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WO2024067936A1 - A method and an aggregated system for forming a demand-response resource to an electricity market zone - Google Patents

A method and an aggregated system for forming a demand-response resource to an electricity market zone Download PDF

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Publication number
WO2024067936A1
WO2024067936A1 PCT/DK2023/050235 DK2023050235W WO2024067936A1 WO 2024067936 A1 WO2024067936 A1 WO 2024067936A1 DK 2023050235 W DK2023050235 W DK 2023050235W WO 2024067936 A1 WO2024067936 A1 WO 2024067936A1
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WO
WIPO (PCT)
Prior art keywords
electric
electric units
power consumption
units
demand
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/DK2023/050235
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French (fr)
Inventor
Mogens Birkelund
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SC Nordic AS
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SC Nordic AS
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Filing date
Publication date
Application filed by SC Nordic AS filed Critical SC Nordic AS
Priority to EP23871118.8A priority Critical patent/EP4595181A1/en
Publication of WO2024067936A1 publication Critical patent/WO2024067936A1/en
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Energy or water supply
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for AC mains or AC distribution networks
    • H02J3/12—Circuit arrangements for AC mains or AC distribution networks for adjusting voltage in AC networks by changing a characteristic of the network load
    • H02J3/14—Circuit arrangements for AC mains or AC distribution networks for adjusting voltage in AC networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
    • H02J3/144—Demand-response operation of the power transmission or distribution network
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
    • F25D—REFRIGERATORS; COLD ROOMS; ICE-BOXES; COOLING OR FREEZING APPARATUS NOT OTHERWISE PROVIDED FOR
    • F25D21/00—Defrosting; Preventing frosting; Removing condensed or defrost water
    • F25D21/06—Removing frost
    • F25D21/08—Removing frost by electric heating
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
    • H02J2310/50—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads
    • H02J2310/56—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads characterised by the condition upon which the selective controlling is based
    • H02J2310/62—The condition being non-electrical, e.g. temperature
    • H02J2310/64—The condition being economic, e.g. tariff based load management

Definitions

  • the present invention relates to a method and an aggregated system for forming a demandresponse resource to an electricity market zone and/or combined market zones using electric units without knowing the response curves for each individual electric unit. This will enable low consumption electric units to be used in demand responses, where the cost of obtaining and maintaining response curves would be greater than the possible income from forming demand responses.
  • a cartridge heater is an example of an electric unit with a simple and predictable response curve.
  • most cartridge heaters have a low power consumption relative to an electricity market, with a great number of cartridge heaters in most electricity markets.
  • the object of the invention is to provide a method and an aggregated system for forming a demand-response resource to an electricity market zone and/or combined market zones using electric units without knowing the response curves for each individual electric unit.
  • An object of the invention is achieved by a method for forming a demand-response resource to an electricity market zone and/or combined market zones, wherein the method comprises steps of
  • the demand-response resources are characterised by a combination of electric units with mapped response profiles that may participate in the electricity market zones and/or combined market zones, where combined market zones are two or more electricity market zones.
  • the electric units are part of a single electricity market zone; however, some demand-response resources are offered for balancing combined market zones.
  • the demand-response resources may for the Danish electricity market zone (DK1) be an FCR response for balance generation and demand; thereby balancing the frequency to 50,000 Hz. All types of demand-response resources are known for a given market.
  • the energy and reserve markets may be divided into electricity market zones and/or combined market zones with different market demands.
  • the demand-response resources need to comply with the technical demands, geographical dependency etc. of a given zone to participate in the market.
  • the electric units may be electric units with low operational power consumption such as e.g., cartridge heaters, where the costs of measuring response curves of each individual electric unit outweigh the potential earnings of forming a demand-response resources to an electricity market zone and/or combined market zones.
  • Electric units of the same type may have response curves of identical curve shapes that only differ in a scaling which depends on the operational power consumption of the electric unit.
  • a reference electric unit of the same type as the electric units provided by the method, it is only necessary to provide a reference response curve of the reference electric units, when the operational power consumption of each individual electric unit is known.
  • the reference electric unit may be a separate electric unit to all the electric units used for forming the demand-response or form part of the electric units used for forming the demandresponse.
  • the scaling factor of each individual electric unit may thus be used to scale the reference response curve to represent the response curve of each individual electric unit. Thereby a plurality of response curves can be obtained from a single reference response curve.
  • the step of providing a reference response curve of a reference electric unit may include performing response tests for generating the response curve.
  • the step of providing a reference response curve may be a step of providing one or more reference response curves of one or more reference electrics units operated at different operational power consumption.
  • the reference response curve and reference operational power consumption within closest proximity to each individual electric unit may then be used to calculate the scaling factor and provide a response curve for each individual electric unit. Thereby increasing the precision of the provided plurality of response curves.
  • the electric units may be operated by one or more third parties and thus the availability of power consumption of each of the electric unit will change as a function of time. It is therefore important that the method receives the operational power consumption and/or activation periods of the plurality of electric units regularly.
  • the method can form a demand-response resource by combining several of the electric units into a virtual electric machine, which is able to provide the necessary balancing demand.
  • the balancing demand could be for stabilising the frequency.
  • the method facilitates that decentralised third party’s electric devices can be offered as a demandresponse resource without disturbing or with limited disturbance of the third party’s operation as the third party operates as required.
  • the third party may be able to observe that for example a cartridge heater is activated at different periods.
  • the third party may accept the limited disturbance as the third party is paid for providing a demand-response resource.
  • the step of operating may be a step of continuously recording the demand-response resource as a function of demand thereby ensuring that the continued qualification of the demandresponse resource to participate in the market.
  • the demand-response resource according to the present invention is only able to respond to a need for increasing power demand since the method can only activate the electric units of the virtual electric machine and the activation will increase power consumption.
  • the electric units will have very limited power consumption or no power consumption when in an off state.
  • the control of the individual electric units will be binary.
  • the method can form a demand-response resource of electric units with low power consumption suitable for participating in one or more markets, and if the demands-response resource ceases to qualify for a particular market or a better market arises, then the method is capable of moving the demands-response source to a different and/or better market.
  • the reference response curve of a reference electric unit may be measured with a resolution of at least 5 seconds, at least 3 seconds, or preferably 1 second or greater.
  • the operational power consumption of one or more electric units may differ from one or more of the other electric units.
  • the scaling factor enables that the method works for electric units having different operational power consumptions by transforming the reference response curve as a function of scaling factor. Thereby, a greater adaptability of the formed demand-response resource may be achieved as the demand-response resource may be suitable for participating in more markets.
  • the operational power consumption of one electric unit may be greater than the other electric units comprised in the formed demand-response resource.
  • a greater flexibility of the demand-response resource may be achieved as the power consumption can be further increased to accommodate the required market demands.
  • the electric units may be cartridge heaters, or motors driving air circulation, or pumps for periodically agitating liquid tanks, or motors driving a mechanical element for agitating liquid tanks.
  • Motors driving air circulation have a simple and predictable response curve and thus a scaling factor can be used for transforming a reference response curve as a function of the scaling factor.
  • Motors driving air circulation of an underground car parking space are suitable to form the demand response according to the invention. Because the motors are periodically turned on to remove CO2, particles, and other gasses.
  • the cartridge heater may be installed in refrigerated counters and the cartridge heater are configured for defrosting the refrigerated counters.
  • the cartridge heater is typically installed for defrosting the condenser of the refrigerated counters such that the efficiency of the condenser is not reduced by the frost.
  • the electric units may all be cartridge heater installed in refrigerated counters.
  • the electric units may be operated between two states
  • the electric units may only have these two states since it makes it possible to control the electric units without knowing precise data as each electric unit is either “on” i.e. in the activated state or “off’ i.e. in the off state where the electric unit is switched off and has no power consumption or an idle power consumption.
  • the electric units may receive instruction to change state to an activated state when an increase in power consumption is required by the market demand.
  • the market demand for increased power consumption will at some point drop off and the electric units will then be instructed to change state to the off state.
  • the state of the electric units may periodically be changed to the activated state and the state of the electric units may after a pre-set period be changed to the off state or as a function of an instruction to change state to the off state.
  • the pre-set period is a fail-safe in the system such that the electric units does not keep consuming power if no instructions have been received. In most methods the electric units should receive instruction to change state to the off state unless something goes wrong.
  • the pre-set period may be pre-set periods of at least 10 minutes or at least 15 minutes or at least 30 minutes.
  • An electric cartridge for a condenser should periodically be changed to the activated state to remove frost.
  • the electric cartridge should receive instruction to change its state to an activated state as the condenser efficiency would drop off thus the state of the electric units may periodically be changed to the activated state.
  • the operational power consumption of the electric units may be in the range of 1 kW to 40 kW or 2 kW to 30 kW or 3 kW to 25 kW.
  • the method steps of providing, calculating, and transforming may be repeated for a second group of electric units and the step of forming a demand-response resource is performed by forming several of the electric units into a virtual electric machine as a function of a balancing demand and the response curves of the plurality of electric units.
  • Another way is to perform the method according to the invention and then form two or more demand-response resources by combining several of the electric units into virtual electric machines, wherein all the electric units of a virtual electric machine are from the same group and afterwards the virtual electric machines are combined into a superimposed virtual electric machine.
  • the method may further include a step of
  • the precision with respect to power consumption that the virtual electric machine can be operated can be increased significantly by measuring a sub-set of electric units in real-time.
  • the measured power consumption is then compared with the sub-set response curve and a deviation factor is then determined and all electric units of the virtual electric machine is then operated as a function of market demand and the deviation factor.
  • the deviation factor will typically be the ratio between summarised power consumption of the sub-set of electric units and the sub-set response curve.
  • the electric units will be instructed to increase power consumption by as an example 1 % or 0.5 % or another number and in other cases the electric units will be instructed to decrease power consumption by as an example 1 % or 0.5 % or another number.
  • the deviation factor will change over the course of a year because temperature and air humidity and other factors will affect the power consumption of the electric units. Hence the deviation factor enables that the method can perform seasonal adjustment.
  • Real-time power consumption may be measured at least once per 5 seconds or with a period of 3 second or with a period of 1 seconds or a period of 0.5 seconds. In most cases a measurement every second is sufficient.
  • the sub-set of electric units may be 5 to 50 % of the electric units or 5 to 40 % of the electric units or 7 to 30 % of the electric units or 10 to 25 % of the electric units or 10 to 20 % of the electric units.
  • the method is still more efficient than measuring all electric units by only measuring 50 % of the electric units. However, in many cases measuring 5 %, or 10 % or 20 % of the electric units is sufficient to control the virtual machine within the needed precision.
  • the sub-set of electric units may be chosen amongst the electric units having a power consumption equal to or above the median power consumption of the electric units.
  • the electric units is preferably taken from the top 5 % consuming electric units or the top 10 % consuming electric units or 15 % consuming electric units.
  • the electric units is preferably taken from the top 10 % consuming electric units or the top 15 % consuming electric units or 20 % consuming electric units.
  • the electric units is preferably taken from the top 15 % consuming electric units or the top 20 % consuming electric units or 25 % consuming electric units.
  • An object of the invention is achieved by an aggregated system for responding to a balancing demand on an electricity market zone and/or combined electricity market zones, wherein the aggregated system comprises - electric units within an electricity market zone operated by one or more third-parties wherein the electric units are the same type of electric unit and each electric unit have an operational power consumption;
  • a storage module having stored thereon response curves of the electric units; the response curves being transformed based on a reference electric unit of the electric units having a reference operational power consumption;
  • a monitoring module adapted for monitoring balancing demand of the electricity market zone and/or the combined market zones
  • a computation module adapted for forming a demand-response resource by combining several of the electric units into a virtual electric machine as a function of response curves and requirements of the balancing demand;
  • a global controller configured to activate the virtual electric machine by sending instructions to the electric units forming part of the virtual electric machine.
  • the aggregated system is in connection with a plurality of electric units through a global controller and enables control the activation of the plurality of electric units.
  • the aggregated system is unable to receive live power consumption data from each electric unit instead the aggregated system works by scaling a reference response curve.
  • the server comprises a storage module having stored thereon a reference response curve of a reference electric unit for determining the response curves of the electric units. Thereby, the aggregated system can form a demand-response resource using electric units without measuring response curves for each individual electric unit.
  • the electric units comprised in the aggregated system may be small electric unit with low operational power consumption such as e.g., cartridge heater, where the costs of measuring response curves of each individual electric unit outweigh the potential earnings of forming a demand-response resources to an electricity market zone and/or combined market zones.
  • Electric units of the same type may have response curves of identical curve shape that only differ in a scaling that depends on the operational power consumption of the electric unit.
  • a scaling factor of each individual electric unit may be calculated by dividing the operational power consumption of each electric unit with the reference operational power consumption of the reference electric unit.
  • the storage module may thereby store a reference response curve for a reference electric unit with a reference operational power consumption that can be scaled to represent response curves for each individual electric unit by the scaling factor.
  • the means for measuring operational power consumption of the electric units and the reference electric unit may be a power meter or similar.
  • the means may be a voltage meter and a current meter which can be combined to measure the power consumption.
  • There may be other solutions capable of determining the power consumption of an electric meter.
  • the storage module may have one or more reference response curves of one or more reference electric units with different operational power consumptions stored thereon.
  • the reference response curve and reference operational power consumption within closest proximity to each individual electric unit may then be used to calculate the scaling factor and provide a response curve for each individual electric unit. Thereby increasing the precision of the stored response curves.
  • the electric units are operated by one or more third parties and thus the plurality of electric units is not on stand-by as such for forming part of a demand-response. Instead, the electric units are operated according to the need of the third-party.
  • the global controller activates two or more virtual electric machines as a function of an imbalance in the electricity market zone or combined electricity market zones.
  • the aggregated system is not limited to only activating and controlling one virtual electric machine.
  • the aggregated system may activate two or more virtual electric machines as the aggregated system is only limited by the available capacity of the plurality of electric units.
  • the electric units are operated between two states
  • the electric units may only have these two states since it makes it possible to control the electric units without knowing precise data as each electric unit is either “on” i.e. in the activated state or “off’ i.e. in the off state where the electric unit is switched off and has no power consumption or an idle power consumption.
  • the electric units may receive instruction to change state to an activated state when an increase in power consumption is required by the market demand.
  • the market demand for increased power consumption will at some point drop off and the electric units will then be instructed to change state to the off state.
  • the server communication module may be configured for receiving real-time power consumption of a sub-set of electric units, and the computation module being further adapted for
  • the global controller being further configured to operate the virtual electric machine as a function of market demand and the deviation factor.
  • the precision with respect to power consumption that the virtual electric machine can be operated can be increased significantly by measuring a sub-set of electric units in real-time.
  • the measured power consumption is then compared with the sub-set response curve and a deviation factor is then determined and all electric units of the virtual electric machine is then operated as a function of market demand and the deviation factor.
  • the deviation factor will typically be the ratio between summarised power consumption of the sub-set of electric units and the sub-set response curve.
  • the electric units will be instructed to increase power consumption by as an example 1 % or 0.5 % or another number and in other cases the electric units will be instructed to decrease power consumption by as an example 1 % or 0.5 % or another number.
  • Real-time power consumption may be measured at least once per 5 seconds or with a period of 3 second or with a period of 1 seconds or a period of 0.5 seconds. In most cases a measurement every second is sufficient.
  • the sub-set of electric units may be 5 to 50 % of the electric units or 5 to 40 % of the electric units or 7 to 30 % of the electric units or 10 to 25 % of the electric units or 10 to 20 % of the electric units.
  • the method is still more efficient than measuring all electric units by only measuring 50 % of the electric units. However, in many cases measuring 5 %, or 10 % or 20 % of the electric units is sufficient to control the virtual machine within the needed precision.
  • the sub-set of electric units may be chosen amongst the electric units having a power consumption equal to or above the median power consumption of the electric units.
  • the electric units is preferably taken from the top 5 % consuming electric units or the top 10 % consuming electric units or 15 % consuming electric units.
  • the electric units is preferably taken from the top 10 % consuming electric units or the top 15 % consuming electric units or 20 % consuming electric units.
  • the electric units is preferably taken from the top 15 % consuming electric units or the top 20 % consuming electric units or 25 % consuming electric units.
  • Fig. 1 illustrates a method for forming demand-response resource to an electricity market zone and/or combined market zones
  • Fig. 2 illustrated an aggregate system for responding to a balancing demand on an electricity market zone and/or combined electricity market zones
  • Fig. 3 illustrates a storage module and the transforming of response curves
  • Fig. 4 illustrates a computation module for forming a demand-response resource
  • Fig. 5 illustrate the relationship between an exemplary reference response curve and a plurality of response curves.
  • Fig. 6 illustrates another method for forming demand-response resource to an electricity market zone and/or combined market zones.
  • Figure 1 illustrates a method 1000 for forming demand-response resource 200 to an electricity market zone 10 and/or combined market zones 20, where electric units EM-1, ..., EM-N of the same type are provided 1100 along with reference response curve 120 of a reference electric unit REM.
  • the provided 1100 electric units EM-1, . . . , EM-N are operated by one or more third parties within an electricity market zone 10 and each electric unit EM-1, . . . , EM-N have an operational power consumption 110.
  • the reference electric unit REM have a reference operational power consumption 130.
  • the step of providing 1100 a reference response curve 120 of a reference electric unit REM may include performing response tests for generating the reference response curve 120.
  • One of the provided electric units EM-1, . . . , EM-N may have operational power consumption differing from the other electric units EM-1, . . . , EM-N.
  • the electric units EM-1, ..., EM-N may be electric units EM-1, ..., EM-N with low operational power consumption 110 such as e.g., cartridge heaters, where the costs of measuring response curves 150 of each individual electric unit EM-1, . . ., EM-N outweigh the potential earnings of forming a demand-response resources 200 to an electricity market zone 10 and/or combined market zones 20.
  • the electric units EM-1, EM-N may have an operational power consumption 110 in the ranges of 1 kW to 40 kW or 2 kW to 30 kW or 3 kW to 25 kW.
  • Electric units EM-1, . . ., EM-N of the same type may have response curves 150 of identical curve shape that only differ in a scaling which depends on the operational power consumption 110 of the electric unit EM-1, . . . , EM-N.
  • a scaling factor 140 can be calculated 1200 for each electric unit EM-1, . . . , EM-N by dividing the operational power consumption 110 of each electric unit EM-1, . . ., EM-N with the reference operational power consumption 130.
  • the scaling factor 140 of each individual electric unit EM-1, . . ., EM-N can be used to transform 1300 the reference response curve 120 as a function of the scaling factor 140 to represent the response curve 150 of each individual electric unit EM-1, . . ., EM-N. Thereby, a plurality of response curves 150 can be obtained from a single reference response curve 120.
  • One or more reference response curves 120 may be provided 1100 for one or more reference electrics units REM operated at different reference operational power consumptions 130.
  • the reference response curve 120 and reference operational power consumption 130 within closest proximity to each individual electric unit EM-1, . . ., EM-N may then be used to calculate 1200 the scaling factor 140 and transform 1300 the reference response curve 120 as a function of the scaling factor 140 to represent a response curve 150 for each individual electric unit EM-1, ..., EM-N.
  • a demand-response resource 200 can be formed 1400 by combining several of the electric units EM-1, . . ., EM-N into a virtual electric machine 30 as a function of a balancing demand and the response curves
  • an overall operational power consumption 110 that is high enough to participate in the market may be achieved.
  • the method 1000 operates 1500 the virtual electric machine 30 as a function market demand.
  • the demand-response resource 200 may be recorded as a function of demand, thereby ensuring that the demand-response resource 200 continues to qualify for the market.
  • the demand-response resource 200 is only able to respond to a need for increasing power demand since the method 1000 can only activate the electric units EM-1, ..., EM-N of the virtual electric machine 30 and the activation will increase power consumption.
  • the electric units EM-1, . . ., EM-N will have very limited power consumption or no power consumption when in an off state.
  • the control of the individual electric units EM-1, . . ., EM-N is binary.
  • the electric units EM-1, . . ., EM-N may be operated between an activated state, wherein the operational power consumption 110 is the operational power consumption, and an off state wherein the electric units EM-1, . . ., EM-N are switched off.
  • the electric units EM-1, ..., EM-N may periodically change to the activated state, and the state of the electric units EM-1, . . . , EM-N may after a pre-set period changed to the off state.
  • the pre-set period is a fail-safe in the system such that the electric units EM-1, ..., EM-N does not keep consuming power if no instructions have been received from the global controller 550. In most methods 1000 the electric units EM-1, . . ., EM-N should receive instructions from the global controller 550 to change state to the off state unless something goes wrong.
  • the pre-set period may be pre-set periods of at least 10 minutes or at least 15 minutes or at least 30 minutes.
  • the electric units EM-1, . . . , EM-N may receive instructions from the global controller 550 to change state to an activated state when an increase in power consumption is required by the market demand.
  • the market demand for increased power consumption will at some point drop off and the electric units EM-1, . . . , EM-N will then be instructed by the global controller 550 to change state to the off state.
  • the method 1000 can thus form 1400 a demand-response resource 200 of electric units EM- 1, . . . , EM-N with low operational power consumption 110 suitable for participating in one or more markets, and if the demands-response resource 200 ceases to qualify for a particular market or a better market arises, then the method 1000 is capable of moving the demands- response resource 200 to a different and/or better market.
  • Figure 2 illustrates an aggregated system 400 for responding to a balancing demand on an electricity market zone 10 and/or combined electricity market zones 20.
  • the aggregated system 400 comprises a plurality of electric units EM-1, . . ., EM-N within an electricity market zone 10 operated by one or more third parties.
  • the electric units EM-1, . . . , EM-N are of the same type and each electric unit EM-1, . . . , EM-N have an operational power consumption 110.
  • One of the electric units EM-1, . . ., EM-N acts as a reference electric unit REM with a reference operational power consumption 130, and a reference response curve 120 having been measured for the reference electric units REM.
  • a dotted circle is drawn around the plurality of electric units EM-1, . . . , EM-N and the reference electric unit REM, as these units can be positioned decentralised within the electricity market zone 10.
  • the aggregated system 400 has a server 500 comprising a server communication module 510 in communication 515 with the electric unit EM-1, . . ., EM-N.
  • the server 500 has a storage module 520 having stored thereon response curves 150 of the plurality of electric units EM-1, ..., EM-N.
  • the response curves 150 have been transformed based on the reference response curve 120 of the electric unit REM having a reference operational power consumption 130.
  • the server 500 has a monitoring module 530 adapted for monitoring balancing demand of the electricity market zone 10 and/or the combined market zones 20. This is required otherwise the requirement of the balancing demand is unknown and no virtual electric machine 30 can be formed.
  • the monitoring module 530 may comprise a frequency measurement unit monitoring the frequency of the electricity market zone 10 and/or the combined market zones 20.
  • the server 500 has a computation module 540 adapted for forming a demand-response resource 200 by combining several of the electric units EM-1, . . ., EM-N into a virtual electric machine 30 as a function of the response curves 150 and requirements of the balancing demand.
  • the virtual electric machine 30 is the at least one demand-response resource 200.
  • the server 500 has a global controller 550 configured to activate 555 the virtual electric machine 30 by sending instructions to the electric units EM-1, ..., EM-N forming part of the virtual electric machine 30.
  • the global controller 550 may be configured to activate 555 a virtual electric machine 30 as a function of the frequency of the electricity market zone 10 and/or the combined market zones 20.
  • the aggregated system 400 is not limited to only activating 555 one virtual electric machine 30.
  • the aggregated system 400 may activate 555 two or more virtual electric machines 30 as the aggregated system 400 is only limited by the available capacity of the plurality of electric units EM- 1 , . . . , EM-N.
  • the aggregated system 400 may operate the electric units EM-1, . . ., EM-N between an activated state, where in the operational power consumption 110 is the operational power consumption, and an off state, wherein the electric units EM-1, . . ., EM-N are switched off.
  • the global controller 550 may send instructions to the electric units EM-1, ..., EM-N to change to the activated state, thereby increasing operational power consumption 110 if required by the market demand.
  • the global controller 550 may also send instructions to the electric units EM-1, . . . , EM-N to change to the off state, where the electric units EM-1, . . . , EM-N are switched off and have no operational power consumption 110 or an idle operational power consumption 110 if required by the market demand.
  • Figure 3 illustrates a storage module 520 and the transforming 1300 of response curves 150.
  • a reference electric unit REM with a reference response curve 120 and a reference operational power consumption 130 is provided 1100 along with a plurality of electric units EM-1, EM-N that each have an operational power consumption 110.
  • the reference electric unit REM and the plurality of electric units EM-1, . . ., EM-N is of the same type of electric unit EM- 1 , . . . , EM-N, thereby the response curves 150 may be of identical curve shape and only differ in a scaling which depends on the operational power consumption 110 of the electric units EM-1, . . . , EM-N.
  • a scaling factor 140 can be calculated 1200 for each electric unit EM-1, . . . , EM-N by dividing the operational power consumption 110 of each electric unit EM-1, . . ., EM-N with the reference operational power consumption 130.
  • the scaling factor 140 of each individual electric unit EM-1, . . ., EM-N can be used to transform 1300 the reference response curve 120 as a function of the scaling factor 140 to represent the response curve 150 of each individual electric unit EM-1, . . ., EM-N. Thereby a plurality of response curves 150 can be obtained from a single reference response curve 120.
  • the plurality of response curves 150 of the plurality of electric units EM-1, ..., EM-N are stored on the storage module 520 comprised in the server 500 of the aggregated system 400.
  • One or more reference response curves 120 may be provided 1100 for one or more reference electrics units REM operated at different reference operational power consumptions 130.
  • the reference response curve 120 and reference operational power consumption 130 within closest proximity to each individual electric unit EM-1, . . ., EM-N may then be used to calculate 1200 the scaling factor 140 and transform 1300 the reference response curve 120 as a function of the scaling factor 140 to represent a response curve 150 for each individual electric unit EM-1, ..., EM-N. Thereby increasing the precision of the provided plurality of response curves 150.
  • Figure 4 illustrates a computation module 550 for forming a demand-response resource 200.
  • a plurality of electric units EM-1, EM-N are combined to a virtual electric machine 30 within the computation module 550 comprised in the server 500 of the aggregated system 400 forming 1400 a demand-response resource 200.
  • the computation module 550 is able to form 1400 new virtual electric machines 30 of the plurality of electric units EM-1, . . ., EM-N as function of balancing demand.
  • the virtual electric machine 30 is a demand-response resource 200 which can be used for balancing a grid of an electricity market zone 10 and/or combined energy market zone 20.
  • the virtual electric machine 30 is regulated by global controller 550 such that the demandresponse matches markets need.
  • Figure 5 illustrates the relationship between an exemplary reference response curve 120 and a plurality of response curves 150.
  • the operational power consumption is the second axis and time is along the first axis.
  • the response curves 120,150 are response curves 120,150 of electric units EM-1, . . ., EM-N of the same type, thereby the response curves 120,150 may be of identical curve shape and only differ in a scaling which depends on the operational power consumption 110 of the electric units EM-1, . . ., EM-N.
  • This graph is a simple representation of how the response curves are transformed by scaling.
  • the response curve EM-N of electric unit EM-N has the largest scaling factor 140 (not shown) due to having the highest operational power consumption I IO(EM-N) and electric unit EM-1 has the lowest scaling factor.
  • a scaling factor 140 can be calculated 1200 for each electric unit EM-1, . . . , EM-N by dividing the operational power consumption 110 of each electric unit EM-1, . . ., EM-N with the reference operational power consumption 130.
  • Fig. 6 illustrates another method 1000 for forming demand-response resource to an electricity market zone and/or combined market zones.
  • the method comprises the same steps as described for figure 1.
  • the method 1000 further includes steps of

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Abstract

A method (1000) for forming a demand-response resource (200) to an electricity market zone (10) and/or combined market zones (20), wherein the method (1000) comprises steps of - providing (1100) electric units (EM-1, …, EM-N) within an electricity market zone (10) operated by one or more third parties, wherein the electric units (EM-1, …, EM-N) are the same type of electric unit (EM-1, …, EM-N) and each electric unit (EM-1, …, EM-N) have an operational power consumption (110); - providing (1100) a reference response curve (120) of a reference electric unit (REM) of the electric units (EM-1, …, EM-N) having a reference operational power consumption (130); - calculating (1200) a scaling factor (140) of each electric unit (EM-1, …, EM-N) by dividing the operational power consumption (110) of each electric unit (EM-1, …, EM-N) with the reference operational power consumption (130); - transforming (1300) the reference response curve (120) as a function of scaling factor (140) associated with each electric unit (EM-1, …, EM-N), thereby providing a plurality of response curves (150); - forming (1400) a demand-response resource (200) by combining several of the electric units (EM-1, …, EM-N) into a virtual electric machine (30) as a function of a balancing demand and the response curves (150) of the plurality of electric units (EM-1, …, EM-N); and - operating (1500) the virtual electric machine (30) as a function of market demand.

Description

A method and an aggregated system for forming a demand-response resource to an electricity market zone
Field of the Invention
The present invention relates to a method and an aggregated system for forming a demandresponse resource to an electricity market zone and/or combined market zones using electric units without knowing the response curves for each individual electric unit. This will enable low consumption electric units to be used in demand responses, where the cost of obtaining and maintaining response curves would be greater than the possible income from forming demand responses.
Background of the Invention
There are many electric units, which have simple and predictable response curves. A cartridge heater is an example of an electric unit with a simple and predictable response curve. However, most cartridge heaters have a low power consumption relative to an electricity market, with a great number of cartridge heaters in most electricity markets.
Thus, there has been an effort to form a demand response using a great number of cartridge heaters. It is possible to measure the response curve of each individual cartridge heater and then form a demand response using known measures. However, the cost of measuring the response curve of each individual cartridge heater outweighs the potential earning.
There are many cartridge heaters in an electricity market such as the Danish DK1. In refrigerated counters frost is a problem as it reduces the cooling efficiency and thus increases cost over time if the frost is not counteracted. The frost is removed by turning on cartridge heaters periodically to remove any build-up of frost. A store such as Netto (Brand name) has more than 500 stores in Denmark (DK1 & DK2) and each store will typically have more than three refrigerated counters equipped with several cartridge heaters. Some refrigerated counters have cartridge heaters with a combined power consumption of 3 kW to 24 kW or even above as it scales with the refrigerated counters. There are thousands of stores across Denmark similar to Netto. Thus, there is the potential for a demand response having a very high-power consumption if the present problems can be solved. Object of the Invention
The object of the invention is to provide a method and an aggregated system for forming a demand-response resource to an electricity market zone and/or combined market zones using electric units without knowing the response curves for each individual electric unit.
Description of the Invention
An object of the invention is achieved by a method for forming a demand-response resource to an electricity market zone and/or combined market zones, wherein the method comprises steps of
- providing electric units within an electricity market zone operated by one or more third- parties, wherein the electric units are the same type of electric unit and each electric unit have an operational power consumption;
- providing a reference response curve of a reference electric unit of the electric units having a reference operational power consumption;
- calculating a scaling factor of each electric unit by dividing the operational power consumption of each electric unit with the reference operational power consumption;
- transforming the reference response curve as a function of scaling factor associated with each electric unit, thereby providing a plurality of response curves;
- forming a demand-response resource by combining several of the electric units into a virtual electric machine as a function of the balancing demand and the response curves of the plurality of electric units; and
- operating the virtual electric machine as a function of market demand.
The demand-response resources are characterised by a combination of electric units with mapped response profiles that may participate in the electricity market zones and/or combined market zones, where combined market zones are two or more electricity market zones. The electric units are part of a single electricity market zone; however, some demand-response resources are offered for balancing combined market zones.
The demand-response resources may for the Danish electricity market zone (DK1) be an FCR response for balance generation and demand; thereby balancing the frequency to 50,000 Hz. All types of demand-response resources are known for a given market. The energy and reserve markets may be divided into electricity market zones and/or combined market zones with different market demands. The demand-response resources need to comply with the technical demands, geographical dependency etc. of a given zone to participate in the market. The electric units may be electric units with low operational power consumption such as e.g., cartridge heaters, where the costs of measuring response curves of each individual electric unit outweigh the potential earnings of forming a demand-response resources to an electricity market zone and/or combined market zones.
Electric units of the same type may have response curves of identical curve shapes that only differ in a scaling which depends on the operational power consumption of the electric unit. Thus, by providing a reference electric unit of the same type as the electric units provided by the method, it is only necessary to provide a reference response curve of the reference electric units, when the operational power consumption of each individual electric unit is known.
The reference electric unit may be a separate electric unit to all the electric units used for forming the demand-response or form part of the electric units used for forming the demandresponse.
However, there can still be a great variance between electric units of the same type such as electric cartridges since the response curve of an electric cartridge for heating room temperature water is not the same as an electric cartridge for removing frost from a condensation, as the task and the difference in temperature and task result in different response curves. The difference may not be large but if 100 or 1000 electric units are combined into the virtual electric machine then one could have an unpredictable market demand response.
Thereby, it is possible to calculate a scaling factor of each individual electric unit by dividing the operational power consumption of each electric unit with the reference operational power consumption of the reference electric unit. The scaling factor of each individual electric unit may thus be used to scale the reference response curve to represent the response curve of each individual electric unit. Thereby a plurality of response curves can be obtained from a single reference response curve.
An advantage of this is that the need for providing response curves of each individual electric unit is overcome. Thereby, the possible earnings of forming a demand-response resource to an electricity market zone and/or combined market zones may surpass the costs. Thus it becomes favourable for these electric units to participate in the electricity market zones and/or combined market zones. The step of providing a reference response curve of a reference electric unit may include performing response tests for generating the response curve.
The step of providing a reference response curve may be a step of providing one or more reference response curves of one or more reference electrics units operated at different operational power consumption. The reference response curve and reference operational power consumption within closest proximity to each individual electric unit may then be used to calculate the scaling factor and provide a response curve for each individual electric unit. Thereby increasing the precision of the provided plurality of response curves.
The electric units may be operated by one or more third parties and thus the availability of power consumption of each of the electric unit will change as a function of time. It is therefore important that the method receives the operational power consumption and/or activation periods of the plurality of electric units regularly.
This enables that the method can form a demand-response resource by combining several of the electric units into a virtual electric machine, which is able to provide the necessary balancing demand. The balancing demand could be for stabilising the frequency.
The method facilitates that decentralised third party’s electric devices can be offered as a demandresponse resource without disturbing or with limited disturbance of the third party’s operation as the third party operates as required. The third party may be able to observe that for example a cartridge heater is activated at different periods. The third party may accept the limited disturbance as the third party is paid for providing a demand-response resource.
The step of operating may be a step of continuously recording the demand-response resource as a function of demand thereby ensuring that the continued qualification of the demandresponse resource to participate in the market.
The demand-response resource according to the present invention is only able to respond to a need for increasing power demand since the method can only activate the electric units of the virtual electric machine and the activation will increase power consumption. The electric units will have very limited power consumption or no power consumption when in an off state. The control of the individual electric units will be binary. Thereby, the method can form a demand-response resource of electric units with low power consumption suitable for participating in one or more markets, and if the demands-response resource ceases to qualify for a particular market or a better market arises, then the method is capable of moving the demands-response source to a different and/or better market.
The reference response curve of a reference electric unit may be measured with a resolution of at least 5 seconds, at least 3 seconds, or preferably 1 second or greater.
In an aspect, the operational power consumption of one or more electric units may differ from one or more of the other electric units.
The scaling factor enables that the method works for electric units having different operational power consumptions by transforming the reference response curve as a function of scaling factor. Thereby, a greater adaptability of the formed demand-response resource may be achieved as the demand-response resource may be suitable for participating in more markets.
In some embodiments, the operational power consumption of one electric unit may be greater than the other electric units comprised in the formed demand-response resource. Thereby, a greater flexibility of the demand-response resource may be achieved as the power consumption can be further increased to accommodate the required market demands.
In an aspect, the electric units may be cartridge heaters, or motors driving air circulation, or pumps for periodically agitating liquid tanks, or motors driving a mechanical element for agitating liquid tanks.
Motors driving air circulation have a simple and predictable response curve and thus a scaling factor can be used for transforming a reference response curve as a function of the scaling factor. Motors driving air circulation of an underground car parking space are suitable to form the demand response according to the invention. Because the motors are periodically turned on to remove CO2, particles, and other gasses.
Many liquid tanks having stagnant liquid is periodically or regularly agitated to prevent sedimentation. This is performed in water purifying plants but also within other industries. This can be performed by pumps agitating liquid tanks or a motor driving a mechanical element for agitating liquid tanks. The pumps’ and/or motors’ drive agitates the liquid in the tanks such that the sedimentation is prevented or at least reduced.
In an aspect, the cartridge heater may be installed in refrigerated counters and the cartridge heater are configured for defrosting the refrigerated counters.
The cartridge heater is typically installed for defrosting the condenser of the refrigerated counters such that the efficiency of the condenser is not reduced by the frost.
The electric units may all be cartridge heater installed in refrigerated counters.
In an aspect, the electric units may be operated between two states;
- an activated state wherein the power consumption is the operational power consumption;
- an off state, wherein the electric units are switched off.
The electric units may only have these two states since it makes it possible to control the electric units without knowing precise data as each electric unit is either “on” i.e. in the activated state or “off’ i.e. in the off state where the electric unit is switched off and has no power consumption or an idle power consumption.
The electric units may receive instruction to change state to an activated state when an increase in power consumption is required by the market demand. The market demand for increased power consumption will at some point drop off and the electric units will then be instructed to change state to the off state.
Thereby power consumption by the electric units comprised in the demand-response resource can be controlled to accommodate the market demand.
In an aspect, the state of the electric units may periodically be changed to the activated state and the state of the electric units may after a pre-set period be changed to the off state or as a function of an instruction to change state to the off state. The pre-set period is a fail-safe in the system such that the electric units does not keep consuming power if no instructions have been received. In most methods the electric units should receive instruction to change state to the off state unless something goes wrong. The pre-set period may be pre-set periods of at least 10 minutes or at least 15 minutes or at least 30 minutes.
Please note that periodic in this application does not mean that the electric units must change their state exactly every 24 hours but more like once per day or once per two days or once per three days, i.e. a relatively broad interpretation should be applied.
An electric cartridge for a condenser should periodically be changed to the activated state to remove frost. However, there may have been a long period without any need for the method to form and operate the virtual electric machine as a function of market demand. At some point the electric cartridge should receive instruction to change its state to an activated state as the condenser efficiency would drop off thus the state of the electric units may periodically be changed to the activated state.
In an aspect, the operational power consumption of the electric units may be in the range of 1 kW to 40 kW or 2 kW to 30 kW or 3 kW to 25 kW.
These power consumptions will in general mean that it will not be economically viable to measure and/or determine each electric unit’s response curve. However, it is possible to use these units in demand-response resources by utilising the scaling factor as described above or in claim 1.
In an aspect, the method steps of providing, calculating, and transforming may be repeated for a second group of electric units and the step of forming a demand-response resource is performed by forming several of the electric units into a virtual electric machine as a function of a balancing demand and the response curves of the plurality of electric units.
This enables that electric cartridges and motors driving air circulation can be combined into a single demand response, i.e. by forming a virtual electric machine. Within each group a reference response curve of a reference electric unit is chosen and all response curves within each group is transformed according to the group scaling factor; the step of forming the demand-response resource is performed by combining electric units from each group. There may be three, four, or five different groups, or even more groups without changing the essence of the invention.
Another way is to perform the method according to the invention and then form two or more demand-response resources by combining several of the electric units into virtual electric machines, wherein all the electric units of a virtual electric machine are from the same group and afterwards the virtual electric machines are combined into a superimposed virtual electric machine.
In an aspect, the method may further include a step of
- measuring real-time power consumption of a sub-set of electric units;
- combining the transformed response curves of the sub-set of electric units into a sub-set response curve;
- determining a deviation factor between summarised power consumption of the sub-set of electric units and the sub-set response curve;
- operating the virtual electric machine as a function of market demand and the deviation factor.
The precision with respect to power consumption that the virtual electric machine can be operated can be increased significantly by measuring a sub-set of electric units in real-time. The measured power consumption is then compared with the sub-set response curve and a deviation factor is then determined and all electric units of the virtual electric machine is then operated as a function of market demand and the deviation factor. The deviation factor will typically be the ratio between summarised power consumption of the sub-set of electric units and the sub-set response curve. In some cases the electric units will be instructed to increase power consumption by as an example 1 % or 0.5 % or another number and in other cases the electric units will be instructed to decrease power consumption by as an example 1 % or 0.5 % or another number.
The deviation factor will change over the course of a year because temperature and air humidity and other factors will affect the power consumption of the electric units. Hence the deviation factor enables that the method can perform seasonal adjustment. Real-time power consumption may be measured at least once per 5 seconds or with a period of 3 second or with a period of 1 seconds or a period of 0.5 seconds. In most cases a measurement every second is sufficient.
In an aspect, the sub-set of electric units may be 5 to 50 % of the electric units or 5 to 40 % of the electric units or 7 to 30 % of the electric units or 10 to 25 % of the electric units or 10 to 20 % of the electric units.
The method is still more efficient than measuring all electric units by only measuring 50 % of the electric units. However, in many cases measuring 5 %, or 10 % or 20 % of the electric units is sufficient to control the virtual machine within the needed precision.
In an aspect, the sub-set of electric units may be chosen amongst the electric units having a power consumption equal to or above the median power consumption of the electric units.
By choosing the electric units above the median power consumption of the electric units will decrease the number of electric units, which need to be measured as the measured electric units have greater weight in the final power consumption compared to the electric units below the median.
In the case where measurement is performed on 5 % of the electric units then then the electric units is preferably taken from the top 5 % consuming electric units or the top 10 % consuming electric units or 15 % consuming electric units.
In the case where measurement is performed on 10 % of the electric units then then the electric units is preferably taken from the top 10 % consuming electric units or the top 15 % consuming electric units or 20 % consuming electric units.
In the case where measurement is performed on 15 % of the electric units then then the electric units is preferably taken from the top 15 % consuming electric units or the top 20 % consuming electric units or 25 % consuming electric units.
An object of the invention is achieved by an aggregated system for responding to a balancing demand on an electricity market zone and/or combined electricity market zones, wherein the aggregated system comprises - electric units within an electricity market zone operated by one or more third-parties wherein the electric units are the same type of electric unit and each electric unit have an operational power consumption;
- a server comprising
- a server communication module in communication with the electric units, and
- a storage module having stored thereon response curves of the electric units; the response curves being transformed based on a reference electric unit of the electric units having a reference operational power consumption;
- a monitoring module adapted for monitoring balancing demand of the electricity market zone and/or the combined market zones;
- a computation module adapted for forming a demand-response resource by combining several of the electric units into a virtual electric machine as a function of response curves and requirements of the balancing demand; and
- a global controller configured to activate the virtual electric machine by sending instructions to the electric units forming part of the virtual electric machine.
The aggregated system is in connection with a plurality of electric units through a global controller and enables control the activation of the plurality of electric units. The aggregated system is unable to receive live power consumption data from each electric unit instead the aggregated system works by scaling a reference response curve. The server comprises a storage module having stored thereon a reference response curve of a reference electric unit for determining the response curves of the electric units. Thereby, the aggregated system can form a demand-response resource using electric units without measuring response curves for each individual electric unit.
The electric units comprised in the aggregated system may be small electric unit with low operational power consumption such as e.g., cartridge heater, where the costs of measuring response curves of each individual electric unit outweigh the potential earnings of forming a demand-response resources to an electricity market zone and/or combined market zones.
Electric units of the same type may have response curves of identical curve shape that only differ in a scaling that depends on the operational power consumption of the electric unit. By having reference electric unit of the same type as the electric units comprised in the aggregated system, a scaling factor of each individual electric unit may be calculated by dividing the operational power consumption of each electric unit with the reference operational power consumption of the reference electric unit. The storage module may thereby store a reference response curve for a reference electric unit with a reference operational power consumption that can be scaled to represent response curves for each individual electric unit by the scaling factor.
The means for measuring operational power consumption of the electric units and the reference electric unit may be a power meter or similar. The means may be a voltage meter and a current meter which can be combined to measure the power consumption. There may be other solutions capable of determining the power consumption of an electric meter.
The storage module may have one or more reference response curves of one or more reference electric units with different operational power consumptions stored thereon. The reference response curve and reference operational power consumption within closest proximity to each individual electric unit may then be used to calculate the scaling factor and provide a response curve for each individual electric unit. Thereby increasing the precision of the stored response curves.
The electric units are operated by one or more third parties and thus the plurality of electric units is not on stand-by as such for forming part of a demand-response. Instead, the electric units are operated according to the need of the third-party.
In an aspect, the global controller activates two or more virtual electric machines as a function of an imbalance in the electricity market zone or combined electricity market zones.
The aggregated system is not limited to only activating and controlling one virtual electric machine. The aggregated system may activate two or more virtual electric machines as the aggregated system is only limited by the available capacity of the plurality of electric units.
In an aspect, the electric units are operated between two states;
- an activated state, wherein the power consumption is the operational power consumption; - an off state, wherein the electric units are switched off.
The electric units may only have these two states since it makes it possible to control the electric units without knowing precise data as each electric unit is either “on” i.e. in the activated state or “off’ i.e. in the off state where the electric unit is switched off and has no power consumption or an idle power consumption.
The electric units may receive instruction to change state to an activated state when an increase in power consumption is required by the market demand. The market demand for increased power consumption will at some point drop off and the electric units will then be instructed to change state to the off state.
Thereby power consumption by the electric units comprised in the demand-response resource can be controlled to accommodate the market demand.
In an aspect, the server communication module may be configured for receiving real-time power consumption of a sub-set of electric units, and the computation module being further adapted for
- combining the transformed response curves of the sub-set of electric units into a sub-set response curve;
- determining a deviation factor between summarised power consumption of a subset of electric units and the sub-set response curve; the global controller being further configured to operate the virtual electric machine as a function of market demand and the deviation factor.
The precision with respect to power consumption that the virtual electric machine can be operated can be increased significantly by measuring a sub-set of electric units in real-time. The measured power consumption is then compared with the sub-set response curve and a deviation factor is then determined and all electric units of the virtual electric machine is then operated as a function of market demand and the deviation factor. The deviation factor will typically be the ratio between summarised power consumption of the sub-set of electric units and the sub-set response curve. In some cases the electric units will be instructed to increase power consumption by as an example 1 % or 0.5 % or another number and in other cases the electric units will be instructed to decrease power consumption by as an example 1 % or 0.5 % or another number.
Real-time power consumption may be measured at least once per 5 seconds or with a period of 3 second or with a period of 1 seconds or a period of 0.5 seconds. In most cases a measurement every second is sufficient.
In an aspect, the sub-set of electric units may be 5 to 50 % of the electric units or 5 to 40 % of the electric units or 7 to 30 % of the electric units or 10 to 25 % of the electric units or 10 to 20 % of the electric units.
The method is still more efficient than measuring all electric units by only measuring 50 % of the electric units. However, in many cases measuring 5 %, or 10 % or 20 % of the electric units is sufficient to control the virtual machine within the needed precision.
In an aspect, the sub-set of electric units may be chosen amongst the electric units having a power consumption equal to or above the median power consumption of the electric units. By choosing the electric units above the median power consumption of the electric units will decrease the number of electric units, which need to be measured as the measured electric units have greater weight in the final power consumption compared to the electric units below the median.
In the case where measurement is performed on 5 % of the electric units then then the electric units is preferably taken from the top 5 % consuming electric units or the top 10 % consuming electric units or 15 % consuming electric units.
In the case where measurement is performed on 10 % of the electric units then then the electric units is preferably taken from the top 10 % consuming electric units or the top 15 % consuming electric units or 20 % consuming electric units.
In the case where measurement is performed on 15 % of the electric units then then the electric units is preferably taken from the top 15 % consuming electric units or the top 20 % consuming electric units or 25 % consuming electric units. Description of the Drawing
Embodiments of the invention will be described in the figures, whereon:
Fig. 1 illustrates a method for forming demand-response resource to an electricity market zone and/or combined market zones;
Fig. 2 illustrated an aggregate system for responding to a balancing demand on an electricity market zone and/or combined electricity market zones;
Fig. 3 illustrates a storage module and the transforming of response curves;
Fig. 4 illustrates a computation module for forming a demand-response resource; Fig. 5 illustrate the relationship between an exemplary reference response curve and a plurality of response curves.
Fig. 6 illustrates another method for forming demand-response resource to an electricity market zone and/or combined market zones. Detailed Description of the Invention
Figure imgf000015_0001
Figure imgf000016_0001
Figure 1 illustrates a method 1000 for forming demand-response resource 200 to an electricity market zone 10 and/or combined market zones 20, where electric units EM-1, ..., EM-N of the same type are provided 1100 along with reference response curve 120 of a reference electric unit REM. The provided 1100 electric units EM-1, . . . , EM-N are operated by one or more third parties within an electricity market zone 10 and each electric unit EM-1, . . . , EM-N have an operational power consumption 110. The reference electric unit REM have a reference operational power consumption 130.
The step of providing 1100 a reference response curve 120 of a reference electric unit REM may include performing response tests for generating the reference response curve 120.
One of the provided electric units EM-1, . . . , EM-N may have operational power consumption differing from the other electric units EM-1, . . . , EM-N.
The electric units EM-1, ..., EM-N may be electric units EM-1, ..., EM-N with low operational power consumption 110 such as e.g., cartridge heaters, where the costs of measuring response curves 150 of each individual electric unit EM-1, . . ., EM-N outweigh the potential earnings of forming a demand-response resources 200 to an electricity market zone 10 and/or combined market zones 20. The electric units EM-1, EM-N may have an operational power consumption 110 in the ranges of 1 kW to 40 kW or 2 kW to 30 kW or 3 kW to 25 kW.
Electric units EM-1, . . ., EM-N of the same type may have response curves 150 of identical curve shape that only differ in a scaling which depends on the operational power consumption 110 of the electric unit EM-1, . . . , EM-N.
Providing 1100 a reference electric unit REM of the same type as the electric units EM-1, . . ., EM-N, it is only necessary to provide a reference response curve 120 of the reference electric unit REM, when the operational power consumption 110 of each individual electric unit EM- 1, . . . , EM-N is known.
A scaling factor 140 can be calculated 1200 for each electric unit EM-1, . . . , EM-N by dividing the operational power consumption 110 of each electric unit EM-1, . . ., EM-N with the reference operational power consumption 130.
The scaling factor 140 of each individual electric unit EM-1, . . ., EM-N can be used to transform 1300 the reference response curve 120 as a function of the scaling factor 140 to represent the response curve 150 of each individual electric unit EM-1, . . ., EM-N. Thereby, a plurality of response curves 150 can be obtained from a single reference response curve 120.
One or more reference response curves 120 may be provided 1100 for one or more reference electrics units REM operated at different reference operational power consumptions 130. The reference response curve 120 and reference operational power consumption 130 within closest proximity to each individual electric unit EM-1, . . ., EM-N may then be used to calculate 1200 the scaling factor 140 and transform 1300 the reference response curve 120 as a function of the scaling factor 140 to represent a response curve 150 for each individual electric unit EM-1, ..., EM-N. Thereby increasing the precision of the provided plurality of response curves 150 and thus the method 1000.
After the method 1000 has provided a plurality of response curves 150 a demand-response resource 200 can be formed 1400 by combining several of the electric units EM-1, . . ., EM-N into a virtual electric machine 30 as a function of a balancing demand and the response curves By combining several of the electric units EM-1, . . . , EM-N into a virtual electric machine 30, an overall operational power consumption 110 that is high enough to participate in the market may be achieved.
The method 1000 operates 1500 the virtual electric machine 30 as a function market demand. Here the demand-response resource 200 may be recorded as a function of demand, thereby ensuring that the demand-response resource 200 continues to qualify for the market.
The demand-response resource 200 is only able to respond to a need for increasing power demand since the method 1000 can only activate the electric units EM-1, ..., EM-N of the virtual electric machine 30 and the activation will increase power consumption. The electric units EM-1, . . ., EM-N will have very limited power consumption or no power consumption when in an off state. The control of the individual electric units EM-1, . . ., EM-N is binary.
The electric units EM-1, . . ., EM-N may be operated between an activated state, wherein the operational power consumption 110 is the operational power consumption, and an off state wherein the electric units EM-1, . . ., EM-N are switched off.
The electric units EM-1, ..., EM-N may periodically change to the activated state, and the state of the electric units EM-1, . . . , EM-N may after a pre-set period changed to the off state.
The pre-set period is a fail-safe in the system such that the electric units EM-1, ..., EM-N does not keep consuming power if no instructions have been received from the global controller 550. In most methods 1000 the electric units EM-1, . . ., EM-N should receive instructions from the global controller 550 to change state to the off state unless something goes wrong. The pre-set period may be pre-set periods of at least 10 minutes or at least 15 minutes or at least 30 minutes.
Please note that periodic in this application does not mean that the electric units EM-1, ..., EM-N must change their state exactly every 24 hours but more like once per day or once per two days or once per three days, i.e. a relatively broad interpretation should be applied.
The electric units EM-1, . . . , EM-N may receive instructions from the global controller 550 to change state to an activated state when an increase in power consumption is required by the market demand. The market demand for increased power consumption will at some point drop off and the electric units EM-1, . . . , EM-N will then be instructed by the global controller 550 to change state to the off state.
The method 1000 can thus form 1400 a demand-response resource 200 of electric units EM- 1, . . . , EM-N with low operational power consumption 110 suitable for participating in one or more markets, and if the demands-response resource 200 ceases to qualify for a particular market or a better market arises, then the method 1000 is capable of moving the demands- response resource 200 to a different and/or better market.
Figure 2 illustrates an aggregated system 400 for responding to a balancing demand on an electricity market zone 10 and/or combined electricity market zones 20.
The aggregated system 400 comprises a plurality of electric units EM-1, . . ., EM-N within an electricity market zone 10 operated by one or more third parties. The electric units EM-1, . . . , EM-N are of the same type and each electric unit EM-1, . . . , EM-N have an operational power consumption 110. One of the electric units EM-1, . . ., EM-N acts as a reference electric unit REM with a reference operational power consumption 130, and a reference response curve 120 having been measured for the reference electric units REM. A dotted circle is drawn around the plurality of electric units EM-1, . . . , EM-N and the reference electric unit REM, as these units can be positioned decentralised within the electricity market zone 10.
The aggregated system 400 has a server 500 comprising a server communication module 510 in communication 515 with the electric unit EM-1, . . ., EM-N.
The server 500 has a storage module 520 having stored thereon response curves 150 of the plurality of electric units EM-1, ..., EM-N. The response curves 150 have been transformed based on the reference response curve 120 of the electric unit REM having a reference operational power consumption 130.
The server 500 has a monitoring module 530 adapted for monitoring balancing demand of the electricity market zone 10 and/or the combined market zones 20. This is required otherwise the requirement of the balancing demand is unknown and no virtual electric machine 30 can be formed. The monitoring module 530 may comprise a frequency measurement unit monitoring the frequency of the electricity market zone 10 and/or the combined market zones 20.
The server 500 has a computation module 540 adapted for forming a demand-response resource 200 by combining several of the electric units EM-1, . . ., EM-N into a virtual electric machine 30 as a function of the response curves 150 and requirements of the balancing demand. Thus, the virtual electric machine 30 is the at least one demand-response resource 200.
The server 500 has a global controller 550 configured to activate 555 the virtual electric machine 30 by sending instructions to the electric units EM-1, ..., EM-N forming part of the virtual electric machine 30. The global controller 550 may be configured to activate 555 a virtual electric machine 30 as a function of the frequency of the electricity market zone 10 and/or the combined market zones 20.
The aggregated system 400 is not limited to only activating 555 one virtual electric machine 30. The aggregated system 400 may activate 555 two or more virtual electric machines 30 as the aggregated system 400 is only limited by the available capacity of the plurality of electric units EM- 1 , . . . , EM-N.
The aggregated system 400 may operate the electric units EM-1, . . ., EM-N between an activated state, where in the operational power consumption 110 is the operational power consumption, and an off state, wherein the electric units EM-1, . . ., EM-N are switched off.
The global controller 550 may send instructions to the electric units EM-1, ..., EM-N to change to the activated state, thereby increasing operational power consumption 110 if required by the market demand. The global controller 550 may also send instructions to the electric units EM-1, . . . , EM-N to change to the off state, where the electric units EM-1, . . . , EM-N are switched off and have no operational power consumption 110 or an idle operational power consumption 110 if required by the market demand.
Figure 3 illustrates a storage module 520 and the transforming 1300 of response curves 150. A reference electric unit REM with a reference response curve 120 and a reference operational power consumption 130 is provided 1100 along with a plurality of electric units EM-1, EM-N that each have an operational power consumption 110.
The reference electric unit REM and the plurality of electric units EM-1, . . ., EM-N is of the same type of electric unit EM- 1 , . . . , EM-N, thereby the response curves 150 may be of identical curve shape and only differ in a scaling which depends on the operational power consumption 110 of the electric units EM-1, . . . , EM-N.
A scaling factor 140 can be calculated 1200 for each electric unit EM-1, . . . , EM-N by dividing the operational power consumption 110 of each electric unit EM-1, . . ., EM-N with the reference operational power consumption 130.
The scaling factor 140 of each individual electric unit EM-1, . . ., EM-N can be used to transform 1300 the reference response curve 120 as a function of the scaling factor 140 to represent the response curve 150 of each individual electric unit EM-1, . . ., EM-N. Thereby a plurality of response curves 150 can be obtained from a single reference response curve 120.
The plurality of response curves 150 of the plurality of electric units EM-1, ..., EM-N are stored on the storage module 520 comprised in the server 500 of the aggregated system 400.
One or more reference response curves 120 may be provided 1100 for one or more reference electrics units REM operated at different reference operational power consumptions 130. The reference response curve 120 and reference operational power consumption 130 within closest proximity to each individual electric unit EM-1, . . ., EM-N may then be used to calculate 1200 the scaling factor 140 and transform 1300 the reference response curve 120 as a function of the scaling factor 140 to represent a response curve 150 for each individual electric unit EM-1, ..., EM-N. Thereby increasing the precision of the provided plurality of response curves 150.
Figure 4 illustrates a computation module 550 for forming a demand-response resource 200. A plurality of electric units EM-1, EM-N are combined to a virtual electric machine 30 within the computation module 550 comprised in the server 500 of the aggregated system 400 forming 1400 a demand-response resource 200.
The computation module 550 is able to form 1400 new virtual electric machines 30 of the plurality of electric units EM-1, . . ., EM-N as function of balancing demand.
The virtual electric machine 30 is a demand-response resource 200 which can be used for balancing a grid of an electricity market zone 10 and/or combined energy market zone 20. The virtual electric machine 30 is regulated by global controller 550 such that the demandresponse matches markets need.
Figure 5 illustrates the relationship between an exemplary reference response curve 120 and a plurality of response curves 150. The operational power consumption is the second axis and time is along the first axis. The response curves 120,150 are response curves 120,150 of electric units EM-1, . . ., EM-N of the same type, thereby the response curves 120,150 may be of identical curve shape and only differ in a scaling which depends on the operational power consumption 110 of the electric units EM-1, . . ., EM-N. This graph is a simple representation of how the response curves are transformed by scaling. Here the response curve EM-N of electric unit EM-N has the largest scaling factor 140 (not shown) due to having the highest operational power consumption I IO(EM-N) and electric unit EM-1 has the lowest scaling factor.
A scaling factor 140 can be calculated 1200 for each electric unit EM-1, . . . , EM-N by dividing the operational power consumption 110 of each electric unit EM-1, . . ., EM-N with the reference operational power consumption 130.
Fig. 6 illustrates another method 1000 for forming demand-response resource to an electricity market zone and/or combined market zones. The method comprises the same steps as described for figure 1. In addition, the method 1000 further includes steps of
- measuring 1600 real-time power consumption of a sub-set of electric units EM-1, ..., EM-N;
- combining 1700 the transformed response curves 150 of the sub-set of electric units EM-1, . . ., EM-N into a sub-set response curve; - determining 1800 a deviation factor between summarised power consumption of the sub-set of electric units EM-1, . . EM-N and the sub-set response curve;
- operating 1500 the virtual electric machine 30 as a function of market demand and the deviation factor.

Claims

1. A method (1000) for forming a demand-response resource (200) to an electricity market zone (10) and/or combined market zones (20), wherein the method (1000) comprises steps of
- providing (1100) electric units (EM-1, ..., EM-N) within an electricity market zone (10) operated by one or more third parties, wherein the electric units (EM-1, ..., EM-N) are the same type of electric unit (EM-1, . . ., EM-N) and each electric unit (EM-1, . . ., EM-N) have an operational power consumption (110);
- providing (1100) a reference response curve (120) of a reference electric unit (REM) of the electric units (EM-1, . . ., EM-N) having a reference operational power consumption (130);
- calculating (1200) a scaling factor (140) of each electric unit (EM-1, . . . , EM-N) by dividing the operational power consumption (110) of each electric unit (EM-1, ..., EM-N) with the reference operational power consumption (130);
- transforming (1300) the reference response curve (120) as a function of scaling factor (1 0) associated with each electric unit (EM-1, . . . , EM-N), thereby providing a plurality of response curves (150);
- forming (1400) a demand-response resource (200) by combining several of the electric units (EM-1, ..., EM-N) into a virtual electric machine (30) as a function of a balancing demand and the response curves (150) of the plurality of electric units (EM-1, . . ., EM-N); and
- operating (1500) the virtual electric machine (30) as a function of market demand.
2. Method (1000) according to claim 1, wherein the operational power consumption operational power consumption of one or more electric units (EM-1, . . ., EM-N) differ from one or more of the other electric units (EM-1, . . . , EM-N).
3. Method (100) according to claim 1 or 2, wherein the electric units (EM-1, . . ., EM-N) are cartridge heaters, or motors driving air circulation, or pumps for periodically agitating liquid tanks, or motors driving a mechanical element for agitating liquid tanks.
4. Method (1000) according to claim 3, wherein the cartridge heaters are installed in refrigerated counters and the cartridge heater are configured for defrosting the refrigerated counters.
5. Method (1000) according to anyone of claims 1-4, wherein the electric units (EM-1, ... , EM-N) are operated between two states; - an activated state, wherein the operational power consumption (110) is the operational power consumption;
- an off state, wherein the electric units (EM-1, . . ., EM-N) are switched off.
6. Method (1000) according to claim 5, wherein the state of the electric units (EM-1, . . . , EM- N) is periodically changed to the activated state and the state of the electric units (EM-1, . . ., EM-N ) are after, a pre-set period, changed to the off state or as a function of an instruction to change state to the off state.
7. Method (1000) according to anyone of claims 1-6, wherein the operational power consumption (110) of the electric units (EM-1, . . ., EM-N) is in the range of 1 kW to 40 kW or 2 kW to 30 kW or 3 kW to 25 kW.
8. Method (1000) according to anyone of claims 1-7, wherein the method steps of providing, calculating and transforming is repeated for a second group of electric units (EM-1, . . ., EM- N) and the step of forming (1400) a demand-response resource (200) is performed by forming several of the electric units (EM- 1 , . . . , EM-N) into a virtual electric machine (30) as a function of a balancing demand and the response curves (150) of the plurality of electric units (EM-1, ..., EM-N).
9. Method (1000) according to anyone of claims 1-8, wherein the method (1000) further includes a step of
- measuring (1600) real-time power consumption of a sub-set of electric units (EM-1, . . . , EM- N);
- combining (1700) the transformed response curves (150) of the sub-set of electric units (EM- 1, . . . , EM-N) into a sub-set response curve;
- determining (1800) a deviation factor between summarised power consumption of the subset of electric units (EM-1, . . ., EM-N) and the sub-set response curve;
- operating (1500) the virtual electric machine (30) as a function of market demand and the deviation factor.
10. Method (1000) according to claim 9, wherein the sub-set of electric units (EM-1, . . . , EM- N) is 5 to 50 % of the electric units (EM-1, . . . , EM-N) or 5 to 40 % of the electric units (EM- 1, . . . , EM-N) or 7 to 30 % of the electric units (EM-1, . . . , EM-N) or 10 to 25 % of the electric units (EM-1, . . . , EM-N) or 10 to 20 % of the electric units (EM-1, . . . , EM-N).
11. Method (1000) according to claim 9 or 10, wherein the sub-set of electric units (EM-1, . . . , EM-N) is chosen amongst the electric units (EM-1, . . . , EM-N) having a power consumption equal to or above the median power consumption of the electric units (EM-1, ..., EM- N).
12. An aggregated system (400) for responding to a balancing demand on an electricity market zone (10) and/or combined electricity market zones (20), wherein the aggregated system (400) comprises
- electric units (EM-1, ..., EM-N) within an electricity market zone (10) operated by one or more third parties, wherein the electric units (EM-1, . . . , EM-N) are the same type of electric unit (EM-1, . . ., EM-N) and each electric unit (EM-1, . . ., EM-N) have an operational power consumption (110);
- a server (500) comprising
- a server communication module (510) in communication (515) with the electric units (EM-1, . . . , EM-N), and
- a storage module (520) having stored thereon response curves (150) of the electric units (EM-1, ..., EM-N); the response curves (150) being transformed based on a reference electric unit (REM) of the electric units (EM-1, . . . , EM-N) having a reference operational power consumption (130);
- a monitoring module (530) adapted for monitoring balancing demand of the electricity market zone (10) and/or the combined market zones (20);
- a computation module (540) adapted for forming a demand-response resource (200) by combining several of the electric units (EM-1, ..., EM-N) into a virtual electric machine (30) as a function of response curves (150) and requirements of the balancing demand; and
- a global controller (550) configured to activate (555) the virtual electric machine (30) by sending instructions to the electric units (EM-1, . . ., EM-N) forming part of the virtual electric machine (30).
13. An aggregated system (400) according to claim 9, wherein the global controller (550) activates (555) two or more virtual electric machines (30) as a function of an imbalance in the electricity market zone (10) or combined electricity market zones (20).
14. An aggregated system (400) according to claim 12 or 13, wherein the electric units (EM- 1, . . . , EM-N) are operated between two states;
- an activated state, wherein the operational power consumption (110) is the operational power consumption;
- an off state, wherein the electric units (EM-1, . . ., EM-N) are switched off.
15. An aggregated system (400) according to any of claims 12 to 14, wherein the server communication module (510) is configured for receiving real-time power consumption of a subset of electric units (EM-1, . . ., EM-N), and the computation module (540) being further adapted for
- combining (1700) the transformed response curves (150) of the sub-set of electric units (EM-1, . . ., EM-N) into a sub-set response curve;
- determining (1800) a deviation factor between summarised power consumption of a sub-set of electric units (EM-1, . . ., EM-N) and the sub-set response curve; the global controller (550) being further configured to operate the virtual electric machine (30) as a function of market demand and the deviation factor.
16. An aggregated system (400) according to claim 15, wherein the sub-set of electric units (EM-1, . . ., EM-N) is 5 to 50 % of the electric units (EM-1, . . ., EM-N) or 5 to 40 % of the electric units (EM-1, . . . , EM-N) or 7 to 30 % of the electric units (EM-1, . . . , EM-N) or 10 to 25 % of the electric units (EM-1, ..., EM-N) or 10 to 20 % of the electric units (EM-1, ..., EM-N).
17. An aggregated system (400) according to claim 16 or 17, wherein the sub-set of electric units (EM-1, ..., EM-N) is chosen amongst the electric units (EM-1, ..., EM-N) having a power consumption equal to or above the median power consumption of the electric units (EM-1, ..., EM-N).
PCT/DK2023/050235 2022-09-30 2023-09-29 A method and an aggregated system for forming a demand-response resource to an electricity market zone Ceased WO2024067936A1 (en)

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