TECHNICAL FIELD
[0001] The disclosed technology relates to heat pump water systems for use in production
of hot water and/or heating systems, and in particular to control of such a heat pump
water heating system to operate on a schedule to optimize energy costs based on dynamic
energy tariff information.
BACKGROUND
[0002] Water heating systems are means of producing hot water for heating applications,
in particular central heating with, e.g., radiators, underfloor heating or other heating
means, water heating systems may alternatively or additionally be used in the production
of domestic and/or sanitary hot water, also referred to as tap water. It will be understood
that while much of the discussion here will center on heat pump water heaters that
are used for the production of domestic hot water (DHW), similar systems may be used
for other heating and/or cooling applications, and the discussion of heat pump water
heaters is intended merely to
illustrate the technology. Similar systems and methods may be applied to a wide range of applications
in which water or other liquids are heated and/or cooled for use in a wide range of
heating and/or cooling applications.
[0003] A heat pump water heater is a water heater with at least one heat pump as a water
heating element. A heat pump water heater may have other associated heating means
such as an electric resistive element or heat exchangers associated with a hot water
circuit or, more generally, with other suitable refrigerant fluids. Supplementary
heating, such as a gas-powered boiler, pellet boiler, thermal solar panel, and/or
other heating systems may also be used.
[0004] Heat pump water heaters need an available energy/heat source to transfer heat to
the water to be heated. Different sources can be used. The type of source can be used
to differentiate and designate different types of heat pump water heaters. For example,
ambient air heat pump water heaters use ambient air as an energy source. Ambient air
entering and leaving the heat pump is drawn in and returned to the volume of air available
at the installation site. The place of installation is often an unheated, frost-free
room such as a utility room in a building (e.g., a cellar, garage, attic, etc.), though
controlled temperature rooms may also be used. Ambient air heat pumps provide a simplified
product compared to other heat pump types. This is because, e.g., the ambient air
used has a limited and positive temperature range. In addition, the pressure losses
in the air flow are low as the air is pulled in and discharged in the same space as
the product location.
[0005] Ducted air heat pump water heaters use outside air as an energy source - i.e., air
that is drawn in and/or discharged from and/or to the outside. This type of heat pump
water heater offers greater flexibility in installation modes and allows the user
to choose a configuration that provides for comfort throughout the year. For example,
it is possible to choose to discharge the air from the heat pump to the outside when
the outside temperature is below the comfort temperature of the room. Alternatively,
one can choose to recirculate the air from the heat pump at the installation site
when this provides comfort. This type of heat pump water heater may be susceptible
to significant pressure drops due to lengths, bends, and height differences in the
ducts. A heat pump system could also be split, with an outside portion (e.g., an outdoor
unit (ODU) with a mono-block or split-block heat pump) and an indoor portion (e.g.,
an indoor unit (IDU) with the tank or heating/cooling circuit).
[0006] Extracted air heat pump water heaters use air extracted from a ventilation network
of the installation building as an energy source. This air has a relatively constant
and high temperature, as it comes from living areas of a dwelling. In general, this
air may be particularly humid and can contain significant levels of dust or other
debris, because it may come from damp rooms, such as bathrooms or kitchens. Heat pumps
using this type of air must be able to operate with a relatively low air flow rate
(that of the building's ventilation system). A fan may be included in the heat pump
water heater. Alternatively, the fan of the ventilation system of the installation
building may be used, removing the need for a fan in the heat pump water heater.
[0007] Water or ground source heat pump water heaters use an open (e.g., for underground
water pumping) or closed (e.g., for soil) water circuit as an energy source. The water
circuit may be the return of a heating circuit, a geothermal circuit or any other
closed or open water circuit.
[0008] For all above-mentioned heat pump water heater types, the heat pump includes at least
one closed refrigerant circuit. The refrigerant circuit includes a first heat exchanger
with the source medium (an evaporator), a compressor, a second heat exchanger with
the destination medium (a condenser), in particular water or other liquids (e.g.,
for use in heating and/or cooling applications, and/or domestic hot water), and an
expansion device.
[0009] Control of heat pump water heating and/or cooling systems can present a number of
challenges. Because it can take some time to heat or cool water using a heat pump,
it may be difficult to ensure that there is sufficient hot or cool water to meet demands.
For example, when the demand for hot water becomes greater than can be readily supplied,
systems may fall back on other heat sources, such as electric resistive heating or
a backup gas boiler. While these sources may be faster at producing hot water than
a heat pump, they may be less energy efficient and/or more expensive or environmentally
harmful to operate.
[0010] Environmental conditions can also cause control challenges. For example, heat pump
water heating systems may be more efficient when the source medium (e.g., outside
air, ambient air) is warm than when it is cold. In systems that use outside air, the
heat pump may not be able to operate when the outside air temperature is too cold.
As with meeting demands for hot and/or cool water, the energy efficiency of heat pumps
will vary with environmental conditions, and the use of other heat sources, such as
electric resistive heating or a backup gas boiler may make sense, depending on environmental
conditions.
[0011] Additionally, users of such heating systems may wish to reduce or control their energy
costs. Energy costs may vary over time, with prices or price forecasts being available
ahead of the time that the energy is used. Thus, the times at which the heat pump
is operated may affect the cost of providing hot water to meet demands, as may the
timing of the demands, and the ability to efficiently store heated water for later
use.
[0012] Control systems for heat pump water heating systems, therefore, may take into account
environmental conditions (e.g., outdoor temperatures, solar production forecasts,
etc.), anticipated hot water demand, energy consumption, defrost cycles, dynamic energy
prices and other factors to deliver a desired level of comfort and a reasonable level
of energy usage and cost.
[0013] While some of these factors, such as forecasted environmental conditions and dynamic
energy prices, may be available, e.g., over the Internet from external sources, other
factors, such as anticipated hot water demand, may vary with each individual user
or household. Typically, anticipated hot water demand is determined on past usage
patterns, which are typically measures using sensors that measure usage of hot water.
Such sensors may be costly to purchase and install, may add significantly to the cost
of a hot water system and/or may not always function correctly so that false sensor
results or no sensor results are given. Additionally, in many existing systems, such
usage sensors are not present and cannot be easily installed or added to the system.
Controllers for such legacy systems, while possibly upgradable to improve the energy
efficiency of the system, will not have access sensor-based measurements of hot water
usage that would provide the data that is typically used to determine the anticipated
hot water demand.
SUMMARY
[0014] Based on the above, it is an object to provide a controller for a hot water system,
particularly a hot water system using a heat pump as a primary heat source, that is
able to optimize energy costs using information such as forecasted environmental conditions,
forecasted energy tariffs, and anticipated hot water demand. Because these factors
may vary over time, it is a further object for the controller to generate a schedule
for operating a heat pump water heating system that optimizes energy costs based on
this information, and to operate the heat pump water heater according to the schedule.
[0015] It is a further object to provide a controller that is able to optimize energy costs
using measures of anticipated hot water demand that do not require additional sensors
to measure hot water usage. It is, therefore, an object to use sensors and measurements
available in existing heat pump water heating systems, without relying on sensors
that measure actual usage of hot water to estimate hot water demand.
[0016] For example, a heat pump may have access to information such as temperature and flow
volume of water entering the heat pump, and temperature and flow volume of water leaving
the heat pump, as well as the temperature of water in the storage tank. These are
measurements relevant to the production of hot water and control of the heat pump,
but generally do not directly indicate hot water usage. In most systems, hot water
from the heat pump will either be delivered to a storage tank or buffer, or will be
used in a heat exchanger to heat water in a tank or buffer. Direct measurements of
hot water usage would depend on measurements of water (e.g., temperature and flow
volume) taken from such a tank or buffer, rather than measurements of heat production
by the heat pump or the temperature of the water in the tank. It is an object to avoid
adding sensors to the system to directly measure usage, and to instead use other measurements,
such as heat production, to estimate hot water usage or demand. By avoiding such additional
sensors, the cost of a hot water system may be reduced, and advanced control systems,
that are able to optimize energy costs, may be used with existing or legacy hot water
systems that do not include sensors that directly measure hot water usage.
[0017] It should be understood that implementations of the present technology each have
at least one of the above-mentioned objects and/or aspects, but do not necessarily
have all of them. Some aspects of the present technology that have resulted from attempting
to attain the above-mentioned objects may not satisfy these objects and/or may satisfy
other objects not specifically recited herein.
[0018] It should also be understood that, as used herein, the term "hot water system" may
provide hot and/or cool water or other liquids for a variety of applications. For
example, a hot water system may provide domestic hot water, hot water for heating
applications, such as room heating, and/or cool water for cooling applications, such
as room cooling.
[0019] It will be understood that as used herein, "optimize" means only that the system
attempts to improve (e.g., reduce) energy costs. There may be instances in which the
system is able to improve the costs, but still lower costs would be possible, or cases
in which no improvement or reduction actually occurs. It will further be appreciated
that an energy "tariff" refers to the amount charged, e.g., by a producer or distributor
of energy for a unit of energy at a particular time, while energy "cost" refers to
the amount paid by a consumer of energy for the consumer's total usage over a period
of time.
[0020] In some implementations, the disclosed technology provides a method of controlling
at least a hot water system, the hot water system including a heat pump and a hot
water tank. The method includes estimating, by a controller, a hot water usage over
a past time period based at least in part on the heat production of the heat pump
during the past time period, without relying on data from a sensor measuring actual
usage of hot water or hot water taken from the hot water tank. The method further
includes estimating, by the controller, hot water usage over a future time period
based at least in part on the estimated hot water usage over the past time period.
The method further includes accessing, by the controller, energy tariff data for at
least a portion of the future time period, and generating, by the controller, a schedule
for operating the heat pump to optimize energy costs based at least in part on the
estimated hot water usage over the future time period and the energy tariff data for
the future time period. The method further includes operating, using the controller,
the hot water system according to the schedule.
[0021] In some implementations, the method further includes estimating, by the controller
a heat demand over the future time period. Estimating, by the controller, hot water
usage over a future time period includes using the estimated heat demand over the
future time period as a proxy for the hot water usage. Advantageously, Heat demand
can be estimated using information on the production of hot water, and does not require
information from a sensor measuring actual usage of hot water or hot water taken from
the hot water tank.
[0022] In some implementations, generating a schedule for operating the heat pump includes
dividing the estimated heat demand over the future time period into an estimated heat
demand for at least two time slots within the future time period. In some implementations,
this may include generating a heat production target for each of numerous time slots
within the future time period. Dividing the estimated heat demand into two or more
time slots facilitates optimizing for a schedule that includes multiple periods of
increased usage or demand, such as a high hot water demand during a time period in
the morning and during a second time period in the evening. Additionally, energy tariff
data may be available for multiple time slots during the future time period, and these
changing tariffs can be taken into account by dividing the future time period into
two or more time slots.
[0023] In some implementations, operating the hot water system according to the schedule
includes using hysteresis control based on a temperature of hot water in the hot water
tank. This is achieved by, for each time slot in the future time period: transforming
the heat production target for the time slot into a temperature setpoint for the hot
water tank, and, in relation to the time slot, setting the hot water tank temperature
setpoint based on the transformed heat production target for the time slot; setting,
at the start of the time slot, a hot water tank hysteresis value to a value low enough
to cause the heat pump to start operating to heat the water in the hot water tank
to the hot water tank temperature setpoint; and setting, at the end of the time slot,
the hot water tank temperature setpoint and the hysteresis value to values sufficient
to stop the heat pump from further heating the water in the hot water tank, and to
prevent heating from starting again except according to the schedule. This provides
a way to use common hysteresis control of a heat pump based on the water temperature
in the hot water tank to more precisely control the heat production of the heat pump
in accordance with the schedule. For example, the temperature setpoint and hysteresis
values can be adjusted such that the heat pump is running during time slots in the
schedule when energy tariffs are low, and is generally not running during time slots
when energy tariffs are high.
[0024] In some implementations, the future time period is a 24 hour period that is divided
into a predetermined number of time slots based on a number of time slots in the energy
tariff data for the future time period. In many areas, future energy tariffs are available
for a 24-hour period, and may vary over that time period, e.g., hourly. When future
energy tariff information is available with, e.g., greater granularity than hourly,
it may be advantageous to optimize for time slots that conform to the granularity
of the future energy tariff information.
[0025] In some implementations, the heat pump uses outside air, and the method further includes:
accessing, by the controller, air temperature predictions for the future time period;
estimating, by the controller, a coefficient of performance (COP) of the heat pump
over the future time period based at least in part on the outdoor air temperature
predictions and on performance characteristics of the heat pump; and generating the
schedule based at least in part on the estimated COP. In some of these implementations,
accessing the air temperature predictions comprises accessing weather forecast data
from a cloud-based weather service, the weather forecast data including the air temperature
predictions or data from which the air temperature predictions can be derived. In
systems with heat pumps that use outside air, the efficiency (i.e., COP) of the heat
pump depends on the temperature of the outside air. To accurately predict the energy
usage of such a heat pump (and the cost of running the heat pump), predictions of
the outside air temperature are needed. These predictions, or data on which temperature
predictions may be derived, may be available through weather forecasting services,
such as cloud-based services, or may be obtained through other sources, such as past
outdoor temperature data or models based on past outdoor temperature data.
[0026] In some implementations, the hot water system includes photovoltaic energy generation,
and the method further includes: accessing, by the controller, solar irradiance predictions
for the future time period; using, by the controller, the solar irradiance predictions
to predict an amount of photovoltaic energy available for use by the hot water system
over the future time period; and generating the schedule based at least in part on
the predicted amount of photovoltaic energy available. For systems that include solar/photovoltaic
energy generation, some or all of the available photovoltaic energy may be used to
operate the heat pump, reducing the need to buy energy for running the heat pump from
the grid. To accurately predict the cost of running the heat pump in such a system,
an estimate of the amount of photovoltaic energy that will be available may be used.
The estimated amount of photovoltaic energy that will be available in the future depends
on solar irradiance predictions for the location where solar/photovoltaic panels are
installed.
[0027] In some implementations, the heat production of the heat pump during the past time
period is determined based at least in part on the measured temperature and flow volume
of liquid into the heat pump and on the measured temperature and flow volume of liquid
out of the heat pump. This is information that is often available for heat pumps,
without requiring additional sensors. The input and output temperature and flow volume
information from the heat pump relate generally to the heat production of the heat
pump, and not to the actual hot water usage.
[0028] In some implementations, the heat production of the heat pump during the past time
period is determined based at least in part on the energy usage of the heat pump over
the past period of time. This information may be available on the heat pump or e.g.,
on a smart meter, without requiring additional sensors. The energy usage of the heat
pump relates generally to the heat production of the heat pump, and not to the actual
hot water usage.
[0029] In some implementations, generating a schedule for operating the heat pump to optimize
energy costs includes using an optimization algorithm with an objective function based
at least on estimated energy usage and the energy tariff data to optimize energy costs.
Many such optimization algorithms are known, and may be used to optimize the schedule
based on estimated future energy usage and future energy tariff information.
[0030] In some implementations, the disclosed technology further provides a controller configured
to operate at least a hot water system, the hot water system including a heat pump
and a hot water tank, the controller being arranged to carry out the method described
above.
[0031] In some implementations, the disclosed technology further provides a hot water system,
including a heat pump and a hot water tank. The hot water system further includes
a controller as described above.
[0032] In some implementations, the disclosed technology further provides a computer-readable
medium, such as a transient or non-transient computer-readable medium. A transient
computer-readable medium may be, e.g., a signal transmitted over a wired or wireless
communication medium, such as a bus or network. A non-transient computer-readable
medium may be, e.g., a computer-readable storage medium, such as a memory device,
an optical storage medium, or a magnetic storage medium. The computer-readable medium
carries instructions for operating a hot water system to carry out the method discussed
above.
[0033] In the context of the present specification, unless expressly provided otherwise,
the words "first", "second", "third", etc. have been used as adjectives only for the
purpose of allowing for distinction between the nouns that they modify from one another,
and not for the purpose of describing any particular relationship between those nouns.
[0034] In the context of the present specification, unless expressly provided otherwise,
directions indicated by terms such as "top", "bottom", "upper", "lower", "above",
"below", etc., are used in their usual sense - i.e., relative to a gravitational direction
or axis.
[0035] Additional and/or alternative features, aspects and advantages of implementations
of the present technology will become apparent from the following description, the
accompanying drawings and the appended claims.
BRIEF DESCRIPTION OF THE DRAWINGS
[0036] In the figures, the subject-matter of the disclosure is schematically shown, wherein
identical or similarly acting elements are usually provided with the same reference
signs.
FIG. 1 is a block diagram of an example controller that could be used in some implementations
of a hot water system.
FIG. 2 is a block diagram of an example hot water system.
FIG. 3 is a block diagram illustrating a method for generating a schedule for operating
a heat pump-based hot water system to optimize energy costs.
FIG. 4 shows an objective function and constraints that may be used for optimization
of cost, in accordance with the described technology.
DETAILED DESCRIPTION
[0037] The examples and conditional language recited herein are principally intended to
aid the reader in understanding the principles of the present technology and not to
limit its scope to such specifically recited examples and conditions. It will be appreciated
that those skilled in the art may devise various arrangements that, although not explicitly
described or shown herein, nonetheless embody the principles of the present technology.
[0038] Furthermore, as an aid to understanding, the following description may describe relatively
simplified implementations of the present technology. As persons skilled in the art
would understand, various implementations of the present technology may be of a greater
complexity.
[0039] In some cases, what are believed to be helpful examples of modifications to the present
technology may also be set forth. This is done merely as an aid to understanding,
and, again, not to define the scope or set forth the bounds of the present technology.
These modifications are not an exhaustive list, and a person skilled in the art may
make other modifications while nonetheless remaining within the scope of the present
technology. Further, where no examples of modifications have been set forth, it should
not be interpreted that no modifications are possible and/or that what is described
is the sole manner of implementing that element of the present technology.
[0040] Moreover, all statements herein reciting principles, aspects, and implementations
of the present technology, as well as specific examples thereof, are intended to encompass
both structural and functional equivalents thereof, whether they are currently known
or developed in the future. Thus, for example, it will be appreciated by those skilled
in the art that any block diagrams herein represent conceptual views of illustrative
systems embodying the principles of the present technology.
[0041] With these fundamentals in place, we will now consider some non-limiting examples
to illustrate various implementations of aspects of the present disclosure.
Controller
[0042] FIG. 1 depicts an example controller 100, which may be any type of computer system
or embedded controller. It will be recognized that some or all the components of the
controller 100 may be virtualized and/or cloud-based. As depicted, the controller
100 may include one or more processors 102, a memory 110, a storage interface 120,
and a communication interface 140. These system components may be interconnected via
a bus 150, which may include one or more internal and/or external buses (not shown)
(e.g. a PCI bus, universal serial bus, IEEE 1394 "Firewire" bus, SCSI bus, Serial-ATA
bus, etc.), to which these various hardware components may be electronically coupled.
[0043] The memory 110, which may be a random-access memory or any other type of memory,
may contain data 112, an optional operating system 114 (it will be understood that
not all controllers require an operating system), and a program 116. The data 112
may be any data that serves as input to or output from any program in the controller
100. The operating system 114, which is optional, since not all control applications
require use of an operating system, may be an operating system such as MICROSOFT WINDOWS,
FreeRTOS, an operating system based on the LINUX kernel (e.g., UBUNTU, DEBIAN, FEDORA,
ARCH, SUSE, etc.), or any other operating system suitable for use on a computer system
or microcontroller. The program 116 may be any program or set of programs that include
program instructions that may be executed by the processor to control actions taken
by the controller 100. In particular, the program 116 may include program instructions
that, when executed by the processor, cause the processor to carry out one or more
of the methods described below.
[0044] The storage interface 120 may be used to connect storage devices, such as the depicted
storage device 125, to the controller 100. The storage device 125 may be a solid-state
drive using an integrated circuit assembly to store data persistently. Alternatively,
the storage device 125 may be a hard drive using any of a variety of types of magnetic
storage media to store and retrieve digital data. As another alternative, the storage
device 125 may be an optical drive, or a card reader that receives a removable non-volatile
semiconductor memory card. As still another alternative, the storage interface 120
may provide a universal serial bus connection to which the storage device 125 may
be hot-pluggable, and the storage device 125 may be a flash memory device (e.g., a
USB thumb drive). In some implementations, in which storage of data is not necessary,
the storage interface 120 and storage device 125 may optionally be omitted.
[0045] In some implementations, the controller 100 may use well-known virtual memory addressing
techniques that allow the programs of the controller 100 to behave as if they have
access to a large, contiguous address space instead of access to multiple, smaller
storage spaces, such as the memory 110 and the storage device 125. Therefore, while
the data 112, the optional operating system 114, and the programs 116 are depicted
as residing in the memory 110, those skilled in the art will recognize that these
items may not necessarily be wholly contained in the memory 110 at the same time.
[0046] The one or more processors 102 may include one or more microprocessors and/or other
integrated circuits able to execute program instructions stored in the memory 110.
When the controller 100 starts up, the processor(s) 102 may initially execute program
instructions of a boot routine and/or the program instructions that make up the operating
system 114.
[0047] The communication interface 140 may be used to communicatively connect the controller
100 to other controllers, computer systems, or still other devices (not shown) via
a communication channel 160. The communication channel 160 may be a serial or parallel
connection, a wired, wireless, mesh or cellular network, or any other type of communication
channel or combination of channels. Data and/or program instructions may be sent to
the controller 100 as signals via the communication channel. The communication interface
140 may include a combination of hardware and software that enables communications
on the communication channel 160. The software in the communication interface 140
may include software that uses one or more communication protocols to communicate
over the communication channel 160, including and not limited to, network protocols
such as TCP/IP (Transmission Control Protocol/Internet Protocol) or Modbus.
[0048] It will be understood that the depicted controller 100 is merely an example, and
that the technology disclosed herein may be used with a wide variety of other controllers
or computer systems, or still other computing devices having different configurations.
Hot Water System
[0049] FIG. 2 depicts an example hot water system 200. The hot water system 200 is generally
used to provide domestic hot water to a domestic hot water installation, such as is
used in a residential dwelling, but may be used in other heating and/or cooling applications,
such as room heating or room cooling. However, it will be understood that the hot
water system 200 may be used in other types of buildings, such as apartment buildings
or other multi-dwelling buildings, office buildings, or any other type of building
at which hot water systems are installed and/or controlled. It will also be understood
that although referred to as a "hot water system", the hot water system 200 may also
be used in cooling applications, in which the water is cooled, e.g., for use in room
cooling.
[0050] As depicted, the hot water system 200 is a heat pump-based system with an optional
electric resistive heating element providing backup heating. The system includes a
heat pump 202 (the construction and operation of such a heat pump being well-known)
and a hot water tank 204, which supplies hot water to a domestic hot water output
220, which may include (for example) hot water taps (not shown), showers (not shown),
and other outlets or appliances that consume domestic hot water (not shown). The domestic
hot water output 220 may mix the hot water from the hot water tank 204 with cold water
to produce a range of water temperatures for domestic use.
[0051] A heat exchanger 206 in the hot water tank 204 transfers heat from primary water
(or other heating fluids, such as a water-glycol mixture) warmed by the heat pump
202 to the sanitary domestic hot water in the hot water tank 204. An electric resistive
heating element 208 may optionally be included in the primary water lines from the
heat pump 202 to the hot water tank 204 (as shown) or may be included directly in
the hot water tank 204 to serve as backup heating, during periods in which the heat
pump 202 may be unable to provide sufficient heating to meet the demand for domestic
hot water. Other backup systems, such as electric, oil, hydrogen, wood, and/or gas-powered
boilers, solar thermal systems, additional heat pumps, and/or other known heating
systems may optionally be used in addition to the heat pump 202 to heat the primary
water (or other heating fluids) that heat the domestic hot water in the hot water
tank 204. These additional heat sources may be referred to herein as hydraulic heat
sources or hydraulic backup heat sources.
[0052] A controller 210, which may be similar to the example controller 100, described above,
controls the heat pump 202, the optional electric resistive heating element 208, any
optional hydraulic heat sources (not shown), and/or other devices and actuators that
control the flow and mixing of domestic hot water through the hot water system 200.
The controller 210 may be connected to various sensors (not shown) that provide information
on, e.g., temperatures and flow volumes of the primary water circulating in the heat
pump 202, a water temperature in the hot water tank 204, ambient air temperature,
and other measurements that may be used (as described below) to control the hot water
system 200. The controller 210 may also be connected to a cloud-based system 250,
which may provide access to databases, updates, commands from users, remote commands
or information, external services, cloud-based storage, or other information sources
and services that may be accessed, e.g., over the Internet. For example, the cloud-based
system 250 may be used by the controller 210 to access weather predictions and tariff
information that may be used by the controller 210. In some implementations, most
of the control of the hot water system 200 may be carried out in the cloud-based system
250, with the controller 210 serving primarily to communicate commands to the hot
water system 200, and as a backup controller if there are communication problems that
prevent communications between the cloud-based system 250 and the controller 210.
[0053] The controller 210 may communicate with various system components in a variety of
ways. For example, the controller 210 may communicate wirelessly with sensors, actuators,
hydraulic heat sources, and/or other system components using a wireless communication
protocol, such as WIFI, Bluetooth, or Zigbee. In some implementations, they may communicate
over a wired bus, using protocols such as OpenTherm. Some devices, such as sensors,
may be directly connected to the controller 210. For some devices, including older
boilers, etc., the controller 210 may be limited to controlling the device using on/off
signals. In some implementations, the controller 210 may use numerous types of communication,
depending on the devices that are being controlled.
[0054] In some implementations, the heat pump 202 may be built within a single housing (not
shown) that also houses the hot water tank 204, the controller 210, and the optional
electric resistive heating element 208, to provide a self-contained water heating
appliance. In some implementations, such a self-contained water heating appliance
may also include an optional backup hydraulic heat source, such as a boiler within
the single housing or as an attachment to the housing. In some implementations, the
heat pump 202 may more directly heat the domestic hot water in the hot water tank
204, without use of primary water or the heat exchanger 206 (e.g., the water in the
hot water tank 204 is heated through heat exchange with the refrigerant circuit of
the heat pump 202).
[0055] It will be understood that although the example hot water system 200 shown in FIG.
2 is configured to provide domestic hot water, other configurations could be used
to provide hot water for heating and/or cooling applications (e.g., through radiators,
underfloor or ceiling heating or cooling loops, etc.). Such systems may include, e.g.,
various load circuits and pumps, to provide hot or cool water to heating or cooling
zones in a house. Other hot water systems 200 may provide hot water for both heating/cooling
and domestic hot water uses. Such systems may include load circuits that include domestic
heating, such as through radiators, and at least one load circuit that includes a
hot water tank for domestic hot water, such as is shown in FIG. 2. While the technology
is discussed primarily in terms of control for providing domestic hot water, it will
be understood that similar optimization techniques could be used in domestic heating
systems, and/or in systems that provide both domestic heating/cooling and domestic
hot water.
Control
[0056] The hot water system 200 may be controlled by the controller 210 and/or a cloud-based
control system to provide enough hot water at the right times to provide adequate
comfort for users of the system, while reducing energy costs to provide that hot water.
In some implementations, the controller 210 and/or a cloud-based control system will
base this control on time-dependent information, such as anticipated hot water usage
at various times of days, electricity tariffs at various times of the day, and weather
conditions, such as outdoor temperatures at various times of the day. Due to the time
dependence of these factors that affect the operation and cost of operating the hot
water system 200, in some implementations, the controller 210 and/or a cloud-based
control system may generate a schedule for operating the hot water system 200 that
attempts to optimize costs while maintaining comfort. Once such a schedule is generated,
it may be used to operate the hot water system 200.
[0057] FIG. 3 shows a block diagram of a method 300 for generating a schedule for operating
a heat pump-based hot water system, such as the hot water system 200, to optimize
energy costs while providing enough hot water to meet estimated user demands. This
is done without relying on data from sensors measuring actual usage of hot water (i.e.,
usage by a human consumer or central heating system - not usage/intake by the hot
water tank 204) or hot water taken from or in the tank (e.g., the hot water tank 204).
The method described with reference to FIG. 3 may be operated as a program on the
controller 210 shown in FIG. 2, may be operated on the cloud-based system 250, may
be operated on separate controllers, which may be hardware-based, virtual, or cloud-based
(not shown in FIG. 2), or may be distributed between any combination of these.
[0058] In block 302, the controller estimates the hot water usage over a past time period
based (HWU_PTP) at least in part on the heat production of the heat pump 202 (HP)
during a past time period (HP_HEAT_PROD_PTP). This is done without relying on data
from sensors measuring actual usage of hot water or hot water taken from the hot water
tank 204 or hot water in the hot water tank 204.
[0059] This may be achieved in some implementations by assessing the heat produced by the
heat pump 202 over the past time period, such as the previous two-week period. The
heat production may be determined based on sensors that are associated with the heat
pump 202, such as the flow volume and temperature of water or other fluids entering
the heat pump, and the flow volume and temperature of water or other fluids that have
been heated by the heat pump 202. By knowing the volume of water or other fluids,
and the temperature increase, the heat produced by the heat pump 202 may be determined.
It should be clear that the flow volumes and temperatures of water or other fluids
entering the heat pump and leaving the heat pump are information related to production
of heat by the heat pump, and are not measures of actual usage of hot water.
[0060] Alternatively, the electricity usage of the heat pump 202 may be measured (e.g.,
by a smart meter). This electricity usage, combined with information on environmental
temperatures (to determine the coefficient of performance (COP) of the heat pump),
may be used to determine the amount of heat produced by the heat pump 202. Again,
this is a measure of energy usage - not a measure of actual hot water usage.
[0061] The heat production of the heat pump 202, while it does not provide a precise measurement
of hot water usage, does provide information on the amount of energy that was delivered
to the hot water tank 204 to provide adequate comfort to the user. In accordance with
some implementations, this may be used as a proxy for estimating hot water usage.
[0062] In block 304, the estimated past hot water usage (EST_HW_USE_PTP) is used to estimate
the expected hot water usage over a future time period (EST_HW_USE_FTP), such as the
following day. In some implementations, this may involve removing outliers from the
heat production measurements that were discussed above, such as by removing any daily
heat production above the 95
th percentile. Once outliers have been removed, the maximum heat production over a predetermined
past time period may be used to estimate the amount of energy that needs to be delivered
to the hot water tank 204 by the heat pump 202 (i.e., an estimated future heat demand
by the hot water system). For example, the maximum (non-outlier) heat production for
a day over the past two weeks could be used. This estimated future heat demand (EST_HD_FTP)
may be used as a proxy for the estimated hot water usage over the future time period,
such as the next day. Use of the maximum heat production may increase the potential
cost, but will reduce the risk of there being too little hot water production to satisfy
needs (which could lead to increased cost if, for example, an electric resistive heating
element is used to quickly heat water to handle the shortage). While using the maximum
heat production may produce excess heating in the short-term, excess heat production
will be effectively carried over to future time periods (less, e.g., heat losses from
the tank), so that the maximum heat production over a past period will tend toward
the heat production needed to meet actual demand. It should be noted that the future
time period may be a period of a day, or a period of time either shorter or longer
than a day. In general, the future period over which heat demand is estimated and
costs are to be optimized may depend on the period of time into the future over which
future tariff information is available.
[0063] It will be understood that other methods of estimating future hot water usage could
also be used. For example, an average or median heat production could be used, instead
of the maximum, though this would increase the risk of producing too little hot water.
Additionally, the daily heat production over other past time periods could be used.
For example, the average, median, or maximum heat production over the past month or
six months could be used instead of over the past two weeks. Parameters such as whether
to use the maximum, average, median, and the past time period to use for estimating
future heat production may be either built-in to the control system, controllable
by the system provider, or selected by the user. Additionally, it will be understood
that data other than past heat production may be used to estimate hot water demand
or heat demand in some implementations, depending on the sensors and other information
available to the system.
[0064] In block 306, the system accesses the energy tariffs for a future time period (ETRF_FTP).
For example, it is common for electricity tariffs to be available hourly over the
next 24-hour period. For example, for some regions, such dynamic tariff information
may be available from the EPEX Spot market, via an API. Such dynamic tariff or pricing
systems will typically depend on the market for electricity in a given market or location,
generally providing lower tariffs for electricity during periods of relatively low
demand, and higher tariffs during high demand periods.
[0065] In some implementations, the controller 210 may access the information directly through
an API associated with the energy market. In some implementations, a system provider,
such as the provider of the controller or heating system may make the future pricing
data available through a cloud-based service or API. Depending on the source of the
tariff information, information for the next day may be made available at a predetermined
time once per day, or may be available at other intervals.
[0066] In block 308, in heat pump systems that include an outdoor unit or that otherwise
use outdoor air as a source of heat, the system accesses outdoor temperature predictions
(TEMP_FTP) for the future time period, such as hourly temperature predictions for
the next 24-hour period. The COP of the heat pump for such air source heat pumps will
be dependent on the outdoor temperature, so predicting how much electricity/energy
will be needed for heat production will be based at least in part on outdoor air temperatures
for the location at which the heat pump is installed, as well as on characteristics
of the heat pump. In general, for each model of heat pump, there will be data on the
COP dependent on the air temperature. While this COP may vary slightly from unit to
unit, it is typically sufficient for the controller to have access to the COP data
for the heat pump model that is being used.
[0067] In some implementations, outdoor temperature predictions can be accessed from, e.g.,
a weather service. In some implementations, a weather model or machine learning algorithm
may be used to predict future temperatures. In some implementations, the controller
210 may access the weather predictions directly through an API associated with, e.g.,
a weather service. In some implementations, a system provider, such as the provider
of the controller or heating system may make weather prediction data available through
a cloud-based service or API.
[0068] In block 310, the system estimates the COP of the heat pump for the future time period
(EST_COP_FTP), based at least in part on the predicted outdoor air temperature for
the location of the heat pump (i.e., TEMP_FTP), and on the performance characteristics
for the heat pump (PERF _HP). As discussed above, the performance characteristics
will vary from unit to unit, but data on the performance characteristics of the model
of the heat pump will generally be sufficient to provide an estimate of the COP for
a given external air temperature. Similarly, while the actual temperature may vary
slightly from the predicted outdoor air temperature, the predictions are usually sufficient
for estimating the COP.
[0069] In block 312, the system generates a schedule for operating the hot water system
(and, in particular, the heat pump) over the future time period (SCHED_FTP), based
at least in part on the estimated hot water usage over the future time period (i.e.,
the estimated future demand for heat production), and the future energy tariffs (and,
in some implementations, estimated COP). In some implementations, due to the lack
of sensors that provide information on the timing of actual usage of hot water, the
system may split its estimate or proxy for hot water usage into time slots based on
predetermined timing strategies either built into the controller, provided by the
user, pre-programmed by an installer, or provided by the system or controller manufacturer
or provider. For example, in some implementations, the heat demand may be split evenly
between two time slots - one occurring in the morning, and one in the evening. This
may represent, e.g., the potentially high demand for hot water in the morning, for
showers, etc., and the potentially high demand in the evening, for cleaning, dish
washing, washing before bed, etc. Of course, this usage pattern may not apply in all
households or to all users of hot water, so in some implementations, other schedules
may be used to divide the heat demand and to assign it to particular times in a schedule.
[0070] Once the heat demand has been assigned to particular times in the schedule, then
the task of the controller in generating the schedule is to meet the heat demand by
the assigned time, at a reduced cost, based on the energy tariffs at particular times,
and on the predicted COP values (based, e.g., on weather predictions). An optimization
method for generating the schedule is described in greater detail below. In general,
once the heat production targets and times are determined, and the estimated COPS
and future energy tariffs for each future time slot are known, numerous known optimization
techniques may be used to determine the schedule for operating the heat pump 202.
[0071] As will be discussed below, the optimization is subject to a number of constraints.
For example, for each time slot during the future time period (e.g., for each hour
of the next 24-hour period), the amount of energy used by the heat pump cannot be
higher than a maximum energy that the heat pump can use during the time slot. Similarly,
during any time slot, the system cannot store more energy in the hot water tank (e.g.,
in terms of volume and temperature) than the hot water tank can hold.
[0072] In some implementations, the schedule for operating the heat pump 202 will result
in a heat production target for each time slot in the future time period. For example,
the schedule may result in a heat production target for each hour over the next 24
hours. This heat production target gives the estimated heat production that should
be achieved by the heating system, and the time (i.e., the end of the time slot) by
which the heat production target should be reached.
[0073] At block 314, the system operates the hot water system, and particularly the heat
pump, according to the generated schedule (i.e., SCHED_FTP). In some implementations,
this may be done using hysteresis control. For hot water systems with hysteresis control,
given a setpoint x and a hysteresis y, the heat pump will start operation when the
temperature inside the tank drops below
x-y. Using such control, the system does not start the heat pump for very small increments
of temperature, but waits until the temperature has dropped more inside the tank.
In such a system, at the start of each time slot (e.g., at the start of each hour),
the heat production target calculated by the optimization is transformed into a temperature
setpoint for the hot water tank. The system may then set the hysteresis value low
(e.g., 2° C) to cause the heat pump to start operating. Once the setpoint is reached
in the hot water tank, the setpoint will be maintained (within the small hysteresis
value) until the end of the time slot. At the end of the time slot (e.g., at the end
of the hour), the system will set the setpoint to a low value (e.g, 40° C) and hysteresis
to a high value (e.g., 20° C) to stop the heating and to prevent it starting again
unless the system needs it to do so according to the generated schedule. It should
be noted that this larger hysteresis band outside of the operation times of the heat
pump may permit the temperature in the hot water tank to drop to a lower temperature
while still maintaining comfort. Because the heat pump is more efficient when heating
water at lower temperatures, this may result in lower energy consumption for providing
substantially the same amount of comfort to the end user.
[0074] It will be understood that there may be many variations on the method described above,
depending on the details of the hot water system, and the availability of information
on future tariffs and weather conditions. For example, some hot water systems may
include the ability to use electricity generated by photovoltaic solar generation.
In such systems, it may be desirable to take the photovoltaic generation into account
in the optimization. This can be done, e.g., by assigning a value to the photovoltaic
electricity used based on the value at which it could have been sold back to the grid
had it not been used in heat production. Performing tariff optimization in such a
system may require estimates of photovoltaic generation, which will depend on solar
irradiance, as well as temperature. Since predictions of solar irradiance at a particular
location are generally less certain than air temperature predictions, it may be desirable
to update the predictions and the generated schedule more often in systems that use
photovoltaic energy generation in the hot water system.
[0075] Other variations will include variations in the number of time slots, the future
period over which the schedule is generated, the past time period that is used for
estimating heat demand or other proxies for hot water usage, the way in which estimated
heat demand is divided over the future time period, etc. Generally, these parameters
may be built into the control system, or may be adjusted by an installer, user, or
by the provider of the control system.
[0076] In some implementations, the method described above for generating a schedule for
control of the hot water system may be run periodically. For example, the method may
be run once during each 24-hour period to generate a schedule for the next 24 hours.
In some implementations, the method may run each day shortly after the hourly energy
tariffs for the next 24 hours are made available. It will, of course, be understood
that other time periods and timing for running the method could also be used, depending
on the system and the availability of future tariffs and weather predictions. For
example, as discussed above, it may be desirable to update the generated schedule
more often for systems that use energy from photovoltaic generation in the hot water
system.
[0077] FIG. 4 shows an objective function 402 and constraints 404 that may be used for optimization
of cost in the method discussed above with reference to FIG. 3. It will be understood
that the objective function and constraints can be used with any of a number of known
optimization techniques or algorithms, such as genetic algorithms, simulated annealing,
particle swarm optimization, or other known heuristic or other optimization techniques.
[0078] It will also be understood that in the objective function 402 and constraints 404,
the variables are vectors of a length that corresponds to the number of time slots
in the future time period. For example, for a system that is attempting to generate
a schedule for each hour of a 24-hour period, the variables will be vectors of length
24.
[0079] The example objective function 402 shown in FIG. 4 includes terms related to photovoltaic
generation of energy that may be used in providing energy to a heat pump. This photovoltaic
energy will be referred to as a PV surplus. It should be noted that in systems without
photovoltaic generation, the terms related to the PV surplus simply drop out of the
function (e.g.,
Etogrid,
Epvsurplus_used, and
Epvsurplus_total will all be 0 - i.e., vectors containing all 0 values).
[0080] The objective function to be minimized through known optimization techniques is shown
as objective function 402:

where:

and x is the energy consumption of the heat pump.
[0081] It will be understood that:
Costtotal is the total cost, which is being optimized;
Efmmgrid is the energy/electricity bought from the grid (a vector containing the energy for
each time slot);
Priceenergy_buy is the energy/electricity tariff or price per unit (a vector with the price for each
time slot in the future time period);
Etogrid is the energy/electricity sold back to the grid (a vector containing the amount of
energy for each time slot);
Priceenregy_sell is the price at which energy/electricity may be sold to the grid (a vector containing
a price for each time slot);
Epvsurplus_total is the total amount of PV surplus available (a vector containing the predicted PV
surplus for each time slot in the future time period); and
Epvsurplus_used is the amount of the PV surplus used for the heat pump (a vector with the amount
of PV surplus used for each time slot).
[0082] The constraints 404 for the optimization are as follows:

where x is the energy consumption of the heat pump.
[0083] It will be understood that these constraints are as follows: (1) for each time slot,
the amount of energy used by the heat pump cannot be higher than the maximum amount
of energy that the heat pump can use during that time slot; (2) during any given time
slot, the amount of energy stored in the water in the hot water tank (in terms of
both volume and temperature) cannot be higher than the maximum amount that the hot
water tank can hold; and (3) the sum of the energy we use for each time slot times
the COP for each time slot must be greater than or equal to the heat demand that was
estimated - this is a constraint on the heat to be produced over the future time period
(divided into n time slots - so
n=24 for a one hour time slot with a 24 hour future time period).
[0084] It will be understood that, although the embodiments and/or implementations presented
herein have been described with reference to specific features and structures, various
modifications and combinations may be made without departing from the disclosure.
For example, it is contemplated that in some implementations, the features described
above may be used in different arrangements, or in other combinations. The specification
and drawings are, accordingly, to be regarded simply as an illustration of the discussed
implementations or embodiments and their principles as defined by the appended claims,
and are contemplated to cover any and all modifications, variations, combinations
or equivalents that fall within the scope of the present disclosure.
REFERENCE SIGNS
[0085]
- 100
- controller
- 102
- processors
- 110
- memory
- 112
- data
- 114
- operating system
- 116
- program
- 120
- storage interface
- 125
- storage device
- 140
- communication interface
- 150
- bus
- 160
- communication channel
- 200
- hot water system
- 202
- heat pump
- 204
- hot water tank
- 206
- heat exchanger
- 208
- electric resistive heating element
- 210
- controller
- 220
- hot water output
- 250
- cloud-based system
- 300
- method
- 302-314
- method blocks
- 402
- objective function
- 404
- constraints
1. A method (300) of controlling at least a hot water system (200), the hot water system
comprising a heat pump (202) and a hot water tank (204), wherein the method (300)
comprises:
estimating (302), by a controller (100, 210), a hot water usage over a past time period
based at least in part on a heat production of the heat pump (202) during the past
time period, without relying on data from a sensor measuring actual usage of hot water
or hot water taken from the hot water tank (204);
estimating (304), by the controller (100, 210), hot water usage over a future time
period based at least in part on the estimated hot water usage over the past time
period;
accessing (306), by the controller (100, 210), energy tariff data for at least a portion
of the future time period;
generating (312), by the controller (100, 210), a schedule for operating the heat
pump (202) to optimize energy costs based at least in part on the estimated hot water
usage over the future time period and the energy tariff data for the future time period;
and
operating (314), using the controller (100, 210), the hot water system (200) according
to the schedule.
2. The method (300) of claim 1, further comprising:
estimating, by the controller (100, 210), a heat demand over the future time period;
wherein estimating (304), by the controller (100, 210), hot water usage over a future
time period comprises using the estimated heat demand over the future time period
as a proxy for the hot water usage.
3. The method (300) of claim 2, wherein generating (312), by the controller (100, 210),
a schedule for operating the heat pump (202) comprises dividing the estimated heat
demand over the future time period into an estimated heat demand for at least two
time slots within the future time period.
4. The method (300) of claim 2 or claim 3, wherein generating (312), by the controller
(100, 210), a schedule for operating the heat pump (202) to optimize energy costs
comprises generating a heat production target for a plurality of time slots within
the future time period, the heat production target specifying an estimated heat production
to be achieved by the heat pump by an end of the time slot associated with the heat
production target.
5. The method (300) of claim 4, wherein operating (314), using the controller (100, 210),
the hot water system (200) according to the schedule comprises using hysteresis control
based on a temperature of hot water in the hot water tank (204) by, for each time
slot in the future time period:
transforming the heat production target for the time slot into a temperature setpoint
for the hot water tank (204), and, in relation to the time slot, setting the hot water
tank temperature setpoint based on the transformed heat production target for the
time slot;
setting, at the start of the time slot, a hot water tank hysteresis value to a value
low enough to cause the heat pump (202) to start operating to heat the water in the
hot water tank (204) to the hot water tank temperature setpoint; and
setting, at the end of the time slot, the hot water tank temperature setpoint and
the hysteresis value to values sufficient to stop the heat pump (202) from further
heating the water in the hot water tank (204), and to prevent heating from starting
again except in accordance with the schedule.
6. The method (300) of any one of the preceding claims, wherein the future time period
comprises a 24 hour period that is divided into a predetermined number of time slots
based on a number of time slots in the energy tariff data for the future time period.
7. The method (300) of any one of the preceding claims, wherein the heat pump (202) uses
outdoor air, and wherein the method (300) further comprises:
accessing (308), by the controller (100, 210), outdoor air temperature predictions
for the future time period;
estimating (310), by the controller, a coefficient of performance (COP) of the heat
pump (202) over the future time period based at least in part on the outdoor air temperature
predictions and on performance characteristics of the heat pump (202); and
generating (312) the schedule based at least in part on the estimated COP.
8. The method (300) of claim 7, wherein accessing the air temperature predictions comprises
accessing weather forecast data from a cloud-based weather service, the weather forecast
data comprising the air temperature predictions or data from which the air temperature
predictions can be derived.
9. The method (300) of any one of the preceding claims, wherein the hot water system
(200) includes photovoltaic energy generation, and wherein the method further comprises:
accessing, by the controller (100, 210), solar irradiance predictions for the future
time period;
using, by the controller (100, 210), the solar irradiance predictions to predict an
amount of photovoltaic energy available for use by the hot water system (200) over
the future time period; and
generating (312) the schedule based at least in part on the predicted amount of photovoltaic
energy available.
10. The method (300) of any one of the preceding claims, wherein heat production of the
heat pump (202) during the past time period is determined based at least in part on
a measured temperature and a flow volume of liquid into the heat pump (202) and on
a measured temperature and a flow volume of liquid out of the heat pump (202).
11. The method (300) of any one of the preceding claims, wherein the heat production of
the heat pump (202) during the past time period is determined based at least in part
on energy usage of the heat pump (202) over the past period of time.
12. The method (300) of any one of the preceding claims, wherein generating, by the controller
(100, 210), a schedule for operating the heat pump (202) to optimize energy costs
comprises using an optimization algorithm with an objective function (402) based at
least on estimated energy usage and the energy tariff data to optimize energy costs.
13. A controller (100, 210) configured to operate at least a hot water system (200), the
hot water system (200) comprising a heat pump (202) and a hot water tank (204), the
controller (100, 210) being arranged to carry out the method (300) of any one of claims
1 to 12.
14. A hot water system (200), comprising a heat pump (202) and a hot water tank (204),
the hot water system (202) characterized in that the hot water system further comprises a controller (100, 210) according to claim
13.
15. A computer-readable medium (110, 125) carrying instructions for operating a hot water
system (200) to carry out the method (300) of any one of claims 1 to 12.