Managing a virtual power plant comprising a plurality of sites

Abstract

According to an embodiment, a computer- implemented method for managing a virtual power plant comprising a plurality of controllable heterogeneous sites (104A, 104B, 104C, 104D), wherein each of the plurality of controllable heterogeneous sites (104A, 104B, 104C, 104D) comprises at least one controllable asset, comprises: estimating an expected number of controllable assets for a future time period; determining an effective down capacity of the expected number of controllable assets at any given moment during the future time period, wherein the effective down capacity is a sum of the maximum power consumption of the expected number of controllable assets at any given moment during the future time period; determining an effective up capacity of the expected number of controllable assets at any given moment during the future time period, wherein the effective up capacity is a sum of the maximum power consumption reduction of the expected number of controllable assets and an active energy amount that can be pushed to the power grid at any given moment during the future time period; and optimizing the amount of available power adjustment with the plurality of controllable heterogeneous sites (104A, 104B, 104C, 104D) of the virtual power plant for the future time period based at least in part on the effective down capacity and the effective up capacity.

Description

MANAGING A VIRTUAL POWER PLANT COMPRISING A PLURALITYOF SITESTECHNICAL FIELD

[0001] The present disclosure relates to distributed energy storage systems , and more particularly to a computer-implemented method for managing a virtual power plant comprising a plurality of sites .BACKGROUND

[0002] A virtual power plant can comprise a large number of sites and each site can comprise various assets . The assets may comprise , for example , loads such as an electric vehicle charger, a water boiler and a battery unit that can be charged . On the other hand, the assets may comprise units , for example , the battery unit that is able to push electrical energy back to the power grid . These as sets can be uti li zed for supporting grid balancing ( for example , aFRR or FCR-D market ) and to provide up-regulation and down-regulation activities towards the power grid . However, it may be challenging to manage the virtual power plant efficiently .SUMMARY

[0003] This summary is provided to introduce a selection of concepts in a s implif ied form that are further described below in the detailed description . This sum-mary is not intended to identify key features or essential features of the claimed subj ect matter, nor is it intended to be used to limit the scope of the claimed subj ect matter .

[0004] It is an obj ective to provide a computer-implemented method for managing a virtual power plant , a computing device , a virtual power plant , and a computer program product . The foregoing and other obj ectives are achieved by the features of the independent claims . Further implementation forms are apparent from the dependent claims , the description and the figures .

[0005] According to a first aspect, there is provided a computer-implemented method for managing a virtual power plant comprising a plurality of controllable heterogeneous sites , wherein each of the plurality of controllable heterogeneous sites comprises at least one controllable asset . The method comprises estimating an expected number of controllable assets for a future time period; determining an effective down capacity of the expected number of controllable assets at any given moment during the future time period, wherein the effective down capacity is a sum of the maximum power consumption of the expected number of controllable assets at any given moment during the future time period; determining an effective up capacity of the expected number of controllable assets at any given moment during the future time period, wherein the effective up capacity is a sum of the maximum power consumption reduction of the expected number of controllable assets and anactive energy amount that can be pushed to the power grid at any given moment during the future time period; and optimi zing the amount of available power adj ustment with the plurality of controllable heterogeneous sites of the virtual power plant for the future time period based at least in part on the effective down capacity and the ef fective up capacity . The method can, for example , enable planning the usage of the virtual power plant before the execution time period .

[0006] In an implementation form of the first aspect , optimi zing the amount of available power adj ustment with the plurality of controllable heterogeneous sites of the virtual power plant for the future time period based at least in part on the effective down capacity and the effective up capacity comprises : evaluating multiple energy transfer strategies for the future time period based on the effective down capacity and the effective up capacity; and selecting an energy transfer strategy of the multiple energy transfer strategies based on at least one selection criterion to optimize the amount of available power adj ustment with the plurality of controllable heterogeneous sites of the virtual power plant for the future time period . The method can, for example , enable using various criteria to optimize the amount of available power adj ustment and / or manage the amount of energy, for example , in a battery unit .

[0007] In an implementation form of the first aspect , evaluating multiple energy transfer strategies for the future time period based on the effective down capacityand the effective up capacity comprises at least one of the following for at least one controllable heterogeneous site : evaluating the effective up capacity with at least one controllable load and without at least one battery unit ; evaluating the effective up capacity with at least one controllable load, with a battery unit and with no power grid feed; evaluating the effective up capacity with at least one controllable load, with a battery unit and with power grid feed; evaluating the effective down capacity with at least one controllable load and without a battery unit ; evaluating the effective down capacity with at least one controllable load, with a battery unit and with no power grid feed; and evaluating the effective down capacity with at least one controllable load, with a battery unit and with power grid feed .

[0008] In an implementation form of the first aspect , optimi zing the amount of available power adj ustment with the plurality of controllable heterogeneous sites of the virtual power plant for the future time period based at least in part on the effective down capacity and the effective up capacity comprises : performing resource allocation planning based on the effective down capacity and the effective up capacity to provide a baseline plan ; calculating a characteristic value for the baseline plan ; determining variations of the baseline plan within the constraints of the controllable assets ; recalculating the characteristic value for each variation of the baseline plan ; and selecting a plan among the baseline plan and the variations of the baseline planbased at least in part of the characteristic values of the baseline plan and the variations of the baseline plan . The method can, for example , enable optimi zation of the state of charge of a battery unit .

[0009] In an implementation form of the first aspect , the method further comprises controlling a plurality of heterogeneous sites comprising controllable assets based at least in part on the optimi zation . The method can, for example , enable to later apply an optimization planned earlier based on statistical data .

[0010] In an implementation form of the first aspect , the at least one controllable as set compri ses at least one of an electric vehicle charger, an electric vehicle battery, a controllable load and a battery unit . The method can , for example , enable to control as sets of a site independently when optimizing the amount of available power adj ustment .

[0011] According to a second aspect , there is provided a computing device for managing a virtual power plant comprising a plurality of controllable heterogeneous sites , wherein each of the plurality of heterogeneous sites comprises at least one control lable asset . The computing device comprises at least one processor and at least one memory including computer program code , the at least one memory and the computer program code being configured to , with the at least one processor, cause the computing device to estimate an expected number of controllable assets for a future time period; determine an effective down capacity of the expected number ofcontrol lable as sets at any given moment during the future time period, wherein the effective down capacity is a sum of the maximum power consumption of the expected number of controllable assets at any given moment during the future time period; determine an effective up capacity of the expected number of controllable assets at any given moment during the future time period, wherein the effective up capacity is a sum of the maximum power consumption reduction of the expected number of controllable assets and an active energy amount that can be pushed to the power grid at any given moment during the future time period; and optimi ze the amount of available power adj ustment with the plurality of controllable heterogeneous sites of the virtual power plant for the future time period based at least in part on the effective down capacity and the effective up capacity .

[0012] In an implementation form of the second aspect , optimi zing the amount of available power adj ustment with the plurality of controllable heterogeneous sites of the virtual power plant for the future time period based at least in part on the effective down capacity and the effective up capacity comprises : evaluating multiple energy transfer strategies for the future time period based on the effective down capacity and the effective up capacity; and selecting an energy transfer strategy of the multiple energy transfer strategies based on at least one selection criterion to optimize the amount of available power adj ustment with the plurality of controllable heterogeneous sites of the virtual power plant for the future time period .

[0013] In an implementation form of the second aspect , evaluating multiple energy transfer strategies for the future time period based on the effective down capacity and the effective up capacity comprises at least one of the following for at least one controllable heterogeneous site : evaluating the effective up capacity with at least one controllable load and without at least one battery unit ; evaluating the effective up capacity with at least one controllable load, with a battery unit and with no power grid feed; evaluating the effective up capacity with at least one controllable load, with a battery unit and with power grid feed; evaluating the effective down capacity with at least one controllable load and without a battery unit ; evaluating the effective down capacity with at least one controllable load, with a battery unit and with no power grid feed; and evaluating the effective down capacity with at least one controllable load, with a battery unit and with power grid feed .

[0014] In an implementation form of the second aspect , optimi zing the amount of available power adj ustment with the plurality of controllable heterogeneous sites of the virtual power plant for the future time period based at least in part on the effective down capacity and the effective up capacity comprises : performing resource allocation planning based on the effective down capacity and the effective up capacity to provide a baseline plan ; calculating a characteristic value for the baseline plan ; determining variations of the baseline planwithin the constraints of the controllable assets ; recalculating the characteristic value for each variation of the baseline plan ; and selecting a plan among the baseline plan and the variations of the baseline plan based at least in part of the characteristic values of the baseline plan and the variations of the baseline plan .

[0015] In an implementation form of the second aspect , the at least one memory and the computer program code are configured to , with the at least one processor, cause the computing device to control a plurality of heterogeneous sites comprising controllable assets based at least in part on the optimi zation .

[0016] In an implementation form of the second aspect , the at least one controllable as set compri ses at least one of an electric vehicle charger, an electric vehicle battery, a controllable load and a battery unit .

[0017] According to a third aspect, there is provided a virtual power plant comprising the computing device according the second aspect and a plurality of controllable heterogeneous sites each comprising at least one controllable asset .

[0018] According to a fourth aspect , there is provided a computer program product comprises program code configured to perform the method according to the first aspect when the computer program product is executed on a computer .

[0019] According to a fifth aspect , there is provided a computing device for managing a virtual power plantcomprising a plurality of controllable heterogeneous sites , wherein each of the plurality of heterogeneous sites comprises means for : estimating an expected number of controllable assets for a future time period; determining an effective down capacity of the expected number of controllable assets at any given moment during the future time period, wherein the effective down capacity is a sum of the maximum power consumption of the expected number of controllable assets at any given moment during the future time period; determining an effective up capacity of the expected number of controllable assets at any given moment during the future time period, wherein the effective up capacity is a sum of the maximum power consumption reduction of the expected number of controllable assets and an active energy amount that can be pushed to the power grid at any given moment during the future time period; and optimi zing the amount of available power adj ustment with the plurality of controllable heterogeneous sites of the virtual power plant for the future time period based at least in part on the effective down capacity and the effective up capacity

[0020] Many of the attendant features wil l be more readily appreciated as they become better understood by reference to the following detailed description considered in connection with the accompanying drawings .DESCRIPTION OF THE DRAWINGS

[0021] In the following, example embodiments are described in more detail with reference to the attached figures and drawings , in which :

[0022] FIG . 1 illustrates a schematic representation of a virtual power plant according to an embodiment .

[0023] FIGS . 2A-2F illustrate the concept of an effective capacity of an asset of assets according to an embodiment .

[0024] FIG . 3 illustrates a flow chart representation of a method according to an embodiment .

[0025] FIG . 4 illustrates a schematic representation of a computing device according to an embodiment .

[0026] In the following, like reference numerals are used to des ignate li ke parts in the accompanying drawings .DETAILED DESCRIPTION

[0027] In the following description, reference is made to the accompanying drawings , which form part of the disclosure , and in which are shown, by way of illustration, specific aspects in which the present disclosure may be placed . It is understood that other aspects may be utilised, and structural or logical changes may be made without departing from the scope of the present disclosure . The following detailed description, therefore , is not to be taken in a limiting sense , as thescope of the present disclosure is defined by the appended claims .

[0028] For instance , it is understood that a disclosure in connection with a described method may also hold true for a corresponding device or system configured to perform the method and vice versa . For example , if a specific method step is described, a corresponding device may include a unit to perform the described method step, even if such unit is not explicitly described or il lustrated in the figures . On the other hand, for example , if a specific apparatus is described based on functional units , a corresponding method may include a step performing the described functionality, even if such step is not explicitly described or illustrated in the figures . Further, it is understood that the features of the various example aspects described herein may be combined with each other, unless specifically noted otherwise .

[0029] According to an embodiment , a virtual power plant 100 comprises a computing device 102 a plurality of controllable heterogeneous sites 104A, 104B, 104C, 104D of the virtual power plant 100 . The computing device 102 can function as a centrali zed control system for the plurality of controllable heterogeneous sites 104A, 104B, 104C, 104D . The computing device 102 may also be referred to as a centralized controller, a virtual power plant controller, a distributed energy storage ( DES ) controller, a centrali zed control system, a virtual power planet control system, or similar . Thevirtual power plant 100 may also be referred to as a virtual power plant system, a distributed energy storage system, or similar .

[0030] Each site 104A, 104B, 104C, 104D in the plurality of heterogeneous sites may be communicatively coupled to the computing device 102 and to a power grid 108 . Each site 104A, 104B, 104C, 104D can be coupled to the computing device 102 via, for example , a telecommunication network . Thus , the computing device 102 may be configured to control each site in the plurality of sites 104A, 104B, 104C, 104D . In an example embodiment, the computing device 102 may be configured to control each site 104A, 104B, 104C, 104D and its assets directly . In another example , one or more of the sites 104A, 104B, 104C, 104D may comprise a site controller that controls the as sets of the corresponding site and that is controlled by the computing device 102 .

[0031] Each site of the heterogeneous sites 104A, 104B, 104C, 104D may comprise one or more controllable assets . The site may refer, for example , to a single household a building comprising the one or more controllable assets . The asset may be , for example , an electric vehicle charger, an electric vehicle battery, a controllable load and a battery unit . One or more of the assets may act as a load for the power grid 108 . One or more of the assets may be able to push electrical energy back to the power grid 108 . One or more assets , for example , the battery unit , may be able to act bothas a load and as an asset pushing electrical energy back to the power grid 108 .

[0032] As used herein, a virtual power plant (VPP) may refer to a distributed power plant comprising a plurality of sites . A VPP can aggregate the capacities of the plurality of sites . Further, the term "site" may correspond to an electrical system of a building and may comprise DC equipment , such as heating, ventilation, and air conditioning (HVAC) equipment , fluid-based cooling equipment , variable speed motor equipment ( also known as variable frequency drives or VFD' s ) , LED lighting equipment , or auxiliary battery equipment , such as electric vehicle (EV) battery and related DC charging equipment , for example .

[0033] FIGS . 2A-2F illustrate the concept of an effective capacity of an asset of assets according to an embodiment .

[0034] An effective capacity of an asset may be equal to the capacity in each direction the asset can provide at any given moment . This may refer to the absolute maximum level of activation in each direction . "Direction" used herein refers to the direction of electricity in the asset ' s point of view . The as set may be able to act as a load thus consuming electricity from the power grid . On the other hand, the as set may be able to push electricity back to the power grid . An effective capacity may consist of an effective down capacity and an effective up capacity . An effective down capacity of anasset is the power capacity of the asset. An effective up capacity is discussed more in the following examples.

[0035] FIG. 2A illustrates an example of the effective up capacity when there are three assets: a water heater 200, an electric car charger 202 and a heating or cooling unit 204.

[0036] In night time, the electric car charging is scheduled at 00:00 to 06:00 at 10 kW power. At 03:00 the water heater 200 is scheduled until 06:00 at 4 kW power. The heating and cooling unit 204 consumes power throughout the day. A dashed line 206 shows the power aggregate of the three power consumers. In this example, the effective up capacity is the instantaneous power consumption of all assets at a given time assuming that the electric car charge and the water heater can be scheduled at any hours of the day.

[0037] FIG. 2B illustrates an example of the effective up capacity when there are two assets: a battery unit 208 and a water heater 210. In this example, the battery unit 208 can either be charged or its energy content can be used by the water heater 210.

[0038] In this example, the water heater 210 is using 4kW and a battery unit 208 is discharging at 4 kW at the request for up regulation. This example assumes that the battery unit 208 cannot feed energy into the power grid. The effective up capacity is 4kW even if there is both a battery unit 208 and a controllable load because the battery unit 208 can only discharge at the same power output as is the consumption of the water heater 210.Then, when triggering up regulation, it is possible to either trigger battery discharge or shut down the water heater 208.

[0039] FIG. 2C illustrates an example of the effective up capacity when there are two assets: a battery unit 212 and an electric car charger 214. In this example, the battery unit can either be charged or its energy content can be used by the electric car charger 214. This example assumes that the battery unit 208 cannot feed energy into the power grid.

[0040] In this example, the electric vehicle car charger 214 uses lOkW and the battery unit 212 is discharging max. 4 kW at the request for up regulation. The effective up capacity is lOkW even if there is both a battery and a controllable load because the battery can only discharge at the same power that the electric car charger 214 is able to use. When triggering up regulation, it is possible to either shut down the electric car charger 214 completely or reduce the electric car charger 214 to 4 kW and trigger 4 kW of discharge from the battery unit 212. Both options will result in 10 kW effective up capacity.

[0041] FIG. 2D illustrates an example of the effective up capacity when there are two assets: a battery unit 218 and an electric car charger 216. In this example, the battery unit can either be charged or its energy content can be used by the electric car charger 216. In addition to this, the battery unit 218 can feed energy into the power grid.

[0042] In this example , the electric car charger 216 is using l O kW and the battery unit 218 is discharging max 4 kW at the request for up regulation . In this case , the effective up capacity is 14 kW because the battery unit 218 can run independently of the load . When triggering up regulation, it is possible to shut down electric the car charger 216 completely and trigger 4 kW of battery discharge from the battery unit 218 .

[0043] FIG . 2E illustrates an example of the effective up capacity when there are three controllable assets : a battery unit 220 , a water heater 222 and an electric car charger 226 . In this example , the battery unit 220 cannot feed energy into the power grid . It is assumed that the battery unit 220 can be controlled during any part of the day . It is also assumed that a heating or cool ing unit 224 is not controlled .

[0044] The effective up capacity with the battery unit 220 is equal to the situation with no battery, as already discussed in the example of FIG . 2A . An effective up capacity 228 is the instantaneous power consumption of all assets at a given time assuming that the electric car charger 226 and the water heater 222 can be scheduled at any hours of the day, as indicated by a dashed line 228 .

[0045] FIG . 2F illustrates an example of the effective up capacity when there are three controllable assets : a battery unit 236 , a water heater 230 and an electric car charger 234 . In this example , the battery unit 236 can feed energy into the power grid . It is assumed that thebattery unit 236 can be controlled during any part of the day . It is also assumed that a heating or cooling unit 232 is not controlled .

[0046] The effective up capacity with the battery unit 236 is now the sum of al l loads and the battery power capacity, as indicated by a dashed line 238 .

[0047] FIG . 3 illustrates a flow chart representation of a computer-implemented method according to an embodiment . The method may enable managing a virtual power plant comprising a plurality of controllable heterogeneous sites , wherein each of the plurality of heterogeneous sites comprises at least one controllable asset . In an example embodiment , the method may be performed by the computing device 102 .

[0048] At 300 , an expected number of controllable assets for a future time period is estimated . The estimation may be based, for example , on statistical data on sites and their associated asset usage . For example , the statistical data may identify how sites have used energy from the power grid and how energy has been pushed back to the power grid in the past . The estimation may be performed, for example , on a time period prior to the future time period . For example , the estimation may be performed on a previous day when the future time period is the next day . In other embodiments , the future time period may refer to any other time period in the future , for example , a night period, several days etc . Some controllable assets may be able to act as a load . Some controllable assets may be able to act as a load and anelectrical energy source pushing electrical energy back to the power grid .

[0049] During the estimation, it is not necessary to know which specific sites will actually be controllable during the future time period . The statistical data "hides" thi s information as it can be determined based the statistical data how many s ites have been control lable before .

[0050] At 302 , an ef fective down capacity of the expected number of controllable assets at any given moment during the future time period may be determined . The effective down capacity may be a sum of the maximum power consumption of the expected number of controllable assets at any given moment during the future time period .

[0051] At 304 , an effective up capacity of the expected number of controllable assets at any given moment during the future time period may be determined . The effective up capacity may be a sum of the maximum power consumption reduction of the expected number of controllable assets and an active energy amount that can be pushed to the power grid at any given moment during the future time period . Examples of the effective up capacity have been discussed in the examples illustrated in FIGS . 2A-2F . As discussed in the examples ,

[0052] At 306 , the amount of available power adj ustment with the plurality of controllable heterogeneous sites of the virtual power plant is optimi zed for thefuture time period based at least in part on the effective down capacity and the effective up capacity . The term "available power adj ustment" may provide the amount of up and down regulation that can be offered by the virtual power plant during the future time period .

[0053] In an example embodiment , when the execution time of the future time period comes , a plurality of heterogeneous sites comprising controllable assets can be controlled based at least in part on the optimi zation . A virtual power plant service provider may have a control access to a set of heterogeneous sites comprising controllable assets . During the execution time period, the virtual power plant service provider sees in real-time or substantially in real-time that a subset of the set of heterogeneous sites comprising controllable assets is actually available for control . For example , the virtual power plant service provider may be also to see how much each site of the subset offers effective up and down capacity . Then, based on the earlier determined amount of available power adj ustment , the virtual service provider may be configured to select a necessary amount of sites from the subset so that the determined amount of available power adj ustment is achieved . In other words , the sites can be controlled to provide up / down regulation so that the determined amount of available power adj ustment is achieved . In an example embodiment , it i s also pos sible that some actor may override the optimi zation . For example , if the state of charge ( SoC) of the battery unit is too low or high,the optimi zation associated with the battery unit may be canceled .

[0054] As a simplified example , during the execution time , a current aggregate load at a specific time instant may be 4 MW, and based on the beforehand performed optimi zation the amount of available power adj ustment indicates a minimum aggregate load of 0 MW and a maximum aggregate load of 10 MW . Then, at the specific time instance , the virtual power plant service provider you would be able to regulate 4 MW in the up direction and 6 MW in the down direction .

[0055] In an example embodiment , the optimi zation may comprise evaluating multiple energy transfer strategies for the future time period based on the ef fective down capacity and the effective up capacity . An energy transfer strategy of the multiple energy transfer strategies may then be selected based on at least one selection criterion to optimize the amount of available power adj ustment with the plurality of controllable heterogeneous sites of the virtual power plant for the future time period . For example , the virtual power plant service provider may be configured to evaluate an expected economic value of multiple energy transfer strategies , for example , one or more of the following :Charging based on least expensive (day-ahead) energy timesCharging based on (uncertain) offering of down regulation capacity . Some time may be left( and leaving some time to adj ust away the uncertainty with home battery)Scheduling charging to specific time , and offering that power to up regulation as well ( and leaving some time to adj ust away the uncertainty with home battery) .

[0056] In an example embodiment , the evaluation may take into account that in night time, various actuators may be scheduled to switch on because electricity is cheap, for example , an electric vehicle charger, a water heater, floor heating etc . To perform up regulation, one or more of these can be switched off or partially switched off to reduce the load on the power grid . Thus , the total effective up capacity is the sum of the reduced power towards the power grid .

[0057] In an example embodiment , the evaluation may take into account that in night time, various actuators may be scheduled to switch on because electricity is cheap, for example , an electric vehicle charger, a water heater, floor heating etc . To perform up regulation, one or more of these can be switched off or partially switched off to reduce the load on the power grid, or a battery unit can be set to discharge thus reducing the effective load on the power grid of the appliances . Thus , the total effective up capacity is the sum of the reduced power towards the power grid .

[0058] In an example embodiment , the evaluation may take into account that in night time, various actuators may be scheduled to switch on because electricity ischeap, for example , an electric vehicle charger, a water heater, floor heating etc . To perform up regulation, one or more of these can be switched off or partially switched off to reduce the load on the power grid, or a battery unit can be set to discharge thus reducing the ef fective load on the power grid of the appl iances . In addition, the battery unit can feed back electricity to the power grid, causing a negative effective power consumption towards the power grid . Thus , the total effective up capacity is the sum of the reduced power towards the grid including the capacity fed to the power grid .

[0059] In an example embodiment , the evaluation may take into account that in day time , a site may be switching off as many actuators as possible because the electricity price is high . To perform down regulation, one or more of these actuators can be switched on or partially switched on to increase the load on the power grid . Thus , the total effective down capacity is the sum of the increased power towards the power grid .

[0060] In an example embodiment , the evaluation may take into account that in day time , a site may be switching off as many actuators as possible because the electricity price i s high . To perform down regulation, one or more of these actuators can be switched on or partially switched on to increase the load on the power grid, or a battery unit can switch on charging to increase the load on the power grid . Thus , the total effective down capacity is the sum of the increased powertowards the power grid including the charging power of the battery unit .

[0061] In an example embodiment , the evaluation may take into account that in day time , a site may be switching off as many actuators as possible because the prices is expensive . A battery unit may also be discharging to sell electricity back to the power grid . To perform down regulation, one or more of these actuators can be switched on or partially switched on to increase the load on the power grid, or the battery unit can stop the power grid feed to increase the load on the power grid . Thus , the total effective down capacity is the sum of the increased power towards the power grid including the discharging power of the battery unit .

[0062] The virtual power plant service provider may then select , for example , the most economic alternative and offer respective expected aggregated capacity to balancing markets .

[0063] In an example embodiment , the optimi zation may comprise performing resource allocation planning, for example , load-shifting and / or automatic frequency restoration reserve ( aFRR) etc . ) based on the effective down capacity and the effective up capacity to provide a baseline plan . A characteristic value may be calculated for the baseline plan . The characteristic value may refer, for example , to expected economic returns relating to the basel ine plan . Variations of the baseline plan may be determined within the constraints of the controllable assets , and the characteristic valuemay be recalculated for each variation of the basel ine plan . Then a plan among the basel ine plan and the variations of the baseline plan is selected based at least in part of the characteristic values of the baseline plan and the variations of the baseline plan . I f the selected plan is not the baseline plan, then adj ustable loads may be controlled according to the differences to the baseline plan .

[0064] In an example embodiment , the baseline plan may involve that electric vehicle charging is scheduled at midnight and charging of a battery unit is scheduled as well . This also means that there is a large effective up capacity potential by stopping at least one of the electric vehicle charging and the battery unit charging . For example , if the electric vehicle charging is stopped, it is possible to provide effective up capacity with 10 kW .

[0065] During the plan execution time , the owner of the electric vehicle may decide to use the electric vehicle , and the charging of the electric vehicle is stopped . This means that the same up regulation potential does not any more exist , and if an up regulation request is received, at least one variation of the baseline plan needs to be available . One possibility of the variation of the baseline plan is , for example , that the charging of the electric vehicle is stopped and the discharge of the battery unit is started, and the overall effect may be 10 kW, i . e . , 5kW for stopping thecharging of the electric vehicle and 5kW for starting the discharge of the battery unit .

[0066] In another example embodiment , the day time may be predicted to be sunny and there will be a plenty of solar power generated . This means that electricity will flow out to the power grid from a site , for example , 5 kW towards the power grid . The basel ine plan may thus involve effective down capacity by allowing reduction of the power grid feed on demand .

[0067] During the plan execution time , it turns out that it is not actually that sunny and only little solar power generation is available at the site . This also means that the effective down regulation of the baseline plan is not available as there is no feed ( 0 kW) the power grid due to the cloudy weather . I f a down regulation request is then received, at least one variation of the baseline plan needs to be available . One pos sibility of the variation of the baseline plan is , for example, that power consumption needs to be somehow increased, for example , by starting to charge a battery unit or an electric vehicle to make up for the loss of 5kW .

[0068] It is noted that the variation ( s ) of the baseline plan does not always have to exactly match the baseline plan on house / site level and the adj ustments may be provided by other houses / sites of the virtual power plant . It is statistically pos sible to match the earlier allocated amount of available power adj ustmentusing the pool of houses / sites in the virtual power plant .

[0069] FIG. 4 illustrates a schematic representation of a computing device according to an embodiment.

[0070] According to an embodiment, a computing device 102 comprises at least one processor 400 and at least one memory 402 including computer program code, the at least one memory 402 and the computer program code configured to, with the at least one processor 400, cause the computing device 102 to perform the method discussed in relation to FIG. 3.

[0071] The computing device 102 may comprise at least one processor 400. The at least one processor 400 may comprise, for example, one or more of various processing devices, such as a co-processor, a microprocessor, a digital signal processor (DSP) , a processing circuitry with or without an accompanying DSP, or various other processing devices including integrated circuits such as, for example, an application specific integrated circuit (ASIC) , a field programmable gate array (FPGA) , a microprocessor unit (MCU) , a hardware accelerator, a special-purpose computer chip, or the like.

[0072] The computing device 102 may further comprise a memory 404. The memory 404 may be configured to store, for example, computer programs and the like. The memory 404 may comprise one or more volatile memory devices, one or more non-volatile memory devices, and / or a combination of one or more volatile memory devices and nonvolatile memory devices. For example, the memory 404 maybe embodied as magnetic storage devices (such as hard disk drives, magnetic tapes, etc.) , optical magnetic storage devices, and semiconductor memories (such as mask ROM, PROM (programmable ROM) , EPROM (erasable PROM) , flash ROM, RAM (random access memory) , etc.) .

[0073] The computing device 102 may further comprise other components not illustrated in the embodiment of FIG. 4. The computing device 102 may comprise, for example, an input / output bus for connecting the computing device 102 to other devices.

[0074] When the computing device 102 is configured to implement some functionality, some component and / or components of the computing device 102, such as the at least one processor 400 and / or the memory 402, may be configured to implement this functionality. Furthermore, when the at least one processor 400 is configured to implement some functionality, this functionality may be implemented using program code comprised, for example, in the memory.

[0075] The computing device 102 may be implemented at least partially using, for example, a computer, some other computing device, or similar.

[0076] Any range or device value given herein may be extended or altered without losing the effect sought. Also any embodiment may be combined with another embodiment unless explicitly disallowed.

[0077] Although the subject matter has been described in language specific to structural features and / or acts, it is to be understood that the subject matter definedin the appended claims is not necessarily limited to the specific features or acts described above . Rather, the specific features and acts described above are disclosed as examples of implementing the claims and other equivalent features and acts are intended to be within the scope of the claims .

[0078] It will be understood that the benefits and advantages described above may relate to one embodiment or may relate to several embodiments . The embodiments are not limited to those that solve any or all of the stated problems or those that have any or all of the stated benefits and advantages . It wil l further be understood that reference to ' an ' item may refer to one or more of those items .

[0079] The steps of the methods described herein may be carried out in any suitable order, or simultaneously where appropriate . Additionally, individual blocks may be deleted from any of the methods without departing from the spirit and scope of the subj ect matter described herein . Aspects of any of the embodiments described above may be combined with aspects of any of the other embodiments described to form further embodiments without losing the effect sought .

[0080] The term ' comprising ' is used herein to mean including the method, blocks or elements identified, but that such blocks or elements do not comprise an exclusive list and a method or apparatus may contain additional blocks or elements .

[0081] It will be understood that the above description is given by way of example only and that various modif ications may be made by those ski lled in the art . The above specification, examples and data provide a complete description of the structure and use of exemplary embodiments . Although various embodiments have been described above with a certain degree of particularity, or with reference to one or more individual embodiments , those skilled in the art could make numer- ous alterations to the disclosed embodiments without departing from the spirit or scope of this specification .

Claims

CLAIMS :1 . A computer-implemented method for managing a virtual power plant comprising a plurality of controllable heterogeneous sites ( 104A, 104B, 104C, 104D) , wherein each of the plurality of controllable heterogeneous sites ( 104A, 104B, 104C, 104D) comprises at least one controllable asset , the method comprising : estimating ( 300 ) an expected number of controllable assets for a future time period; determining ( 302 ) an effective down capacity of the expected number of controllable assets at any given moment during the future time period, wherein the effective down capacity is a sum of the maximum power consumption of the expected number of controllable assets at any given moment during the future time period; determining ( 304 ) an effective up capacity of the expected number of controllable assets at any given moment during the future time period, wherein the effective up capacity is a sum of the maximum power consumption reduction of the expected number of controllable assets and an active energy amount that can be pushed to the power grid at any given moment during the future time period; optimi zing ( 306 ) the amount of available power adj ustment with the plurality of controllable heterogeneous sites ( 104A, 104B, 104C, 104D) of the virtual power plant for the future time period based at least in part on the effective down capacity and the effective up capacity; andcontrolling the plurality of heterogeneous sites comprising controllable assets based at least in part on the optimi zation .2 . The computer-implemented method according to claim 1 , wherein optimi zing the amount of available power adj ustment with the plurality of controllable heterogeneous sites ( 104A, 104B, 104C, 104D) of the virtual power plant for the future time period based at least in part on the effective down capacity and the effective up capacity comprises : evaluating multiple energy transfer strategies for the future time period based on the ef fective down capacity and the effective up capacity; and selecting an energy transfer strategy of the multiple energy transfer strategies based on at least one selection criterion to optimi ze the amount of available power adj ustment with the plurality of controllable heterogeneous sites ( 104A, 104B, 104C, 104D) of the virtual power plant for the future time period .3 . The computer-implemented method according to claim 2 , wherein evaluating multiple energy transfer strategies for the future time period based on the ef fective down capacity and the effective up capacity comprises at least one of the following for at least one controllable heterogeneous site ( 104A, 104B, 104C, 104D) :evaluating the effective up capacity with at least one controllable load and without at least one battery unit ; evaluating the effective up capacity with at least one controllable load, with a battery unit and with no power grid feed; evaluating the effective up capacity with at least one controllable load, with a battery unit and with power grid feed; evaluating the effective down capacity with at least one controllable load and without a battery unit ; evaluating the effective down capacity with at least one controllable load, with a battery unit and with no power grid feed; and evaluating the effective down capacity with at least one controllable load, with a battery unit and with power grid feed .4 . The computer-implemented method according to claim 1 , wherein optimi zing the amount of available power adj ustment with the plurality of controllable heterogeneous sites ( 104A, 104B, 104C, 104D) of the virtual power plant for the future time period based at least in part on the effective down capacity and the effective up capacity comprises : performing resource allocation planning based on the effective down capacity and the effective up capacity to provide a baseline plan ; calculating a characteristic value for the baseline plan ;determining variations of the baseline plan within the constraints of the controllable assets; recalculating the characteristic value for each variation of the baseline plan; and selecting a plan among the baseline plan and the variations of the baseline plan based at least in part of the characteristic values of the baseline plan and the variations of the baseline plan.

5. The computer-implemented method according to any one of claims 1 - 4, wherein the at least one controllable asset comprises at least one of an electric vehicle charger, an electric vehicle battery, a controllable load and a battery unit.

6. The computer-implemented method according to any one of claims 1 - 5, wherein estimating (300) an expected number of controllable assets for a future time period comprises estimating the expected number of controllable assets for the future time period based on statistical data on sites and their associated asset usage .

7. A computing device (102) for managing a virtual power plant comprising a plurality of controllable heterogeneous sites (104A, 104B, 104C, 104D) , wherein each of the plurality of controllable heterogeneous sites (104A, 104B, 104C, 104D) comprises at least one controllable asset, the computing device (102) compris- mg :at least one processor (400) ; and at least one memory (402) including computer program code (404) , wherein the at least one memory (402) and the computer program (404) code are configured to, with the at least one processor (400, cause the computing device (102) to perform the method according to any preceding claim.

8. A virtual power plant comprising: the computing device (102) according to claim 7 ; and a plurality of heterogeneous controllable sites (104A, 104B, 104C, 104D) each comprising at least one controllable asset.

9. A computer program product comprising program code configured to perform the method according to any of claims 1 - 6, when the computer program product is executed on a computer.

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