WO2023073335A1

WO2023073335A1 - An energy system incorporating a controller and a method of operating an energy system

Info

Publication number: WO2023073335A1
Application number: PCT/GB2022/000085
Authority: WO
Inventors: Christopher Charles Farrell
Original assignee: Christopher Charles Farrell
Priority date: 2021-11-01
Filing date: 2022-10-28
Publication date: 2023-05-04
Also published as: GB202115681D0

Abstract

This document describes, amongst other things, a system and method of controlling energy use on the consumer side of a connection to a supply network, where the connection has a maximum permissible current rating and where devices on the consumer side include at least one load and at least one battery, and wherein a controller is responsive to a measurement of current in the connection and a time varying electricity tariff to control the charging of the battery, and wherein the controller can increase the current used to charge the battery up.

Description

AN ENERGY SYSTEM INCORPORATING A CONTROLLER AND A METHOD OF OPERATING AN ENERGY SYSTEM

Background

The United Nations recognises that climate change represents an existential threat to humanity. A threat that scientists and national governments across the world attribute to humanity’s continued and increasing capacity to bum fossil fuels. The burning of fossil fuels is known to release harmful emissions that do damage to our ecological wellbeing due to rising sea levels, changing weather patterns, fires, drought and floods.

In response to meeting the challenges of climate change, nations are implementing sustainability and Net Zero policies that aim to reduce harmful emissions by reducing the burning of fossil fuels. A key element to these climate change policies is the need to transform our use of energy to electricity that can be generated from clean renewable energy.

The transition to renewable energy introduces new challenges in meeting the increased electricity loads as past investments in national grid infrastructure supply chains of power generation, transmission and distribution has, in non-equatorial regions, largely been shaped by the use of fossil fuels for heating, hot water and transportation. The historical shaping of electricity supply capacity around the use of fossil fuels now means that our existing end to end grid capacity is only about one third of our post transition electricity needs.

Electricity is normally supplied from a supply grid to a building or dwelling via a meter that records the kWh electrical energy consumed through the meter. However, the meter is blind to the actual use of the electricity or its priority of need. Essentially, the meter provides an open power gateway. A user can arbitrarily demand power from the supply grid with the only physical constraint being placed on them is that they do not exceed a maximum current limit as defined by a master fuse or circuit breaker. The meter and master fuse or circuit breaker represent a connection that delineates between the supply network and a user’s wiring and equipment. Typically the master fuse and the meter remain the property of a supply authority or grid company. Responsibility for maintaining equipment and wiring usually transitions from a supplier to a consumer at the output side of a meter.

The electricity supply grids for all nations are based on alternating current typically referred to as AC power that’s mostly distributed via grid connected meters ranging from 40-100 Amperes at 120 to 240V for domestic and upwards of 110-440V for commercial needs.

Across the world there’s thought to be ~500 million buildings or dwellings connected to grid supplies with electricity meters that share a common architecture and it is these installations that need to support the transformational loads in order to achieve each nation’s sustainability and Net Zero goals.

A typical electricity supply to a building or dwelling is formed of one or more suppling grid connected cables that connects to a meter installation comprising of a main fuse, a meter and a distribution panel. The distribution panel connects with various power circuits for example, one or more lighting circuits, a circuit for powering small power devices (typically no more than 3kW per device), electric cooker circuits and electric shower circuits, and more recently electric vehicle charging points and heat pump installations.

The total possible power consumption of the connected loads is often in excess of the main fuse limit as electrical contractors assess and only connect the power demands that anticipates a concurrency of use that falls within the meter and main fuse limits. Put another way, no user is assumed to switch everything on at once. However, due to the increased demands from EV and heat pump electrical loads there are new and emerging rules including the electric vehicle consumer code in the UK that requires notification to the supplying authority for installations with demands in excess of 13.8kVA. At a nominal 240V AC this corresponds to 57.7A RMS.

The required notification of the increased power needs of one or more buildings or dwellings highlights a serious challenge in achieving net zero policy as it’s well understood that electricity demands are set to increase more than three-fold from ~19% to over 70% of all power needs (taking the UK as an example). Therefore even a building or dwelling with a lOOAmpere main fuse limit may impact the resilience of the power distribution system as an increasing number of buildings and dwellings transform their energy needs to electricity. Put another way it is assumed that a number of adjacent buildings or dwellings will not concurrently try to draw their maximum power load. If they do then the supply infrastructure supplying such a number of adjacent buildings may fail.

Electricity bill payers typically pay for electricity based on supply contracts that set tariff costs per kWh and time of use. Due to the increased transformational loads (as countries transition away from fossil fuel use to use more electricity) and grid infrastructure many nations face the prospect of introducing frequently changing and wide ranging electricity tariffs in response to supply, capacity and demand needs.

Today’s existing market norm is for an always open meter connection where disconnection from supply is mainly caused through non-payment of electricity costs. Electricity meters work by measuring and recording the variations in current and voltage that pass through an electricity meter. This approach means that a power user can turn on one light, or a thousand lights and only the knowledge of historical energy use can inform the energy supplier of likely demand. Consequently the traditional approach to measuring power is limited as it is not possible to determine what the power was used for or the priority of need especially when there is less current available to the one or more supplying meter(s), for example because of reduced generating capacity or distribution constraints. Therefore, it would be beneficial if the use and costs for electricity was provided on the basis of a specific user using one or more supplying meter where the use of electricity is predetermined to be selectively prioritised by specified user, appliance, application, device or need relative to the distribution network capacity, emissions and costs.

Challenges in the future resilience and affordability of electricity supplies mean that today’s open grid architecture has the potential to increase costs and limit power services.

Electricity is used to power appliances, applications or devices to meet a specific user need and in this regard the user has no easily available knowledge of how their energy demand impacts a meter’s fuse limit, energy costs, grid capacity or emissions. In this context an “application” is a desired outcome that may involve the interaction of multiple devices. For example providing hot water can be regarded as an application as it is a desired outcome that may require the interaction of several devices, such as boilers, heat-pumps, pumps and electric heaters working in consort to achieve the desired objective, namely hot water when a user turns a hot water tap or faucet on.

Electricity providers are now seeking ways to curtail building or dwelling power demands especially during peak periods and/or low renewable power generating periods in order to protect grid services. An example (but not limited) of such a way to curtail demand is set out in PAS 1878/1879. PAS 1878 specifies the requirements and criteria that an electrical appliance needs to meet in order to be classified as a smart energy appliance. PAS 1878 is seen as a critical component in the uptake of devices for implementing “demand side response”. PAS 1879 enables standardised control of smart energy appliances to: 1) match the short-term availability of intermittent renewable energy sources such as wind and solar; 2) decrease the peak load on the electrical transmission and distribution networks to alleviate the need for network upgrades to handle new domestic appliance types; 3) allow control of electricity network characteristics, such as grid frequency, system inertia and network voltage, and help prevent network and generation outages; and 4) allow electricity suppliers to offset their short-term market imbalance by controlling flexible load on the network. In other words these standards are intended to enable electricity supply operators to remotely switch off appliances so as to protect grid services.

Therefore, there is a need for a system that helps to control the use of electricity and better meets stakeholder needs by helping energy suppliers and users to prioritize use of power. By this action it becomes possible to enhance reliability so as to maintain continuity of supply. It would also be beneficial to be able to inform electricity bill payers, users and upstream stakeholders of the real-time electricity costs, emissions and grid capacity impacts of their holistic power needs. Summary of the teachings of this disclosure

According to a first aspect of this disclosure there is provided a method of controlling energy use on the consumer side of a connection between a consumer and a supply network, where the connection has a maximum permissible current rating and where devices on the consumer side include at least one load and at least one battery, and wherein a controller is responsive to a measurement of current in the connection and a time varying electricity tariff to control the charging of the battery, and wherein the controller can increase the current used to charge the battery up to the maximum permissible current rating.

Preferably the controller can disconnect at least one of the loads so as to increase the amount of current available to be used to charge the battery up.

It is thus possible to provide a method of providing a user definable electricity power management system in a building or dwelling, where the building or dwelling uses one or more supplying A/C electricity services rated at ~110-440 V single phase, split phase or three phase electricity to power one or more appliances, applications, or devices. For example, applications may include (but not be limited to) space heating, domestic hot water generation, cooking, refrigeration, medical use. Devices may include electric vehicles (including drones) that incorporate the need for charging one or more battery. Devices may also include battery storage or other forms of energy storage. In use the inhabitant(s) or user(s) of a building or dwelling has a desire or possibly a need to limit variable tariff electricity costs for the benefit of buying or supplying electricity (including the sale of electricity to a supplying electricity provider) For example the building or dwelling has one or more electricity meters with a notified power or current limit which differs from a meter main fuse limit, for example but not limited to a notified power limit of 13.8KVA (corresponding to a current limit of 62.7A RMS for a 220V RMS AC supply) and/or a limited current at a main fuse of, for example but not limited to, less than 101 A. A controller for controlling the electrical current input to one or many appliances, applications and devices is adapted to be responsive to a measurement of the current and/or scheduled for use within a building or dwelling in conjunction with a time varying energy cost in order to vary the amount of electrical energy being used to power one or more appliances, applications or devices (including but not limited to, space heating, domestic hot water generation, cooking, refrigeration, medical, electric vehicles including drones or other forms of energy storage). The total electricity current in use within a building or dwelling may exceed a notified limit or meter main fuse rating of for example but not limited to 13.8KVA or one or more supplying meter’s main fuse rating up to lOlAmperes.

Advantageously the current measurement may be made upstream of a supplying meter (which forms the bridge or gateway between the supply network and the consumer side wiring), at the meter (the meter may provide the current measurement data) or in use downstream of a supplying meter.

Advantageously the controller adjusts the use of the available current from one or more supplying meter(s) to, for example but not limited to, appliances, applications, and devices in such a way as to selectively limit and/or increase current so as to prioritise the use of electricity supply for one or more appliances applications or devices within the maximum user determined energy costs and/or permissible current rating of the supply, notified limit and/or a meter’s main fuse Amperage rating plus any power or current from additional battery storage contributions that may serve to increase or decrease the current drawn from a supplying meter in relation to actual or anticipated variable tariff costs.

It is thus possible to maintain device operation when a building or dwelling requires the use of excess (more) electrical current than is permitted or where this current value is above and beyond that of the meter main fuse rating.

The building or dwelling is installed with one or more appliances, applications or devices that can be separated into: a) Appliances, applications or devices that incorporate predetermined power control logic, for example but not limited to, a washing machine may have one or more wash programmes where each uses a specific pattern of electrical current; and b) Appliances, applications or devices that have a fixed or min to max power rating, for example a kettle has a fixed power rating, whereas a radio has a variable power rating between a min and max value depending on the audible volume setting.

In both cases, the appliances, applications or devices may have specific start current demands that momentarily increase current rating above a nominal power rating. The appliances, applications and devices all represent different classes of loads.

Advantageously a building or dwelling is fitted with a controller or other devices that incorporates a means of identifying the flow of electricity for individual appliances, applications or devices through the measurement and recording of the unique flow of electricity characteristics of each appliance, application or device that the inventor calls digital fingerprinting.

Digital fingerprints comprise of a discrete set of the flow characteristics of electricity for one or more appliance, application or devices and includes the start current, min-max variable and individual power control logic.

Preferably the controller is adapted to learn the pattern of use for one or more appliances, applications or devices and matches the digital fingerprint to projected energy costs, emissions and coefficient of performance to recommend and automatically prioritise the use of electrical energy to achieve the lowest costs including the duration of use that fits within available current to the supplying meter, the notified supplying power limit and/or meter main fuse limit.

A user may register a priority of use for one or more specific appliance, application or devices to the controller and pair these with the controller so as to learn and store the digital fingerprint and/or use a look up table from a cloud based software service that holds a library of pre-leamt digital fingerprints.

Users may adapt the use of one or more appliances, applications or devices via the use of a smart plug or a smart plug adaptor, where the smart plug or smart plug adaptor can be configured to notify the controller of the type of appliance, application or device. The terms smart plug and smart plug adaptor will be used interchangeably. The smart plug is adapted to communicate with the controller and notify users of the cost of electricity relative to the priority of need as determined by the user.

The controller is adapted to cooperate with the smart plug adaptor that is configurable to identify the connected appliance, application or device. For example, but not limited to, the smart plug adaptor is configurable by means of a current generator that generates an appliance, application or device specific flow of electricity, for example, but not limited to, a current draw that can be used to encode a device identification, for example a current burst in Morse code that spells the name of the product, i.e. KETTLE where the controller is adapted to recognise the unique characteristics of the flow of electricity burst as the start and stop periods of use and the controller learns the pattern of use of appliance, application or device. The above example is relatively simple and is provided just by way of illustration, and more complex codes or identifiers for a device may be transmitted using other coding and transmission schemes that might be expected to provide greater resilience in the presence of noise or other interfering signals

Preferably the controller is adapted to work with cloud services that cooperate in such a way as to predict future current availability and/or changing energy costs, emissions and network capacity. Such capacity changes (and by implication energy costs) may for example (but not limited to) be assessed by reference to TV and sporting schedules, weather forecasts, religious events (such as synchronised times of feasting) and predicted network grid capacity. In what might be considered an unconscious bias some of the UK and European building regulations have developed around the historical doctrine of a Christian society. However, non Christian religions events that are timed to coincide with sunset and sunrise, for example Ramadan, have the potential to overload electricity supplies stipulated by these building regulations and current assumptions for example but not limited to CIBSE concurrency guidelines, and especially so during synchronised feast times, for example Shia Islam Ramadan 19th day Odd nights, Ehya prayers during Laylat-al-Qadr Night Advantageously the controller either alone or in cooperation with cloud software services builds a library of many digital fingerprints where one or more can be assigned to a registered user’s account and to these fingerprints can be assigned a specific energy cost that varies by priority of need by user, appliance, application or device. Thus the energy cost for using a particular device can be varied from the supplying electricity meter tariff costs by one or many third party organisation such as a national government including welfare payments, corporate enterprise, charity, or non-profit organisation. To build on this, a governmental or some other organization may decide that a class of users and/or user devices may benefit from subsidized electricity. For example a policy may be that electric mobility scooters may be charged at a significantly reduced cost. The electricity meter acting as a gateway sees the power being used to charge the scooter and records it at the prevailing general tariff. A correction or revised tariff can then be applied to the user’s bill as a concurrent or post processing activity such that the reduced electricity cost is applied to charging of the mobility scooter but not to power drawn by other devices. Similarly electricity use which is deemed “undesirable” such as charging an electric vehicle beyond 80% (or some other limit value) may incur an additional cost beyond the equivalent prevailing tariff for charging the electric vehicle at the same time but up to less than 80% charge.

This concept can be extended further such that by identification of the device or application using power, that device or application can have its power use billed at a respective tariff. Thus the current passing thorough the supplying meter can be seen to be a superposition of a plurality of currents, where some or all of the plurality of currents may have respective tariffs. The respective tariffs may be fixed or be variable. Variable tariff prices may vary with time or some other function such as grid capacity or as a function of the environmental cost of generation (such as being more expensive when fossil fuels have to be combusted to meet the electricity demand).

The addition of cloud based energy costs by priority of user need for one or more appliance, application or device need enables the transfer of energy cost billing to move from the traditional utility supplying meter to the power management system’s cloud based software services.

Preferably the controller is adapted to be responsive to the supplying grid capacity and use this information to adjust the flow/use of electricity so as to protect the grid from being overloaded.

A non-limiting example of where the controller would help to contain the flow of electricity and energy costs is when a building or dwelling is using electricity for a multitude of appliances, applications or device needs where those needs include a heat pump with thermal store and the recharging the batteries of one or more electric vehicles. In the example it is foreseen that during the first hour of a winter day the combined energy demand is above that of the available supplying current and/or supplying meter’s notified limit or main fuse limit. In this example a controller apportions the available current, notified limit and or supplying meter capacity to meet the needs of each appliance, application or device in relation to the user having set priority and tariff limits that further inform the controller about the amount of current it should be passing to a given device or appliance or application (devices working together to achieve a desired outcome). Thus in this non limiting example the controller may modify the current allocated to either the EV charging or space heating needs. For example where the temperature of a hot water store is below the desired value the controller may elect to use a combination of power from both the supplying meter and electric vehicle or other battery storage facility to modify the temperature of the hot water store.

Alternatively, a controller may use a user’s calendar for the purposes of calculating the best economic outcome for buying and selling electricity to a supplying electricity provider. The controller may, for example but not limited to, inspect a user’s google calendar and with information gleaned therefrom the controller calculates the energy needs for an electric vehicle and uses this information to adjust the charging and use of one or more batteries For example, in a case where the controller recognises that the electric vehicle is not scheduled to be used during the first hours of a day at a time that correlates to higher tariff costs, then the controller may elect to sell energy back to the supplying electricity provider for a profit, having charged the batteries during a previous low tariff period.

Preferably the controller is informed of or learns the likely pattern of use of electrical appliances, applications or devices within the building or dwelling and schedules their use to reduce energy costs. Advantageously the controller is informed of or learns the likely pattern of energy cost variation and schedules the use of electricity that takes into account the available electrical power of one or more battery storage devices in order to reduce energy costs by proportionally increasing the use of low tariff electricity relative to high tariff periods. Additionally or alternatively in order to lower electricity costs the controller may lower or increase the actual energy consumption based on the controller’s determination of the method of power generation and may further reduce actual energy costs by selling stored electricity during high tariff periods and or high fossil fuel power generation periods so as to profit from selling electricity that has lower associated emissions than the then prevailing electricity supply.

In an embodiment, the controller is adapted to be responsive to measurements of current drawn by devices within the building or dwelling and more specifically the current drawn by respective ones of the one or more appliances, applications and or devices and is adapted to communicate with a device or a power controller associated with the respective device to vary the power supplied to the device. In this way the current to the respective appliances, applications or devices can be modulated to keep the total current drawn to within the maximum permissible current available from the mains electricity supply and taking into account any additional current from electrical battery storage devices, for example but not limited to, an electric vehicle or fixed storage battery appliance. Therefore, it’s possible to automatically suppress the use of electricity for one or more specific user’s appliance, application or device need in favour of another user’s appliance, application or device needs.

Advantageously a user interface is provided such that users can register with the controller, and advantageously a user can inform the controller of their specific energy tariff parameters, a schedule of use and appliance, application or devices requirements.

In learning patterns of energy use in the home, the controller is able to modulate power supply for one or more appliance, application or device in order to ensure that no one application takes priority to the detriment of another, unless it is intended to do so as defined by the registered user’s priority of use and specific need. Consider by way of a non-limiting example a situation where a user has a meeting in an hour and the user’s EV is in need of recharging sufficient for a 20 mile journey. Also, the dwelling has a heat pump and thermal store which are required to maintain a warm home and deliver heating and hot water services. In such a case today, the user might assume that all appliances are switched on and therefore the EV will be charged and there will be enough heating and hot water to meet the need. However, in this scenario combined current loads of the EV and heat pump might actually invoke a current limiting controller to turn one or more of the appliances off in order to protect the meter main fuse from overload or the heat pump may sense a lack of current and switch off. In either case, the user would not know how to manage the separate appliance needs within the capacity of the supplying electricity and or notified current limit and or meter’s main fuse capacity and possibly find that the EV battery is flat or that there is a lack of heating and or domestic hot water available.

However, the controller makes it possible to manage the electricity use for each registered user by appliance, application or device and categorise these in relation to importance of use, ranging from for example but not limited to:

• Priority 1 , Emergency power, for example but not limited to, smoke, fire alarms and lighting

• Priority 2, Essential shared power, for example but not limited to, heating, hot water, TV, lighting, cooking, fridge/freezer

• Priority 3, Personal daily power, for example but not limited to, kettle, computers, EV, washing, hairdryer

• Priority 4, Non time dependent power, for example, but not limited to, vacuum cleaners, washing machine, tumble dryer Enabling one or more users in a building or dwelling that independently use power from one or more shared supplying meter(s) to register and set priorities for their energy needs by appliance, application or device enables the controller to consider the impacts of these user based power demands on one or more of the available supplying current, energy costs, and emissions associated with the generation of the available current from the supplying meter.

This is important because the controller may recognise that for a 100 Ampere meter connected to supply electricity to a heat pump store, the heat pump store may now have an increased heat input capacity of up to the meter’s main fuse capacity or indeed, the controller may temporarily warn a user or suspend the use of non-emergency appliances in order to save tariff costs, emissions and/or when there’s low tariff costs, increase for example but not limited to, the EV charge rate to a high power input ~19kW, in such a case an 80k Wh EV battery could fully recharge in ~4 hours rather than ~11 hours if using a 7kW charge rate.

In some embodiments of this disclosure the controller may be responsive to warnings of high energy demand on an electricity supply to modify for example but not limited to, appliance, application or device behavior to increase the charge rate of a battery or heat into a thermal store in anticipation of an impending change to increased tariff costs or possible loss of power from the supplying electricity provider.

Such warnings may be issued by a service provider based on knowledge of general system load, knowledge of planned or unplanned generator outages, weather forecasts, TV broadcast sporting events, adverts or the end of or start of a new programme, religious events for example but not limited to Christmas, Ramadan, and television schedules.

In some embodiments the controller’s operation is distributed between a local unit and a cloud based service. Use of a cloud based service enhances the ability to monitor, for example, the scheduled TV programme timetable to better manage energy use of and by the system through the predictive and proactive use of one or more electrical needs that might otherwise overload the electrical supply capacity of the supplying grid or electricity meter. For example, but not limited to, the use of electric kettles during advert breaks and set periods of sporting or religious events that may induce a collective behaviour of a group of people or population to synchronise their near simultaneous use of power.

Similarly such a controller working in cooperation with a cloud based software service, where data inputs from, for example, weather data, national grid capacity data and known events that drive high dynamic electrical loads across the national grid are monitored by the system so as to enable predictive and proactive management of the system’s electrical loads, helping protect system users from potential power failures by rationing electrical input to the system during critical event periods. Alternatively, the system may predict such an event and increase the rate of charging of one or more battery store(s) in readiness for a critical event that would otherwise limit electrical services to one or more user(s). Consequently the system may be able to provide at least limited time protection for essential and emergency electrical needs as defined by the user, and optionally for more discretionary loads should the user so desire.

The controller may also recommend alternative appliance, application or device use times based on predicted tariffs and or loads to help protect the needs or one or more user’s required use of one or more appliance, application or device registered to the system.

Preferably the controller is arranged to schedule and/or inhibit the operation of electrical loads as a function of cost, emissions resulting from the prevailing mix of electricity generating stations or current available from the electricity supply, wherein, additional battery power can be used to replace or make up for high tariff periods or where there is insufficient electricity from the grid supply.

Thus there is provided a system where the controller is informed of or learns the likely pattern of use of for example but not limited to, users, appliances, applications or devices within one or more buildings or dwellings and schedules electrical loads to reduce the energy cost and emissions and/or in which the controller is informed of or learns the likely pattern of energy use cost variation and schedules the use of electrical loads in order to reduce the energy cost and emissions. With this knowledge the controller can for example but not limited to, charge a battery by a specific amount or allow a battery to discharge its energy or allow a thermal store to warm or allow it to cool so as to improve the energy management and delivery of electrical services of the system.

According to another aspect of this disclosure there is provided a method of controlling energy use on the consumer side of a connection between a consumer and a supply network, where the connection has a maximum permissible current rating and where devices on the consumer side include a heating system, a further load and at least one battery, and wherein a controller is responsive to a measurement of current in the connection and a time varying electricity tariff to control the heating system, and the controller is operable to disconnect the further load to increase the current used to the heating system up to the maximum permissible current rating.

According to a further aspect of this disclosure there is provided a method of controlling the use of electricity in a building or a dwelling, where the building or dwelling contains a plurality of devices, the method further comprising providing means for identifying the load that one or more of the devices presents, and associating a device with a respective electricity consumption tariff, such that a plurality of tariffs can be applied concurrently.

Brief description of the Drawings

Embodiments of the present disclosure will now be described by way of non-limiting example with reference to the accompanying figures, in which:

Figure 1 shows the relative contribution of energy sources to the UK energy use in 2019;

Figure 2 is a diagram showing relative use of oil in the UK in 2019 by categories of nonenergy use (feedstock), non-domestic building use, industry use, domestic use and transport;

Figure 3 is a schematic diagram of an electrical system constituting an embodiment of the present disclosure;

Figure 4 schematically illustrates an embodiment of the system including various electrical loads within a dwelling and how they can be associated with devices to monitor the load current drawn by an appliance, application or device and/or to switch the load on and off under the direction of the controller;

Figure 5 is a graph illustrating how dynamic pricing may cause the cost of electricity to vary over time during part of a day; and

Figure 6 illustrates part of a user interface to the controller.

Description of embodiments of this disclosure

To put the present disclosure in context it is worthwhile considering the following factors:

1) What proportion of energy is electrical?

2) How is energy use broken down by category?

3) Energy supply to the home

4) The time varying nature of energy use in the home

1) What proportion of energy use in electrical?

Figure 1 reproduces chart 1.6 from https://assets.publishing.service.gov.uk/govemment/uploads/ system/uploads/attachment data/ file/9 24605/DUKES_2020_Chapter_l.pdf. This shows that in the UK in 2019 the total amount of energy consumed was equivalent to approximately 150 Million Tonnes of oil and of that total only the equivalent of 28 million Tonnes was provided by electricity, i.e. roughly 19%. In this figure “other” corresponds to industrial feedstock. Furthermore the UK still has to import electricity. For example “The Times” (of London) reported on 5 August 2021 at page 42 that in July 2021 the UK imported 15% of its electricity. However the UK government is committed to driving a change to move consumers away from fossil fuel in homes and as a fuel for automobiles. At the time of writing electrical power demands grow as consumers switch to Electric Vehicles and electric heating. It’s well documented that power supplies are likely to struggle to cope with the increased demand. However, what’s less well understood is that electricity meters, including new smart meters, are not designed for these coming energy loads.

2) How is the energy used?

Chart 1.5 of the same document found at https ://assets.publishing. service.gov.uk/government/ploads/ system/uploads/ attachment data/ file /9 24605/DUKES 202 O_Chapter_l.pdf (presented here as Figure 2) shows that Domestic fuel use was equivalent to roughly 40 Million Tonnes of oil while transport use accounted for about 55 Million Tonnes of oil. Consequently the conversion of transport from petroleum to electrical power will have a huge impact on amount of electricity that needs to be generated and distributed.

3) Energy supply to the home.

The UK has an established national gas grid that supplies gas to most homes in cities, towns and large villages. Rural dwellings are unlikely to be served by the national gas grid, but also use electricity, LPG or oil.

If we consider the majority of houses, then they get their energy from the national gas grid and from the national electricity grid. However these have different capabilities. Considering electricity, until recently, electricity was seen as an expensive and more polluting second choice for space heating and domestic hot water due to the higher energy costs, lower generating efficiency to useful heat and limited scope of market ready solutions that operate within the capacity of standard issue, 40A, 60A, 80A or 100A electricity supply meters. Electricity was initially generated by burning coal. Around the 1990’s gas (which had previously been perceived as too important to be wasted being burnt to make electricity) started to be used for electricity generation.

However the fact remains that useful fuel is burnt at a power station to boil water to make electricity which is then distributed to users. At each stage of this process some of the original energy is lost. The UK government recognises that useful energy is lost (compared to the theoretical maximum energy content of the fuel used by the power station) and this loss is measured by the use of a notional Primary energy Factor, PEF. The PEF for gas is -1.15/1 whereas the PEF for electric ranges from ~2.3 to 4.5/1 depending on method of power generation. For the purposes of national and European regulations, the stated PEF value is represented as an average of the combined fossil fuel and renewable contribution to the overall power generation. Therefore, the fossil fuel PEF is offset by the estimated contribution of wind/solar that serves to lower the current or future published electricity PEF from today’s ~2.8 to -<2.5/1 in 2024.

In the UK, due to the benefit of north sea gas, meter main fuse limits were often 30Amp or 60Amp. Many houses are now capable of accepting 80Amp or 100 Amp fuses (or circuit breakers) without needing an upgrade to the cables supplying the property although the supplying electricity operator may stipulate a maximum amperage below that of the main fuse limit. In any event, above 1 OOAmps most properties require modification of the cables that supply the house from the local supplying electricity distribution transformer. While, even the maximum size 100A fuse, limits the maximum power draw to ~24kW. For a 60 Amp fuse the maximum power draw is 14.4kW. However, the actual intended maximum amperage of one or more buildings or dwellings is often lower than the stipulated main fuse limit and often at 13.8kVA.

Meanwhile homes that use gas for heating, are mostly fitted with a U6 standard meter that provides the equivalent power in terms of electricity of 60kW. Therefore, there is a great difference between the maximum rate of energy delivery of an existing gas meter compared with an ~18kW electric meter. Thus gas can and often does provide much more energy (or at least a greater dynamic delivery rate) to a dwelling than electricity does or could, given a typical domestic supply and electricity meter installation. This point being recognised by the fact that ~80% of all gas installations use an instantaneous gas heating and hot water combination boiler, whereas electrically heated space heating and hot water services require stored water volumes in order to deliver the required dynamic rate of heating and hot water demands.

In reality the average UK domestic electricity meter has only about -23% (18/(18+60)) of the power supply capacity of existing and combined gas/electric meter installations. It is clear that if we move from a mixed gas and electric scheme to an all-electric environment then providing enough current to support all home services including the additional heating and/or hot- water and Electric Vehicle charging presents obvious and significant challenges.

Thus a significant infrastructure upgrade is required, both in terms of generation capacity but also transmission and distribution capacity.

The UK Government recognises the need to update the electricity supply infrastructure and to this end are installing millions of Smart Meters into homes and businesses that provide the capability for energy suppliers to monitor and use new evolving technical standards including PAS 1878 to limit heat pump electrical loads across the grid along with variable time-based tariffs and/or through forced disconnection of loads via “demand side response” remote initiated power controls.

Industry stakeholders, including the Chartered Institute of building Services Engineers, CIBSE, recognise that limited electricity power issues are real and have been generally well managed within the scope of the available power generation and supply limits.

To help tame demand across the network and for economic and reliable design of an installation, CIBSE standards including BS7671 - 2018 and IET Wiring Regulations Eighteenth Edition, allows for diversity and load factors to increase the maximum potential installed load for a domestic meter to be upwards of -180A for a 100A meter, whereas the true anticipated concurrent load might only be 80A in practice. However, there are no fixed rules for diversity calculating true current load values and each installation should be individually assessed based on the economic viability of the supply, experience and historic best practice guidelines. Whereas, the dramatic shift away from gas/oil in the home and switch away from petrol/diesel vehicles means that these additional loads of electric heating/hot water generation and EV charging will increase concurrency in current loads thereby changing diversity values and as a result, increase the actual true current load through the meter predictably above the average 80A or 100 A single phase meter fuse limit.

In order to confidently support increased power loads then the home owner must upgrade to a 3 phase supply. 3 phase is typically required to simultaneously charge Electric Vehicles and operate power intensive Air Source Heat Pumps and air-conditioning units. The typical cost of such an upgrade can range from ~£2,000 to £20,000 per home.

Upgrading power supplies based on a first come first served bases does not guarantee the required power for all homes is available even including from local generating and or storage facilities.

Also, not all homes can be upgraded to 3 phase power as an increased number of households are already stretching distribution network services

To help mitigate over-loading the power grid, a new BSI Public Accessible Standard, PAS 1878/9 is proposed that will allow the grid supply operators to automatically control the power usage of domestic appliances including heat pumps used in the generation of domestic heating and hot water services. Additionally, unlike traditional electro-magnetic meters, smart meters incorporate a remote disconnection function that can be used with or without the building or dwelling operators consent.

4) The time varying nature of energy use. To gain an understanding of the impact of changing from gas/oil heating to electricity then we need to consider how this energy is used within a home and learn how the energy values vary significantly over the course of a year and also over the course of a day.

4.1) Seasonality.

The following table (table 1) shows how the UK Standard Assessment Procedure, SAP, calculates heating and hot water required energy values for a 3 bedroom house in the UK over a calendar year. The table shows a typical UK kWh heating and domestic hot water requirement of 14,363kWh and 1978kWh respectively. These loads need to be increased by the generating losses.

The energy usage depends on things such as the weather so if the experiment were repeated we would expect different results. However what can be seen is that the required energy for domestic hot water varies between 102kWh in July and 238kWh in January. This is predominantly because of variation in the temperature of the water in the cold main as it enters the house being much warmer in summer than in winter. Consequently a boiler has to impart only ~60% of the winter energy during the summer months due to the lower temperature rise needed in order to achieve a domestic hot water temperature of around 45C.

Table 1

However it can be seen that the space heating requirement varies from OkWh in summer to 2583kWh in winter (roughly 86kWh per day in January). Factoring in the domestic how water use this comes to around 94kWh. The pattern of energy use varies through the day as will be discussed in more detail later at section “4.2 Daily Patterns” where it is proposed that about 1/3 of the energy use occurs in a one hour long period close to the time that the occupants get up. Using that assumption then, in this example, the home has a peak load of 3 IkWh around the time that the occupants get up.

Someone familiar with UK SAP will recognise that the standard uses EN13203/2 M and L/XL fixed daily hot water volumes to calculate domestic hot water loads and this standard in itself excludes seasonal use factors, for example, we are more likely to take a hot bath in the winter and cool showers in the summer. Also, product test standards are considered comparative rather than representing actual in-use efficiency, while test labs used for calculating heating and hot water efficiencies have a maintained air temperature of ~20 Degree C during product test cycles, therefore, if actual home owners experience winter temperatures that are lower, for example, 0 Degree C on a winter’s day, then there is a likely increase in the heat input energy demands compared with a product’s comparative test efficiencies.

4.2) Daily patterns.

In a home about 1/3 of the daily energy use occurs close to when occupants get up. For example for a family that gets up at 7am, the heating may be instructed to start increasing the room temperature from 6am onwards to reach a warmer value by 7am. The occupants then get up, boil the kettle, make breakfast and/or shower. These energy intensive activities may be complete by 8am when people leave to travel to work and the central heating system may be scheduled to switch off until late afternoon when the occupants return.

However, it should be noted that modern heating system climatic controls place the heating system in an always on state using day and night setback minimum temperatures for their actual operating regime.

Bringing these observations together we might expect an average 31 kWh of the daily energy use in January (the most power hungry month) to be around 7-8am.

Taking the UK as an example, most of the space heating and domestic hot water load is provided by a gas boiler. The most popular type of gas boiler installed in the UK are instantaneous combination boilers. Combination boilers are compact units that do not reply on thermal stores or additional immersion heaters and work by providing instantaneous heating and hot water therefore removing the need for a large hot water cylinder. This is only possible because of the large dynamic energy capacity of gas meters. That said, combination boilers have some fundamental drawbacks. For example during the winter months they are less able to produce domestic hot water without having to reduce the water flow rate due to the colder incoming mains water supply. To counter this loss of seasonal performance, combination boilers have steadily increased their heat input ratings, in some cases to over 50kW, thereby, lowering efficiency and increasing harmful greenhouse gas emissions.

Additionally, gas boilers are most likely to fail during winter months when heating and hot water requirements are most critical. For example, on average the UK installs over 4,000 new gas boilers each day while the majority of these are crises purchases, experienced as emergency boiler replacements during the winter heating months. However gas boilers do provide a truly staggering proportion of the energy used in a home. If gas boilers are not installed in homes, either because of legislation stopping them being installed in new houses or replacement becoming unavailable for old boilers) then the electricity system has to take up a considerable additional load.

Comparing actual PEF for electricity and gas at -4.5/1 and 1.15/1 respectively means that even with the PEF calculated renewable offset to 2.8/1 today, requires a doubling of in-use efficiency for electrical based systems if emissions are to actually be reduced.

Doubling the in-use efficiency of electricity for space heating in the home is now thought possible due to the introduction of heat pumps. These devices use a reverse refrigeration cycle to generate and release heat that increases the useful heat output of electricity by upwards of -2.5 times the consumed energy at the plug.

Heat pumps are seen as an attractive option for new heating systems and the Government is backing this technology for installation in UK homes. The heat pump industry is still in a relative early stage of development and presents home owners with complex challenges in how to satisfy their expectations and achieve the expected levels of efficiency. This problem becomes more acute as the ambient temperature falls during the winter and the performance coefficient of air-source heat pumps decreases with reduced ambient temperature. In other words they work less well on cold days, which is the time that heating demand rises, while ground source heat pumps present their own problems in terms of space and reducing heat output due to the effect of permafrost around buried coiled loops.

In an ideal installation, the use of heat-pumps could reduce the daily heating load to around 40kWh (except when it’s very very cold or when domestic hot water is required). Similarly the “first hour” load could be expected to be reduced from 28kWh to something in the 10 to 15kWh range. However, as we know the current load for many UK homes is limited tolOOAmperes or 80Amperes, putting pressure on the assumed diversity loads, especially for existing homes. As a consequence, the use of a 100A meter fuse means that many dwellings are not suitable for installation for either air or ground source heat pumps. Similarly the number of ground source heat pumps that can be deployed in a residential area is limited by the need for large areas for buried heat exchange loops and probability for creating permafrost conditions. In any event, both air and ground source heat pumps normally rely on large thermal stores with high capacity immersion heaters in order store sufficient energy to make up for the lower heat output from the heat pump device.

Therefore, many of the UK’s 29 million -80A, 18kW electric meters require significant current capacity upgrades to cope with the typical dynamic “first hour” energy loads for heat pump space heating/hot water as well as additional electricity used in the home and for EV charging.

Mitigating the problem As discussed above, electricity supplies will be called upon to cope with increased power demands. These demands will manifest in a couple of ways: firstly much more power will be required on average from the electricity supply infrastructure in order to support increased start currents, dynamic peak time needs and general operational loads; and secondly, the supply structure will have to cope with variations in load which if left unchecked would be bigger than those it currently experiences.

Therefore, if there is no workable solution to cap or mitigate home owner’s use of grid supply services (but as noted before standards including PAS 1878 are being developed to allow remote control of devices to inhibit or modify their operation to protect the power grid) then nations will likely introduce super high electricity tariffs to dissuade consumers from using power hungry devices at critical times of the day.

This may result in energy companies having to use pricing as a way of moderating the use of electricity. The utility companies may respond with a tariff increase around the 7am peak demand to encourage the use of optional or non-time critical loads (washing machines, tumble dryers etc.) to be delayed until the demand subsides.

The switch to EV and home battery packs presents an opportunity to help home owners better manage their energy needs as high capacity battery storage devices and EV vehicle batteries may provide a multi-purpose role providing for example but not limited to, motive power and domestic energy needs as well as an opportunity to profit from the sale of electricity to third party organisations. While home battery packs are becoming more prevalent and a search as of October 2021 shows that 2.4k Wh of storage could be purchased, excluding installation for £1700 and 7.2kWh of battery storage purchased and installed for £4300.

Figure 3 shows an example of loads that might be found in a dwelling. In this example a single phase electrical supply to a building or dwelling is represented by live 64 and neutral lines 66 which provide electrical power for a percentage of the total of the potential power load up to a limit of the electrical supply where an assumed percentage of the total various electrical loads 68 is known as the assumed economic diversity allowance ‘diversity’.

Switching from gas boilers to heat pumps and associated thermal stores means that the Amperage and kW rating for electric powered heating and domestic hot water equipment including immersion heaters may increase electrical loads beyond the supportable level of economic diversity and therefore, beyond the load rating of the single phase supply. For example, a building or dwelling may have a connected electrical load 68 totaling >150A where the electricity meter can support a maximum current of 100A at any one moment in time.

However, heat pumps, thermal stores and EV’s for example substantially increase the connected loads, typically these may increase by ~3-19kW for both heating/hot water systems and EV and or battery storage charging requirements. Whereas, a single phase domestic electricity supply is available in various sizes having nominal current limits including but not limited to 40 A, 60A, 80A to 100A, where a 100A supply is equivalent to ~24kW.

Alternatively, the electricity supply may be upgraded to a 3 phase supply supporting higher Amperage loads, however this upgrade may or may not be possible and costs vary with an estimated average of £8000. Also, upgrading single phase to three phase has the potential to virtually treble electricity loads beyond the network’s current levels. Therefore, there is a balance to be struck between network capacity and existing domestic energy loads plus the anticipated additional requirements for a building or dwelling’s space heating/hot water and EV and or battery storage needs.

Therefore, it’s likely that the required dynamic and start current electrical loads from new electrically operated heating/hot water and EV and or battery charging systems would place an unacceptable strain on the electricity demands of the supplying meter/ fuse/ circuit breaker relative to its maximum amperage rating.

To prevent this situation from arising and to enable higher power electrical loads including but not limited to, heating/hot water and EV and or battery storage systems to be installed in buildings, with the type of installed single phase electrical supply meters to be normally found in domestic properties the inventor has realised that the switching of loads needs to be controlled. In an embodiment of this disclosure a current sensor 70 is arranged to measure the amount of current being drawn and to provide this information to a controller 60 where the electrical connection (be that power or control signals) between appliances, applications or devices including but not limited to, sensors, controls, heaters, meters, EV and or battery storage systems is represented by a solid line extending between them. Also, current sensor 70 could be of any suitable technology for example but not limited to inexpensive technologies including a Hall sensor, or inductive sensors such as current clamps or a Rogowski Coil.

The system controller 60, figure 3, is arranged to be aware of the electrical meter installation supply’s (meter’s) maximum amperage rating or permitted load, and is responsive to a measurement of the instantaneous (or near instantaneous current) being drawn from the supply 64 by virtue of data provided by the current sensor 70. With this information it becomes possible to manage the current being drawn by appliances, for example but not limited to, thermal store 270 with heaters 16,17, 18 and EV 250, and/or fixed battery storage 260, electric vehicle 250 and heat pump 280.

The controller may be provided as a hardware unit in wired communication with the various components of the space heating and hot water system (270 and 280) and EV and or battery storage appliances. However advantageously the controller may be a distributed device. For example the sensors or appliances remotely addressable by, for example but not limited to PAS 1878 or as an “Internet of Things”, IOT, device. To help facilitate distributed communications, each appliance, application or device may be assigned an IP address and controlled by way of internet style commands either delivered by wireless communication within a dwelling or sent over existing wiring, such as the mains supply (as is already done by Powerline adaptors). Once the controller becomes a distributed device one or more of its functions can be exported to remote computing facilities. Thus the controller 60 may act as a gateway to a cloud based software service. Thus the appliances including but not limited to, space heating and hot water heaters and EV and or battery storage systems can be controlled in a way that is reactive to the maximum electrical supply current available from the metered supply, as well as the real-time dynamic electrical demands through the meter/supply, these being continuously communicated to the system controls.

Therefore, as controller 60 is instructed to or learns to predict patterns of electrical loads for each registered user’s appliances, applications and devices, it becomes possible to both predict future electrical demand periods in association with changing tariff periods and provide a further energy management and electrical load control for improved energy efficiency, energy cost reductions and critically to prevent the overloading of the supplying meter’s maximum rated output. Also, controller 60 is aware of the battery status and power reserves for EV and or battery storage systems and may elect to use this power to improve diversity of in-use appliances, applications or devices and to create an emergency power reserve capacity that varies in total capacity dependent on the predicted electricity network supply or electrical loads.

For appliances, applications or devices that support variable current input electrical loads, for example but not limited to thermal store immersion heaters, EV charging and or battery charging and storage devices that are predominately heated and or receive their operational power from electricity supplied by the supplying electric meter, then it is now possible to significantly increase electrical loads to these appliances, applications or devices during for example but not limited to, otherwise low electrical power periods. Therefore, it is now possible to install and operate for example but not limited to, higher power electrical heaters or EV and or battery storage charging systems that increase the scope for diversity across the building or dwelling’s electrical distribution system to approach or reach the maximum economic or emissions benefit of the viable rate of the meter installation’s amperage main fuse or permitted limit. Additionally in such circumstances as the controller 60 decides that the supplying meter is at or approaching the limit of it’s main fuse limit, the controller 60 may opt to segregate current by adding additional power from battery storage, such that the electrical distribution system operates in excess of the meter main fuse limit. For example, but not limited to, where controller 60 notionally transfers one or more appliances, applications or devices of the domestic electrical loads 68 from the supply grid and chooses to supply one or more of these with battery power such that within the dwelling or building the total current consumed by the plurality of devices therein is greater than the supplying electric meter current load. It is therefore possible to temporarily increase the power supplied to one or more thermal store heaters 16, 17, 18 and or EV 250 and or dedicated battery charging and storage system 260 or EV 250.

To put this in context consider by way of a non-limiting example a dwelling where a -100A supplying meter provides current for a fixed or time phased ~19kW fast charge for an EV batter}', current for a heat pump system including thermal store with up to 20kW variable input heaters, and a dedicated 3 to 7.2 kWh battery storage system. The controller 60 could prioritize the current supply during one tariff period to one of the loads such as the heat pump while at the same time using a dedicated ~3-7.2kW battery storage system or one or more EV battery capacity to provide power to one or more essential or emergency applications, appliances or devices, for example but not limited to, a fridge, a freezer, a cooker, a medical device.

Advantageously, the controller’s 60 power management intervention enables variable additional current to the meter’s maximum available current limit to power increased kW heat input or rapid charge to thermal stores or battery storage to be achieved during limited time low or surge tariff periods for the benefit of lower costs, emissions and improved energy efficiency of the building or dwelling.

Furthermore, the controller may be adapted to learn to recognise one or more appliance, application or device specific start current and operational pattern of flow of electricity profile demands. This may be achieved by using for example but not limited to analysing the changing current or voltage profiles resulting from use of a device. Such analysis can be performed by supplying the changing current or voltage profiles to an audio fingerprinting device or algorithm. The voltage and frequency of the flow of electricity for the one or more appliance, application or device use of power is analysed so as to create a flow of electricity ‘digital’ fingerprint of one or more power control cycle, for example, a washing machine may have one or many power cycle strategies, cold wash or hot wash, fast or slow spin, meaning that the time duration and flow of electricity varies depending on the selected washing machine power control cycle selected.

The flow of electricity may be analysed in real time or may be recorded and converted into a suitable file format and processed by audio fingerprinting software used to generate a computer referenceable library of audio fingerprints of one or more appliance with one or more power control logic that can cooperate with one or more cloud service or instance of a cloud service, controller and one or many users.

Thus the use of a device can be inferred from its modulation of the current supply. As an alternative a device may be associated with a smart plug where the smart plug provides a plug identification signal when the device or devices supplied by the plug draw power. The controller is then arranged to recognise a specific appliance and or smart plug configuration. This may be achieved by a pairing process between the controller 60 and one or more target appliance, application, device or smart plug.

Controller 60 may be pre-configured with, or is arranged to maintain by addition and deletion, a library of smart plug digital fingerprints for one or more appliance, application or device. The one or more smart plug(s) is configured to produce a respective plug or product identifiable voltage signal or unique flow of electricity identifier for noncurrent varying appliances, applications or devices for example but not limited to a plug in kettle, hairdryer, vacuum cleaner or light. The smart plug unique identifier enables the controller 60 to recognise the use of the one or more appliance, application or device and therefore improve control of the flow of electricity in order to manage diversity for the sake of powering one or more application, appliance or device. The smart plug approach can also be used to identify current varying appliances such as washing machines and freezers and the approach can be adapted to provide a permanently wired monitoring module for identifying the current drawn by larger loads such as heat-pumps.

In use the controller 60 switches current from one or more battery storage or EV battery to power essential and or emergency needs leaving the maximum available current from the supplying electricity meter to power, for example but not limited to, an air conditioning unit or a heat pump system including fan coil unit including circulation pumps, defrost heaters or other high flow of electricity demands where the start currents or combined current demands could otherwise overload the notified current limit and or meter installation’s main fuse limit of the one or more supplying electricity meter(s).

Therefore, if the energy provider uses dynamic pricing then the controller 60 may vary its strategy based on price. For example, windy conditions may result in an over-supply of electricity from wind turbines. If this was to occur at time of low demand, then the supplier may drop the energy tariff for a short period of time to encourage users to take energy from the grid. Thus, for example, the price of electricity could drop for a short time (say thirty minutes) due to excess generation capacity early in the morning. The controller can respond to this cheap electricity by seeking to suppress the use of electricity for all non-emergency or non-essential needs, for example but not limited to, toaster, cooker, vacuum cleaner, hair dryer, heat pump, and or kettle and therefore utilise the full allowable capacity of the one or more supplying electricity meter for only emergency and essential power needs while allowing up to the maximum remaining potential current draw available to fully heat a thermal store and to a higher temperature than would normally be the case or to charge a battery storage system or one or more EV batteries within that thirty minute drop in the energy tariff period of lower cost electricity. This is particularly important as single phase electricity supplies to one or more meter may be limited to ~13.8kVA being ~59Amperes at 220V meaning that prioritising the allocation of the flow of electricity through one or more supplying meter becomes critical to sustaining and maintaining essential services within the building or dwelling. Just focusing on this point, although a building may have an 80 Ampere or 100 Ampere main fuse, the supply grid was built with an assumption it would never have to concurrently supply 80 Amperes or 100 Amperes to all the connected buildings concurrently.

Consequently the authorities charged with maintaining the supply infrastructure may wish or mandate that the maximum load drawn by a dwelling or building is limited to less than the maximum load supported by the main fuse. The supply companies can monitor compliance with this wish or mandate by use of a smart meter as it can monitor the current supplied from the supply grid to the dwelling. It therefore becomes possible for the authorities to apply a sanction for excessive current draws over, for example a current equating to a power consumption of 13.8kVA or such other limit as the authorities deem necessaiy.

For example, the current needed to fully heat a thermal store or recharge a battery storage device may require drawing 9kWh of energy in thirty minutes, equivalent to an 18kW load. This may equate to roughly the maximum current that can be drawn from a non-upgraded single phase -lOOAmperes main fuse limited electricity supply. To do this it can be seen that the maximum heating power of the water heaters is much greater than would have been the case in prior art single phase powered thermal store systems in order to legally comply with, for example (but not limited to) the economic viability of supply as defined in the Uk’s BS 7671:2018 Requirements for Electrical Installations, IET Wiring Regulations.

Also the controller needs to monitor the current being drawn to make sure that the heating load or battery system charge rate is modulated to take account of other loads for example but not limited to essential and or emergency power needs, so that the maximum power is available for heating of a thermal store or recharging of a battery or that the start current for an appliance is as rapid and cost effective as possible without exceeding the notified or current supply limit of the dwelling or compromising the function of essential or emergency appliances, applications or devices.

Additionally, the electric charging rate and or heat input loads and or start currents and or battery storage and or EV batteries may be time shifted to improve energy efficiency, control higher energy costs or to meet general load needs such as at times when for example but not limited to, one or more other electrical loads would limit the system’s ability to meet the space heating or domestic hot water needs.

A dwelling may comprise multiple loads of one or more different types, as shown in Figure 4. These might be divided into different categories of priority depending on whether the load can be delayed or time shifted. For example essential or emergency loads might include cookers 200, as electric ovens might be seen as priority loads which take preference over other loads, tariff depending. The same might be true of medical devices, televisions and computers. These can be assigned priority 1 essential loads. Loads such as freezers 210 can be delayed a bit without problem, so might be identified as priority 2. Washing machines 220 and tumble dryers can generally be delayed for several hours and might be identified as priority 3. Loads such as vacuum cleaners 230 may be classified as truly discretionary and given a lower priority, priority 4. Electrical vehicle charging hub 250 may be given a dynamic priority allocation if the controller knows when a journey is likely to be made. Thus if a user indicates that a vehicle is required to drive to work each morning and the journey distance and time has been identified then the controller can give the electric vehicle a low priority if the vehicle already has sufficient charge. If the vehicle has an insufficient charge the priority can be set based on the duration to the next expected journey and elevated as time progresses.

Each of the loads may be fitted with an individual current monitoring and switching device 200A, 210A, 220A, 230 A. These devices could be provided as part of a plug, part of a socket or a module placed in the wires of the device or be integral to the device. The electric vehicle charging station can already be expected to include current monitoring and control capability although the range of charging rate can be increased from for example, 7kW extended to 19kW or even 24kW for a 1 OOAmperes single phase 240V supplying meter capacity by taking account of the controller 60 power management capabilities. Each current monitoring and switching device can communicate with the controller 60 either by a dedicated communication link such as link 252, to the electric vehicle charging hub 250, 272 to the thermal store 270, 282, to the heat pump 280, and 262 to the battery storage device 260 (such a link or links may be wireless) or by using power line technology to send data over the mains wiring as is the case for example but not limited to, monitoring and switching devices 200A 210A 220A and 230A.

Load priorities may change in line with changing tariffs or actual power needs or specific coefficient of performance of one or more appliance, application or device, such that a priority load 1 may be downgraded when the use of one or more loads might impact the cost saving or stored energy benefits from selectively switching current to and for the benefit of faster, high capacity recharging of an EV during low tariff periods.

Thus for each device the controller 60 can be appraised in real time of the load the device is using and/or whether an attempt is being made to turn a device on. Thus the controller can look at the predicted and prevailing current load and enable the switching of one or more priority 2 priority 3 and priority 4 devices on (as appropriate) when their demand can be serviced, taking into account all the other loads to make sure that a maximum current is not exceeded.

There is of course a continuum of options between these extremes and a “master priority” may be set for the system by virtue of a slider or dial on a controller interface (such as an app). Such a user interface is shown in Figure 6. Indeed individual users may identify themselves to the controller and specify their individual preferred appliance, application or device priority needs so that the controller can seek to meet the anticipated loads whilst seeking to reduce costs but also seeking to assure an acceptable level of system performance. Users may identify their presence in the house by any suitable means, but given that most people have mobile phones a convenient way is for a wireless interface to detect the presence of individual user’s phones for example via the phone connecting to the house Wi-Fi.

Advantageously the controller also takes electricity cost into account. In some cases this may include suggesting that some loads (such as the vacuum cleaner) be delayed to a time when power is less expensive. Suggestions that a load should be deferred may be made via a text message or email via an app or web page, or a power controller associated with the load. Thus a power controller may be provided as a module that may be interposed between the plug of the appliance and the Wall socket (e.g. effectively take the place of the plug or be a smart plug) or for example be some form of control logic in an appliance such as PAS 1878 to give an audible or visual indication to a user that it would be advantageous to use or delay use of the appliance, for example but not limited to, audible sound signals such as an sequence of on off alarm sounds or an occulting or flashing light pattern to indicate status in the same way as SOS dots and dashes are used in Morse code to send a message where messages for example but not limited to may include minutes to wait for use of an appliance or tariff costs or minutes left for using an appliance. Alternatively and/or additionally the power controller may pulse the device on and off a predetermined number of times and if the user still continues to try and use the device this can be taken as an indication that the user wishes to use the device now. Where a load controller is associated with a refrigerator or freezer it may be adapted to monitor the temperature of the freezer. Thus a freezer could be allowed to warm a bit more than usual when electricity is comparatively more expensive and may even be set to target a lower temperature when electricity is comparatively less expensive.

As noted earlier the move to more use of renewable energy can result in mismatches between when electricity is being generated and when consumers wish to use it. The most obvious example of this occurs in the context of space heating which is generally required in winter just when solar panels contribute little or nothing to the electricity supply. However large wind farms can be expected to be more productive in winter and may result in quite a large amount of power being generated when most people are asleep and businesses shut. This may result in providers using smart meters to set a low tariff price, as shown in Figure 5 between midnight and 3 am. The price might change during the night, getting reduced further in this example between 3 and 4am. Then as increasing numbers of people get up, wash and eat, and as heating systems come on the overall demand from the grid rises and the real time electricity price may rise reaching a peak between 06: 15 and 08:30 in this example before starting to reduce again as people leave home. If these changes become predictable or are flagged in advance by the electricity providers it becomes possible to move some loads from relatively costly periods to less costly periods. Thus, the controller 60 may decide to warm a thermal store between 3 and 4am to reduce the user’s heating costs. This paradoxically may slightly increase the amount of energy that the user uses (due to heat loss from the store) but overall reduces the user’s energy bill, and is more advantageous to the network supply as it uses the excess capacity of intermittent renewable energy that would otherwise go to waste or where wind turbines are switched off during windy days so as to protect the grid from over supply of electricity during low demand periods.

Advantageously, the controller has a calendar and is informed of the energy billing periods so that the controller can inform a user to defer energy use leading up to the end of a billing period. For example but not limited to, the controller and or the controller working in cooperation with cloud based software services may adjust a thermal store to a lower temperature or defer charging a battery storage device or EV at the end of a billing period and then make good the temperature of a store or battery charge at the beginning of a new billing period.

The transition to the electrification of heating and transportation services creates new energy supply issues where the UK as well as many nations across the world face critical primary energy, electrical generating and distribution challenges that potentially may lead to the failure of the national supply grid to be able to meet these challenges.

To help better manage the balance of the holistic energy system and to the betterment of all stakeholders, the inventor recognises that it is known that weather related impacts, TV schedules and/or but not limited to, other significant national events can place predictably high levels of electrical demand on the electrical supply grid at critical times that may lead to the future failure of the electrical supply network and therefore, power cuts. For example but not limited to, where news report indicates that energy may be in short supply, then users may rush to use or store as much energy as they can, as happens when petrol/diesel supplies are disrupted and drivers will panic buy fuel for both their immediate needs and for stock meaning that the system of supply more easily fails than may or may not have been the case had drivers cooperatively rationed their own use of fuel.

Advantageously, to help protect electricity grid supplies against potentially damaging power cuts or panic use in response to new information, the controller 60 in cooperation with a cloud based software service receives data updates from information sources. Such sources may include but not limited to, Govememnt information sources, the stock market, electricity generation, transmission or distribution stakeholders, UK’s Met Office, the Balancing Mechanism Reporting System, BMRS, or entrepreneurial sources including grid.iamkate.com. Other equivalent services can be expected to exist in other countries. Information received about potentially damaging future events help inform the controller 60 either alone or in cooperation with a cloud based software service to assess the need to predictively act to raise or not raise the temperature of for example but not limited to, one or more thermal stores or to bring forward, increase or delay the recharging of battery storage devices or EV batteries and/or to time shift the electrical inputs during the critical events so as to lower the actual and dynamic electrical current required during the significant event period. This may be the case even when the act to predictively warm a thermal store or add additional charging of a battery storage system or EV occurs during a higher tariff period where normally the controller would prevent such a warming or charging of a battery storage system or EV battery.

Additionally, the controller and such a controller in cooperation with a cloud based software service can inform users and suggest alternative times for pre-planned priority loads that coincide with the predicted future critical event, for example but not limited to, when for any reason future power cuts are predicted.

In some embodiments an appliance that does not have variable power control logic, for example a plug in kettle, may be fitted with a smart plug or adaptor that in addition to audible or visual signaling is configurable to generate a voltage signal, for example, an identifiable or encrypted pulse of voltage for example but not limited to, a smart plug working in cooperation with a kettle may signal a Morse code burst of current to spell KETTLE in the form of an identifiable audio fingerprint and or, where the current burst is in an encrypted form when the power to the kettle is plugged into a power socket and or switched on and or off. A further embodiment of the system is where the controller 60 communicates with battery storage systems and EV controller such that when the stored battery power is in excess of essential or emergency priority loads then this additional battery power could be sold to a third party at an increased tariff cost or benefit from what it would cost to recover the battery charge from grid supplies. Selling electricity from battery storage back to the grid could form an intrinsic function of a symmetric energy grid where power generation occurs both upstream and downstream of a supplying meter.

As noted before, the system includes the concept of meeting user’s needs and each user may specify their needs directly to the system. However the system may also adapt to the presence or absence of specific users. The system may include means to actively predict appliance, applications or device use by but not limited to, the thermal imaging of people entering or leaving a building, taking the average weight of a person as an indication of number of people in a building, or the detection of mobile phones and wifi connections or other passive measures of calculating predictive heating and hot water needs.

The system may also educate users to the cost of their energy use and how the energy cost varies throughout the day. The controller may, via a suitable interface, generate an electricity bill identifying for example but not limited to, use costs, savings or emissions for individual appliances, applications or devices and inform users of changing electrical tariffs and calculate a future cost to pre-planned use of appliances, applications or devices thereby helping users to become more aware of their service delivery costs. The controller may also recommend alternative times for lower electrical tariff periods for preplanned energy demands.

It is thus possible to provide an electric power management system incorporating a controller and such a controller working in cooperation with a cloud based software service that provides a means by which to automatically, but not limited to, receive frequently changing energy tariffs and network loads so as to control the electrical current for appliances, applications and devices to improve upstream and downstream efficiency from a supplying single phase electricity meter with the aim of profiting from the sale of electricity, reducing dynamic energy loads, lower energy bills and harmful emissions in support of the government’s net zero policy objectives.

It is thus possible, in some embodiments, to provide a system where a user registers themselves as a registered user of an energy management system incorporating a controller working in cooperation with cloud software services. The system incorporates a novel electricity flow monitoring and recording system.

In some embodiments the system may cooperate with an electricity supplying authority that determines one or more variable suppling maximum current value and or electricity tariff by user, appliance, application or priority need. Therefore, the supplying authority can prioritise more or less power for essential and non-essential appliances, applications or device needs. For example but not limited to, a time varying tariff may be applied that lowers the cost of charging a mobility scooter while at the same time increasing the tariff for charging a high end Electric Vehicle

In some embodiments the system may cooperate with third party organisations that offer tariff discounts in support of achieving carbon reductions by incentivising a user to use electricity at a time and for a need that is in support of reducing harmful emissions

In some embodiments the present disclosure provides for the introduction of itemised energy billing by prioritisation of user, appliance, application or device need. An appliance that uses power control logic, for example but not limited to, a washing machine, or heat pump where the appliance use of power is varied, is configured with a power supply and means for measuring voltage and/or current fluctuations.

In operation of some embodiments, a controller includes means that continually monitors the flow of electricity and optionally records the use of electric digital fingerprints for power control logic devices and smart plug signal bursts.

In use the method may act to Anticipate not just start time but duration of appliance operation to see if it will overlap with changing tariffs and therefore assess the composite of energy costs for the completed power use.

Claims

1. A method of controlling energy use on the consumer side of a connection to a supply network, where the connection has a maximum permissible current rating and where devices on the consumer side include at least one load and at least one battery, and wherein a controller is responsive to a measurement of current in the connection and a time varying electricity tariff to control the charging of the battery, and wherein the controller can increase the current used to charge the battery up.

2. A method as claimed in claim 1 in which the controller can disconnect at least one of the loads to increase the current used to charge the battery.

3. A method as claimed in claim 1 or 2 in which there are a plurality of loads and individual ones of the loads can be associated with a priority such that loads can be inhibited or allowed to operate based on their priority and/or a user policy.

4. A method as claimed in claim 1 , 2 or 3 in which the maximum permissible current rating is the least of a current defined by a fuse or a circuit breaker and a notified current limit set by a supply network operator.

5. A method as claimed in any preceding claim where the battery is at least one of : a) a static battery ; and b) a battery in an electric vehicle, and the controller is operable to draw power from the battery to supply energy for use on the consumer side of the connection between the consumer and the supply network or to supply energy to the supply network.

6. A method as claimed in any preceding claim wherein the at least one load comprises a plurality of loads and the controller is responsive to a measurement of current to identify a given load from the flow of current to the plurality of loads.

7. A method as claimed in any preceding claim further comprising associating one or more loads with respective interface units that connect the load to a power socket or wall plug, and where the interface units are adapted to identify the attached load or a load priority to the controller and to respond to the signals from the controller to allow or inhibit supply of power to the associated load.

8. A method as claimed in claim 7 wherein one or more of the interface units are provided with means for identifying a load attached thereto by reference to the current profile of the load and/or voltage changes resulting from use of the load.

9. A method as claimed in any of the preceding claims where the controller is adapted to learn a pattern of use for one of more loads and to recommend or control use times to reduce operating costs.

10. A method as claimed in claim 5 in which the amount of supplying electrical current used for appliances, applications or devices may exceed the supplying meter main fuse limit by the total available current from the battery storage and or electric vehicle battery output capacities.

11. A method as claimed in any preceding claim in which the amount of supplying electricity used to power appliances, applications or devices is adjustable up to a maximum value which substantially matches a maximum permitted current draw to the building or dwelling.

12. A method as claimed in any of the preceding claims in which the amount of electricity used to power the recharging of the battery is adjustable up to a maximum value where the maximum value is greater than 3kW and less than 99.9% of the maximum permitted current draw through the connection to the supply network.

13. A method as claimed in any of the preceding claims in which a heat-pump system and/or a thermal store is provided on the consumer side of the connection and the amount of electricity used to power the starting of a heat pump system or the heating of a thermal store is adjustable up to a maximum value where the maximum value is greater than 3kW and less than 99.9% of the maximum permitted current draw through the connection to the supply network.

14. A method as claimed in any preceding claim in which the controller is informed of or learns the likely pattern of use of appliances, applications and devices including heat pump and electric vehicles and schedules the use and electrical current needs for and including, the heating or charging of such appliances, applications and devices to reduce energy cost.

15. A method as claimed in any preceding claim in which the controller is informed of or learns the likely pattern of energy cost variation and schedules the electrical current needs for appliances, applications and devices including heating of one or more thermal stores, operation of a heat pump system and or charging of a battery storage and or electric vehicle battery so as to reduce energy costs.

16. A method as claimed in any of the preceding claims in which the controller is adapted to be responsive to measurements of current drawn by respective devices within the dwelling or building supplied by the supplying meter and the controller is adapted to communicate with a device or a power controller associated with the respective device to vary the power supplied to the respective device.

17. A method as claimed in any preceding claim in which users can register with the controller, and wherein a user can inform the controller of their specific heating or hot water requirements.

18. A battery storage and/or electric vehicle battery system and a controller for controlling the charging of one or more battery storage and/or electric vehicle battery, wherein the controller is responsive to a measurement of the current being drawn from a supplying meter having a nominal maximum current value and the controller is operable to modulate the amount of current used for the charging of one or more battery systems in response to the measurement of the current.

19. A system as claimed in claim 18 in which the controller is responsive to information about a time varying energy cost and is arranged to schedule charging of one or more battery storage or electric vehicle battery system so as to reduce operating costs of the system.

20. A system as claimed in claim 18 or 19 where the supplying meter supplies a heat pump installation and the controller is responsive to the required start current loading of a heat pump installation including fan coil unit and circulation pumps, where the start current is in excess of the normally supportable load from a domestic meter with a maximum fuse rating of up to and including 100A

21. A system as claimed in claim 18, 19 or 20 where one or more thermal stores are provided which comprise a first heater for heating water where the first heater is supplied by the supplying meter and is electrically operated to a maximum current in excess of the normal supportable load from a domestic meter with a maximum fuse rating of up to and including 100A.

22. A system as claimed in any of claims 18 to 21 where the controller is adapted to estimate at least one of battery storage and/or electric vehicle battery and heat pump and one or more thermal stores electrical current loads within a period of time and to enable such current so as to meet the target battery charge, start current or temperature sufficient to meet the aforementioned appliance, applications or device demands within that period of time.

23. A system as claimed in claim 22 in which the period of time is one of a plurality of periods of time defined with reference to a clock or a combination of a clock and calendar.

24. A system as claimed in any of claims 18 to 23 where the battery storage and electric vehicle and heating hot water systems achieve their target operational charge or temperature as calculated by the controller as a function of an expected need for battery capacity, electric vehicle bater}' range and heating and/or hot water load in response to a measurement of or predicted external temperature.

25. A system as claimed in any of claims 18 to 24 where the controller is responsive to warnings of high energy demand on an electricity supply and is adapted to modify the target needs be they battery charge capacity, start current operation of a heat pump or temperature of one or more thermal stores to facilitate meeting expected current needs during a high energy demand period.

26. A system as claimed in any of the claims 18 to 25 where the controller’s operation is distributed between a local unit and a cloud based service.

27. A system as claimed in any of claims 18 to 26 where the controller is responsive to electricity cost and cost schedules to preferentially charge battery storage and electric vehicle and/or heat one or more thermal store when electricity is less expensive.

28. A system as claimed in any of claims 18 to 27 where the controller is arranged to schedule and/or inhibit the operation of electrical loads as a function of cost or current drawn from the supply.

29. A system as claimed in any of claims 18 to 28 where the controller is arranged to schedule the selling of electricity from one or more battery storage and electric vehicle batery as a function of cost of the supplying electricity.

30. A system as claimed in any of claims 18 to 29 in which the controller is informed of or learns the likely pattern of use of stored battery capacity from one or more battery storage and electric vehicles within the building or dwelling and schedules variable charging rates of one or more batteries to reduce the future energy cost and/or in which the controller is informed of or learns the likely pattern of energy cost variation and schedules charging of one or more bateries to reduce the energy cost.

31. A method of controlling an electrically operated heat pump and one or more associated thermal stores where the method predictively controls the amount of start current and electrically generated heat input to the system in response to variable electricity price tariffs and real-time electrical current loads through the supplying electricity meter.

32. A battery storage and electric vehicle batery and heat pump with one or more thermal stores operating as a system that further comprises a controller and current measurement sensor for determining the varying levels of start current and heat input needs for one of space heating and one of hot water heating.

33. A method of controlling energy use on the consumer side of a connection between a consumer and a supply network, where the connection has a maximum permissible current rating and where devices on the consumer side include a heating system, a further load and at least one battery, and wherein a controller is responsive to a measurement of current in the connection and a time varying electricity tariff to control the heating system, and the controller is operable to disconnect the further load to increase the current used to the heating system and/or a charger for the battery up to the maximum permissible current rating.

34. A method of controlling the use of electricity in a building or a dwelling, where the building or dwelling contains a plurality of devices and the method comprising providing means for identifying the load that one or more of the devices presents, and associating a device with a respective electricity consumption tariff, such that a plurality of tariffs can be applied concurrently.

35. A method as claimed in claim 34 in which a tariff associated with a device can vary dynamically based on a property of the device.

36. A method as claimed in claim 35 in which the device is an electric vehicle and the tariff can vary as a function of the state of charge of the electric vehicle.