calculation of the consumption taking into account the real values ​​of the variables. For example, when adjusting for radiation, the heat loss coefficient of site G is calculated to determine the average impact of radiation (for example 1200 kWh / m2 per year). 2 or 120 kWh / m per month 2 ) can be calculated. Adding an adjustment variable for radiation allows us to modify the calculation of consumption. For example, this is actually the 1300 kWh / m2 measured over a one-year period. 2 (or 100 kWh / m for the entire period 2 ) The calculation of the value of the heat loss coefficient G of the site is modified using the radiation adjustment factor and the adjustment variable (e.g., adjusted consumption = average consumption + Coeff x (1300 / 1200-1)).

[0146] As shown in FIG. 1, the method of determination according to the invention advantageously comprises a step 150 of analysing the power consumption.

[0147] In particular, the use of auxiliary heating can be detected based on analyses 150 of power consumption. These analyses of power consumption can correspond to estimations by statistical models, calculations based on analysis of electricity prices, or even measurements by electronic power meters.

[0148] Thus, as shown in FIG. 1, the determination method according to the invention may advantageously include a step 160 of quantifying the use of the additional heating device.

[0149] This quantification step 160 of the usage of additional heating devices is preferably based on an analysis of documents including, inter alia, data from electronic power meters or consumption reports such as electricity bills.

[0150] As shown in FIG. 1, the determination method according to the invention can advantageously include a step 170 of calculating an individualized heating cost as a function of the determined amount of thermal energy supplied.

[0151] In particular, the step 170 of calculating the individual heating cost may be a step 170 of calculating the individual heating cost for the premises 20 of the building 2 as a function of the determined amount of thermal energy supplied to said premises 20 by the collective thermal management device 30 .

[0152] Preferably, the method may include the step of calculating a predicted comfort cost for the premises as a function of a given expected internal temperature, a local variable and an adjustment factor.

[0153] As shown in FIG. 1, the method of determination according to the invention may further comprise a step of calculating expected savings in the amount of thermal energy supplied to the premises as a function of the modification of the value of the adjustment variable.

[0154] Thus, when implementing the use of the adjustment variables, the method according to the invention can include a calculation step of what the amount of heat energy supplied to the premises would be as a function of the values ​​of the other adjustment variables, for example, it can be calculated how much savings there would be in terms of the amount of heat energy supplied to the premises if the number of window openings were reduced by two.

[0155] Such steps may generate recommendations for energy improvement measures to allow the user to reduce heating costs.

[0156] As shown in FIG. 1, the determination method according to the present invention may further include a step 180 of transmitting data to the electronic display device 50 .

[0157] The transmitted data may include, for example, a determined amount of thermal energy to be delivered.

[0158] According to another aspect, the present invention relates to an allocator 10 for determining an amount of thermal energy to be provided to a premises 20 in a building 2 by a collective thermal management device 30 for a given period of time.

[0159] The allocator 10 may be an electronic device and may include one or more processors. Preferably, the allocator 10 according to the invention includes one or more processors configured to execute the method according to the invention, preferably the method 100 for determining the amount of thermal energy to be supplied, whether advantageous or not, and its various preferred embodiments.

[0160] The allocator 10 may be installed inside the building 2. However, as shown in FIG. 2, the allocator 10 may also be located outside the building 2 housing the site 20 to be studied. For example, the allocator 10 may be a functional module of an electronic device, such as a functional module of a computer server. Under these conditions, the same computer server 40 may host several allocators 10, 10b, each dedicated to a building 2. As shown in FIG. 2, the computer server 40 may also host the thermal simulation models 41, 41b used to calculate the heat loss coefficients used by the allocators 10, 10b. Alternatively, and preferably, the allocator does not need to store the thermal simulation model used to generate the heat loss coefficients. More specifically, once the several thermal coefficients have been generated, at least one for each site 20, the model is no longer essential for the determination of the amount of thermal energy to be supplied. This allows the applicant to propose a lightweight and responsive solution for real-time calculations without sacrificing the accuracy of the results.

[0161] To determine the amount of thermal energy to be supplied by the collective thermal management device 30 to the site 20 of the building 2 over a given period of time, the allocator 10, and in particular one or more processors of the allocator 10, are preferably configured to use a plurality of ambient temperature values ​​of the building 2, a value of the temperature outside the building 2, the volume of the site 20, and the heat loss coefficient of the site.

[0162] Advantageously, the allocator 10 uses a heat loss coefficient of the site calculated based on a thermal simulation model 41 of the building 2, taking into account the geometry of the site 20, the wall configuration and optionally the fittings configuration of said site 20.

[0163] Additionally, the thermal simulation model 41 of the building 2 may take into account data representative of local solar radiation over a given period of time.

[0164] As mentioned above, local solar radiation data is preferably taken into account, although it is not measured, as it is generated based on a model using local historical data.

[0165] The allocator 10 may include one or more processors configured to calculate allocation data, in particular to allocate financial costs associated with collective heating as a function of all the amounts of supplied energy determined for each site 20.

[0166] According to another aspect, the invention relates to a system 1 for allocating heating costs. The system 1 for allocating heating costs may comprise an electronic device with one or more processors. Preferably, the system 1 for allocating heating costs according to the invention comprises one or more processors configured to execute the method according to the invention, preferably the method 100 for determining the amount of thermal energy to be supplied, advantageous or not, and its various preferred embodiments.

[0167] In particular, the system 1 for allocating heating costs may include an allocator 10 according to the invention. As mentioned above, this allocator may be supported by a computer server 40. Furthermore, the computer server 40 may be arranged to communicate with an electronic display device 50 or other electronic device capable of receiving data relating to heating costs or the amount of thermal energy supplied to the premises.

[0168] Furthermore, the system 1 for allocating heating costs according to the invention may include a number of electronic temperature measuring devices 22. These devices may be electronic temperature measuring devices 22 dedicated to the system 1 for allocating heating costs according to the invention or may be devices already present in the home and configured to communicate data to the system 1 for allocating heating costs according to the invention. For example, these devices may be integrated into smoke detectors and connected thermostats.

[0169] 2, the electronic temperature measurement devices 22 may be located in various zones or rooms 21 of the premises 20. For example, multiple electronic temperature measurement devices 22 may be located in rooms 21 within the same premises 20 that may or may not include supplemental heating means 23.

[0170] In particular, these electronic temperature measuring devices 22 can include sensors in addition to temperature sensors. In particular, the electronic temperature measuring devices 22 can include humidity sensors. They can also include CO2 sensors. With such sensors, placing the electronic temperature measuring device 22 in a room that contains a window 24 can generate enough data to estimate the amount of time the window 24 has been open.

[0171] The electronic temperature measuring device 22 is preferably configured to transmit measurement data directly or indirectly to the allocator 10. The temperature can be measured at least once a day, preferably at least twice a day, more preferably at least every hour, more preferably at least every 30 minutes. In contrast, these data can be stored in the electronic temperature measuring device 22 and can be transmitted directly or indirectly to the allocator 10 at least once a month, preferably at least weekly, more preferably at least daily, more preferably at least six times a day.

[0172] The electronic temperature measurement devices 22 are preferably configured to transmit the measurement data directly to the allocator 10 via wireless or wired communication, most preferably via wireless communication. Alternatively, the data may be transmitted to the data collector 60 via a wireless or wired connection.

[0173] The data collector 60 may in particular be installed in a common area of ​​the building 2 or outside the building 2. If the system 1 includes the data collector 60, the system 1 may be configured to implement, on the one hand, a first wireless communication carried out inside the building 2 between the data collector 60 and the electronic temperature measurement devices 22 associated with each premises, and, on the other hand, a second wireless communication from the data collector 60 of the building 2 to the allocator 10 (usually centralized and accessible via a communication network such as the Internet).

[0174] The present invention can include many alternatives and applications other than those described above. In particular, unless otherwise specified, the various structural and functional features of each of the above implementations should not be considered as being coupled and / or in close proximity and / or closely related to one another, but rather as being simply juxtaposed in contrast. Moreover, the structural and / or functional features of the various embodiments described above may be the subject of any different juxtapositions or any different combinations, in whole or in part.

Claims

1. 1. A method (100) for allocating energy costs in a collective building (2) including a plurality of individual premises (20) and at least one collective thermal management device (30), the method (100) being applicable to all individual premises (20) of the collective building (2) and comprising determining an amount of thermal energy provided to at least one individual premises (20) of the collective building (2) over a predetermined period of time by at least one collective thermal management device (30), the determination being performed by one or more processors and comprising using: Simulation models; a plurality of ambient temperature values ​​for the collective building (2), the plurality of ambient temperature values ​​for the collective building (2), including a plurality of temperatures for the individual premises (20); one or more values ​​of the temperature outside the collective building (2); The volume of the individual lot (20); and At least one heat loss coefficient of the individual premises (20); The method (100) includes calculating (130) at least one heat loss coefficient for the individual site (20) based on the simulation model; the simulation model is a thermal simulation model (41) that virtually represents the complex building (2) and takes into account, for each individual site (20), the shape of the individual site (20), the wall configuration of the individual site (20), and the heat exchange between the various sites of the complex building (2); The method is characterized in that it uses a plurality of temperatures of a collective building (2) site or common space adjacent to the individual site (20).

2. 2. The method (100) according to claim 1, characterized in that if the individual site (20) is further defined by a fixture configuration, the method further comprises the thermal simulation model (41) of the complex building (2) taking into account the fixture configuration.

3. 3. The method (100) according to claim 1 or 2, characterized in that the thermal simulation model (41) of the apartment building (2) further takes into account data representative of local solar radiation over a given period of time.

4. 4. The method (100) according to claim 1 or 3, characterized in that the thermal simulation model (41) of the complex building (2) is a dynamic thermal simulation model (41) of the complex building (2).

5. The method (100) according to any one of claims 1 to 4, characterized in that at least one heat loss coefficient of an individual premises (20) is selected from at least two predetermined heat loss coefficients, each of said predetermined heat loss coefficients corresponding to a time period.

6. A method (100) according to any one of claims 1 to 5, characterized in that the determination of the amount of thermal energy supplied by at least one collective thermal management device (30) to at least one individual site (20) of the collective building (2) comprises the use of one or more adjustment factors, each adjustment factor being applied to an adjustment variable measured or calculated for a given period of time.

7. The method (100) according to claim 6, characterized in that the adjustment variables are selected from the following: variables representative of heat losses associated with window openings, variables representative of the occupancy level of the individual premises (20), variables representative of weather conditions and / or variables representative of the use of auxiliary heating.

8. 8. The method (100) according to claim 6 or 7, characterized in that the adjustment variables are measured directly on the individual sites (20) of the collective building (2), modeled probabilistically based on statistics, or reconstructed based on measurements of machine learning algorithms.

9. The method (100) according to any one of claims 1 to 8, characterized in that it comprises a step (120) of calibrating the thermal simulation model of the collective building (2), said step (120) being preferably carried out on the basis of a first measurement period of ambient and external temperature values ​​and a Bayesian calibration algorithm, so that the temperatures calculated by the thermal simulation model (41) of the collective building (2) reproduce the measured temperature values ​​as accurately as possible.

10. The method (100) according to any one of claims 1 to 9, characterized in that the ambient temperature of the individual premises (20) corresponds to temperatures measured at a plurality of locations within the individual premises (20).

11. A method (100) according to any one of claims 1 to 10, characterized in that it comprises a step (170) of calculating the individual heating costs of the individual premises (20) of the collective building (2) as a function of the determined amount of thermal energy supplied to said individual premises (20) by the collective thermal management device (30).

12. 12. The method (100) according to claim 11, characterized in that the step (170) of calculating the individual heating costs takes into account the orientation and location characteristics of the individual buildings (20) within the collective building (2) in such a way as to correct disparities between the sites or common spaces of the collective building (2).

13. 13. The method (100) according to any one of claims 1 to 12, characterized in that the calculation (130) of at least one heat loss coefficient for an individual site (20) based on a thermal simulation model of the building may comprise calculating, for the individual site (20), at least one heat loss coefficient based on a plurality of simulations in which values ​​of the shape and wall configuration of the individual site (20) are varied in such a way as to incorporate uncertainties related to the collective building (2).

14. 14. The method (100) according to claim 2 or any one of claims 3 to 13 dependent on claim 2, characterized in that the calculation (130) of at least one heat loss coefficient for an individual site (20) based on a thermal simulation model (41) of the collective building (2) can include calculating, for the individual site (20), at least one heat loss coefficient based on a plurality of simulations in which values ​​of the building construction are changed in such a way as to incorporate uncertainties associated with the collective building (2).

15. 15. The method (100) according to any one of claims 1 to 14, characterized in that the calculation (130) of at least one heat loss coefficient for an individual site (20) based on the thermal simulation model (41) of the building may comprise calculating, for the individual site (20), at least one heat loss coefficient based on a plurality of simulations in which values ​​of the use and / or the weather conditions are further varied in such a way as to incorporate uncertainties related to the use and the weather conditions.

16. An energy cost allocator (10) in a collective building (2) including a plurality of individual sites (20) and at least one collective thermal management device (30), said allocator being applied to all individual sites (20) of the collective building (2) and comprising determining an amount of thermal energy to be supplied to at least one individual site (20) of the collective building (2) over a predetermined period of time by at least one collective thermal management device (30), said allocator (10) comprising one or more processors configured to determine the amount of thermal energy to be supplied using: Simulation models; a plurality of ambient temperature values ​​for the collective building (2), the plurality of ambient temperature values ​​for the collective building (2), including a plurality of temperatures for the individual premises (20); one or more values ​​of the temperature outside the collective building (2); The volume of the individual lot (20); and At least one heat loss coefficient of the individual premises (20); the allocator (10) is configured to calculate (130) at least one heat loss coefficient for each individual site (20) based on the simulation model; the simulation model is a thermal simulation model (41) that virtually represents the complex building (2) and takes into account, for each individual site (20), the shape of the individual site (20), the wall configuration of the individual site (20), and the heat exchange between the various sites of the complex building (2); The allocator (10) is characterized in that it includes one or more processors configured to further use a plurality of temperatures of the complex building (2) site or common space adjacent to the individual site (20) to determine the amount of thermal energy to be supplied.

17. The allocator (10) of claim 16, characterized in that if the individual sites (20) are further defined by a building construction, the system further takes into account the building construction in the thermal simulation model (41) of the complex building (2).

18. A system (1) for allocating heating costs, comprising an allocator (10) according to any one of claims 16 to 17.

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