GB2508755A

GB2508755A - Renewable Energy Supply and Demand Management System

Info

Publication number: GB2508755A
Application number: GB1403873.1A
Authority: GB
Inventors: Thomas Jolyon Beese; Michael Harasimiuk
Original assignee: Individual
Current assignee: Individual
Priority date: 2014-03-05
Filing date: 2014-03-05
Publication date: 2014-06-11
Also published as: GB201403873D0

Abstract

An energy management system 10, comprising a controller 12 controls one or more energy consumption devices 18 in a premises such that a short-term optimal energy consumption target and a long-term optimal energy consumption target are met. User preferences are provided via a user interface 20 relating to energy-consumption related parameters 22 for the premises. A renewable-energy condition data receiver 24 receives short-term and long-term renewable energy forecast information. A processor 28 determines an energy requirement by ranking, in order of importance, the energy-consumption related parameters 22 according to the user preference, and determining a short-term renewable energy availability based on the short-term renewable energy forecast information, and a long-term energy availability based on long-term renewable energy forecast information from the renewable-energy condition data receiver 24. The processor 28 determines a short-term optimal energy consumption target and a long-term optimal energy consumption target based on the energy availability against the energy requirement of each energy-consumption related parameters 22, and outputting a processing signal to the controller 12 so that the controller 12 can control the energy consumption devices 18.

Description

Dynamic Energy Management System The present invention relates to a dynamic energy management system, and a method of controlling energy supply to one or more energy consumption devices using said dynamic energy managcrncnt system.

To date, energy supply has been managed principally on the basis of energy demand.

During periods where energy demand is known or predicted to be high. for instance in early mornings and early evenings, energy suppliers increase non-renewable energy supply, such as fossil fucl, to meet this heightened demand. Whilst the supply of energy from non-renewable energy sources can be manually adjusted, the environment and/or weather conditions during the peak periods may not provide adequate supply of renewable energy to sustain demand.

During peak energy demand periods. energy demand may exceed energy generation capacity. To manage this, extra capacity olten has to he built into non-renewable energy power supply stations, for instance gas-fired power stations, in order to cope with the temporary surge in demand. However, the extra capacity is underutilised during non-peak demand periods.

There have been persistent efforts to try to substitute non-renewable energy sources with renewable energy sources, and to thereby improve the efficiency of energy consumption in general. This has become particularly important worldwide, as various countries have pledged to reduce their carbon emissions.

One way of improving efficiency of energy consumption in a domestic situation is by setting energy consumption parameters or targets rdatcd to an energy consumption unit. For example, it is known to set time periods to he activated and/or ambient temperature to be achieved for a central heating system in a premises. The central heating system is therefore constantly being regulated, with the aim of maintaining the system at a level in accordancc with set paramctcrs.

To increase the efficiency of such a central heating system, thermostats with increasing sophistication arc providcd in the premises to accuratcly monitor the ambient temperature. in order to reduce overshooting and undershooting of the temperature of the central heating system. In recent years, digital controls have been made available to monitor the energy related performances of the premises, such as heat loss and heat retention, so that these can he factored in when regulating the central heating system.

In another example, many electrical appliances, for instance a washing machine or oven, allow a user to set a time in which the appliance is to be switched on, and for how long. Therefore, the oven may be activated in the absence of the user, such that a meal is cooked and ready for when the user returns to the premises. This pre-planned activation of electrical appliances helps to smooth energy demand during peak demand periods. Computer programs or applications are also available for computers and mobile telecommunications devices, such as smartphones', which allow the user to be able to wirelessly control electrical appliances.

Although the abovementioned technologies smooth demand, which can help in some way to reduce the use of non-renewable energy and improve energy efficiency, it does little to encourage or increase use of renewable energy. When energy is scheduled to bc required for powering one or more electrical appliances, the demand needs to be met, regardless of whether weather conditions are favourable for renewable energy gcncration. Furthermore, these tcchnologies are usually premises specific, thus cach premises, whether it is a domestic property or a conmiercial premises. is managed on its own and independently.

As there is often a mismatch between when energy demand is highest and when weather conditions are most favourable for producing renewable energy, euergy suppliers have not been able to fully harvest all the renewable energy available when the renewable energy supply is at its highest.

When renewable energy supply exceeds demand, the renewable energy power stations may be temporarily switched oIL Therefore, renewable energy power stations are not reaching their full generation and carbon emission lowering potential.

It is an object of the invention to provide a dynamic energy management system which reduces or substantially obviates the ahovemcntioncd problems.

According to a first aspect of the present invention there is provided a dynamic energy management system. comprising a controller for controlling one or more energy consumption devices in a premises such that a short-term optimal energy consumption target and a long-term optimal energy consumption target are met or substantially met, and for receiving user preferences from a user interface relating to a plurality of energy-consumption related parameters for the premises, a renewable-energy condition data receiver for receiving at least short-term and long-term renewable energy forecast information, a processor adapted for determining an energy requirement by ranking, in order of importance, the plurality of energy-consumption related parameters according to the user preference, and determining a short-term renewable energy availability based on the short-term renewable energy forecast information and a long-term energy availability based on thng-term renewable energy forecast information from the renewable-energy condition data receiver, the processor dynamically determining a short-term optimal energy consumption target and a long-term optimal energy consumption target based on the energy availability against the energy requirement of each energy-consumption related parameter, the processor outputting a processing signal to the controller so that the controller can control the one or each energy consumption device based on the determined said short-term optimal energy consumption target and a long-term optimal energy consumption target.

Preferable and/or optional features of the first aspect of the invention arc set forth in any one of claims 2 to 28.

The dynamic energy management system is advantageous as the energy-consumption related parameters are prioritised in order of importance, the system activating the or each energy consumption target depending on the renewable energy available in the short-term and long-term. Therefore, the system can dynamically manage energy consumption of the or each device, such that it does not exceed or substantially exceed the renewable energy available. The ranking of the parameters takes into account what the user considers to he important, for example, heating of the premises or completion of a wash cycle of a washing machine, and prioritiscs activation of the or each energy consumption device accordingly.

The dynamic energy management system is a dynamic and flexible method of managing energy demand. Although the user can set energy-consumption related parameters based on his or her preference. each parameter is set such that it serves as a guide or reference point rather than an absolute target to be met, thereby allowing them to be ranked against each other in order of importance.

This removes the need to supply energy so that fixed, rigid targets set by the or each energy consumption device are met, the targets being usually activation time and/or temperature to be achieved.

Instead of the traditional rigid process of increasing energy supply in order to meet demand, especially during peak demand periods, the dynamic energy management system of the current invention dynamically and flexibly intelligently assess the level of renewable energy available in the short-term and long-term. The system manages energy demand in such a way that it maximises energy usage when renewable energy supply is high and minimises energy usage when renewable energy supply is low, whilst at the same time prioritising the more urgent energy consumption requirement over less urgent requirements. The system therefore undertakes a continuous review of the conditions and responds to opportunities to increase efficiency in meeting the user's prioritised requirements.

The dynamic energy management system therefore helps to smooth out energy demand in thnc periods which traditionally relate to peak energy demand, such as early evenings and early mornings. It also reduces the need to utilise or increase supply of non-renewahie energy sources to supplement the renewable energy supply when the weather is not favourable for utilising a renewable energy supply. The system therefore encourages use of renewable energy. which is the most effective way in lowering carbon emission.

The system also reduces the pressure to increase capacity and infrastructure relating to non-renewable energy to cope with peak energy demands, for example. from an ever-expanding population.

The dynamic energy management system allows individual buildings to he managed separately, but the system may also manage multiple buildings or properties as a single entity. This increases management efficiency and streamlines resources.

The ability for the system to analyse a short-term renewable energy availability and a long-term renewable energy availability allows the processor to anticipate changes in the renewable energy availability, which the system can then exploit to meet the demand most efficiently.

According to a second aspect of the present invention there is provided a method of dynamically controlling energy supply to one or more energy consumption devices in a premises by determining short-term and long-term optimal energy consumption targets and short-term and long-term renewable energy availabilities using the dynamic energy management system as claimed in any preceding claim, comprising the steps of: a] receiving user preferences data relating to a plurality of energy-consumption related parameters; hi receiving short-teirn and long-term renewable energy forecast information data; ci ranking, in order of importance, the plurality of energy-consumption related parameters data according to the user preference data and determining the energy requirement relating to the or each energy consumption device according to the energy-consumption related parameters data, and determining a short-term renewable energy availability based on the short-term renewable energy lorecasi information dala and a long-lerm renewable energy availability based on (lie long-term renewable energy forecast information data; d] dynamically determining the short-term optimal renewable energy consumption target and the long-term optimal renewable energy consumption target based on the renewable energy availabilities against the energy requirement of the or each energy consumption device determined in step ci; e] switching on or off the or each energy consumption device depending on the renewable energy availabilities and position of the or each energy consumption device on the ranking of importance determined in step ci.

Preferable and/or optional features of the second aspect of the invention are set forth in any one of claims 32 to 40.

According to a third aspect of the present invention there is provided a method of dynamically managing energy demand at one or more premises to maximise energy usage when a renewable energy supply is high and to minimise energy usage when renewable energy supp'y is low using a dynamic energy management system in accordance with the first aspect of the invention, the method comprising the steps of: a] receiving user preference data relating to a plurality of energy-consumption related parameters; hi receiving short-term and long-term renewable energy lorecast information data; ci ranking. in order of importance. the plurality of energy-consumption related parameters according to the user preference data and determining the energy requirement relating to one or more energy consumption devices according to the energy-consumption related parameters, and determining a short-term renewable energy availability based on the short-term renewable energy forecast information data and a long-term renewable energy availability based on the long- term renewable energy forecast information data; dj dynamically determining a short-term optimal energy consumption target and a long-term optimal energy consumption targct based on the renewable energy availabilities against the energy requirement determined in step c]; and e] automatically controlling the or each energy consumption device depending on the renewable energy avaflahilities determined in step di and position ol (lie or each energy consumption device on the ranking ol importance determined in step ci.

Preferable and/or optional features of the third aspect of the invention are set forth in claims 43 to 51, inclusive.

According to a fourth aspect of the present invention there is provided a method of dynamically controlling energy supply to one or more energy consumption devices at one or more premises by determining short-term and long-term optimal energy consumption targets and short-term and long-term renewable energy availabilities, the method comprising the steps of: a] receiving user preference data relating to a plurality of energy-consumption related parameters; h] receiving short-term and long-term renewable energy forecast information data; e] ranking. in order of importance.

the plurality of energy-consumption related parameters according to the user preference data and determining the energy requirement relating to the or each energy consumption device according to the energy-consumption related parameters, and determining a short-term renewable energy availability based on the short-term renewable energy forecast information data and a long-term renewable energy availability based on the long-term renewable energy forecast information data: d] dynamically determining the short-term optimal energy consumption target and the long-term optimal energy consumption target based on the renewable energy availabilities against the energy requirement determined in step ci; ci switching on or oR the or each energy consumption device depending on the renewable energy availabilities and position of the or each energy consumption device on the ranking of importance determined in step e].

According to a fifth aspect of the present invention there is provided a method of dynamically managing energy demand at one or more premises to maximise energy usage when a renewable energy supply is high and to minimise energy usage when renewable energy supply is low, the method comprising the steps of: a] receiving user preference data relating to a plurality of energy-consumption related parameters; b] receiving short-term and long-term renewable energy forecast information data; c] ranking, in order of importance, the plurality of energy-consumption related parameters according to the user preference data and determining the energy requirement relating to one or more energy consumption devices according to the energy-consumption related parameters, and determining a short-term renewable energy availability based on the short-term renewable energy forecast information data and a long-term renewable energy availability based on the long-term renewable energy forecast information data; d] dynamically detemilning a short-term optimal energy consumption largel and a long-term optimal energy consumption target based on the renewable energy availabilities against the energy requirement determined in step c]; and e] automatically controlling the or each energy consumption device depending on the renewable energy availabilities determined in step d] and position of the or each energy consumption device on the ranking of importance determined in step ci.

For a better understanding of the present invention, and to show more clearly how it may be carried into effect, reference will now be made, by way of example only, to the accompanying drawings. in which: Figure 1 shows a diagrammatic representation of one embodiment ol a dynamic energy management system, in accordance with the first aspect of the current invention, and Figures 2a and 2b diagrammatically depict the method of controlling energy supply to one or more energy consumption devices, preferably utilising the dynamic energy management system ci Figure 1, in accordance with the second aspect of the current invention.

Referring firstly to Figure 1. there is provided a dynamic energy management system which comprises a controller 12 provided in a housing 14. the controller 12 having a control circuit 16 for controlling at least one energy consumption device 18 in a premises, such that a short-term optimal energy consumption target and long-term optimal energy consumption t' *get are met or substantially met.

An energy consumption device 18 is any device that requires an input of energy in order to function, for instance, central and/or underiloor heating, or electrical appliances such as a washing machine, dishwasher, cooker and television.

The dynamic energy management system 10 further comprises a user interface 20 that is preferably accessible directly on the housing 14, to allow a user to enter his or her user preferences relating to a plurality of energy-consumption related parameters 22 for the premises. such as energy consumption targets.

The system 10 also comprises a renewable-energy condition data receiver 24. in the form of a renewable energy condition data circuit 26 provided as part of the controller 12, for receiving short-term and long-term renewable energy forecast information, preferably as well as current renewable energy information.

A processor 28, in the foim of a processor circuit 30 provided as pail of the controller 12. is provided in the housing 14 for receiving data from the user interface 20 and the renewable energy condition data circuit 26. The processor circuit 30 then utilises the information to dynamically determine short-term and long-term renewable energy availability and the energy requirement of the and each energy consumption device 18.

A data monitoring and storage module 32 is further provided in the housing 14 for collecting and storing data from the user interface 20, the renewable energy condition data circuit 26, the processor circuit 30 and the control circuit 16. The data monitoring and storage module 32 also collects and stores current renewable energy condition data, as well as performance related data, such as actual energy usage and energy efficiency, related to the or each energy consumption device.

Information stored in the data monitoring and storage module 32 can he recalled hy the user interface 20 and/or the processor circuit 30 to improve the accuracy of the processor circuit 30 when processing data.

The user interface 20 is hard-wired to the controller 12 to allow the user to input or adjust user preferences, which is to be received by the processor circuit 30 of the controller 12. The user interface 20 is also hard-wired to the data monitoring and storage module 32 for recording and storing such user preferences.

User preferences include energy-consumption related parameters such as carbon emission target data, energy consumption target data, energy consumption expenditure target data, temperature data of the premises to be maintained, and/or completion of at least one premises rdated task that requires energy input.

The premises related tasks include activation of household appliances, such as to complete a wash cycle of a washing machine or a dishwasher, activation of an oven or microwave for a certain period of time, switching on of lighting, and activating of a hot water system.

Input means 34, such as an input module 36. is provided on the user interface 20 to allow the user to select energy-consumption rdated parameters to which targets can be set. Preferably, adjustment means 38, such as an adjustment module 40, is provided on the user interface 20 so that the user can enter upper and lower limits of the target for each parameter. The dynamic energy management system 10 therefore aims to achieve a target within thc upper and lower limits for each parameter. and not a precise figure. This further provides flexibility when the processor circuit 30 dynamically determines the energy requirement of the and each energy consumption device 18.

Thc user interface 20 may further allow a user to rank the plurality of cncrgy-consumption related parameters 22 in their preferred order of importance. For example, if it is important for the user to reduce their energy bills, then the user may rank the energy consumption target having the highest priority, so that when the processor circuit 30 determines energy requirement, it will aim to not exceed the energy consumption target regardless of the energy demand and energy supply.

Alternatively or additionally to the sell ranking ol parameters by the user, the processor circuit 30. on receipt of the energy-consumption related parameters, analyses the lower and upper limits set for each target and logically ranks the parameters in order of importance. For example, if the target for maintaining the temperature of the premises is set by the user as a broad range, for example from 15°C to 21°C. and the targeted time to complete a wash cyde of a dishwasher is imminent, then the processor circuit 30 will determine that the completion of a wash cycle of the dishwasher is more important than maintaining the temperature of the premises. The processor circuit 30 will therefore rank the parameters accordingly and prioritise activation of the dishwasher over heating.

The lists of nmking, set by the user and/or the processor circuit 30, are storable in the data monitoring and storage module 32. The user interface 20 preferably includes a recall button, for recalling the target set for a particular energy-consumption related parameter, and also any one of the lists stored in the data monitoring and storage module 32. A selection button may also preferably be provided for selecting a particular list of rankings saved previously. The user interface 20 further preferably comprises an on/oil huRon For activating and deaclivating [lie syslem 10.

It is thus possible for a user to create multiple lists of rankings, for example, lists corresponding to each season of the year. and to save lists previously determined by the processor 28. These lists are stored in the data monitoring and storage module 32 and are recallable and reusable at any time.

Furthermore, overnde means may he provided On the user interlace 20 such that, when activated, the ranking received or deternuned by the processor 28 can be overridden by one or more tasks requiring energy input to he completed, regardless of the energy consumption target set by the processor 28. Details of the or each task can he inputted via the input means 34. For example, if a washing cycle oF the washing machine in the premises requires urgent completion. this requirement can he inputted via the override means, either by inserting this task as the first in the ranking. or reordering the ranking.

The user interlace 20 may also prelerably he controflable wirelessy. for examp'e. hy a data processing unit, such as a computer, or mobile telecommunications device.

such as a smartphonc.

It will bc appreciated that the input means 34. adjustment means 38. recall button, selection button and/or on/off button, may be provided virtually on a user display screen 42, such as an LCD screen.

The renewable-energy condition data receiver 24 is preferably provided with a wireless communication module 44 forming part of the renewable energy condition data circuit 26 and adapted to communicate and receive data remote from the renewable-energy condition data receiver 24. In particular, the wireless communication moduk 44 is adapted to communicate with a transmitter of at least one weather station 46, distanced from the dynamic energy management system 10, for receiving the short-term and long-term renewable energy forecast information.

The short-term and long-term renewable energy forecast information includes at least information that can be used to predict renewable energy availability, in particular but not necessarily exclusively solar energy, wind energy, tidal and/or hydroelectnc power. such as predicted cloud cover data, sunrise and sunset time, solar intensity data, wind direction data, wind speed data, atmospheric pressure data, rainfall data and/or tidal flow data.

In particular, the short-term renewable energy forecast information relates to a forecast preferably equal to or less than 5 hours ahead of time, and the long-term renewable energy forecast information relates to a forecast more than S hours, and preferably up to and equal to 72 hours, ahead of time. More preferably, the short-term renewable energy forecast information relates to forecast data in a range of 0.5 to 5 hours ahead of time, and the long-term renewable energy forecast information relates to forecast data in a range of 5 hours to 48 hours. However, long term could be as much as ten days to two weeks and/or potentially longer, dependent on the reliability of the data.

It will he appreciated that the renewable-energy condition data receiver 24 may communicate with more than one weather station 46. In particular, the receiver 24 may communicate with one weather station 46 to receive weather forecast information at a macro level, such as weather inlormation available on a national scale, and also a local weather station 46 to receive local area weather forecast information. Weather forecast at a macro level helps the processor 28 in determining the long-term energy consumption target, and weather forecast at a micro level helps in deteimining the short-term energy consumption target.

The wireless communication module 44 is preferably further adapted to communicate and receive information from a transmitter of one or more renewable energy generation units 48, such as a solar energy panel or a wind turbine, or a renewable energy power generation site containing multiple units. If the renewable energy generation unit 48 is offsite, then depending on the distance between the renewable energy generation unit 48 and the premises, the culTent renewable energy information related to the renewable energy generation unit 48 can help the processing circuit to determine the short-term or long-term renewable energy availability.

For example, if high wind speed is detected at a renewable energy generation unit 48 near the premises, and the wind direction is detected such that a wind turbine at the prcmiscs is cxpcctcd to gcncratc a largc amount of clcctricity from thc wind powcr, then the renewable-energy condition data receiver 24 receiving this information will communicate this to thc processor circuit 30. such that the processor circuit 30 factors this in when determining the short-term and long-term renewable energy availability.

Preferably, the wireless communication module 44 also receives current renewable energy information from the or each weather station 46 to help determine the short-term and long-term renewable energy condition data.

More preferably, if a renewable energy generation unit 48 is available onsite. or is very close to the premises, the wireless communication module 44 is further adapted to conmiunicate and receive current renewable energy information from such unit to obtain current renewable energy information. For example, current daylight level can be determined by detecting how much solar energy is currently being collected by an onsite solar panel. Alternatively, sensing means may he provided onsite to detect current renewable energy information and the information is communicated.

preferably wirelessly to the renewable-energy condition data receiver 24.

Further prelerably, the wireless communication modu'e 44 is further adapted to communicate and receive current renewable energy information from a wireless transceiver of one or more other similar dynamic energy management systems 50.

Such information can be used to help determine the short-term and long-term renewable energy availability associated with the premises.

Monitoring of the current renewable energy information allows the processor 28 to monitor and manage what is actually happening, compared to what is predicted. This ensures a continuous ability to revise the energy consumption targets based on real time data to exploit a sudden surge of renewable energy supply, or to reduce consumption if there is less than anticipated renewable energy supply.

The data monitoring and storage module 32 is adapted to store short-term and long-term renewable energy forecast information, as well as current renewable energy information, associated with the or each weather station 46 and/or the or each renewable energy generation unit 48 onsite and/or offsite. A renewable energy forecast for a particular time period and the actual renewable energy condition information for the same period arc linked, so that the processor 28 can make comparisons between the predicted data versus the actual data.

Preferably, the data monitoring and storage module 32 also monitors and stores short-term and long-term optimal energy consumption targets determined by the processor 28 associated with the same particular period, as well as the actual energy consumption for the same period, such that the processor 28 can also make compari soils between the two.

Preferably, the data monitoring and storage module 32 further comprises sensing means 52, such as a thermometer or an energy consumption sensor, to monitor energy efficiency data related to the or each energy consumption device 18 in the premises or the energy efficiency of the premises itself. For example. the ability of the premises to retain heat is monitored by the sensing means 52 and recorded by the data monitoring and storage module 32.

Another example of the sensing means 52 may he user presence monitoring means, such as motion sensing means, the purpose of which will be described later.

A leedhack circuit 53. provided on the data monitoring and storage module 32. may then provide feedback to the processor 28 regarding energy efficiency and user presence, along with demand requirements associated with renewable and non-renewable energy requirements.

The data monitoring and storage module 32 can preferably store lists of rankings selected previously by the user via (he user interface 20 or determined by the processor 28, so that the user may recall said list to be reused.

The data monitoring and storage module 32 preferably further comprises an outputting module 54 for outputting the stored data to the user interface 20 when recalled, for instance a particular list of rankings. and/or for outputting the stored data to an external device, such as a data proccssing unit and/or a mobile communication device.

Alert means 56, such as a text message. audio and/or visual prompt, is preferably provided on the data monitoring and storage module 32 to alert the user to data monitored and/or stored. Such alert may be displayed on the user interface 20, or may be sent wirelessly via a wireless communication module 58 on the data monitoring and storage module 32.

The processor 28 is adapted to receive the chosen list of energy-consumption related parameter targets from the user interface 20. if not already ranked, the processor circuit 30 of the processor 28 ranks the energy-consumption related parameters in order of importance. as described above.

On rcccipt of thc short-term and long-term rcncwablc cncrgy forecast information from the renewable-energy condition data rcccivcr 24, the processor 28 analyses the information to determine a short-term energy availability based on the short-term renewable energy forecast information, and a long-term encrgy availability based on the long-term renewable energy forecast information.

Thc processor 28 comparcs the cncrgy availability or supply against the cncrgy requirement related to the energy-consumption related parameters ranked in the order ol importance. to determine a short-term optimal energy consumption target and a long-term optimal energy consumption target.

The processor 28 is also preferably adapted to receive current renewable energy information from the renewable-energy condition data receiver 24. A comparison module 60 is preferably provided on the processor 28 for comparing the current renewable energy information against the predicted short-term optimal energy consumption target. and/or the predicted long-term optimal energy consumption target.

If there is a mismatch between the current renewable energy information and the optimal energy consumption targets and the mismatch is above a predetermined threshold, the processor 28 dynamically re-calibrates to revise the short-term and/or long-term optimal energy consumption targets.

For example, the short-term optimal energy consumption target is set to he low if the short-term renewable energy forecast information received by the renewable-energy condition data receiver 24 indicates that, for instance, low solar or light iiitensity level is predicted in the next 0.5 hour to 1 hour. However, if the current renewable energy information indicates that the current daylight levd associated with the premises is beyond a predetermined threshold, such that it is unlikely that the daylight level will be reduced to the level predicted by the short-term renewable energy forecast information, (lie processor 28 will revise at least lie short1errn op1ima energy consumption target to a higher level in order to exploit the currently available solar energy.

The processor 28 preferably associates each energy-consumption related parameter to one of short-term and long-term optimal energy consumption targets, taking into account the nature of the energy requirement of each parameter and its position in the order of ranking.

In particular, if the short-term optimal energy consumption target is high, then the energy consumption device 18 requiring short bursts or low levels of energy, for instance, the activaticri of a kettle or a sIwrt wash cycle of a dishwasher, will he prioritised to he activated over devices requiring long periods of or high kvels of energy requirement or devices that do not require immediate activation, for instance activation of a long wash cycle of a washing machine, or activating a cooker with a completion target date that is over 12 hours away.

In yet another example, ii the short-term optimal energy consumption target is low and there is sufficient renewable energy currently available, such that there is predicted to he a renewable energy surplus. the processor 28 may allow the or each energy consumption device 18 associated with the long-term optimal energy consumption target to be activated, to take advantage of the surplus energy. For example, an underfloor heating system may he activated when there is surplus renewable energy in the day time in order to preheat the premises, even though the parameter targets set for heating do not immediately call for activation of the heating.

This preheating is beneficial to cope with, for exanipk, forecast drops in temperature later in the day, which would otherwise have to be addressed in part, or entirely, through use of non-renewable energy.

The comparison module 60 preferably also accesses information stored in the data monitoring and storage module 32. Such information is used to compare historic data with current data. When short-term and/or long-term renewable energy forecast information is received by the processor 28. the comparison module 60 recalls similar historic forecast information recorded in the data monitoring and storage module 32.

The actual energy consumpthm achieved over the same historic period is also recalled so as to help the processor 28 to determine the short-term and/or long-term renewable energy availability.

The processor 28 preferably also takes into consideration energy efficiency data recorded by the data monitoring and storage module 32 associated with the or each energy consumption device 18 to further improve accuracy when determining a future energy requirement of each energy-consumption related parameter.

Therefore, the dynamic energy management system 10 can, over time, become more accurate in its energy consumption target predictions. For example, when a cold night is expected, a central heating system will normally be switched on iii anticipation of the cold weather. However, if the processor 28 has learnt or determined over a period of time that the building warms up quickly by way of data feedback from a regulating hub and/or radiator thermostat, and that the anticipated cold night is due to the arrival of strong wind, the processor 28 may suspend or defer activation of the heating system until the strong wind arrives at the renewable energy generation unit 48. so that the building can utilise an energy supply entirely or at least in part from the wind energy to power the heating system in the evening, rather than switching the heating system on immediately thereby utilising only or predominantly a non-renewable energy supply. As such, the processor 28 is responding to the expected supply of energy, rather than the demand.

The processor 28 preferably also receives feedback from the data monitoring and storage module 32 regarding the presence of a user, so that the processor 28 takes into account extra energy used by occupant of the premises determining energy requirement.

Once the short-term and long-term optimal energy consumption targets and the ranking of the energy-consumption related parameters are determined by the processor 28, a processing signal is sent to the controller 12 from the processor 28 so that the controller 12 can control the or each consumption device associated to each energy-consumption related parameter.

The controller 12 is preferably provided with the wireless communication module 44 in order to communicate with the or each energy consumption device 18 wirelessly.

The or each energy consumption device 18 includes a wireless transceiver for receiving control signals from, and outputting status data to, the controller 12.

The controller 12 is also preferably provided onsite, but may be offsite, for instance, in a master control facility controlling a plurality of premises. or may be provided through a virtual platform accessible through the internet, such as through cloud computing' or a distributed computing network utilising data transfer, preferably via the Internet. Additionally or alternatively, the processor 28 may be offsite or remote, and for example. may be based in a distributed intercommunicable computing network in order to dispense with the necessity of onsite processing.

Although it is preferable to provide a controller 12 that automatically controls the or each energy consumption device 18, for example, via an electronic control switch associated with the or each energy consumption device 18, a transmitter module 62 may he provided on the controller 12 for alerting the user to a pending and/or imminent controller-preferred action, for instance switching on of the central heating.

If preferred. the user may manually intervene or control the controller 12 to switch on or off the central heating. A user control may be provided on, at or for the controller 12 br activating the or each energy consumption device 18. Alternatively, die controller 12 may be pre-set such that it will carry out the pending controller-preferred action, if no user input is received for a predetermined period of time.

Referring to Figures 2a and 2b. in use, the dynamic energy management system 10 can dynamically control energy supply to one or more energy consumption devices 18 in the premises by determining optimal energy consumption targets and energy availability. As seen in Step 100 of Figure 2a, the user sets his or her user preference relating to a plurality of energy-consumption related parameters 22 via the user interface 20 of the dynamic energy management system 10. The renewable-energy condition data receiver 24 receives short-term and long-term renewable energy forecast information, and as seen in Step 102, preferably also takes into account current renewable energy information.

RefelTing to Step 104, the processor 28 receives the abovementioned information and, as seen in Step 106, ranks, in order of importance, the plurality of energy-consumption related parameters 22 according to the user preference and determines the energy requirement of the or each energy consumption device 18 according to the energy-consumption related parameters 22. in order of their relative importance. The processor 28 also determines a short-term renewable energy availability based on the short-term renewable energy forecast information and a long-term renewable energy availability based on renewable energy forecast information, as seen in Step 108. The processor 28 also preferably takes into account the current renewable energy information when determining the short-term and long-term renewalie energy availability.

Preferably, as seen in Step 110, the data monitoring and storage module 32 receives the abovementioned data from the user interface 20, renewable-energy condition data receiver 24, and/or the controller 12, and stores the data accordiny.

Referring to Step 112, the processor 28 then dynamically determines in real-time the short-term optimal energy consumption target and the long-term optimal energy consumption target based on the short-term and long-term renewable energy availability, preferably also the current renewable energy availability, against the energy requirement.

Preferably, lhe processor 28 also receives and considers feedback or historic data produced by the user interface 20, renewable-energy condition data receiver 24, and/or the controller 12 and stored in the data monitoring and storage module 32, when determining the optimal energy consumption targets.

The processor 28 may also receive and consider feedback on energy efficiency related to the or each energy consumption device 18 in the or a group of premises when determining the energy requirement of the energy-consumption related parameters.

Preferably, the data monitoring and storage module 32 monitors and stores energy efficiency data of the or each energy consumption device that is being switched on, so that the data can he recalled by the processor, when required.

More preferably, the processor 28 also receives feedback on a user's presence in the premises when determining the optimal energy consumption targets.

The processor 28 may also determine current renewable energy availability from the current renewable energy information received from the data monitoring and storage module 32. The short-term and/or long-term renewable energy availability data is compared with the current renewable energy availability. If a mismatch is detected to be above a certain predetermined threshold, the processor 28 dynamically re-determines the short-term and/or long-term optimal energy consumption targets, taking into account the current renewable energy availahihty. Such data is preferably storcd in the data nionitoring and storage module 32. A processing signa' is thcn sent to the controller 12, as seen in Step 114, for controlling activation or deactivation of the or each energy consumption device 18 depending on the position of the or each energy consumption device 18 on the ranking of importance determined by the processor 28, as seen in Step 116.

Optionally. before the controller 12 activates or deactivates the or each energy consumption device 18, an alert is sent to the user related to a pending action to be carried out by the controller 12.

The processor 28 and/or controller 12 of the system. referenced as 118 in Figures 2a and 2h, may also output demand data to the respective sources of renewable and non-renewable energy, referenced as 120 and 122, respectively in Figure 2b, either being the power stations or the intermediate energy or utility supplier, enabling power generation to he controlled and demand to he monitored and predicted accordingly.

For example. if a non-renewable energy supply 122 is required to supplement or substitute the available renewable energy from supply or supplies 120, this can he seamlessly called for or anticipated by the, preferably real-time dynamic, feedback output from the system.

It is therefore possible to utilise the dynamic energy management system 10 to dynamically and flexibly control energy supply to the or each energy consumption device 18 in the premises, based on renewable energy forecast information and the renewable energy consumption target.

The dynamic energy management system 10 takes into account user preferences and uses the user preferences as a guide when determining how to expthit the renewable energy available in the most efficient way. It smooths out the traditional peak energy demand periods, arid thus reduces reliance of non-renewable energy supply, and therefore carbon emission.

Although the premises discussed above is typically a domestic dwelling, it will be appreciated that the premises may be other types of buildings or facilities, such as a swimming pool, electric car charging point and/or a business premises, for example.

The premises may also be a collocation of buildings within the same vicinity, for example houses in the same village. The premises may also he a group or network of buildings spread out in different geographical areas, but may, for example, belong to the same energy supplier.

Where the dynamic energy management system involves more than one building, the system, or part of the system. may be provided offsite, for example via a virtual platlorm accessible through the internet, such as via cthud computing and/or processing utilising a distributed computing network. This allows multiple users and thus multiple premises or groups of premises to access the system easily and conveniently.

The user interlace may additiona'ly allow a user to enter building specific user preferences and the processor is able to identify each energy-consumption related parameter relating to a specific building within a group of buildings or facilities. The user interlace may therefore allow access by multiple users, or centrally by one user representing all the buildings.

This also allows occupants of the buildings to delegate energy management responsibility to their energy supplier, which will make central, macro level management, particularly regarding carbon emission and costs.

When ranking the order of importance for buildings. the processor will review all of the energy-consumption related parameters related to multiple buildings as one single network. It is therefore possible for the dynamic energy management system to manage multiple buildings or facilities as one entity. This is particularly useful for effectively managing one or more renewable energy generation units, or for an energy supplier to manage supply of renewable energy to a group of buildings or facilities that may be in the same or different geographical area.

Furthermore, having multiple buildings in a single network allows more effective exploitation of a renewable energy supply surge.

It will be appreciated that although the user interface is preferably accessible via the housing, it may he provided separate to the controller and the housing, and communicates with the processor wirelessly. The user interface may therefore he provided virtually, for example via a program or application accessible via a data processing unit, for instance a computer, or a mobile communications unit, for instance a smartphone.

Alternatively, a user preference receiver circuit may he provided on the controller for receiving user preference information, instead of the provision of a user interface by the dynamic encrgy management systcm. A uscr interface separate from the dynamic energy management system communicates with the user preference receiver circuit wirelcssly to provide the necessary user prcference information.

Although the processor and the renewable energy data receiver are provided as part of the controller, it will be appreciated that the processor and/or the renewable energy data receiver may be provided in the housing, separate to the controller. Alternatively, the processor and/or the renewable energy data receiver may he provided separate to the housing altogether. and communicate with the controller wirelessly.

Although the renewable energy data receiver preFerably receives current renewable energy information, the renewable energy data receiver may be adapted to receive forecast information only. However, current energy information is useful in allowing the processor to dynamically review and adjust the short-term and long-term energy consumption targets based on renewable energy forecast information, as well as current renewable energy information.

It is feasible that a networked forecasting facility may be implemented through feedback associated with the energy supply at one or more of the localised and/or remote renewable energy supply centres, and/or through feedback from one or more premises. This would dispense with the need for dedicated mctrological forecasting devices, either being long range or short range. For example. where cloud cover was present. solar energy generation may be noticeably lower at a particular site whilst higher at another remote site, allowing real-time forecast data to be fed into the system. Similarly, if wind energy generation was high due to stronger winds at a particular wind farm whilst bcing lower at onc or more other wind farms, this particular higher energy generation availability data and lower energy generation availability data can he Fed mb the system to provide Further real-lime Iorecasb daba for predictive energy availability purposes. With regard to potentially utilising one or more premises to accumulate forecasting data, it is feasible to monitor specific characteristics of the property or building in question. For example, by monitoring and feeding back the thermal loss or thermal gain of, preferaffly, a range of premises, meteorological data in the immediate vicinity of the monitored building can be determined, and thus forecast predictions of the immediate environment can be generated as part of the networked forecasting facility. For example, if the thermal mass of a group of buildings in one part of the country decreases compared to a group in another part of thc country, it may bc determined that a cold or low pressure front is progressing. Additional data may be generated from, for example, pressure sensors included in the wails or windows oF the building, determining and Feeding hack wind strength in the immediate vicinity of the monitored building. Other characteristics of the premises may be monitored also, allowing additional forecasting data patterns to be fed into the network without the specific requirement of dedicated meteorological instruments at the sites.

The data monitoring and storage module is beneficial in providing historic data to the processor. so that past performance and accuracy of the dynamic energy management system can he reviewed and taken into account, when determining the current short-term and long-term consumption targets. However, it will be appreciated that the module may be dispensed with, in order to reduce cost of and/or simplify manufacture, and the user interface may he provided with separate data storage means for storing user preferences.

The dynamic energy management system is particularly suited for controlling supply of renewable energy to the or each energy consumption device. It. will be appreciated that the dynamic energy management system may also he adapted to monitor supply of non-renewable energy to the or each energy consumption device in the premises, the processor taking into account the non-renewable energy availability when determining optimal energy consumption targets. Thus the dynamic energy management system may control the or each energy consumption device by controlling supply of renewablc and non-renewable energy to the or cach energy consumption device.

The words comprises/comprising' and the words having/including' when used herein with reference to the present invention arc used to specify the presence of stated features, integers, steps or components. but does not preclude the presence or addition of one or more other features, integers, steps, components or groups thereof.

It is appreciated that certain features of the invention, which are, for clarity, described in the context of separate embodiments, may also he provided in combination in a single embodiment. Conversely, various features of the invention which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable sub-combination.

The embodiments described above are provided by way of examples only, and various other modifications will be apparent to persons skilled in the field without departing from the scope of the invention as herein defined.

Claims

Claims I. A dynamic energy management system, comprising a controller for controlling one or more energy consumption devices in a premises such that a short-term optimal energy consumption t' *get and a long-term optimal energy consumption target are met or are substantially met, and for receiving user preferences from a user interface relating to a plurality of energy-consumption related parameters for the premises.a renewable-energy condition data receiver for receiving at least short-term and long-term renewable energy forecast information.a processor adapted for determining an energy requirement by ranking, in order of importance, the plurality of energy-consumption related parameters according to the user prelerenee, and determining a short-term renewable energy availability based on the short-term renewable energy forecast information and a long-term energy availability based on long-term renewable energy forecast information from the renewable-energy condition data receiver, the processor dynamically determining a short-term optimal energy consumption target and a long-term optima' energy consumption target based on the energy availability against the energy requirement of each energy-consumption related parameter.the processor outputting a processing signal to the controller so that the controller can control the one or each energy consumption device based on the determined said short-term optimal energy consumption target and a long-term optimal energy consumption target.
2. A dynamic energy management system as claimed in claim 1, wherein the short-term renewahk energy forecast information relates to a renewable energy forecast equal to or less than 5 hours ahead of time, and the long-term renewable energy forecast information relates to renewable energy forecast more than 5 hours ahead of time.
3. A dynamic energy management system as claimed in claim I or claim 2, wherein the renewable-energy condition data receiver is further adapted for receiving current renewable energy information, the processor further adapted for determining current renewable energy availability based on the current renewable energy information, and the processor having a comparison module for comparing the current renewable energy availahflity and the previously forecast short-term and/or long-term renewable energy availability for the same time period, the processor dynamically recalculating the short-term and/or long-term optimal energy consumption targets, taking into account the current renewable energy availability.
4. A dynamic energy management system as claimed in any preceding claim, wherein the renewable-energy condition data receiver forms part ol the controller, the renewable-energy condition data receiver having a renewable energy data circuit on the controller.
5. A dynamic energy management system as claimed in any preceding claim, wherein the processor forms part of the controller, the processor having a processing circuit on the controller.
6. A dynamic energy management system as claimed in any one of claims 1 to 3.wherein the renewable-energy condition data receiver and/or the processor are formed separate to the controller.
7. A dynamic energy management system as claimed in claim 6, wherein at least the processor forms part of a distributed computing network.
8. A dynamic energy management system as claimed in any preceding claim, wherein the controller further comprises a user preference receiver circuit for receiving user preferences from the user interface.
9. A dynamic energy management system as daimed in any preceding claim, wherein the controller is provided offsite of the premises, the controller being remotely controllable from the premises.
10. A dynamic energy management system as claimed in any preceding claim.wherein the premises is a domestic dwelling, a building, a facility, a collocation of buildings or facility, and/or a group of buildings or facility remote from each another.
11. A dynamic energy management system as claimed any preceding claim, wherein the controller includes a wireless communication module for wirelessly controlling the or each energy consumption device.
12. A dynamic energy management system as claimed in any preceding claim, wherein the controller includes an electronic control switch for remotely automatically controlling the or each energy consumption device.
13. A dynamic energy management system as claimed in any one of claims 1 to 12, wherein the controller includes a transmitter module for alerting the user to a pending controller-preferred action, the or each energy consumption device being manually controllable by the user.
14. A dynamic energy management system as claimed in claim 13. wherein the controller further comprises a user control for controlling the or each energy consumption device.
15. A dynamic energy management system as claimed in any preceding claim, wherein the dynamic energy management system further comprises a user interface which is in wireless communication with and/or hard-wired to the controller.
16. A dynamic energy management system as claimed in claim 15, wherein the user interface is accessible via a data processing unit, a mobile communications device and/or a virtual platform via the internet.
17. A dynamic energy management system as claimed in claim 15 or claim 16, wherein the plurality of energy-consumption related parameters includes at least one of: carbon emission target data*, energy consumption expenditure target data: target temperature data of the premises to be maintained: and a target time data in which to complete one or more premises related tasks requiring energy input.
18. A dynamic energy management system as claimed in claim 17. wherein the one or more premises related tasks requiring energy input includes completion of a wash cycle of a washing machine, completion of a wash cycle of a dishwasher, activating a hot water system, and/or activating a cooking oven for a certain period of time.
19. A dynamic energy management system as claimed in claim 17 or claim 18, wherein a tolerance level associated with the or each energy-consumption related parameter can be input via the user interface.
20. A dynamic energy management system as claimed in any preceding claim, wherein the renewable-energy condition data receiver has a wireless communication module adapted for communicating and receiving data remote from the renewable-energy condition data receiver.
21. A dynamic energy management system as claimed in claim 20, wherein the wireless communication module is adapted for communicating with at least one weather station for receiving the short-term and long-term renewable energy forecast information, and/or current renewable energy information, the processor processing the information to determine short-term and long-term renewable energy availability.
22. A dynamic energy management system as claimed in any preceding claim, wherein the renewable-energy condition data receiver is adapted for communicating with at least one renewable energy generation unit, for receiving current renewable energy information specific to the renewable energy generation unit, the processor processing the information when determining the short-term and/or short-term renewable energy availability.
23. A dynamic energy management system as claimed in claims 21 or claim 22, when dependent on claim 3, wherein the processor is adapted to further process the information collected from the or each weather station and/or the onsite and/or offsite renewable energy generation unit to determine the current renewable energy availability related to the premises.
24. A dynamic energy management system as claimed in any preceding claim, wherein the short-term and long-term renewable energy forecast information.and/or the current renewable energy information include: temperature data; atmospheric pressure data; wind speed data; wind direction data; cloud covcr data; and/or time of sunrise and time of sunset.
25. A dynamic energy management system as claimed in any preceding claim, wherein the short-term and/or long-term renewable energy forecast information is at least in part assimilated via monitoring of energy output from a plurality of renewable energy sources, and/or change of premises characteristics.
26. A dynamic energy management system as claimed in any preceding claim, further comprising a data monitoring and storage module adapted for monitoring and recording short-term and long-term renewable energy information data providable by the renewable-energy condition data receiver, short-term optimal and the long-term optimal energy consumption target data providaffle by the processor. and/or the actual renewable energy availability data and/or the actual energy consumption data.
27. A dynamic energy management system as claimed in claim 26, the data monitoring and storage module having a feedback circuit for providing feedback data relating to historic predicted versus actual renewable energy availability and/or actual energy consumption to the processor, to improve accuracy in determining the short-term and the long-term optimal energy consumption target in future.
28. A dynamic energy management system as claimed in claim 27, the data monitoring and storage module being further adapted for monitoring and recording energy efficiency data related to the or each energy consumption device in the premises. the feedback circuit providing feedback relating to the energy efficiency data to the processor to improve future accuracy when determining the energy requirement of the plurality of energy-consumption related parameters.
29. A dynamic energy management system as claimed in claim 27 or claim 28, the data monitoring and storage module furthcr comprising user presence monitoring means for monitoring occupancy of the premises, the feedback circuit of the data monitoring and storage module providing user presence leedhack data to the processor such that the presence ol a user is taken into account when determining the energy requirement of the plurality of energy-consumption related parameters.
30. A dynamic energy management system as claimed in claim any one of claims 26 to 29, the data monitoring and storage module further comprising output means for outputting data stored in the data monitoring and storage module to the user interface or an external device for energy efficiency analysis.
31. A dynamic energy management system substantially as described herein with reference to Figures 1. 2a and 2b of the accompanying drawings.
32. A method of dynamically controlling energy supply to one or more energy consumption devices in a premises by determining short-term and long-term optimal energy consumption targets and short-term and long-term renewable energy availabilities using the dynamic energy management system as claimed in any preceding claim, comprising the steps of: a] receiving user preference data relating to a plurality of energy-consumption related parameters; hi receiving short-term and long-term renewable energy lorecast information data; ci ranking. in order of importance, the plurabty of energy-consumption related parameters according to the user preference data and determining the energy requirement relating to the or each energy consumption device according to the energy-consumption related parameters, and determining a short-term renewable energy availability based on the short-term renewable energy forecast information data and a long-term renewable energy availability based on the long-term renewable energy forecast information data; di dynamically determining the short-term optimal energy consumption target and the long-term optinia energy consumption target hased on the renewable energy availabilities against the energy requirement determined in step ci; ci switching on or off the or each energy consumption device depending on the renewable energy availabilities and position of the or each energy consumption device on the ranking of importance determined in step ci.
33. A method of dynamically controlling energy supply as claimed in claim 32, further comprising step fj prior to step dj of receiving feedback on historic predicted renewable energy availability data and actual renewable energy availability data, step d] further includes considering feedback received in step fj when determining the short-term and long-term optimal energy consumption targets.
34. A method of dynamically controlling energy supply as claimed in claim 33.wherein each of step a]. hi. ci and d] further includes recording of the data received, ranked and/or determined in each respective step. such that data can be accessed as historic data in step f].
35. A method of dynamically controfling energy supply as claimed in any one of claims 32 to 34, further comprising step g] prior to step d] of receiving energy efficiency data related to the or each energy consumption device in the premises, step di further includes considering feedback received in step g] when determining the energy requirement ol the energy-consumption related parameters.
36. A method of dynamically controlling energy supply as claimed in claim 35, further comprising step hi after step ci of monitoring the energy efficiency of the or each energy consumption device that is being switched on, such that energy efficiency data can be recalled in step g].
37. A method of dynamically controfling energy supply as claimed in any one of claims 32 to 36, further comprising step fl prior to step d] of receiving feedback on a user's presence in the premises, step d] further includes monitoring the presence of a user when determining the energy requirement of the energy-consumption related parameters.
38. A method of dynamically controlling energy supply as claimed in any one of claim 32 to 37, further comprising step jj prior to step ci of receiving current renewable energy information and determining a current renewable energy availability based on the current renewable energy forecast information data, comparing the current renewable energy availability data with the forecast short-term and/or long-term renewable energy availahibty data, and then dynamically re-determining the short-term and/or long-term optimal energy consumption targets, taking into account the current renewable energy availability.
39. A method of dynamically controlling energy supply as claimed in claim 38, wherein step j] further includes recording of the data received and re-determined in step j].
40. A method of dynamically controlling energy supply as claimed in any one of claims 32 to 39. further comprising step k] prior to step ci of alerting a user to a pending activation or deactivation of the or each energy consumption device.
41. A method of dynamically controlling energy supply substantially as described with reference to Figures 2a and 2b of the accompanying drawings.
42. A method of dynamically managing energy demand at one or more premises to maxinlise energy usage when a renewable energy supply is high and to minimise energy usage when renewable energy supply is low using a dynamic energy management system as claimed in any one of claims 1 to 30, the method comprising the steps of: a] receiving user preference data relating to a plurality of energy-consumption related parameters; b] receiving short-term arid long-term renewable energy forecast information data; c] ranking, in order of importance, the plurality of energy-consumption related parameters according to the user preference data and determining the energy requirement relating to one or more energy consumption devices according to the energy-consumption related parameters. and determining a short-term renewable energy availability based on the short-term renewable energy forecast information data and a long-term renewable energy availability based on the long-term renewable energy forecast information data; d] dynamically determining a short-term optimal energy consumption target and a long-term optimal energy consumption target based on the renewable energy availabilities against the energy requirement determined in step c]; and e] automatica1y controlling the or each energy consumption device depending on the renewable energy availabilities determined in step dl and position of the or each energy consumption device on the ranking of importance determined in step e].
43. A method of dynamically managing energy demand as daimed in claim 42, further comprising a step f] prior to step dl of receiving feedback on historic predicted renewable energy availability data and actual renewable energy availability data, step d] further including considering feedback received in step F] when determining the short-term and long-term optimal energy consumption targets.
44. A method of dynamically managing energy demand as claimed in claim 43, wherein each of steps a], h], c] and d] further includes recording of the data received, ranked and/or determined in each respective step, such that data can be accessed as historic data in step 11.
45. A method of dynamically managing energy demand as claimed in any one of claims 42 to 44, further comprising a step g] prior to step dj of receiving energy efficiency data related to the or each energy consumption device associated with the premises, step d] further including considering feedback received in step g] when determining the energy requirement of the energy-consumption related parameters.
46. A method of dynamically managing energy demand as claimed in claim 45, further comprising a step h] subsequent to step ci of monitoring the energy efficiency of the or each energy consumption device that is being controlled, such that energy efficiency data can be recalled in step g].
47. A method of dynamically managing energy demand as claimed in any one of claims 42 to 46, further comprising a step i] prior to step dj of receiving feedback on a user's presence in the premises, step dl further including monitoring the presence of a user when determining the energy requirement of the energy-consumption related parameters.
48. A method of dynamically managing energy demand as claimed in any one of claim 42 to 47. further comprising a step j] prior to step e] of receiving current renewable energy information and determining a culTent renewable energy availability based on the current renewable energy forecast information data, comparing the current renewable energy availability data with the forecast short-term and/or long-term renewable energy availability data, and then dynamically re-determining the short-term and/or long-term optimal energy consumption targets. taking into account the current renewable energy availability.
49. A method of dynamically managing energy demand as daimed in claim 48, wherein step j] further includes recording the data received and re-determined in stepj].
50. A method of dynamically managing energy demand as claimed in any one of claims 42 to 49. further comprising a step kj prior to step e] of alerting a user to a pending activation or deactivation of the or each energy consumption device.
51. A method of dynamically managing energy demand as claimed in any one of claims 42 to 50, wherein, in step ci, demand feedback is outputted to a supply source of the renewable energy and non-renewable energy, such that energy generation is optimised.
52. A method of dynamically managing energy demand substantially as described with reference to Figure 2a and Figure 2b of the accompanying drawings.
53. A method of dynamically controlling energy supply to one or more energy consumption devices at one or more premises by determining short-term and long-term optimal energy consumption targets and short-term and long-term renewable energy availabilities, the method comprising the steps of: a] receiving user preference data relating to a plurality of energy-consumption related parameters; b] receiving short-term and long-term renewable energy forecast information data; c] ranking, in order of impertance, the plura'ity of energy-consumption related parameters according to the user preference data and determining the energy requirement relating to the or each energy consumption device according to the energy-consumption related parameters, and determining a short-term renewable energy availability based on the short-term renewahk energy forecast information data and a long-term renewable energy availability based on the long-term renewable energy forecast information data; di dynamically determining die short-term optimal energy consumption target and the long-term optimal energy consumption target based on the renewable energy availabilities against the energy requirement determined in step c]; e] switching on or off the or each energy consumption device depending on the renewable energy availabilities and position of the or each energy consumption device on the ranking of importance determined in step ci.
54. A method of dynamically managing energy demand at one or more premises to maximise energy usage when a renewable energy supply is high and to minimise energy usage when renewable energy supply is low, the method comprising the steps of: a] receiving user preference data relating to a plurality of energy-consumption related parameters: h] receiving short-term and long-term renewable energy forecast information data; c] ranking, in order of importance, the plurallty of energy-consumption related parameters according to the user preference data and determining the energy requirement relating to one or more energy consumption devices according to the energy-consumption related parameters. and determining a short-term renewable energy availability based on the short-term renewable energy forecast information data and a long-term renewable energy availability based on the long-term rencwable energy forecast information data; d] dynamically determining a short-term optimal energy consumption target and a long-term optimal energy consumption target based on the renewable energy availabilities against the energy requirement determined in step ci: and e] automatica'ly controlling the or each energy consumption device depending on the renewable energy avaflabilities determined in step dj and position of the or each energy consumption device on the ranking of importance determined in step e].