EP3224547A1

EP3224547A1 - Modulating learning thermostat

Info

Publication number: EP3224547A1
Application number: EP16744873.7A
Authority: EP
Inventors: Jacobus Cornelis Rasser
Original assignee: Rasser De Haan BV
Current assignee: Rasser De Haan BV
Priority date: 2015-05-08
Filing date: 2016-05-04
Publication date: 2017-10-04
Also published as: NL2016068B1; WO2016182434A1; NL2016068A

Abstract

A learning thermostat is disclosed for controlling an intelligent HVAC system. The thermostat may be connected to the HVAC system via wireless communication means or via two, three or four wires. The thermostat and the HVAC system may follow a master/slave configuration, with the thermostat acting as master and the HVAC system as slave. The thermostat is capable of modulating the operation of the HVAC system.

Description

MODULATING LEARNING THERMOSTAT

BACKGROUND OF THE INVENTION

1. Field of the Invention

[0001] The invention relates generally to learning thermostat for controlling an intelligent HVAC system.

2. Description of the Related Art

[0002] It is generally recognized that the energy required for heating and/or cooling a building can be reduced by adjusting thermostat settings according to the time of day, the absence or presence of people, the activity level of the people in the building, and the like.

[0003] Manually operated thermostats can in principle be used to adjust the thermostat set point according to the varying needs for heating or cooling in the course of a 24-hour day or a 7-day week. Very few consumers have developed the discipline to make the frequent manual adjustments that would be required for an optimum energy usage.

[0004] Programmable thermostats have been developed to eliminate the need for frequent manual adjustments. Programmable thermostats can be pre-programmed for different temperature set points during daytime and nighttime, with further refinements for daytime periods during which the building, for example a family home, is expected to be unoccupied. Most programmable thermostats permit different programs to be set for weekdays and weekends, or for individual days of the week.

[0005] Many consumers find the task of programming a programmable thermostat too daunting to deal with. As a result, many installed programmable thermostats operate on a factory-set program, which is rarely optimum for the actual situation. Even properly programmed programmable thermostats do not automatically deal with unscheduled absences and presences. Many users deal with this problem by allowing the thermostat to follow its pre-programmed schedule during unforeseen absences, which results in waste of energy.

[0006] WO 2013/058968 Al discloses a thermostat comprising activity sensors. Activity data generated by the activity sensors are used in two ways. The thermostat comprises a processor that contains an algorithm for deriving a schedule from patterns observed in the activity log. The schedule is translated into a schedule of desired temperatures corresponding to the pattern of regular absences and presences. Persistent changes in the presence/absence schedule form a basis for adjustments to the energy schedule.

[0007] The activity sensors also serve to detect irregular absences. If an irregular absence has a duration exceeding a predetermined length of time, for example 1 hour, the thermostat switches to an "Auto Away" mode, which is associated with an energy saving temperature set point. Upon return of at least one person to the building the thermostat automatically resumes its daily schedule.

[0008] Thermostats of the type disclosed in WO 2013/058968 Al are commercially available under the trade name Nest from Nest Labs, Inc., Palo Alto, CA (USA). Nest thermostats enjoy a reputation for innovative design and consumer convenience, paired to considerable energy savings.

[0009] Sophisticated HVAC systems are capable of modulated operation. Such systems modulate their operation depending on anticipated needs. For example, such systems may operate at a fraction of full capacity if the difference between a detected temperature and a set point temperature is small. Modulated operation avoids overshoot of the set point temperature, reduces wear and tear of the HVAC system, and saves energy. Modulating HVAC systems generally require a dedicated thermostat for optimum operation.

[0010] Nest thermostats control HVAC systems with which they are used in a simple on/off operation. When Nest thermostats are used in conjunction with a modulating HVAC system, no use is made of the modulation capability.

[0011] US 2014/0084072 Al discloses an auxiliary hardware box to be placed in the vicinity of a HVAC system. The hardware box allows modulated operation of an intelligent HVAC system. The hardware box is connected to the HVAC system by a plurality of wires, for example 16 or more wires. A learning thermostat is connected to the hardware box.

[0012] Thus, there is a need for a learning thermostat for controlling an intelligent HVAC system in modulating mode. There is a further need for a learning thermostat that can be connected to an intelligent HVAC system by a small number of wires, for example 2, 3 or 4 wires. BRIEF SUMMARY OF THE INVENTION

[0013] The present invention addresses these problems by providing a learning thermostat system for controlling an intelligent HVAC system, said thermostat system comprising:

means for determining an ambient temperature;

means for determining an outside temperature;

means for detecting human presence in a building controlled by the thermostat system; means for determining a temperature set point;

means for establishing a heat demand based on input relating to the temperature set point and at least one of (i) the ambient temperature; (ii) the outside temperature; (iii) detected presence in the building controlled by the thermostat system;

means for communicating the heat demand to the intelligent HVAC system.

[0014] Another aspect of the invention comprises a controlled system comprising a learning thermostat and an intelligent HVAC system.

BRIEF DESCRIPTION OF THE DRAWING FIGURES

[0015] Figure 1 shows a learning thermostat system of the invention connected to an intelligent HVAC system.

[0016] Figure 2 shows an alternate embodiment of the invention

DETAILED DESCRIPTION OF THE INVENTION

[0017] The following is a detailed description of the invention.

Definitions

[0018] The term "learning thermostat" as used herein means a thermostat provided with at least one algorithm for developing a schedule of temperature set points based on a detected pattern of occurrences. The pattern of occurrences may relate to any type of occurrences that are relevant for an energy efficient operation of the HVAC system.

Examples of such occurrences include the presence or absence of people in the building being serviced by the HVAC system; the operation of heat producing equipment in the building, such as computers, servers, ovens, stoves, cook tops, and the like; the amount of physical activity of people present in the building, and the like.

[0019] A learning thermostat may comprise additional algorithms for further increasing the sophistication of its operation. For example, the thermostat may learn how long it takes for the environment surrounding the thermostat (e.g., a room where the thermostat is installed) to reach a desired set point temperature in function of the actual temperature and, optionally, the outdoor temperature.

[0020] The term "HVAC system" as used herein means a system used for heating, cooling and/or ventilating a building. The system may include one or more heating units, for example a boiler, a hot air furnace, a heat pump or a resistor heating unit. The system may further include one or more cooling units, for example an evaporative cooler, a Carnot cycle compressor cooler, and the like. The system may further comprise a mechanical ventilation system, which may include one or more heat exchangers for recovering heat from air being expelled from the building. The system may further comprise a means for transporting heat from the HVAC system to the building or buildings being serviced by the HVAC system. Such means may be any means for propelling a fluid, such as air, water, antifreeze, and the like. Examples include water pumps, turbines and fans.

[0021] The term "intelligent HVAC system" as used herein means a HVAC system comprising at least one controller for modulated operation of at least one component of the HVAC system. Modulated operation means controlled operation at all or a fraction of the maximum capacity of the component. For example, a burner may operate at 0%, 30%, 50%, 70%) etc. to 100% of its maximum capacity, instead of being either off (0% of capacity) or on (95%>-100%> of capacity). A fan may be operated at various fan speeds, for example 0%, 30%>, 50%, 70% or 100% of capacity, instead of being either on or off. In a hot water heating system, in modulated operation the water temperature may be kept at, for example, 50 °C instead of at the pre-set maximum of, for example, 90 °C.

[0022] The term "heat" as used herein means the amount of thermal energy contained in a fluid medium, for example air or water. The term is used herein in the contexts of both heating and cooling, as mathematically "cooling" and "heating" both refer to the transport of heat energy, albeit in opposite directions.

[0023] In its broadest aspect the present invention relates to a learning thermostat system for controlling an intelligent HVAC system, said thermostat system comprising: means for determining an ambient temperature;

means for determining an outside temperature;

means for detecting human presence in a building controlled by the thermostat system; means for determining a temperature set point; means for establishing a heat demand based on input relating to the temperature set point and at least one of (i) the ambient temperature; (ii) the outside temperature; (iii) detected presence in the building controlled by the thermostat system;

means for communicating the heat demand to the intelligent HVAC system.

[0024] The means for determining an ambient temperature can be any type of electronic temperature sensor or thermometer. It may be present in the housing of a learning thermostat, or it may be separate from the learning thermostat. In the latter case it may communicate with the learning thermostat, for example by WiFi or a an IEEE 802.15.4 standard, for example Zigbee. The system may comprise more than one indoor electronic sensor or thermometer.

[0025] The means for determining an outside temperature may comprise any type of electronic temperature sensor or thermometer mounted outside the building controlled by the learning thermostat system. The electronic sensor or thermometer may communicate with the learning thermostat, for example by WiFi or an IEEE 802.15.4 standard. In addition to, or in lieu of the outside temperature sensor or thermometer, the means for determining an outside temperature may comprise a connection to a nearby weather station, for example a government operated weather station. The connection to the nearby weather station may be by Internet.

[0026] The means for detecting human presence in a building controlled by the thermostat system can be any means suitable for detecting motion, a heat source (such as a person's body), and the like. Examples include passive infrared (PIR) sensors, microwave sensors, and the like. A purpose of the means for determining activity is to determine whether occupants are present in a building, or part of a building, being controlled by the thermostat system. The sensor may be present in a housing of the thermostat system, or it may be separate. In the latter case it may communicate with the thermostat system by a wire, or wireless, for example by WiFi or an IEEE 802.15.4 standard. In an embodiment the thermostat system comprises a plurality of activity sensors, for example located in different rooms of a building. The sensors may be integrated with devices such as smoke detectors, carbon monoxide detectors, leak detectors, video cameras, and the like.

[0027] The means for determining a temperature set point can be any means known in the art of room thermostats. Examples include variable resistors (potentiometers), variable capacitors, variable transistors, position sensors, and the like. In addition, the means may include an algorithm or pre-programmed schedule establishing a temperature set point based on such variables as the time of day, the day of the week, the presence or absence of occupants, and the like.

[0028] The heat demand is a measure for the amount of heating energy required from the HVAC system. The term "heat demand" encompasses cooling demand, which is mathematically a negative heat demand. The heat demand can have a value zero, meaning that no heating energy is required from the HVAC system. The heat demand can have a value 100%, which means that the HVAC system is required to operate at full heating (or cooling) capacity. Importantly, the heat demand can have a value between zero and 100%, for example 30%, 50%, 70%, 80%, etc.

[0029] The means for establishing a heat demand comprises an algorithm for computing present and predicted energy requirements. The algorithm computes the energy requirement based on any of a number of input parameters. An input parameter generally used in computing the energy requirement is the temperature set point, that is, the temperature desired for the building or part of the building at that time. Another input parameter generally taken into account is the ambient temperature. Yet other possible input parameters include the outside temperature, the presence or absence of occupants, the activity level of occupants, the relative humidity in the building, the weather forecast, and other input parameters relevant to the energy consumption of the HVAC system and the comfort of the building's occupants.

[0030] The means for communicating the heat demand to the HVAC system may be any means suitable for data communication within a building. Examples include wireless communication, such as WiFi or a radio protocol such as Zigbee. In a preferred embodiment the means for communicating the heat demand comprises communication wires.

[0031] In an embodiment the learning thermostat further comprises means for receiving information from the intelligent HVAC system. The information received from the intelligent HVAC system may be information pertaining to the operation of the intelligent HVAC system. Examples of such information include a fan speed; an air temperature; a water temperature; a water pressure; a maintenance reminder; a filter cleaning reminder; a malfunction alert; and the like.

[0032] The learning thermostat may comprise a display means for displaying information to a user or a maintenance or repair technician. The information being displayed may include data obtained from sensors associated with the thermostat, such as an ambient temperature, an ambient humidity, an outdoor temperature, an outdoor humidity, and the like. The information displayed may further include data pertaining to the operation of the thermostat, such as a program setting; a heat demand; an operation mode; and the like. The information displayed may further comprise information pertaining to the operation of the intelligent HVAC system, such as a fan speed; an air temperature; a water temperature; a water pressure; a maintenance reminder; a filter cleaning reminder; a malfunction alert; and the like.

[0033] In a preferred embodiment the thermostat presents the user or maintenance or repair technician with a menu for selecting the information to be displayed.

[0034] In an embodiment the learning thermostat comprises a means for connecting to the intelligent HVAC system via two, three or four wires, preferably two wires. In a four wire configuration a first wire may be for communicating data from the thermostat to the HVAC system. A second wire may be for communicating data from the HVAC system to the thermostat. A third wire and a fourth wire are for supplying power to the thermostat.

[0035] In a three wire configuration a first wire may be for both communication from the thermostat to the HVAC system and from the HVAC system to the thermostat. The second and third wires may be for supplying power to the thermostat.

[0036] In a two wire configuration the two wires may be for supplying power to the thermostat. One or both of the wires also serve to provide data communication between the thermostat and the HVAC system. Data communication from the thermostat to the HVAC system may use current signals, and data communication from the HVAC system to the thermostat may use voltage signals, or vice versa.

[0037] The learning thermostat system may use a coding standard for communication with the HVAC system, for example Manchester encoding. The bit rate may be 1000 bits per second, for example.

[0038] The HVAC system is generally connected to an external source of electrical power, for example grid power. This power serves to meet the power needs of electrical components within the HVAC system, such as a fan, a water pump, a resistance heater, a gas ignition system, a control system, a system memory, and the like.

[0039] In an embodiment the HVAC system provides power to the learning thermostat. Power may be provided to the thermostat using a power stealing protocol. Preferably the HVAC system continuously provides the thermostat with power, for example, 12 V DC power. In this embodiment the thermostat may not comprise a secondary power source, such as a capacitor or a rechargeable battery. The thermostat may comprise a back-up battery to provide power in case of a black-out, to protect data stored in memory from erasure.

[0040] In an embodiment the learning thermostat communicates wirelessly with the HVAC system. In this embodiment the learning thermostat may receive power from a battery, or the learning thermostat may be plugged into an external power source, such as the grid or a building energy system.

[0041] The intelligent HVAC system may comprise a boiler for providing hot water for central heating. The hot water is circulated through radiators and/or heating tubes embedded in floors and or walls for transporting heat to rooms of a building. In this embodiment the heat demand generated by the thermostat may comprise a desired temperature of the hot water for central heating. The boiler may provide hot water using electric power, or by burning a fossil fuel such as heating oil or natural gas.

[0042] For example, the HVAC system may have a set point for the maximum temperature of the hot water for central heating, for example 90 °C or 95 °C. The heat demand generated by the thermostat may specify a temperature of the hot water for central heating equal to this maximum set point, or it may specify a lower temperature, for example 50 °C. If the thermostat detects an ambient temperature that is much lower than the temperature set point for the room or building, and also detects a low outside temperature, the thermostat may generate a heat demand comprising a hot water temperature equal to the maximum set point of e.g. 90 °C or 95 °C. If the thermostat detects an ambient temperature that is only slightly lower than the room set point, and/or it detects a mild outdoor temperature, it may generate a heat demand comprising a hot water temperature lower than the maximum set point, for example 50 °C. A heat demand may initially comprise a temperature demand at or near the maximum, and be adjusted to lower temperature demands as the ambient temperature starts approaching the desired set point temperature.

[0043] As can be seen from this example, the thermostat modulates the operation of the HVAC system. It does not simply send an on or off signal to the HVAC system. It formulates a heat demand that tells the HVAC system to turn itself on and operate at less than 100% capacity. [0044] A learning thermostat may comprise an algorithm allowing it to anticipate future needs. For example, the thermostat may be at a night time set point of 15 °C. Its time program (which may itself have been created in a learning algorithm) may specify a day time temperature of 20 °C as of 7 am. The thermostat has learned that, given the outside temperature, the building will require 1 hour of heating at full capacity. The thermostat may send the HVAC system a heat demand for maximum heating at 6 am. Or the thermostat may start the preheating earlier, for example at 5:30 am, so that at least part of the heating cycle can be carried out at below maximum capacity. It has been found that the latter may save energy and wear and tear of the HVAC system.

[0045] The learning thermostat may take into account observed trends. For example, the learning thermostat may detect a certain outside temperature, and may further detect that the outside temperature is rising. This may cause the thermostat to generate a heat demand that calls for a lower temperature of the hot water than if the outside temperature had the same value but was constant or falling.

[0046] Modulation may not be limited to the temperature of the hot water. The thermostat may also modulate the rate of circulation of the hot water through the radiators, for example by modulating the speed of the circulation pump. In general, any component of the HVAC system that is involved in the generation and/or transmission of heat is a candidate for modulation.

[0047] It will be understood that the HVAC system itself may comprise algorithms for modulation. For example, a HVAC system receiving a heat demand comprising a hot water temperature of 50 °C may modulate its burner to a setting well below its maximum.

[0048] In a configuration in which both the thermostat and the HVAC system comprise intelligent control systems it is important to designate a master and a slave, so as to prevent conflicts. It has been found advantageous to assign master status to the thermostat, and slave status to the HVAC system.

[0049] The learning thermostat system may consist of one unit, which comprises the means for determining an ambient temperature; a means for determining an outside temperature; the means for detecting human presence in a building controlled by the thermostat system; the means for establishing a heat demand; and a means for communicating the heat demand to the intelligent HVAC system. The unit is typically installed in a room of which the temperature needs to be controlled. [0050] In an alternate embodiment the learning thermostat may comprise a first unit for installation in a room of a building, and a second unit installed near the HVAC system. In this configuration the first unit comprises the means for determining the ambient temperature and the means for detecting human presence in a building controlled by the thermostat system. The first unit also comprises any user interaction means, such as user controls and a display. The first unit is connected to the second unit via wireless communication means or via wires. The means for communicating the heat demand to the HVAC system is comprised in the second unit. The second unit is connected to the HVAC system via wireless communication means or via wires. The means for establishing a heat command may be comprised in the first unit or in the second unit.

[0051] Generally, in this configuration, any components that are bulky and/or generate heat, and that do not require to be present in the room of the building, can be put in the second unit, so that the first unit can be kept small and of elegant design, and its operation kept free of influences from self-generated heat.

[0052] The second unit may receive power from the HVAC system, or it may receive power from an external source, such as an electric grid. The first unit may receive power from the second unit.

[0053] In an alternate embodiment the system may comprise additional means for determining the ambient temperature and/or addition means for detecting human presence. Such additional means may be installed in other parts of the building than the location of the thermostat, so that ambient temperatures and/or human presence can be monitored across more than one room of the building.

[0054] Another aspect of the invention is a controlled system comprising a learning thermostat and an intelligent HVAC system connected via two, three or four wires. The learning thermostat controls the HVAC system in a master/slave configuration, the learning thermostat acting as master and the HVAC system as slave.

[0055] In the controlled system the learning thermostat may send messages to the intelligent HVAC system using current signals, and the HVAC system may send messages to the learning thermostat using voltage signals, or vice versa.

[0056] In an alternate embodiment the controlled system comprises a learning thermostat connected to a non-intelligent HVAC system, for example an HVAC system having analog controls. The learning thermostat is connected to the HVAC system via two, three or four wires. The thermostat controls the HVAC system using pulse width modulation.

DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS/EXAMPLES

[0057] The following is a description of certain embodiments of the invention, given by way of example only.

[0058] Figure 1 shows a controlled system 10, which comprises a learning thermostat system 11 and a HVAC system 12. Learning thermostat 11 communicates with HVAC system 12 via communication link 13. Communication link 13 may be a wireless communication link or a wired communication link. The embodiment shown in Figure 1 will be explained with reference to a wired communication link 13 consisting of two wires.

[0059] Learning thermostat system 11 may be installed in an existing installation replacing a prior art thermostat. When learning thermostat system 11 is first installed and activated it sends a signal to HVAC system 12 to check whether HVAC system is capable of receiving modulating commands from thermostat 11. If the HVAC system is capable of receiving modulating commands from thermostat system 11 it returns a confirmatory signal to thermostat system 11.

[0060] If thermostat system 11 does not receive a confirmatory signal from HVAC system 12, it concludes that HVAC system 12 is not intelligent. It will then

communicate with HVAC system in analog mode, for example using pulse width modulation.

[0061] If thermostat system 11 receives a standard compliant confirmatory signal from HVAC system 12, it concludes that HVAC system 12 is intelligent. It will communicate with HVAC system in digital mode. Depending on the selected standard, thermostat system 11 may send its messages to HVAC system 12 using voltage signals; HVAC system 12 may send its messages to thermostat system 11 using current signals. In addition VAC system 12 may use communication link 13 to supply electric power to learning thermostat system 11. Electric power supplied to learning thermostat 11 may be low voltage, for example 12 Volts, DC power.

[0062] Learning thermostat system 11 further comprises a means for determining an ambient temperature; a means for determining an outside temperature; and a means for detecting human presence in a building controlled by the thermostat system; schematically depicted by communication links 14, 15 and 16. It will be understood that one or more of these means may be integrated in one unit.

[0063] Learning thermostat system 11 determines a temperature set point, for example by receiving an external instruction from a user, who may communicate with learning thermostat system 11 using controls 17, or wirelessly via a WiFi system, for example. The learning thermostat system 11 may also use a program schedule in determining the temperature set point. The program schedule may be factory installed, provided by a user, or may be based on an algorithm using stochastic input data such as provided by the means for detecting human presence in a building controlled by the thermostat system. Learning thermostat system 11 may decide to ignore the program schedule, for example if it determines that there is no human presence in the building.

[0064] Learning thermostat system 11 determines a heat demand based on the determined temperature set point. In converting the determined temperature set point to a heat demand it takes into account one or more parameter inputs, such as the ambient temperature, the absence or presence of humans in the building, the outside

temperature, etc. The heat demand may take the form of, for example, a desired temperature of hot water for radiant heat to be generated by HVAC system 12, and/or a desired pump speed for the pump circulating the hot water. In an alternate embodiment the heat demand may take the form of a relative modulation level, which instructs HVAC system to operate at a specified percentage of full capacity.

[0065] Controlled system 10 may collect and store a variety of data relevant to its operation. For example, HVAC system 12 may comprise a central heating (CH) hot water system; a domestic hot water (DHW) system; a solar storage and solar collector system, etc. HVAC system may monitor and store data for the CH water pressure, the CH water temperature, the return water temperature, the solar collector temperature, the solar storage temperature, the DHW temperature, the number of burner starts, the burner operating hours, the exhaust temperature, the number of CH pump starts, the CH pump operating hours, and the like.

[0066] The learning thermostat system 11 may monitor and store data such as the calendar date, the time, the day of the week, the temperature set point, the ambient temperature, the outside temperature, the time-to-temperature, a pattern of human presence and absence, and the like. [0067] In general, learning thermostat 11 may obtain data stored by HVAC system 12, so that it may display such data and/or incorporate these data into its algorithms. For example, learning thermostat 11 may calculate an energy usage of HVAC system 12 based on burner operating hours and relative modulation levels. Learning thermostat 11 may use these data to improve energy efficiency, for example by adjusting its heat demands to avoid an excessively high number of burner starts.

[0068] Figure 2 shows a controlled system 20 comprising a learning thermostat unit 21, a HVAC system 22, and an interface 24. Learning thermostat unit 21 communicates with interface 24 via communication link 26; HVAC system 22 communicates with interface 24 via communication link 25. Interface 24 may comprise functionalities that can be considered to belong to the learning thermostat system of the invention. For example, interface 24 may be connected to a means for determining an outdoor temperature via communications link 27, and to a means for detecting human presence in a building controlled by the thermostat system via communications link 28. Learning thermostat unit 21 may be connected to a means for determining an ambient temperature via communications link 29. Whether interface 24 contains learning thermostat functionalities, and if so, which ones, is not essential to the operation of this embodiment of the invention, and may be selected based on practical convenience.

[0069] Thermostat unit 21 may communicate with interface 24 as a virtual HVAC system; HVAC system 22 may communicate with interface 24 as a virtual thermostat system.

[0070] Thus, the invention has been described by reference to certain embodiments discussed above. It will be recognized that these embodiments are susceptible to various modifications and alternative forms well known to those of skill in the art.

[0071] Many modifications in addition to those described above may be made to the structures and techniques described herein without departing from the spirit and scope of the invention. Accordingly, although specific embodiments have been described, these are examples only and are not limiting upon the scope of the invention.

Claims

WHAT IS CLAIMED IS:

A learning thermostat system for controlling an intelligent HVAC system, said thermostat system comprising:

a) means for determining an ambient temperature;

b) means for determining an outside temperature;

c) means for detecting human presence in a building controlled by the

thermostat system;

d) means for determining a temperature set point;

e) means for establishing a heat demand based on input relating to the

temperature set point and at least one of (i) the ambient temperature; (ii) the outside temperature; (iii) detected presence in the building controlled by the thermostat system;

f) means for communicating the heat demand to the intelligent HVAC system.

The learning thermostat system of claim 1 further comprising a means for receiving information from the intelligent HVAC system pertaining to the operation of the intelligent HVAC system. 3. The learning thermostat system of claim 1 or 2 wherein the means for

communicating the heat demand to the intelligent HVAC system comprises a wireless communication means.

4. The learning thermostat system of one of the preceding claims further comprising means for connecting to the intelligent HVAC system via two, three or four wires.

5. The learning thermostat system of claim 4 comprising means for connecting to the intelligent HVAC system via two wires.

6. The learning thermostat system of claim 4 or 5 wherein the learning thermostat system receives power from the intelligent HVAC system via two wires. The learning thermostat system of claim 4, 5 or 6 wherein the thermostat system is capable of sending messages to the intelligent HVAC system using current signals.

The learning thermostat system of claim 4, 5, 6 or 7 wherein the thermostat system is capable of receiving messages from the intelligent HVAC system using voltage signals.

The learning thermostat system of any one of the preceding claims wherein the intelligent HVAC system comprises a boiler providing hot water for central heating.

The learning thermostat system of claim 9 wherein the heat demand comprises a desired temperature of the hot water for central heating.

The learning thermostat system of any one of the preceding claims consisting one unit.

The learning thermostat system of any one of claims 1-10 comprising a first unit for installation in a room of a building intended for human occupancy, and a second unit installed near the HVAC system.

A controlled system comprising the learning thermostat of one of claims 1-12 connected to an intelligent HVAC system, wherein the learning thermostat system controls the intelligent HVAC system in a master/slave configuration, the learning thermostat system serving as master and the intelligent HVAC system serving as slave.

The controlled system of claim 13 wherein the learning thermostat system sends messages to the intelligent HVAC system using current signals and the intelligent HVAC system sends messages to the intelligent thermostat system using voltage signals.

15. A controlled system comprising a learning thermostat system of one of claims 1- 12 connected to a non-intelligent HVAC system via two, three or four wires, wherein the learning thermostat controls the non-intelligent HVAC system using pulse width modulation.