Patent Description:
Nowadays there are different systems for heating residential units, such as flats and buildings.

Some of the residential units have independent heating, i.e. each unit has its own heating system. For example, the residential unit may be equipped with a boiler that heats water that is circulated through radiating elements inside the residential unit. Alternatively, the residential unit can be equipped with an HVAC (Heat Ventilation Air conditioning and Cooling) system, wherein a heat pump heats or cools an air flow that is sent into the residential unit.

Other solutions involve the use of a central heating system serving several residential units. This is the case in apartment blocks, where a central heating unit - a boiler or a condominium HVAC system - heats a vector fluid (water or air, respectively), which is sent to the different residential units. Each residential unit is then equipped with a regulation system to increase or decrease the temperature inside the residential unit. For example, in the case of boilers, the water heated by the boiler is sent to radiators equipped with valves that can be regulated manually or by a thermostat inside the residential unit.

Yet another form of heating is district heating. In this case, a large thermal power station heats water that is sent to several buildings, each of which is then equipped with pumps to distribute the hot water to the different residential units inside the building.

Regardless of the size and type (boiler or HVAC) of the heating system, there is the issue of optimising the energy consumption needed to heat the vector fluid (water or air) that is sent to the residential units.

Various means for controlling heating systems have been proposed in the art, for example <CIT> discloses an energy management system for proactively determining and regulating a flow temperature of a heating system of a building. A system controller receives a room temperature of one room of a building and is connected to the building's heating system to regulate the system's flow temperature based on the measured temperature.

The management system of <CIT> is based on a static estimation of the building's thermal capacity and its control capability is limited to modifying the flow temperature of the heating system according to a forecast of the external temperature trend.

Furthermore, heating control systems based on a model of the building to be heated are known in the art through <CIT>, <CIT>, <CIT>, and <CIT>.

An object of the present invention is to overcome the disadvantages of the prior art.

In particular, it is an object of the present invention to present a method and an associated heating system for reducing the energy consumption associated with heating the vector fluid and, at the same time, ensuring a substantially constant and comfortable ambient temperature within a heated building or residential unit.

These and other objects of the present invention are achieved by a method incorporating the features of the appended claims, which form an integral part of the present description.

According to a first aspect, the invention relates to a method of controlling the temperature of a vector fluid of a heating system for heating at least a portion of a building. The heating system considered comprises, but is not limited to:.

The method envisages that the control unit:.

The method further advantageously comprises having the control unit:.

Hereinafter, the term 'off control command' or the term 'off command' means a command given to the heating means to bring a set-point value of the temperature of the vector fluid to a minimum value or, alternatively, a command which inhibits the boiler from being switched on.

Thanks to this solution, it is possible to achieve dual-mode control of the temperature of the vector fluid, which makes it possible to achieve high energy savings and, at the same time, to maintain an ambient temperature in the building that ensures optimal comfort for users. In fact, dual-mode control combines the rapid on-off mode response when the temperature of the vector fluid is far from the target temperature value, with the exact compensation of the thermal load - in particular, from variations due to changes in the outside temperature - and thus the stability of the ambient temperature guaranteed by a continuous control mode. This makes it possible to effectively control the temperature inside the building, while at the same time reducing the amount of measurements taken over time at the building and generally reducing the overall number of sensors required, simplifying the hardware, firmware and/or software requirements of the system, as well as the consumption of the measurement equipment. Furthermore, the Applicant has determined that it is possible to achieve particularly reliable control of the ambient temperature in the building while keeping the computational load of the control system low.

In one embodiment, it is further envisaged that the control unit:.

Preferably, said at least one portion of the reference building corresponds to the at least one portion of the building to be heated or corresponds to the portion of the building characterised by a lower average ambient temperature than the other portions of the building.

This also makes it possible to optimise the operation of the heating system in on-off mode according to the calculated mathematical model.

In one embodiment, the step of calculating at least one operational parameter of the continuous control mode on the basis of said integral or pseudo-integral type mathematical model envisages using:.

The Applicant has determined that the use of such coefficients of the mathematical model processed by the control unit allows for adaptation of the operating modes of the heating system substantially in real time, obtaining responsive and particularly effective temperature control, at the same time, requiring a limited amount of computation.

In one embodiment, it is envisaged that the control unit, at a first activation of the heating system, implements a min-max operating mode instead of continuous control mode. In particular, the min-max operating mode being configured for:.

Furthermore, during each heating of the vector fluid, the method comprises having the control unit:.

Preferably, the first control command imposes a maximum temperature of the vector fluid and the second control command imposes a minimum temperature of the vector fluid determined by applying the theory of asymptotic properties of prediction error models (PEM) and the asymptotic theory of Ljung (<NUM>).

This solution makes it possible to quickly and efficiently acquire a quantity of data necessary to reliably calculate the integral or pseudo-integral mathematical model and, at the same time, to guarantee that the ambient temperature - or the perceived temperature - is maintained at or around the target temperature value, thus guaranteeing the comfort of the building's users during such system learning phase.

In one embodiment, it is envisaged that the control unit:.

where the target temperature value is a desired value of the operating temperature or the ambient temperature does not reach another predetermined lower limit value.

Advantageously, it is envisaged that the control unit maintains an on-off control command during the on-off control mode until the first radiant temperature reaches a predetermined lower limit value.

Thanks to this solution, it is possible to determine in a simple way and with a very limited number of sensors the operating temperature - essentially corresponding to the temperature perceived by users - inside the building - preferably, at least in the coldest portion of the building. Advantageously, using the operating temperature as a reference for assessing the reaching of the target temperature value allows a significant reduction in the consumption of the heating system without affecting the comfort level of the users inside the building. In addition, taking into account heat loss by estimating the radiant temperature of the heating element allows for additional switch-off periods of the heating means, at the same time, ensuring that users do not perceive a change in temperature in the building.

In one embodiment, the continuous control mode involves processing the continuous control command by means of a proportional-integrative function applied to the temperature estimated by the model or to the temperature measured by the sensor, where the proportional coefficient and the integrative coefficient are calculated on the basis of the integral or pseudo-integral mathematical model.

Preferably, the proportional and supplementary coefficients are calculated according to the so-called λ-tuning technique, so as to ensure that the target temperature value is reached within a predetermined time each time the heating means is switched on.

In one embodiment, the continuous control mode further involves processing a feed-forward term by means of a feed-forward function applied to a temperature outside the building, where the feed-forward coefficient is calculated on the basis of the integral or pseudo-integral mathematical model, and processing the continuous control command as the combination of the result of the proportional-integral function and the feed-forward term.

Even more preferably, the integral or pseudo-integral mathematical model involves estimating an integral gain operating parameter by two different methods. In detail, the model involves assessing the difference between two estimates, as well as the variability, of the operating parameter. If both of these conditions fall within predetermined threshold values, the operating parameter of the integral or pseudo-integral model is used to calculate the proportional coefficient and the integrative coefficient of the proportional-integrative function, as well as the feed-forward coefficient of the feed-forward function. Otherwise, if the conditions do not fall within the threshold values, a default coefficient is used to determine the proportional coefficient and the integrative coefficient of the proportional-integrative function and the feed-forward coefficient of the feed-forward function.

For example, in one embodiment the proportional coefficient is calculated as: <MAT> where λ is a time within which it is desired to reach the target temperature value, Δtr is a time indicating a delay between a change in the delivery temperature - i.e. of the vector fluid output by the heating means - and a change in the value of the ambient temperature, kp is a determined parameter defined by the mathematical model of the integral or pseudo-integral type, while 2σp is the standard deviation associated with parameter kp.

In addition, the integrative coefficient Ti is calculated as: <MAT>.

Finally, the advance coefficient k ff is calculated as: <MAT>.

Thanks to the solution that integrates one or more, preferably all, of the above features, it is possible to implement the continuous control mode that can dynamically adapt to variations in the building's thermal system (or a portion thereof) and compensate for changes in thermal load rapidly. This makes it possible to reach the target temperature value in a predetermined time and to maintain the ambient - or operating - temperature at the target temperature value in a particularly stable manner.

In one embodiment, the continuous control mode involves processing the continuous control command by means of a predictive control that receives as input the temperature estimated by the model or the temperature measured by the sensor and the temperature outside the building. Preferably, predictive control is a Model Predictive Control (MPC), optionally configured to acquire future external temperature values, for example, from a remote entity external to the heating system such as a server implementing a weather forecast service.

With this variant, a continuous control mode can be achieved that reacts more precisely to changes in the building's thermal system at the price of a higher computational cost.

This solution allows the target temperature to be reached in the shortest possible time at the cost of higher energy consumption than in the previous case.

According to a further aspect, the invention relates to a heating system comprising conduits for transporting a vector fluid within a building, the at least one heating element arranged within at least one portion of the building, the at least one heating element being configured to receive the vector fluid and release heat to the surrounding environment, means for heating the vector fluid, the at least one sensor capable of transmitting ambient temperature measurements within the building, and a control unit operatively connected to the sensor and the heating means and configured to implement a method of controlling the temperature of the vector fluid as set out above and further described below.

Further features and advantages of the present invention will be more apparent from the description of the accompanying drawings.

The invention will be described below with reference to some examples, provided for explanatory and non-limiting purposes, and illustrated in the accompanying drawings. These drawings illustrate different aspects and embodiments of the present invention and, where appropriate, reference numerals illustrating similar structures, components, materials and/or elements in different figures are indicated by similar reference numbers.

While the invention is susceptible to various modifications and alternative constructions, certain preferred embodiments are shown in the drawings and are described hereinbelow in detail. It is in any case to be noted that there is no intention to limit the invention to the specific embodiment illustrated, rather on the contrary, the invention intends covering all the modifications, alternative and equivalent constructions that fall within the scope of the invention as defined in the claims.

The use of "for example", "etc.", "or" indicates non-exclusive alternatives without limitation, unless otherwise indicated. The use of "includes" means "includes, but not limited to" unless otherwise stated.

<FIG> illustrates a building <NUM> comprising a plurality of residential units <NUM> to be heated. The building is equipped with a heating system comprising a central heating unit <NUM> which heats a vector fluid and sends it to the residential units where the vector fluid yields heat to the environment by heating it. The central heating unit may be installed locally within the building, as shown in <FIG>, or be a remote unit serving the building <NUM> and possibly also other buildings. For the sake of clarity, in the following example, the central heating unit is a boiler equipped with a burner <NUM> which heats water by sending it into a delivery conduit <NUM> to which manifolds <NUM> are connected, from which each residential unit on the floor receives the heated water, circulates it through radiators <NUM> arranged in the various rooms of the residential unit, and feeds it back into a return conduit <NUM> which arrives at the central heating unit <NUM> to be heated again. Other embodiments may include the use of a heat pump apparatus, or other HVAC system capable of heating air that is sent to the residential units.

The heating unit <NUM> also includes a control unit <NUM> and a radio interface <NUM>. The radio interface <NUM> receives temperature values measured by temperature sensors located in the various residential units. In the example described here there are three sensors S1, S2 and S3, but it is clear that the number can vary depending on the number of residential units. At least three sensors are preferably provided in a building at the coldest points - among those to be heated - of the building. The assessment can be made by studying the exposure of the building and identifying the coldest rooms.

The temperature sensors are preferably IoT sensors, capable of communicating with the heating unit via a radio link, e.g. Wi-Fi, Bluetooth, Zigbee, Lora, Sigfox or NB-IoT, suitable for the distances to be covered. In one embodiment, the IoT sensors are battery operated, so they can also be installed in existing buildings without the need to bring new power lines to power them in the optimal locations, i.e., as mentioned above, the cooler parts of the building.

Each residential unit <NUM> provides, in a known manner, a thermostat, indicated with the references T1 and T2 in <FIG>, which controls one or more valves <NUM> placed at the entrance to the residential unit in order to let new hot water from the delivery conduit <NUM> enter the radiators <NUM>.

In a known manner, the user sets a desired temperature value or temperature time trend unit on the residential unit thermostat and the thermostat opens and closes the valve <NUM> to reach the temperature value desired by the user.

The presence of thermostats is not essential and is only an example, as the residential unit could be equipped with thermostatic valves on the radiators that are individually regulated by a user. Again, the residential unit could be equipped with heating circuits without radiators or thermostatic valves, but with simple radiator valves that can be manually regulated by a user.

As each user adjusts - either manually or via a thermostat - the temperature of their radiators, the heat load seen by the boiler - i.e. the amount of heat required by the boiler - varies over time.

In order to optimise the amount of heat yielded by the boiler to the delivery water, the control unit <NUM> is configured to implement a method for controlling the temperature of the delivery water intended for heating the building. Having determined the temperature value to which the delivery water is to be brought, in one embodiment the control unit <NUM> controls the burner <NUM> in a known way to bring the delivery water to the calculated temperature value. Given that there are already boilers which manage the burner by varying its thermal power according to a given temperature to be reached, we will not go into the merits of this mechanism here.

The method of controlling the delivery water temperature implemented by the control unit is illustrated in its general lines in <FIG>, and envisages:.

As illustrated schematically in <FIG>, the control unit <NUM> comprises a selection module <NUM> which receives as input the temperature values TS measured by the environmental sensors Si and the ambient temperature estimates Tv and generates as output an ambient temperature value Tc which is used by the controller <NUM> to control the burner <NUM>. The selection module <NUM> checks if the measurements of the sensors TS are valid and selects one according to a pre-determined criterion, preferably the lowest temperature TS. Checking whether measurements are valid involves checking various conditions indicative of problems with the measurement sensor and/or environmental situations such that the measurement is not considered usable for control purposes, e.g. it is checked whether:.

The ambient temperature value estimate Tv is carried out by the estimation module <NUM>, which will be discussed in more detail below.

Periodically, the control unit <NUM>, in particular the selection module <NUM>, compares the ambient temperature value estimated by the estimation module <NUM> with the ambient temperature value TS measured by one of the sensors Si. In particular, the estimated ambient temperature Tv is compared to the lowest temperature among those measured by the installed sensors Si, however, it is possible to use other criteria for selecting the sensor with which to compare the estimate Tv.

Depending on the comparison, the control unit <NUM> regulates the frequency with which the sensors Si take measurements and transmit them to the control unit <NUM>, where they are received by the radio interface <NUM> and supplied to the control unit <NUM>. For this purpose, the control unit <NUM> sends a control message via the radio interface <NUM> to the sensors Si.

In one embodiment, in the event that the estimate Tv and the measurement TS coincide at less than a predetermined tolerance threshold, e.g. within <NUM>%, then the control unit <NUM> reduces the measurement frequency of the actual sensor Si. Otherwise, the measurement unit increases the measurement frequency of the actual sensor Si.

In other embodiments, it is also possible to provide a tolerance range, e.g. <NUM>% to <NUM>%, whereby if the difference between the estimate Tv and the measurement TS falls within this range then the frequency of the sensors is not changed, whereas if the difference is greater than the upper limit of the range then the frequency is increased, and if it is less than the lower limit of the range then the measurement frequency of the sensors is reduced.

Returning to the estimate of the ambient temperature Ts, this is preferably obtained by means of a machine learning algorithm of the model-based type, i.e. an artificial intelligence algorithm based on a basic model which is preferably a basic model of the integral or pseudo-integral type.

In the example described here, the basic model is of the pseudo integral type and connects the estimated ambient temperature Tv to the delivery water temperature and the temperature outside the building, according to the following relationship (<NUM>): <MAT>.

In <FIG>, the module <NUM> receives as input both a value of the delivery water temperature measured by means of a sensor (TDPV), and the desired value (also called set-point, TDSP) of the delivery water temperature provided as output by the controller <NUM>. In this way, when a variation between command (TDSP) and measured value (TDPV) occurs, the system knows to expect a subsequent variation of both the measured value TDPV and the building temperature Ts, and can use this information to validate the temperature measurements received from the sensors Si.

The module <NUM> also receives as input the ambient temperature values TS measured by the sensors Si, so the machine learning algorithm starting from the base model can begin to estimate the model parameters, with one of the techniques known in literature, to adapt to the building consumption.

In order to make the estimate of the system parameters kp and kd more robust, the module estimates <NUM>p using two different estimation procedures. If the estimate of kp obtained from the two procedures differs by less than a predefined threshold, then the values of kp and kd generated by one of the two estimation procedures are taken. Otherwise, the estimate is not considered reliable and is not passed on to the controller <NUM>. In other words, the module <NUM> does not provide the module <NUM> with any Tv estimates, and the controller <NUM> will base its decisions solely on the measurements received from the sensors TS as long as the kp values obtained by the two procedures coincide at less than the predetermined threshold.

In particular, one embodiment uses a heuristic procedure based on the recognition of proper conditions for the excitation of the system to be controlled. In particular, the procedure involves looking for variations in the desired value of the delivery water temperature (TDSP) that have sufficient energy (e.g. are greater than <NUM>) to cause a visible response of the ambient temperature inside the building. Herein, a 'visible' response means a response to a stimulus characterised by an adequate signal-to-noise ratio - for example, a signal-to-noise ratio greater than or equal to <NUM> and more preferably greater than or equal to <NUM> in the case of sensors typically installed in the generic boiler <NUM>.

The model parameters are then estimated at the TDSP changes that satisfy the above energy criterion. When estimated, the parameters are then compared with the output of a more traditional procedure such as recursive least squares with oblivion coefficient or Kalman filter or with the output of a machine learning algorithm of regression type - for example, a support vector regression algorithm or a neural network -, which estimates identical quantities, i.e. the growth rates kp and kd, linked to the boiler delivery temperature and the outdoor temperature respectively.

A procedure for estimating kp, implemented by the module <NUM>, is illustrated below with reference to the flowchart in <FIG>. After the start of the estimation method (step <NUM>), some parameters are initialised (step <NUM>), in particular, a counter i which takes into account the i-th parameter kp,i calculated, and a counter n which takes into account the n-th sampling step performed, are initialised to the value <NUM>; moreover, the variable kp,i_ITER used in the calculation of the parameter kp,i, is initialised to zero, and the mean value and the standard deviation of the previously calculated parameters kp are acquired.

The module <NUM> therefore checks whether three conditions are met to start the estimation process, in detail:.

Where ε is the aforesaid predetermined threshold. This allows the estimate to be activated only if the controller <NUM> has determined the need for an increase in the delivery water temperature such that there is a noticeable deviation in the ambient temperature inside the building.

If at least one of the above conditions is not met, then the module <NUM> does not initiate the estimation procedure and the method returns to step <NUM> without producing an output estimate of kp. In such a case, as described below, the values kp and kd of the mathematical model will not be updated.

If, on the other hand, all three of the above conditions are met, the module <NUM> proceeds to calculate the estimate of kp.

First a stopwatch is started (step <NUM>), then:.

Next, step <NUM>, the parameter kp,i_ITER is calculated, as: <MAT> wherein.

Next, the method comprises checking whether the sensor measurements are valid (step <NUM>), whether the boiler is on (step <NUM>) and checking (step <NUM>) whether ΔTD at step n (i.e. TDSP(n) minus TDPV(n)) is above a threshold which may be equal to the threshold ε considered at step <NUM>, or more preferably be a percentage of the value that ΔTD had at the beginning of the estimation process, i.e. when n=<NUM>.

If all three checks are satisfied, then the value of n is increased (step <NUM>) and the ambient temperature (TS), outdoor temperature (Te) and the delivery temperature set-point (TDSP) measurements are re-sampled. Steps <NUM> to <NUM> are then repeated cyclically until one of the three checks in steps <NUM>, <NUM> and <NUM> fails.

When the sensor measurements are invalid, the boiler is switched off or the delivery water temperature falls below a dynamic threshold value - for example a threshold value lower than the maximum value reached by a predetermined amount - such as a value less than <NUM>% of the maximum value reached -, then the method involves stopping (step <NUM>) the stopwatch started in step <NUM> and storing - at least temporarily - a new kp,i value which is then used to estimate the ambient temperature (Tv) inside the building.

In the example in <FIG>, the method envisages a number of verifications before providing the estimate of kp,i as output. First of all, it is checked (step <NUM>) whether the overall change in ambient temperature measured by the sensors (Σ ΔTS) is greater than a predefined threshold δ, e.g. <NUM>.

If this is not the case, then the temperature variation inside the building is not considered large enough to cause a change in the previously calculated model, so the method goes to step <NUM> and a value kp,i equal to the mean value of kp is provided as output to the algorithm. This mean value is calculated from the previously calculated and stored values of kp,j (with j between <NUM> and i-<NUM>).

If, on the other hand, Σ ΔTS ≥ δ, then the method involves carrying out (step <NUM>) further checks on the calculated value kp,i_ITER. In particular, it checks whether.

The mean value and standard deviation of kp are calculated from the previously calculated and stored values of kp,j (with j comprised between <NUM> and i-<NUM>).

If these two conditions are also verified, then the estimation method gives as output kp,i = kp_iTER (step <NUM>). Otherwise, the method goes to step <NUM> and a value kp,i equal to the mean value of kp is provided as the output to the algorithm.

Once the i-th estimate of kp has been generated, the method moves on to estimate the next parameter kp, so the value of the counter i is increased by one unit (step <NUM>) and all other parameters of the algorithm, e.g. counter n, are re-initialised (step <NUM>) as described above in step <NUM>. Then the method returns to repeat the checks of steps <NUM>, <NUM> and <NUM> and proceeds to calculate the next value kp,i+<NUM>.

As mentioned above, each i-th estimate of kp generated by the method described above with reference to <FIG>, is compared with the estimate obtained by a different procedure, e.g. using a recursive system for parameter estimation, in particular a Kalman filter, a recursive least squares identification system with an oblivion coefficient or a machine learning algorithm of the regression type - for example, a support vector regression algorithm or a neural network.

In detail, if there is a discrepancy between the kp parameters estimated by the two estimation procedures, then the model is out of date. Consequently, the ambient temperature estimate TV is calculated using the kp and kd values calculated in the previous iteration of the method described above. Differently, if there is a match between the kp parameters estimated by the two estimation procedures, the model is updated and the estimation module <NUM> and the ambient temperature estimation Tv is performed based on the newly calculated kp and kd values. The ambient temperature estimate Tv is then provided by the estimation module to the selection module <NUM>. The selection module <NUM> is configured to verify that the estimated value Tv substantially corresponds to the measured temperature TS (at the times when the measurement TS is available). If so, the selection module <NUM> requires TC to correspond to Tv. If this is not the case, the model is considered to be unreliable and TC therefore corresponds to TS - until a subsequent check of the value Tv proves the reliability of the model. If the estimate Tv proves not to be consistent with the measurements TS, the sampling period of the sensors TS is updated to more frequent values, as described above.

In one embodiment, the correspondence between the parameters kp estimated by the two estimation procedures is considered verified if the two kp values estimated by the two estimation procedures differ by less than a threshold value. Preferably, the threshold value is set substantially equal to the lower value kp estimated by the two estimation procedures, i. e: <MAT> where kp,i is the kp value estimated by the first estimation procedure, and kp,i is the kp value estimated by the other estimation procedure.

Even more preferably, the verification of the correspondence between the kp parameters estimated by the two estimation procedures envisages a second requirement. In particular, this correspondence is considered verified if it is also found that the uncertainty - e.g., the standard deviation - of the lower value of the uncertainties associated with the kp parameters estimated by the two estimation procedures is the smallest kp value estimated by the two estimation procedures, i. e: <MAT> where σp,<NUM> is the standard deviation of the kp values estimated by a first estimation procedure, and σp,<NUM> is the standard deviation of the kp values estimated by the other estimation procedure.

The controller <NUM> may be a controller of a known type which acts on the basis of the ambient temperature value Tc received as input and provides as output the new set-point value of the delivery temperature of the vector fluid TDSP to reach the desired ambient temperature value.

Preferably, the control unit <NUM> is configured to operate in dual-mode: the first mode is linear control, while the second mode is on-off control. The first mode provides exact compensation for variations in heat load, while the second mode ensures rapid system response when the controlled variable - the delivery water temperature - is far from the set-point value.

In the embodiment illustrated in <FIG>, the control unit <NUM> in addition to the components already mentioned includes an on-off module <NUM> that manages the on-off control mode of the control unit, while the controller module <NUM> manages the continuous variable control mode, also referred to as continuous control mode for brevity in the following. In addition, the control unit includes a supervisor module <NUM> configured to manage the operation of the other components of the control unit <NUM>. Preferably, the control unit <NUM> also comprises a planner or scheduler module <NUM> configured to store and impose one or more ambient temperature set-point values TSSP, for example according to a schedule defined on an hourly basis.

In the example considered, the controller <NUM> comprises a training module <NUM> configured to operate as a min-max controller and a continuous control module <NUM> configured to operate as a continuous controller of the heating system.

In particular, the supervisor module <NUM> is configured to enable the min-max module <NUM> simultaneously with the initial activation of the heating system after installation of the heating system in the building. The min-max module <NUM> makes it possible to minimise the learning time of the mathematical model for estimating the ambient temperature Tv - i.e. in the case of formula (<NUM>) the time for estimating the parameters kp. In fact, at the first activation of the heating system, the mathematical model referred to in formula (<NUM>) above is not yet defined, as the values of the parameters kp and kd are not known.

Advantageously, the min-max module <NUM> is configured to vary the set-point value TDSP of the delivery water temperature discretely between a minimum value TDSP_MIN and a maximum value TDSP_MAX, as illustrated in the quality graphs in <FIG> and the flow diagram in <FIG>. The analysis of the disturbances in the thermal system, substantially consisting of the building <NUM>, caused by this operating mode of the controller <NUM> makes it possible to obtain reliable ambient temperature estimates Tv in a short time and, at the same time, ensure that the desired temperatures are maintained inside the building.

In detail, when the heating system is first switched on following its installation, the supervisor module <NUM> commands the controller <NUM> to operate in min-max controller conditions <NUM> (initial step <NUM>).

The min-max module <NUM> controls the burner <NUM> by setting the set-point value of the delivery water temperature to the maximum value TDSP_MAX, which determines the heating of the delivery water and consequently of the temperature measured by the sensors Si inside the building (t = <NUM> in <FIG> and step <NUM> of the flow chart in <FIG>).

The maximum set-point temperature value TDSP_MAX of the delivery water temperature is maintained until the desired ambient temperature value TSSP provided by the scheduler <NUM> to the controller <NUM> is reached or exceeded or, more preferably, when an upper limit value (local maximum of the curve Ts(t) in t = t<NUM> in <FIG>) equal to the ambient temperature set-point value TSSP plus a first margin ΔTSSP_M - for example, between <NUM>° C and <NUM>, preferably equal to <NUM>° C - is reached (step <NUM>).

When the ambient temperature TS detected by the sensors Si reaches the set-point value TSSP or the upper limit value, the min-max module <NUM> switches the set-point value TDSP of the delivery water temperature to the minimum value TDSP_Min, e.g. the minimum delivery temperature value manageable by the boiler (step <NUM>).

This variation leads to a progressive reduction of the ambient temperature TS inside the building. This reduction continues until the desired set-point value TSSP is exceeded or, more preferably, a lower limit value (local minimum of the curve Ts(t) in t = t<NUM> in <FIG>) equal to the ambient temperature set-point value TSSP reduced by a second margin ΔTSSP_m - for example, between <NUM>° C and <NUM>, preferably equal to <NUM>° C - (step <NUM>).

Once the ambient temperature set-point value TSSP has been exceeded or the lower limit value has been reached, the min-max module <NUM> switches the delivery water temperature back to the maximum set-point temperature value TDSP_MAX, until the ambient temperature set-point value TSSP (local maximum of the Ts(t) in t = t<NUM> curve in <FIG>) is reached or exceeded again, and then switches back to the minimum value TDSP_Min as described above. Preferably, the procedure is iterated until an off condition of the heating system is reached (step <NUM>). In this case, the on-off module <NUM> forces the burner <NUM> to switch off (step <NUM>), for example by bringing the set-point value TDSP of the delivery water temperature to a minimum value or, alternatively, by dropping (bringing to zero) the boiler start-up consent (instant t = t<NUM> in <FIG>). The activation of the on-off module <NUM> may be caused by the supervisor module <NUM> upon reaching a predetermined time - for example, during night-time hours or imposed by a regulation - by means of a command provided to the on-off module <NUM> or by bringing the ambient temperature set-point value TSSP provided by the scheduler <NUM> to the on-off module <NUM> to a minimum value. The operation then returns to the min-max module <NUM> of the controller <NUM> at the next switch-on of the heating system (step <NUM>) - for example, at a predetermined time in the morning - (instant t = t<NUM> in <FIG>). In the same way as switching off, the heating system can be switched on by means of a start command given to the min-max module <NUM> or by bringing the set-point value TSSP to a desired value greater than the current ambient temperature value.

Advantageously, starting with each transition from the minimum value TDSP_min to the maximum value TDSP_MAX until the next, opposite transition from the maximum value TDSP_MAX to the minimum value TDSP_min the estimation module <NUM> is configured to detect the trend of the ambient temperature value and to refine and estimate a corresponding kp value by means of the kp estimation procedure described above in relation to <FIG> so as to progressively refine the system model.

The controller <NUM> operates in min-max controller mode as just described, as long as the control unit <NUM> does not have sufficient history to calculate an average kp value that is stable over time, for example until as <NUM>p values have been calculated.

Advantageously, the maximum value TDSP_MAX and the minimum value TDSP_min are chosen to minimise the number of transitions required to process a sufficient number of kp value estimates - making the model usable - while allowing the ambient temperature in the building to be controlled to ensure user comfort. The Applicant has determined that it is possible to determine the optimum maximum value TDSP_MAX and minimum value TDSP_min by applying the theory of asymptotic properties of prediction error models (PEMs) and the asymptotic theory of Ljung (<NUM>), as defined in <NPL> and <NPL>.

In particular, the Applicant has determined that it is possible to minimise the time required to obtain the model parameters and to guarantee the comfort of the users by imposing a minimum value TDSP_min comprised between <NUM>° C and <NUM>° C, preferably equal to <NUM>° C or equal to <NUM>° C and a maximum value TDSP_MAX comprised between <NUM>° C and <NUM>° C, preferably equal to <NUM>° C or <NUM>° C, in the case of heating systems comprising a boiler that heats water.

When the estimation module <NUM> computes a reliable model - that is, makes available an average value of kp and, thus, of kd that is stable over time, the supervisor module <NUM> notifies the controller <NUM> to switch the control mode from min-max to continuous variable control by deactivating the min-max control module <NUM> and activating the continuous control module <NUM>.

In the embodiments, continuous control mode is defined by exploiting the model - described above - used to represent the thermodynamic system of the building and provide the ambient temperature Tv estimate. Preferably, it is contemplated to determine one or more control parameters used by the linear control module <NUM> on the basis of the kp value and, preferably, the kd value determined by the estimation module <NUM>.

Advantageously, the integral or pseudo-integral nature of the model considered above makes it possible to employ a particularly simple but at the same time particularly effective controller <NUM>. In detail, when the two estimates of the kp and kd values converge as described above, these kp and kd values are considered sufficiently accurate to allow reliable self-tuning, or autotuning, of the controller <NUM> to the thermal system - i.e., the building - being controlled. Since the thermal system to be controlled is approximated by an integral or pseudo-integral model, it is possible to apply control by integral system, in particular, it is possible to initially supply the energy necessary to reach the set-point value TSSP in a predefined time, and then the flow temperature can be brought to the minimum equilibrium value necessary to keep the temperature stable by compensating the thermal load of the building - that is, by compensating the heat losses of the building mainly due to the difference between the ambient temperature TS and the outside temperature Te. Minimisation of the delivery temperature for most of the operating period of the heating system results in minimisation of the return temperature and thus maximises the efficiency of the boiler.

In more detail, the controller <NUM> in the continuous controller mode envisages determining - on the basis of the values Tc, kp, kd and, preferably, the value Te - a set-point value TDSP of the delivery temperature of the water such that the ambient temperature in the building reaches the desired set-point value TSSP within a predetermined time (t = tλ in <FIG>) - for example, within one hour after the system is switched on. Once the desired set-point value TSSP has been reached, the set-point value TSSP of the delivery water temperature is adjusted to maintain the ambient temperature value at, or at least around, the set-point value TSSP. In particular, the controller <NUM> is configured to determine - on the basis of the values Tc, kp, kd and, preferably, the value Te - the minimum set-point value TDSP of the delivery water temperature which allows the ambient temperature to be maintained at the set-point value TSSP in the face of variations in the observed values Tc and Te (time interval between t = tλ and t = tOFF1 in <FIG>), until the predetermined switch-off of the heating system (time interval between t = tOFF1 and t = t<NUM> in <FIG>).

In a particularly economical and compact embodiment, the continuous module <NUM> of the controller <NUM> (as schematically illustrated in <FIG>) comprises a proportional-integrative block <NUM> whose operating parameters are dynamically determined on the basis of the value kp and the value kd determined by the estimation module <NUM>. Preferably, the calculation of the control parameters - i.e. a proportional coefficient kC and an integrative coefficient Ti - of the proportional-integrative block <NUM> is based on the technique known as lambda-tuning.

Even more preferably, the coefficients kC and Ti are determined from a connection block <NUM> of the estimation module <NUM> and supplied to the proportional-integrative block <NUM>.

In this case, the proportional coefficient kC of the proportional-integrative module <NUM> is calculated as: <MAT> where λ is a time within which the set-point value TSSP of the ambient temperature is to be reached, Δtr is a time indicating a delay between a change in the delivery temperature and a change in the ambient temperature value TS, while σp is the uncertainty associated with the value of kp defined as the standard deviation associated with the set of kp, i values acquired.

In addition, the integrative coefficient Ti of the proportional-integrative block <NUM> is calculated as: <MAT>.

Preferably, the linear control module <NUM> of the controller <NUM> also comprises a feed-forward block <NUM> whose operating parameter - i.e., an advance coefficient - is determined based on the value kp and the value kd determined by the estimation module <NUM>.

Even more preferably, the advance coefficient kff of the feed-forward block <NUM> is also determined by the connection block <NUM> of the estimation module <NUM>.

For example, the advance coefficient kff of the feed-forward block <NUM> is calculated as: <MAT>.

Advantageously, the estimation module <NUM> implements the following procedure for processing the control parameters of the proportional-integrative block <NUM> and the feed-forward block <NUM> (a flow chart of which is shown in <FIG>).

At each iteration of the procedure that calculates the value kp and the value kd, performed by the estimation module <NUM> an indication of the result of the congruence check of the values kp calculated according to the two procedures is provided to the supervisor module <NUM> (initial step <NUM>).

If the values kp and kd are reliable (step <NUM>), the connection block <NUM> of the estimation module <NUM> calculates (step <NUM>) the coefficients kc e Ti of the proportional-integrative block <NUM> and the advance coefficient kff of the feed-forward module <NUM> according to formulas (<NUM>) - (<NUM>) above on the basis of the values kp and kd. Conversely, if reliable kp and kd values are not available, the supervisor module <NUM> is configured to force the use (step <NUM>) of default coefficients kc, Ti and kff - for example, stored in a memory area of the control unit <NUM>.

During operation in continuous mode, the controller <NUM> receives as input the ambient temperature value TC from the selection module <NUM> and, preferably, the outside temperature value of the building Te. On the basis of these inputs and the set-point value TSSP of the ambient temperature provided by the scheduler <NUM>, the continuous module <NUM> controller <NUM> determines in real time the set-point value TDSP of the delivery water.

On the basis of the set-point value TDSP of the delivery water, the control unit <NUM> operates the burner <NUM> of the building's heating unit in such a way as to reach the desired set-point value TSSP within the set time λ and thus maintain the building's ambient temperature at the set-point value TSSP or, at least, in its vicinity.

In the exemplary case of the controller <NUM> equipped with the proportional-integrative block <NUM> and the feed-forward block <NUM>, the set-point value TDSP of the delivery water is defined by the combination of the outputs of the modules <NUM> and <NUM> as described below and illustrated by the flow chart in <FIG>.

As soon as the system is switched on, the feed-forward block <NUM> is configured to compensate (step <NUM>) for heat dispersion due to the difference between the ambient temperature inside the building and the outside temperature. In particular, the feed-forward block <NUM> provides an output value Tff given by the combination of the outdoor temperature Te and the advance coefficient kff <MAT>.

The proportional-integrative block <NUM> is configured to cancel (step <NUM>), or at least minimise, a difference between the ambient temperature and the desired set-point value TSSP. In detail, it provides an output value TPI provided by the difference between the ambient temperature set-point value TSSP and the ambient temperature value Tc provided by the selection module <NUM> combined with the control coefficients kc and Ti: <MAT>.

The output values of the blocks <NUM> and <NUM> are then combined (step <NUM>), preferably summed, with each other to determine an overall output value corresponding to the set-point value TDSP of the delivery water temperature (TDSP = TPI+Tff).

The set-point value TDSP of the delivery water temperature is then recalculated at each (step <NUM>) control cycle performed by the control unit <NUM> (typically once per minute, more generally with a period such as to ensure a rapid response of the system to a variation of the variables observed by the control unit <NUM>) and by first recalculating the control parameters kc, Ti and kff as described above (step <NUM>) in case the variation of at least one of the values kp and kd is verified (step <NUM>).

The preceding steps of the procedure are iterated during the operating period of the heating system (step <NUM>) while outside this operating period the heating system is switched off (step <NUM>) by means of the on-off module <NUM> which forces the shutdown of the burner <NUM> - in a similar manner as described above - until the beginning of the next operating period in which the continuous module <NUM> of the controller <NUM> forces the re-ignition of the burner <NUM>.

Preferably, at each boiler start-up, the estimation module <NUM> is configured to detect the trend of the ambient temperature value from start-up to the time of reaching the desired set-point value TSSP and estimate a corresponding value kp by means of the kp estimation procedure described above in relation to <FIG> so as to progressively refine the thermal system model.

In one embodiment, the control unit <NUM> is configured to exploit the thermal inertia of the thermal system of the building or parts thereof - such as, for example, the radiators <NUM> - in order to reduce the energy consumption of the heating system, without affecting the comfort of the users.

The estimation module <NUM> is configured to estimate an operating temperature TOP, which is defined as the weighted average between the ambient temperature measured by the sensors Si and the radiant temperature TRAD to which a user is subjected within a portion of the building - for example, a residential unit or a room.

In one embodiment, a reference radiant temperature TRAD is defined according to the following formula - suitable for wall-mounted radiators (radiators): <MAT> wherein the term α<NUM> ·(TC - <NUM>)is indicative of the radiant temperature of the floor, α<NUM>· (TC + <NUM>)is indicative of the radiant temperature of the ceiling, the termα<NUM> · Tc is indicative of the radiant temperature of the walls and the term β·TDPV is indicative of the radiant temperature of the radiator <NUM> or radiators <NUM> positioned in the portion of the building. Furthermore, the coefficients α<NUM>, α<NUM>, α<NUM>, β are associated with floors, ceilings, walls and radiators, respectively, and are coefficients proportional to the area of each surface in relation to the total area within the portion of the building considered. In one embodiment, the reference radiant temperature TRAD is calculated by considering a square room with a side of <NUM> and a wall height of <NUM> and a single radiator was considered with a radiant surface essentially equal to <NUM><NUM>.

The operating or perceived temperature is then, as known in the literature of the sector, calculated as the average between the measured ambient temperature and the radiant temperature, i.

The radiant temperature of the radiators <NUM> is set equal to the measured delivery water temperature TDPV, while the boiler is switched on. Otherwise, the radiant temperature of the radiators <NUM> becomes unknown once the boiler is switched off, as the circulation of water in the heating system is interrupted. Advantageously, the estimation module <NUM> is configured to calculate an estimate of the radiant temperature of the radiators <NUM> as a function of time and/or a cooling time required to reach a predetermined final temperature.

In one embodiment, the estimation module <NUM> is configured to calculate an estimate of the radiant temperature of the radiators <NUM> based on a model defined based on the characteristics of the radiators (e.g. size and constituent materials) and the temperature of the radiators at the time of boiler lockout (e.g. set equal to the temperature of the water returning to the boiler).

Alternatively, the control unit <NUM> is configured to allow selection of a radiator cooling curve from the following options: cautionary curve (curve A shown in <FIG>), intermediate saving curve (curve B) and high saving curve (curve C). In detail, such curves make it possible to determine the time required for the radiators <NUM> to reach a desired final radiant temperature value, for example corresponding to the minimum delivery water temperature manageable by the boiler, or the ambient temperature, considering the radiator immersed in fluid at the ambient temperature, for example the desired set-point value TSSP, starting from an initial radiator temperature, for example estimated corresponding to the measured temperature TR,S of the water returning to the boiler.

In one embodiment, the curves are described by the following parametric formulae - derived using a concentrated parameter approach and using the Biot number -, where an ambient temperature of <NUM>° C and a final radiant temperature of <NUM>° C have been assumed:.

where tA, B, C corresponds to the cooling time (in minutes) required by the radiators to reach the minimum temperature of <NUM>° C since the boiler was turned off and TR,S is the temperature of the water returning to the boiler at the instant when the supply of heat to the radiators is suspended.

In particular, each of these curves is based on a respective interpolating equation, obtained by averaging the cooling times of radiators made of aluminium, cast iron and steel, and determined for a respective radiator size selected from large (curve A), medium (curve B) and small (curve C). The Applicant has determined that such curves allow for an adequate estimate of the thermal performance of the radiators after the interruption of the flow of heated water regardless of the actual characteristics of the radiators actually installed based on the desired degree of energy saving - thus without requiring the installation engineer to enter precise data regarding the radiators installed in the building.

In general, the operating temperature TOP has a faster dynamic than the ambient temperature as the radiators <NUM> heat up faster than the surrounding air. By using the operating temperature TOP, it is therefore possible to determine boiler shutdown intervals - during the daily operating period thereof - which are generally longer than if only the ambient temperature were used as a reference. This makes it possible to substantially reduce the energy consumption of the heating system in a way that is transparent to users - i.e. without substantially changing the temperature perceived by users - and thus the level of comfort.

With reference to the graphs in <FIG> and the flowchart in <FIG>, starting from the switching on of the heating system the continuous module <NUM> of the controller <NUM> is configured to bring the operating temperature TOP - instead of the ambient temperature - to the desired set-point value TSSP within the time λ (step <NUM> and time interval from t = <NUM> to t = tλ in <FIG>).

Once the operating temperature value TOP has reached the set-point value TSSP or, more preferably, an operating upper limit value equal to the set-point value TSSP plus a predetermined margin ΔTOP_M - for example, between <NUM>° C and <NUM>° C, preferably equal to <NUM>° C - or the continuous module <NUM> maintains the set-point value TDSP of the delivery water temperature at the minimum value TDSP_min - capable of compensating for variations in the outside temperature Te as described above - for a predetermined time interval ΔtOP (step <NUM>, time from t = tλ to t = t<NUM> in <FIG>), the on-off module <NUM> forces the boiler to be turned off - for example, the on-off module <NUM> imposes a minimum set-point temperature TDSP for the delivery water temperature (step <NUM>).

The on-off module <NUM> keeps the boiler off until the value Tc of the ambient temperature is lower than the set-point value TSSP by a predetermined margin value ΔTSSP_L - for example, between <NUM>° C and <NUM>, preferably equal to <NUM>° C - (step <NUM>, time interval from t = t<NUM> to t = t<NUM> in <FIG>), when the continuous module <NUM> imposes a set-point value TDSP of the delivery water temperature different from the minimum (step <NUM>), in particular such as to quickly bring the value of the operating temperature TOP back to the set-point value TSSP. Preferably, it is planned to impose a dead-band ΔtDB between boiler shutdown and subsequent restart, so as to limit the frequency of switching the boiler on and off.

The steps of the procedure as described above are iterated during the operating period of the heating system (step <NUM>) while outside this operating period the heating system is switched off (step <NUM>, from t = tOFF1 in <FIG>) by means of the on-off module <NUM> which forces the shutdown of the burner <NUM> - in a similar manner as described above - until the beginning of the next operating period in which the continuous module <NUM> of the controller <NUM> forces the re-ignition of the burner <NUM>.

Alternatively or additionally, the control unit <NUM> is configured to detect a shutdown of the boiler imposed by an internal circuitry of the boiler - the so-called control level <NUM> - when a limit value is exceeded, preferably equal to the set-point value TDSP of the delivery water temperature increased by a margin value - for example, equal to <NUM>° C (step <NUM> of the flow chart in <FIG>). Upon detecting the shutdown, the control unit <NUM> is configured to prevent a restart of the boiler controlled by the internal boiler circuitry (step <NUM>) until it detects that the operating temperature is substantially equal to a desired temperature - for example, substantially equal to the ambient temperature- or the cooling time has elapsed (step <NUM>). For example, the on-off module <NUM> is configured to forcibly keep the boiler off until the value of the operating temperature TOP equals the value of the ambient temperature Tc or is equal to the average of the ambient temperature and the minimum radiant temperature, or after a time corresponding to the cooling time tA, B, c has elapsed. Subsequently, the continuous module <NUM> of the controller <NUM> imposes a set-point value TDSP of the delivery water temperature allowing the boiler to be reactivated (step <NUM>).

The implementation of at least one, preferably both, of the procedures described above allows the boiler to be kept off for as long as possible by exploiting the radiation of the heat accumulated by the radiators - a condition known as 'coasting' or 'sailing' in technical jargon. Thanks to the coasting obtained in this way, it is possible to guarantee the comfort of the users and, at the same time, prevent continuous switching on/ off due to the level <NUM> circuitry of the boiler, which is inefficient both from an energy and thermal point of view.

The invention thus conceived is susceptible to several modifications and variations, all falling within the scope of the inventive concept.

For example, in one embodiment, it is envisaged to control the temperature of the vector fluid based on the temperature estimates generated by the mathematical model when there is a breakdown in communication between the sensors located inside the building and the control unit or the data received at the control unit is corrupted.

In a simplified embodiment (not illustrated), it does not include the min-max module <NUM>. In this case, the control unit <NUM> contemplates using the on-off module <NUM> to perform the initial procedure necessary to acquire the data required to allow the estimation module <NUM> to construct a reliable model of the building's thermal system.

In an alternative embodiment (not illustrated), the control unit <NUM> provides for combining, e.g. summing, an outdoor temperature compensation curve Te - like a climate curve - to the minimum value TDSP_min and to the maximum value TDSP_MAX. This improves the operating efficiency of the system during min-max operation, at least partially compensating for variations in the thermal load due to outside temperature Te variations.

In one embodiment, it is planned to implement the on-off module <NUM> adaptively. In particular, the on-off module is configured to calculate a variable set-point value on the basis of the integral or pseudo-integral mathematical model developed by the module <NUM>. In detail, the on-off module <NUM> is configured to calculate a regulation value el to be combined, in general subtracted, from the set-point value TSSP, leading to an earlier shutdown of the boiler and thus reducing the consumption of the heating system.

Preferably, the variable set-point value is processed starting from the ambient temperature set-point value TSSP or from a set-point value of the operating temperature on the basis of the values kp and kd processed by the module <NUM> and the delay time to of the heating system - indicative of thermal inertia of the heating system -, i.e., the time required to heat the radiators and heat the room in the building.

In particular, it is possible to identify the threshold value el according to the following relationship: <MAT>.

The Applicant has determined that it is possible to assume a delay time to substantially between <NUM> and <NUM> minutes, preferably <NUM> minutes, in the case of a heating system using water as the vector fluid and radiators as the heating elements.

In a different embodiment instead of the adaptive threshold el the operating temperature and a fixed threshold is used to achieve the same control purpose.

In a different embodiment (not illustrated), the on-off module <NUM> is configured to also control the reaching of the set-point value TSSP of the ambient temperature by imposing operation at maximum boiler power - for example, by imposing a set-point value TDSP of the delivery water temperature equal to the maximum temperature reachable by the boiler - in order to minimise the time to reach the set-point value TSSP at the cost of higher power consumption during the start-up phase.

Of course, there is nothing to prevent providing a different continuous control module <NUM>, for example, including a PID block or configured to implement predictive control instead of a PI block and an FF block. Accordingly, the connection block <NUM> of the estimation module <NUM> will be configured to calculate and provide appropriate control parameters to the continuous control module <NUM>. Preferably, predictive controller is a Model Predictive Control (MPC), optionally configured to acquire future external temperature values, for example, from a remote entity external to the heating system such as a server implementing a weather forecast service.

Similarly, there is nothing to prevent the use of a criterion other than λ-tuning to determine the parameters of the proportional-integrative block <NUM>, just as the feed-forward block <NUM> may involve a more complex transfer function including, for example, one or more filters.

In an alternative embodiment, the feed-forward block involves acquiring at least one predicted outside temperature value Te - for example, provided by an external entity, as described above - and calculating an output value Tff as a function of the current outside temperature value and one or more future temperature values. Preferably, the output value Tff will be calculated as the sum of the products of each outside temperature considered by a corresponding advance coefficient. Preferably, each advance coefficient is calculated by means of the kp and kd values estimated by the model based on the outside temperature considered.

In other embodiments, it is envisaged to use the operating temperature TOP as the ambient reference temperature even without implementing the coasting procedures described above. In dual mode, there is nothing to prevent the implementation of coasting procedures using a set-point value TSSP plus an operating margin - for example, in the order of tenths of a degree Celsius.

In one embodiment (not shown), the control unit includes a diagnostic system, or fault diagnosis, configured to analyse the performance of the continuous control module <NUM> in order to detect any malfunctions - for example, too slow a response, excessive ambient temperature fluctuations, boiler in maximum or minimum saturation, etc. - and, in response to these malfunctions, switch the building management to normal on-off control - and, in response to these malfunctions, switch building management to normal on-off control. For example, the fault diagnosis system can be implemented by the supervisor module <NUM>.

In addition, the control unit can implement an early switch-off procedure to reduce the length of the switch-on period on the other hand, exploiting the thermal inertia of the radiators and possibly of the building itself. This reduces the overall consumption by reducing the overall daily operation time of the heating system. Advantageously, the optimal switch-off advance times are calculated on the basis of the processed thermal system model of the building, and the outside temperature, applying the principle of one-step prediction logic.

Similarly, the control unit can implement a procedure to vary the switch-on time according to the current and/or predicted outside temperature (acquired from an external entity as described above). In this way, it is possible to adapt the switch-on timing of the heating system to the actual environmental conditions, making it possible to reduce the power required to reach the desired ambient temperature in unfavourable climatic conditions or to delay the heating system switch-on in favourable climatic conditions, thus reducing the operating period of the heating system.

Furthermore, in a highly configurable embodiment (not illustrated), the control unit <NUM> is configured to receive - for example, from an installation technician via a user interface - characteristic parameters of the radiators <NUM> installed in the building or average values of the characteristic parameters if radiating elements of different types are installed in the building. These characteristic parameters include, but are not limited to, a radiator size - for example, selectable between small, medium and large size depending on the volume of the radiator - and a radiator material - for example, selectable between aluminium, cast iron and steel. The control unit <NUM> is then configured to calculate the radiant temperature of the radiators and/or its trend over radiator time according to the entered characteristic parameters. On the contrary, there is nothing to prevent - in a simplified embodiment (not illustrated) - defining the operating temperature TOP as equal to the ambient temperature plus an offset based on an estimate of the thermal characteristics of the radiators <NUM>.

It will be clear to a person skilled in the art that control unit <NUM> can be equipped with one or more additional modules. In the example illustrated in <FIG>, the control unit <NUM> comprises a reference trajectory module <NUM> and, preferably, a comfort estimation module <NUM>.

In detail, the scheduler <NUM> provides temperature set-point values TSSP to the reference module <NUM> which is configured to define a time-variable set-point value TSSP(t), which assumes the desired set-point values and defines transients to minimise the energy consumed by the system during the transition from one set-point value to the next. For example, when the thermal load is compensated and the action of the proportional-integrative block <NUM> and feed-forward block <NUM> is reduced, the rate of growth of the ambient temperature towards the desired set-point value TSSP is decreased, in order to show the proportional-integrative block <NUM> a smaller control error and thus minimise the control effort. Thanks to this configuration, it is possible to slow down the achievement of the set-point value TSSP, reducing the energy consumed by the heating system, without causing discomfort to the building's users.

The comfort estimation module <NUM> allows the identification of a temperature perceived by the user based on a plurality of input information - in accordance with<NPL>. In detail, it is planned to control and regulate a thermo-hygrometric comfort variable called TPMW instead of the ambient temperature of the building. This TPMW variable is calculated by combining a plurality of measurements taken by sensors and information provided by the user - e.g. through a user interface - or approximated according to season, time of day and/or intended use of the building. Preferably, the acquired information comprises two or more of: the ambient temperature, a measurement of ambient humidity - for example, by means of a humidity sensor that can be easily integrated into the ambient temperature sensors -, a radiant temperature of the radiators <NUM> - for example, estimated as a function of the boiler delivery temperature and the type of radiators <NUM> - air speed, an activity performed by the users and a type of clothing worn.

The comfort variable TPMW is calculated as a temperature perceived by the building users and is used as a reference value instead of the ambient temperature value Tc in the procedures described above. In this way, it is possible to reduce, or at least calibrate, the consumption of the heating system while ensuring that the user perceives a comfortable temperature.

In one embodiment, the heating system comprises two or more separate heating circuits. In this case, the control unit <NUM> is configured to perform an optimisation of the thermal balancing of the circuits, which involves removing heat from the more thermally advantaged or lower activity circuits and moving it to the more thermally disadvantaged or higher activity circuits, so as to produce further energy savings in the overall heating system.

Naturally, one or more components of the control unit can be implemented with hardware, firmware, software or combinations thereof.

It will in particular be clear to a person skilled in the art that although the description refers to a central heating system, the controller and/or methods described above can be implemented in other equipment of a different heating system such as a wall thermostat, a condensing boiler for individual residential units, as well as an HVAC system, a heat pump or a remote control system.

Claim 1:
Method of controlling the temperature of a vector fluid of a heating system (<NUM>) for heating at least a portion of a building, said heating system comprising:
heating means (<NUM>) configured to heat the vector fluid in response to a temperature command,
at least one heating element (<NUM>) arranged inside said at least a portion of the building, the at least one radiating element being configured to receive the vector fluid and give heat to the surrounding environment,
a temperature sensor (S<NUM>, S<NUM>, S<NUM>) configured to measure the ambient temperature inside said at least one portion of the building and transmits a value of the measured temperature,
a control unit (<NUM>) configured to receive the measured temperature value and to generate a command for controlling the heating means based on said measured temperature value,
wherein the method comprises having the control unit:
- implementing (<NUM>-<NUM>; <NUM>-<NUM>) a continuous control mode which comprises generate a continuous control command to maintain a target temperature value in said at least a portion of the building,
- implementing (<NUM>; <NUM>; <NUM>-<NUM>; <NUM>-<NUM>) an on-off control mode which comprises generate an off command control when the target temperature value is reached in said at least a portion of the building or when the continuous control command is kept at a minimum value for a predetermined period of time, and
- providing one selected between said continuous control command or said off control command to the heating means,
characterized in that
the method further comprises having the control unit:
- implementing (<NUM>-<NUM>) a mathematical model of the integral or pseudo-integral type configured to estimating the value of the ambient temperature as a function of the temperature of the vector fluid and a temperature outside the building, and
- calculating (<NUM>-<NUM>) at least one operating parameter of the continuous mode on the basis of said mathematical model of the integral or pseudo-integral type.