AU2016200978A1

AU2016200978A1 - Method and apparatus for distributing an available energy quantity in a local network

Info

Publication number: AU2016200978A1
Application number: AU2016200978A
Authority: AU
Inventors: Armin Uwe Schmiegel
Original assignee: Robert Bosch GmbH
Current assignee: Robert Bosch GmbH
Priority date: 2015-02-17
Filing date: 2016-02-16
Publication date: 2016-09-01
Also published as: DE102015202803A1; AU2020204009A1; ITUB20160659A1

Abstract

Abstract The invention relates to a method (200) for distributing the available amount of energy in a local energy network (100). In a reading-in step (202), an energy plan (112, 114, 116, 118) for a component (104, 106, 5 108, 110) is read in from the central computer (102) that controls the energy network (100). In a receiving step (204), instantaneous consumption information (128, 130, 132, 134) regarding at least one other component (104, 106, 108, 110) of the local energy network (100) is received. In an allocation step (206), energy (312) is allocated to the 1o component (104, 106, 108, 110) and the other component (104, 106, 108, 110), using the consumption information (128, 130, 132, 134) the component'[s (104, 106, 108, 110) own consumption, and the energy plan (112, 114, 116, 118). (Fig. 4) 2569668v1 CpC mr C%4 +~ ~~ 0=0 o0 0 00000 4*

Description

Method and Apparatus for Distributing an Available Energy Quantity in a Local Network

Prior Art

This invention relates to a method for distributing the available amount of energy in a local energy network, a corresponding apparatus, and a corresponding computer program.

Disclosure of the Invention

With this background, the approach proposed here provides a method for distributing the amount of energy available in a local energy network, an apparatus employing this method, and finally, a corresponding computer program, in accordance with the main claims. Advantageous further developments will emerge from the respective dependent claims and the following description.

Energy can be distributed within a household in such a way that energy generated in the household is utilised particularly well. External factors can be taken into consideration as well. A method for distributing the available amount of energy in a local energy network is proposed. This method has the following steps: - reading-in an energy plan for a component, from a central computer controlling an energy network; - receiving instantaneous consumption information regarding at least one other component of the local energy network; and - allocating energy to the component and the other component, using the consumption information, the component’[s own consumption, and the energy plan.

An energy network may be understood as referring to a household, for example. Within the energy network, energy can be generated, consumed, and stored; and the amount of energy available will be the power currently being generated, plus the power obtainable from the energy storage unit. If the amount of energy available is less than the power currently being consumed, then the shortfall can be drawn from a public power supply network. When the accumulator’^ storage capacity is filled up, additional power can be supplied to the public network, for example. An energy plan constitutes basic settings for a component. The central computer may be a server, in a data network such as the internet.

The method may have a step of sending instantaneous consumption information regarding the component, over the local energy network. This instantaneous consumption information represents the components own consumption. In this way, the components are able to communicate in both directions, thereby optimising the flow of energy in the energy network.

The consumption-information regarding a component may be an item of demand information as to the energy required by that component, or an item of supply information as to the energy available from that component. In this way, the energy demand or energy supply can be signalled.

The method may have a step of providing the central computer with consumption data for a given period. In this way, the central computer is able to produce improved energy plans.

In the allocation step, energy can be allocated first to the component with the highest consumption. In this way, a suitable priority-based sequence can be readily established.

Priority can be given to using locally generated energy, i.e. energy being generated in the local energy network, to cover energy consumption. Thus, energy being generated is used before stored energy, and stored energy is used before energy from the public power supply network.

The energy can be allocated using a weighting factor. This enables preferred transmission paths to be used.

The approach presented here also provides a control unit that is adapted to performing, controlling, and implementing the steps of a variant of the method presented here, in suitable equipment. Also, this variant embodiment of the invention in the form of a control unit enables the underlying objective of the invention to be achieved quickly and efficiently. A control unit can be understood as being, in the present case, an item of electrical equipment that processes sensor signals and, as a function thereof, outputs control signals and/or data signals. The control unit may have an interface implemented as hardware and/or software. When implemented in hardware, the interfaces may for example be part of a so-called system ASIC containing all sorts of functions of the control unit. However, the interfaces may also be separate, integrated circuits, or may consist at least partly of discrete components. When implemented in software, the interfaces may be e.g. software modules that are provided, along with other software modules, on a microcontroller.

Also advantageous is a computer program product or computer program with program code that can be stored on a machine-readable storage device or medium — such as a semiconductor memory, hard disk, or optical storage — and that serves to perform, implement, and/or control the steps of the method according to one of the forms of implementation described above, particularly when the program-product or program is executed on a computer or an apparatus.

The approach presented here will be described in more detail below through examples, which are illustrated in the accompanying drawings. In the drawings:

Fig. 1 is a block circuit diagram of a local energy network with a central computer, in an example of an embodiment of the present invention;

Fig. 2 is a flowchart of a method for distributing the amount of energy available, in an example of an embodiment of the invention;

Fig. 3 is a block circuit diagram of a control unit for a component of a local energy network, in an example of an embodiment of the invention;

Fig. 4 is a representation of the connection of a local energy network to a central computer, in an example of an embodiment of the invention;

Fig. 5 is a schematic representation of components of a local energy network, in an example of an embodiment of the invention;

Fig. 6 is a table of weighting factors, in an example of an embodiment of the invention;

Fig. 7 is a representation of an energy plan for an energy storage system in a local energy network, in an example of an embodiment of the invention;

Fig. 8 is a representation of an energy plan for a washing machine in a local energy network, in an example of an embodiment of the invention; and

Fig. 9 is a representation of an energy plan for a heat storage unit in a local energy network, in an example of an embodiment of the invention.

In the following description of favourable embodiments of the present invention, those elements, in the various Figures, that are similar in function will be given the same or similar reference numbers, and will only be described once.

Fig. 1 is a block circuit diagram of a local energy network 100, with a central (or “host”) computer 102, in an example of an embodiment of the present invention. In this example, the local energy network 100 has four components 104, 106, 108, 110. These components 104,106,108,110 are all networked to one another, and to the central computer 102. The central computer 110 is located outside of the local energy network 100.

The central computer 102 provides: a first energy plan 112 for the first component 104; a second energy plan 114 for the second component 106; a third energy plan 116 for the third component 108; and a fourth energy plan 118 for the fourth component 110. These energy plans 112, 114, 116,118 represent boundary time-settings for the use of energy within the energy network 100.

The first component 104 provides first consumption data 120, to go to the central computer 102. The second component 106 provides second consumption data 122 to go to the central computer 102. The third component 108 provides third consumption data 124 to go to the central computer 102. And the fourth component 110 provides fourth consumption data 126 to go to the central computer 102. The consumption data 120, 122, 124, 126 represent the actual energy consumption within the energy network 100; these data are collected over a given period.

Thus, the central computer 102 receives the first consumption data 120, the second consumption data 122, the third consumption data 124, and the fourth consumption data 126. The central computer 102 uses the consumption data 120, 122, 124, 126 — and other information from sources outside of the energy network 100 — to produce the energy plans 112, 114, 116, 118.

In addition, the first component 104 sends first consumption-information 128 to the other components 106, 108, 110; the second componenf\ 06 sends second consumption-information 130 to the other components 104, 108, 110; the third component 108 sends third consumption-information 132 to the other components 104, 106, 110; and the fourth component 110 sends fourth consumption-information 134 to the other components 104, 106, 108. For each component 104, 106, 108, 110, these items of consumption-information 128, 130, 132, 134 represent its present energy demand or energy available for supply.

Thus, the first component 104 receives the first energy plan 112, the second consumption information 130, the third consumption information 132, and the fourth consumption information 134; the second component 106 receives the second energy plan 114, the first consumption information 128, the third consumption information 132, and the fourth consumption information 134; the third component 108 receives the third energy plan 116, the first consumption information 128, the second consumption information 130, and the fourth consumption information 134; and the fourth component 110 receives the fourth energy plan 118, the first consumption information 128, the second consumption information 130, and the third consumption information 132.

Fig. 2 is a flow chart of a method 200 for distributing the amount of energy available, in an example of an embodiment of the present invention. The method 200 is performed in the components of the local energy network, shown in Fig. 1. The method 200 includes at least a reading-in step 202, a receiving step 204, and an allocation step 206. In the reading-in step 202, an energy plan for a component is read in from the central computer controlling the energy network. In the receiving step 204, at least one item of instantaneous consumption information regarding at least one other component of the local energy network is received. In the allocation step 206, energy is allocated to the component and to the at least one other component, using the consumption information, the components own consumption, and the energy plan.

In one example, the method 200 includes a data-provision step 208, in which consumption data collected over a period under consideration are provided to the central computer.

In one example, the method 200 has a sending-step 210, in which an item of instantaneous consumption information regarding the component is sent over the local energy network. This instantaneous consumption information represents the component’[s own energy consumption.

The method 200 presented here may be used to better retain renewable energy in the household. Similarly, it may be used for other consuming and producing devices. The approach presented here may also be used in industrial plants, large office buildings, and medium-size industrial buildings.

Fig. 3 is a block circuit diagram of a control unit 300 for a component 104 of a local energy network 100, in an example of an embodiment of the present invention. The control unit 300 is described here with reference to the first component 104 (shown in Fig. 1), as an example. A method as shown in Fig. 2 can be performed on the control unit 300. The control unit 300 comprises at least a device 302 for reading in, a device 304 for receiving, and a device 306 for allocating. The reading-in device 302 is adapted to reading-in the first energy plan 112 for the first component 104, from the energy-network-controlling central computer 102, through a first data interface 308. The receiving device 304 is adapted to receiving instantaneous consumption information 130,132,134 from other components of the local energy network 100, through a second data interface 310. The allocating device 306 is adapted to allocating energy 312, received from the energy network 100 through a first energy interface 312, to the component 104 through a second energy interface 314, using the consumption information items 130, 132, 134, the component’[s 104 own energy consumption, and the energy plan 11.

In an example of an embodiment of the invention, the control unit 300 has a data-provision device 316. This device 316 is adapted to providing consumption data 120, recorded over an observation period, to the central computer 102, through the first data interface 308. The control unit 300 may also have a sending device 318. The sending device 318 is adapted to sending the component’[s 104 own instantaneous consumption information 128 through the second data interface 310, to the local energy network 100.

In other words, Fig. 3 is a block circuit diagram of a control unit 300, on which a method for central energy management can be performed. The system presented here is adapted to optimising the energy consumption in the house, involving the use of self-generated PV energy when possible. The components perform the task of optimising the energy flows in the house, while an external central energy manager 102, not installed in the house, sets the boundaries.

The central, local energy management system (EMS) illustrated here is equipped with technology that allows data 120 regarding the household to be sent to another computer 102, either to enable further analysis there or to retrieve forecast data.

With the decentralised energy management (dEMS) concept presented here, loads, generators, and accumulators agree amongst themselves on the energy flows, within the boundary value settings, and hence a reduction in energy costs is achieved. With an oversupply of solar electricity, for instance, individual power outlet sockets may be switched on or off, so as to switch a waiting electric load on.

In the approach presented here, there are two control loops, but no local EMS. The individual devices optimise themselves by communicating with one other, thereby adjusting their behaviour to the prevailing boundary settings.

Fig. 4 shows the connection of a local energy network 100 to a central computer 102, in an example of an embodiment of the present invention. The energy network 100 shown here essentially corresponds to the energy network in Fig. 1. The energy network 100 in Fig. 4 is a household energy network 100, in which energy-consuming loads 104, 106, energy sources 108, and energy accumulators 110 in a house 400 are interconnected.

In the example shown here, there are, in the house 400, an electric stove 104, a washing machine 106, a heating system 108, and an electric buffer-storage unit 110. These are networked together, and organise among themselves with respect to energy supply and demand. Any extra electrical energy required is drawn from the public power supply network (the “mains” or “grid”).

The central computer 102 receives the consumption data 120, 122, 124, 126 and provides the energy plans 112, 114, 116, 118. For this, the central computer 102 uses additional information 402, such as weather information and power pricing information.

The following benefits can be achieved with the concept of a combination of decentralised and centralised energy management as presented here.

For the central computer 102, only one entity needing maintenance and development is required. Changes in electricity tariffs and feed-in tariffs are inputted into the central computer 102 only. New energy consuming/producing devices 104, 106, 108, 110 are linked up centrally, in the central computer 102. The central computer 102 can support various communication protocols and can therefore cater for different consuming/producing devices 104, 106, 108, 110.

New consuming devices automatically sign up to the central computer 102. At the same time, any changes in technical characteristics are communicated directly, and can thus be actioned. The central computer 102 knows all the consuming/producing devices 104, 106, 108, 110.

Due to the decentralised energy management, there are no increased installation costs in the house 400, because no additional “box” has to be installed. Therefore, there is no “single point of failure” locally. Any changes to the technical characteristics or the consumption/production strategy are recorded directly in the consuming/producing devices. In particular, this information is stored directly in the component 104, 106, 108, 110, by the manufacturer.

For this, a common communication protocol or platform for decentralised energy management is required.

The advantage of the decentralised energy management concept presented here is that no additional box need be installed, and the devices are themselves able to differentiate themselves through their own prioritisation strategies. In addition, the inventive approach, with the method presented here, allows the inclusion of forecasts or other market signals, through the central computer 102. This enables good use to be made of synergies achieved by aggregating different data sources located outside of the household.

The central energy management system EMS 102 is able to aggregate data 120, 122, 124, 126 pertaining to different households 400 and use them for a more precise forecast. Data 402 can be used from different sources (such as mobile phones, weather maps, traffic information, and price signals from the electricity exchange), with powerful processing, so as to send more-accurate instructions 112, 114, 116, 118 to the local decentralised energy management 100. The household 400 needs no additional “box”, since the devices 104, 106, 108, 110 are connected, by a data link, to the central EMS 102; and there, they only receive additional information 112, 114, 116, 118. Novel energy-consuming devices, with their particular behaviour, can be incorporated at a central location 102. The method presented here uses only aggregated, anonymised data, so no “personal data” is sent.

In Fig. 4, the approach presented here is illustrated schematically. It is based on two energy management control loops, separated in time and space, which are based on data of different granularity. In the local, decentralised, control loop 100, the individual devices 104,106, 108, 110 each try, by internal communication, to optimise the local energy demand. For the target variables, it is possible to use e.g. the load on the network, self-consumption of self-generated energy, or energy costs.

The historical data 120,122, 124, 126 regarding this local, optimised operation are sent by the individual consuming and producing devices 104, 106, 108, 110, in aggregated form, to the EMS 102. The EMS 102 collects additional data 402 from weather reports, and from other, anonymised, households 400, etc., and determines from this information a schedule 112, 114, 116, 118 for each producing and consuming device 104, 106, 108, 110, which the latter can incorporate into its local, decentralised management. These schedules 104, 106, 108, 110, which have different degrees of detail for different consuming devices 104,106, 108, 110, are adjusted periodically. And they feed into the local, decentralised control system.

Fig. 5 is a schematic representation of components of a local energy network 100, in an example of an embodiment of the present invention. The energy network 100 essentially corresponds to the energy network shown in Figs. 1 and 4, except that the energy network 100 in Fig. 5 has five components. The energy network 100 here comprises a first generator G1, a second generator G2, an energy storer S, a first load L1, and a second load L2.

Fig. 6 shows a table of weighting factors pxy, in an example of an embodiment of the present invention. The weighting factors r|xy are in each case associated with a connection between two components of an energy network such as that shown in Fig. 5. In each case, one component is a source 600, while the other component is a sink 602. The loads L1 and L2 are sinks 602 only. The generators G1 and G2 are sources 600 only. The energy storer S is the only component that can be used both as a source 600 and a sink 602. A transfer of energy from the first generator G1, as the source 600, to the first load L1, as the sink 602, is given a weighting factor qG1Li of 0.95. An energy transfer from the first generator G1 as the source 600 to the second load L2 as the sink 602 is likewise given a weighting factor r|G1L2 of 0.95. An energy transfer from the first generator G1 as the source 600 to the energy storer S as the sink 602 is given a weighting factor qG1s of 0.9.

An energy transfer from the second generator G2 as the source 600 to the first load L1 as the sink 602 is given a weighting factor r|G2i_i of 0.45. An energy transfer from the second generator G2 as the source 600 to the second load L2 as the sink 602 is likewise given a weighting factor Hg2L2 of 0.45. An energy transfer from the second generator G2 as the source 600 to the energy storer S as the sink 602 is given a weighting factor r|G2s of 0.9.

An energy transfer between the energy storer S as the source 600 and the first load L1 as the sink 602 is given a weighting factor r|SL1 of 0.93. An energy transfer between the energy storer S as the source 600 and the second load L2 as the sink 602 is given a weighting factor r|3L2 of 0.93.

Figs. 5 and 6 show the basic concept of the local, decentralised energy management. The entities participating in the dEMS will negotiate amongst themselves at any time to determine how an optimum apportionment of power-flows is to be made. For this purpose, each entity has the option of taking three roles.

Loads Li consume thermal or electrical energy. Gi represents generators, which can provide power. Si represents an energy storer. Energy storers can act as loads and as generators, and thus have a special role. A simple household 100, consisting of two loads, two generators, and an energy storer, is shown in Fig. 5, to explain the method. The transfer costs are shown in Fig. 6, in a structural power/energy flow diagram for a household at time t. Costs of r|xy in magnitude are associated with the paths. Thus, for example, when power is transferred from G1 to L1, costs amounting to nGiu will occur.

The decentralised energy management works like this: at any given time, the loads try to “negotiate” the best energy demand among one another. The load with the greatest need has the right to bid first. After that, come the other loads, according to their size. The exact procedure will be illustrated with three examples.

In the first example, the first load L1 needs 100 watts and the second load L2 needs 300 watts. The first generator G1 supplies 250 watts. The energy storer S is filled with 1000 kilowatt hours, and can supply 1000 watts. The first generator G1 therefore does not provide enough energy to feed the two sinks L1 and L2. L2 may choose first, and takes 250 W from G1 at a transfer price of 250 W x r|G1L2'1. L1 chooses second, and draws 100 W from the energy storer, at a transfer price of Hsu"1· L2 may bid once again, and takes 50 W from the energy storer S at a transfer price of Hsl2 1 S has no schedule that would warrant charging from the network, so all the loads are satisfied. The bidding round is now finished.

In the second example, the first load L1 again needs 100 watts and the second load L2 needs 300 watts. The first generator G1, however, is now making 600 watts available. There is now a surplus being produced, which, this time, could be used to charge the energy storer S. L2, being the largest load, gets first choice, and takes 300 W from G1 at a transfer price of r|G1L2. L1 takes 100 W from G1 at a transfer price of nGii_i1 The energy storer S now takes another 200 W at a price of nGiS"1- The bidding round is now finished.

In the third and last example, the first load L1 again requires 100 watts and the second load requires 300 watts. Now, however, the first generator G1 is only providing 50 watts. Thus, there is less being produced than is being consumed, so power is drawn from the energy storer S. L2 goes first, taking 50 W from G1 at a transfer price of qGiL2· L1 takes 100 W from the energy storer at a transfer price of Hsu"1· L2 still needs another 250 W, which it takes from the energy storer S, at a transfer price of Hsl21· The bidding round is now over.

These examples make it clear how the decentralised management works. The individual entities negotiate among themselves to achieve a locally optimised distribution of the energies available. If the negotiations are too slow or are taking too long, due to technical reasons or latency periods, then there is still not only the second generator G2 but also the public power supply network, which, in doubtful cases, can always supply energy to the loads.

Figs. 7 to 9 show examples of schedules 114, 116, 118, generated by the EMS.

Fig. 7 shows a representation of an energy plan 118 for an energy storage system in a local energy network, in an example of an embodiment of the present invention. Here, the energy plan 118 is represented as a graph with time of day t over 24 hours on the abscissa, and with the energy storage system’[s capacity κ on the ordinate. In the graph, minimum storage capacity minK and maximum storage capacity maxK are shown over time of day t.

Fig. 7 shows a generated schedule 118 for a solar electricity storage system. Here, the device is told the limits within which the energy storer may be charged. For this purpose, the maximum and minimum capacities for the next 24 hours are given as time series. The solar electricity storer may itself define the actual state of charge, under the decentralised energy management system. This is an example of a schedule, for an energy storage system 118, that is prescribed by a central EMS. The central EMS provides specifications as to maximum and minimum storage capacity (max κ and min κ), for a period of 24 hours. The solar electricity storage system can itself decide how it regulates things within these limits in such a way as to optimise costs.

Fig. 8 shows an energy plan 114 for a washing machine in a local energy network, in an example of an embodiment of the present invention. As in Fig. 7, the energy plan 114 is shown as a graph, with the time of day t, over 24 hours, on the abscissa, but with utility U on the ordinate. The utility value U(t) is graphed as a characteristic curve.

Fig. 8 shows the schedule 114 for a washing machine. In this example, utility value U(t) indicates how much the use of the washing machine is desired, based on the user behaviour detected and the alternative energy sources or favourable electricity prices available. Under the decentralised energy management system, the washing machine can utilise this utility value, and thus act autonomously; here too, however, it has to take user requirements into account. This is an example of a schedule 114 for a washing machine. In this case, a utility function U(t) is predetermined by the central management system. The machine itself can take these values into account internally, under the decentralised energy management system.

Fig. 9 shows an energy plan 116 for a heat storage unit of a local energy network, in an example of an embodiment of the present invention. As in Fig. 7, the energy plan 116 is shown in graph form, with the time of day t, over 24 hours, on the abscissa, and with the storage capacity κ of the heat storage unit on the ordinate. This graph shows minimum storage capacity minKW over time of day t and maximum storage capacity maxKW over time of day t.

Fig. 9 shows the schedule 116 for a heat storage unit. Flere, similarly to the solar electricity storage unit, minimum and maximum heat amounts are specified, which the thermal storage unit must adhere to. This is an example of a schedule 116 for a heat storage unit. In this case, similarly to the solar electricity storage system, the minimum and maximum heat capacities max kw min kw are preset.

The embodiments selected for description and illustration in the Figures are given by way of example only. Different embodiments can be combined with one another in whole or in part. Also, one embodiment can be supplemented with features of another embodiment.

Furthermore, the steps of the method presented here may be repeated, or may be performed in a different order from that described.

If an example includes an “and/or” relation between a first feature and a second feature, this sis to be read as meaning that, in one form of embodiment, both the first feature and the second feature are present, while in another form of embodiment only the first feature or only the second feature is present.

Claims

Claims

1. A method (200) for distributing the available amount of energy in a local energy network (100), said method (200) comprising the steps of: - reading-in (202) an energy plan (112, 114, 116, 118) for a component (104, 106, 108, 110), from a central computer (102) controlling an energy network (100); - receiving (204) instantaneous consumption information (128, 130, 132, 134) for at least one other component (104, 106, 108, 110) of the local energy network (100); and - allocating (206) energy (312) to said component (104, 106, 108, 110) and said other component (104,106,108,110), using the consumption information (128, 130, 132, 134), the components (104,106,108,110) own consumption, and the energy plan (112, 114, 116, 118).
2. A method (200) as claimed in claim 1, with a step (210) of sending instantaneous consumption information (128, 130, 132,134) regarding the component (104, 106, 108, 110) over the local energy network (100), said instantaneous consumption information (128, 130, 132, 134) representing the components (104, 106, 108, 110) own consumption.
3. A method (200) as claimed in one of the above claims, in which the consumption information (128, 130, 132, 134) regarding a component (104,106,108, 110) represents information as to that components energy demand, or information as to the energy available from that component.
4. A method (200) as claimed in any of the above claims, with a step (208) of providing consumption data (120, 122, 124, 126), collected over an observation period, to the central computer (102).
5. A method (200) as claimed in any of the above claims, in which, in the allocation step (206), energy is allocated first to the component (104, 106, 108, 110) with the highest energy consumption (312).
6. A method (200) as claimed in any of the above claims, in which, in the allocation step (206), the energy produced locally in the energy network (100) is preferably used to cover the energy consumption.
7. A method (200) as claimed in any of the above claims, in which, in the allocation step (206), the energy (312) is allocated using a weighting factor.
8. A control unit (300) for a component (104, 106, 108, 110) in a local energy network (100), said control unit (300) having the following features: - a device (302) for reading-in an energy plan (112, 114, 116 118) for the component (104, 106, 108, 110), from a central computer (102) controlling the energy network (100); - a device (304) for receiving instantaneous consumption information (128, 130, 132, 134) regarding another component (104, 106, 108, 110) of the local energy network (100); and - a device (306) for allocating energy (312) to the component (104, 106, 108, 110) and the other component (104, 106, 108, 110), using the consumption information (128, 130, 132, 134), the components (104, 106, 108, 110) own consumption, and the energy plan (112, 114, 116, 118).
9. A computer program that is adapted to performing, implementing, and/or controlling all the steps of a method as claimed in any of the above claims.
10. A machine-readable storage medium, with a computer program as claimed in claim 9 stored on it.