A method to manage power distribution in a power grid

Abstract

The present invention relates to a system to manage energy distribution in a power grid having an EMS with an energy storage and a hybrid inverter. The hybrid inverter being connected to the energy storage, controllable loads, and a main power grid via fuses, the EMS being configured to at least optimize power consumption at a site by controlling power consumed by selected controllable loads, monitoring power received from the main power grid, and controlling power from the energy storage. The optimization is provided by a core node within the EMS based on predicted power consumption for a time period, available power capacity in energy storage and power that can be received from the main power grid without exceeding a set power level of the fuses.

Description

[0001] A METHOD TO MANAGE POWER DISTRIBUTION IN A POWER GRID

[0002] TECHNICAL FIELD

[0003] The present disclosure relates to the field of power management relating to power grid structures based on decentralized assets.

[0004] BACKGROUND

[0005] More and more people are discovering home batteries and the possibility of being able to store electricity from their solar panels to make better use of them. Investing in solar panels for your property is a smart decision for those who want to increase their self- sufficiency and take a step towards more sustainable energy consumption. If you want to get the most out of your solar panels, you should also consider investing in a battery connected to the panels, as it allows you to store solar energy.

[0006] When the sun shines, it could result in your solar panels producing more electricity than you need at the time. With a home battery for the solar cells, the surplus electricity is stored in the battery and that electricity can then be used when on a cloudy occasion or in the evening. This feature is often referred to as time shifting. If you have a home battery without intelligent control, that’s how it works - the battery is charged when the sun is shining and then discharged as soon as you consume electricity at home. It is a smart way to expand the use of solar power, but to improve savings on the electricity bill, it is required that the battery comes with an intelligent control - so called Energy Management System (EMS).

[0007] On the market today there are several different smart home batteries that allow you to store solar energy, but it can be difficult to know what differentiates them and what the benefits really are when the battery has an EMS. Most smart batteries have functionality to control consumption according to electricity prices and use electricity from the battery when the price is high. This is a great advantage, as it means that the cost of electricity will be lower when you can use your self-generated electricity at these times.

[0008] The investment cost for solar panels and batteries is significant for a single individual, and the power ratings for the connection to a property usually have limitation preventing the user from providing high power to the main grid. The combination of these drawbacks makes it difficult for an individual to receive a return on investments for grid services. The effect of receiving power during peak hours can be very costly, especially if there is an unbalance power consumption within the network that causes unnecessarily high cost for the received power during peak hours.

[0009] SUMMARY

[0010] An object of the present disclosure is to provide a method which seeks to mitigate, alleviate, or eliminate one or more of the above-identified deficiencies in the art and disadvantages singly or in any combination and to provide an automated system for energy management.

[0011] This object is obtained by a local system to manage power distribution in a local power grid having a local energy management system, EMS, provided with a local energy storage and a hybrid inverter, the hybrid inverter being connected to the energy storage, controllable loads, and a main power grid via fuses, the local EMS being configured to at least optimize power consumption at a site by:

[0012] - controlling power consumed by selected controllable loads

[0013] - monitoring power received from the main power grid, and

[0014] - controlling power from the energy storage, wherein the optimization is provided by a core node within the local EMS based on:

[0015] - predicted power consumption for a time period,

[0016] - available power capacity in energy storage, and

[0017] - power that can be received from the main power grid without exceeding a set power level of the fuses.

[0018] This object is also obtained by a system to manage power distribution in a main power grid, the main power grid being connected to a plurality of local systems with a local energy management system, EMS, wherein the local EMS is further configured to predict available power that can be distributed to the main power grid, wherein a control system is used to control the power distribution in the main power grid, and data regarding available power within the plurality of EMSs is aggregated and the control system controls the amount of power provided from the aggregated power to the main power grid based on power needs.

[0019] Advantages and other aspects of the invention is provided in the detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The foregoing will be apparent from the following more particular description of the example embodiments, as illustrated in the accompanying drawings in which like reference characters refer to the same parts throughout the different views. The drawings are not necessarily to scale, emphasis instead being placed upon illustrating the example embodiments.

[0021] Figure 1 shows a local power grid with an energy management system;

[0022] Figure 2 shows a platform for intelligent energy management comprising a core node; Figure 3 shows an overview of the functionality of an advanced core node in an energy management system;

[0023] Figure 4 shows an overview of an energy system comprising several local Energy Management System and an aggregator; and

[0024] Figure 5 illustrates an Al based cloud implementation used to assist energy management systems.

[0025] DETAILED DESCRIPTION

[0026] Aspects of the present disclosure will be described more fully hereinafter with reference to the accompanying drawings. The system and method disclosed herein can, however, be realized in many different forms and should not be construed as being limited to the aspects set forth herein. Like numbers in the drawings refer to like elements throughout.

[0027] The terminology used herein is for the purpose of describing particular aspects of the disclosure only, and is not intended to limit the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

[0028] Some of the example embodiments presented herein are directed towards energy management methodology. As part of the development of the example embodiments presented herein, a problem will first be identified and discussed. The underlying problem is that power distribution capacity in the main power grids is underused due to an unbalanced power need by the consumers, An enforcement of the distribution capacity of the electric power grid is needed, but not by investing in new infrastructure, but by optimizing the use of the existing power grids.

[0029] Fig 1 shows a local power grid with an energy management system that is connected to the main power grid via a fuse box (in this example with 16A fuses). The core of the system is a 3-phase hybrid inverter. The hybrid inverter can, unlike a conventional string inverter, manage the production from both a photovoltaic system and an energy storage (battery). The objective of the inverter is to convert the direct current produced by the photovoltaic system or taken from the energy storage, into the alternating current used in the property. In buildings, there is often an imbalance in the consumption of electricity, which is scattered into three different phases. This means that some phases are more heavily loaded than others. By intelligent phase balancing, the hybrid inverter ensures that the production from the photovoltaic system (solar panels) and / or the energy storage (batteries) is balanced so that the right amount of energy is distributed to the different phases. This enables optimized use of the energy produced and stored and reduces the need for purchased electricity. With a hybrid inverter, the user can create a complete power handling system including energy storage and intelligent energy management, as described in Figure 2.

[0030] Fig 2 shows a typical platform for intelligent energy management comprising a core node that communicates (dashed lines) with at least one node controlling hardware (such as lamps and equipment connected to a power outlet), one or more car chargers, off-grid back-up power system, energy storage (battery), photovoltaic system (PV) and hybrid inverter.

[0031] The core node is the brain of the power handling system that controls, analyzes, and acts based on the property’s prevailing conditions and needs. The core node communicates with both the energy storage and the hybrid inverter to be able to intelligently regulate the energy flows to and from the property. The unit is also connected to the property’s network, which enables real-time visualization of ongoing management and historical data.

[0032] The energy flows in the property can be monitored and managed by the user via an app (not shown), which the user can easily download to a mobile phone. Configuration of user specific settings can be done from the app; for example, selection of different scenarios such as peak-shaving, tariff control, time-shifting, or smart car charging. Fig 3 shows an overview of the functionality of an advanced core node in the energy management system. The system has a built-in functionality to protect the grid fuses by monitoring the energy consumption of each phase and supply energy from the energy storage or adapting different loads connected to the local power grid, such as EV- charger, to ensure that the energy consumption does not exceed the size of the fuses for incoming energy from the main power grid. Below is the functionality supported by the advanced core node described in more detail.

[0033] Energy Price Optimization

[0034] What makes the energy management system described below stand out when it comes to electricity price optimization is simply the amount of data that is analyzed. Prior art home batteries on the market take prices into account, but this could ultimately mean that your saved solar energy is drained from the battery at the first peak in electricity prices or at a time when you’re not at home and using as much energy, because the system acts right now instead of thinking ahead.

[0035] The energy management system not only considers the current electricity price, but also considers how the price will develop in the future and can, for example, predict an even higher electricity price peak or predict that you will need to use a lot of electricity later in the day when you start the dishwasher, shower, and charge the electric car at the same time. This type of advanced analysis ultimately means that you get even lower electricity costs, as the intelligence in energy management system makes careful decisions for when the electricity should be saved and when it should be sold.

[0036] The system may include an additional feature that optimizes the import of energy to the property by controlling the system based on hourly price for energy. The hourly prices are set by Nord Pool Group on the Nordic electricity market and are available one day in advance, a.k.a. Spot price. By using spot prices and the knowledge of the consumption and production of the property, the system will control charge and discharge of the energy storage, EV charging, heat pumps and other controllable loads to minimize the electricity cost.

[0037] Peak Power Shaving

[0038] Another benefit of intelligent energy storage is that the system can cut your power peaks.

[0039] You get a power peak when you use a lot of electricity at the same time, and when this happens, you want as little as possible of that electricity to come from the grid, because you pay a fee based on the highest power measured during a month. This fee is not a reality for everyone yet, but by 2027 all Swedish electricity customers will be forced to pay these power tariffs. A battery that does not have an intelligent EMS cannot predict or notice these power peaks in real time, but a smart battery can, and thus you can get reduced grid fees because you do not have as high peaks in your consumption. The energy management system is constantly learning how to use energy at home and automatically adjusts the limit of what counts as a power peak.

[0040] Phase balancing

[0041] Something important to keep in mind, regardless of whether you have energy storage or not, is that the three phases in your property do not become overloaded and use approximately the same amount of energy for each phase. An intelligent battery ensures that the phases are balanced and pushes energy out to the phase where it is needed. This allows you to optimize the use of energy from your solar panels and the electricity stored in the battery, thus reducing the risk of having to buy and sell electricity at the same time - something that could otherwise be the case when you have a lot of production from the solar panels but low demand on any of the phases. An overview of this functionality is presented in Figure 1 .

[0042] Tariff Management

[0043] The tariff costs are fees applied on the power grid, and the grid fee is simply higher during times when the strain on the grid is high. Tariff Management minimizes the grid cost by automatically steering the property’s energy storage usage to times outside the tariff intervals without compromising the comfort of the property.

[0044] EV-control

[0045] Enables faster charging and more cost-efficient car charging through automated adjustments of charging power and when charging takes place with regards to how energy is used in the rest of the property. In combination with other features, such as phase balancing and tariff management, EV-control makes sure to optimize your car charging every time. In addition, the EV-control reglates the available power to the charger in case the power demand by other loads in the property is high to ensure that the maximum power level set by the fuses is not exceeded.

[0046] Renewable Time shifting

[0047] This function, time shifting, takes your property’s energy consumption into account. When overproduction from the PV panels is available it’s stored from day to be used at night, to always make sure you optimize your own energy production.

[0048] Back-up Power - island mode

[0049] This function, also known as off-grid, makes it possible to turn on the lights when the neighbors have a power outage using intelligent energy storage and off-grid functionality. It is also possible to continue producing and storing solar energy when the grid is not available and keep critical supplies alive.

[0050] To secure the possibility to handle a situation where power from the grid is not available, the energy system needs to reserve some part of available capacity to operate as backup power. This is a setting that as a default is 50% of the state-of-charge, SOC, of the energy storage, which means that the energy storage will save 50% of available energy for prioritized loads in the system in case there is a power outage. The setting may be adjusted to comply with personal preferences.

[0051] The reserve in the energy storage is activated automatically within a short time interval (less than 1 second) without the user having to physically turn on a switch etc. and it is activated to supply power to the prioritized loads. When power is available from the main power grid, the system automatically reconnects the property to the main power grid. The prioritized loads are selected to be operational during a power outage by the user, and these loads will be powered if there is available energy in the energy storage or from own production (e.g. PV system)

[0052] Island mode operates in a similar way as Back-up power, but with the difference that there is no main power grid available.

[0053] Property Load Management Another feature that you will find in smart batteries is the ability for the system to control large electricity consumers towards times when electricity costs less. This is completely automatic in the system, with the help of a lot of data and analysis. For example, your heat pump can be a major consumer of electricity.

[0054] This minimizes the cost and grid loads, locally and in the community.

[0055] Comfort Energy management

[0056] This function allows for personal settings to meet expectations regarding personal comfort inside a building.

[0057] Weather optimization

[0058] The weather optimization predicts the next day’s energy production from the PV system. Based on the predicted energy production, the system makes decisions if the energy storage should be charged during the night or wait for a predicted overproduction from the PV system.

[0059] Flexible Market - FCR (Frequency Containment Reserve)

[0060] The amount of electricity consumed and produced must, in every moment, be equal. To ensure that this balance is maintained, the transmission system operator (TSO) buys balancing services from producers and consumers that can quickly increase or decrease their production or consumption. The fastest-responding type of balancing service currently used in Sweden is called FCR (Frequency Containment Reserve). Resources that deliver this service respond directly to deviations from the 50 Hz target grid frequency. Such frequency deviations occur whenever there is a mismatch between production and consumption.

[0061] In Sweden, the TSO Svenska Kraftnat procures two types of FCR services: FCR-N (Normal) and FCR-D (Disturbance). FCR-N is used to continuously respond to both positive and negative deviations from 50 Hz, whereas FCR-D only responds to large negative frequency deviations. A producer that provides FCR-N therefore must be able to both increase and decrease its output, whereas a producer that provides FCR-D only needs to be able to increase production. Svenska Kraftnat procures these services separately for each hour through competitive auctions that take place 1 -2 days in advance. The resources that are willing to supply the services at the lowest price are awarded the contracts and the compensation is pay- as-bid. Figure 4 shows an aspect related to how several energy management systems may collaborate to provide this service to the TSO.

[0062] Other aspects of the Advanced core node

[0063] As for the core node described in connection with figure 2, the functionality of the Advanced core node can also be monitored and managed by a user app. The user may select to prioritize car charging through the app, and the system takes necessary actions to ensure prioritizing charging of the car. This means that the system temporarily disregards all user settings and only consider efficient EV charging and that the fuses are protected.

[0064] The system may also include one or more power nodes, which introduces the possibility to control the loads in the property in a new way. The user may program different scenarios for how different loads that are connected to one power node should be controlled. One example of a utilization area is when the back-up power functionality is activated, non-essential loads connected to power nodes may be shut down, e.g. outdoor lighting. A power node may also be used to control the water boiler or heat pump.

[0065] Figure 4 shows an overview of an energy system comprising seven local Energy Management System, EMS 1 - EMS 7, at different sites, where each local EMS comprises an Advanced core node. The energy system further comprises an aggregator configured to communicate with each Advance core node and to aggregate available power to provide services to a Balance Responsible Party (BRP) that respond directly to deviations from the 50 Hz target grid frequency at TSO level. By aggregating available power from multiple sites, it is possible to win contracts at the auction. However, the bidder with the lowest price normally wins the contract, and sometimes it is not economically sane to win a contract even though the aggregator has access to enough power to deliver the request services.

[0066] One factor that needs to be taken into consideration is the cost of cycling the battery. Each charge / discharge operation of the battery directly affects the cycle life of the battery. Also, the depth of discharge has a direct impact of expected life of the battery. Therefore, the amount of available energy capacity and power are important parameters when deciding to place a bid for a specific service to the TSO. Figure 5 describes a system configuration to acquire knowledge before a decision is made to place a bid.

[0067] Figure 5 illustrates a local energy management system for a property which is connected to a main power grid. The local EMS is provided with a Common Application Program Interface (CAPI) and is equipped with an Al based cloud computing functionality. The local EMS and the cloud computing functionality are also configured to communicate with a centralized control center. The cloud computing functionality may communicate with multiple local energy management systems to collect necessary data from each local EMS in order to gain information regarding availability of necessary resources to meet the requested service, the cost for performing the requested service, and finally to make a decision regarding placing a bid or not.

[0068] In short, the local EMS is Al driven to optimize the use of own production and grid connection in a property, fully automated with energy visualisation, cloud based with local control expansions, and algorithms to:

[0069] • Reduce electricity costs and maximize the utilization of self-produced power

[0070] • Support energy storage optimization, for best performance / lifetime performance

[0071] • Support EV charging and heat pump control, to avoid power and cost peaks

[0072] The basic concept of the invention is to optimize the power consumption (and optionally energy consumption) in both local and main power grids.

[0073] In one embodiment, there is suggested a local system to manage power distribution in a local power grid having a local energy management system, EMS, provided with a local energy storage and a hybrid inverter, the hybrid inverter being connected to the energy storage, controllable loads, and a main power grid via fuses, the local EMS being configured to at least optimize power consumption at a site by:

[0074] - controlling power consumed by selected controllable loads

[0075] - monitoring power received from the main power grid, and

[0076] - controlling power from the energy storage, wherein the optimization is provided by a core node within the local EMS based on: - predicted power consumption for a time period,

[0077] - available power capacity in energy storage, and

[0078] - power that can be received from the main power grid without exceeding a set power level of the fuses.

[0079] This embodiment optimizes the power consumption in a local power grid while minimizing the cost for the user since available power inside the local power grid is controlled by the user according to personal settings (see examples above).

[0080] In some embodiments, the local EMS further comprises an energy production plant which is connected to the hybrid inverter, and the local EMS is further configured to at least optimize power consumption by monitoring locally produced power from the energy production plant based on weather conditions to predict power production for the time period.

[0081] The addition of an energy production plant, such as PV panels, makes the system less vulnerable to power outage in the main grid.

[0082] In some embodiments, the local EMS is configured to operate in back-up mode if no power is available from the main power grid, and wherein the core node is further configured to randomly reconnect to the main power grid when power is available again to reduce the risk of power surges in the main power grid when many loads are reconnected at once.

[0083] By having a random reconnect functionality, it is less risk that the main power grid fails to reconnect all consumers due to high power surges that may cause additional failures to the infrastructure.

[0084] In some embodiments, the time period is selected to be the next 24 hours, divided into hourly slots.

[0085] In some embodiments, the optimization is performed by an Al based algorithm.

[0086] In one embodiment, a system is suggested to manage power distribution in a main power grid, the main power grid being connected to a plurality of local systems with a local energy management system, EMS, which is further configured to predict available power that can be distributed to the main power grid, wherein a control system is used to control the power distribution in the main power grid, and data regarding available power within the plurality of EMSs is aggregated and the control system controls the amount of power provided from the aggregated power to the main power grid based on power needs.

[0087] When the available power from several EMSs are aggregated, it is possible to support the main power grid and provide a service to the operator of the main grid.

[0088] In one embodiment, a method is suggested to control power distribution in a local power grid with a local energy management system, EMS, wherein a core node in the local EMS controls the power distribution in the local power grid while performing the following steps: a) predicting power consumption for a time period, based on weather conditions and historic data, b) calculating available power capacity in energy storage, c) determining the amount of power that can be received from the main power grid without exceeding a set power level, d) optimizing power distribution based on the predicted power consumption in step a), available power capacity in step b) and amount of power from main grid in step c) by o controlling power consumed by selected controllable loads o monitoring power received from the main power grid, and o controlling power from the energy storage.

[0089] In one embodiment, a method is suggested to manage power distribution in a main power grid, the main power grid being connected to a plurality of local systems with a local energy management system, EMS, which is further configured to predict available power that can be distributed to the main power grid, wherein a control system controls the power distribution in the main power grid and the following steps are performed by the control system to manage the power distribution:

[0090] - receiving data regarding available power from each local EMS,

[0091] - aggregating the received data to determine aggregated power for the plurality of local EMSs, and

[0092] - controlling the amount of power provided from the aggregated power to the main power grid based on power needs. It should be appreciated that a flowchart comprises some operations which are illustrated with a solid border and some operations which are illustrated with a dashed border. The operations which are comprised in a solid border are operations which are comprised in the broadest example embodiment. The operations which are comprised in a dashed border are example embodiments which may be comprised in, or a part of, or are further operations which may be taken in addition to the operations of the broadest example embodiments. It should be appreciated that these operations need not be performed in order. Furthermore, it should be appreciated that not all of the operations need to be performed. The example operations may be performed in any order and in any combination.

[0093] Aspects of the disclosure are described with reference to the drawings, e.g., block diagrams and / or flowcharts. It is understood that several entities in the drawings, e.g., blocks of the block diagrams, and also combinations of entities in the drawings, can be implemented by computer program instructions, which instructions can be stored in a computer-readable memory, and also loaded onto a computer or other programmable data processing apparatus. Such computer program instructions can be provided to a processor of a general purpose computer, a special purpose computer and / or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer and / or other programmable data processing apparatus, create means for implementing the functions / acts specified in the block diagrams and / or flowchart block or blocks.

[0094] In some implementations and according to some aspects of the disclosure, the functions or steps noted in the blocks can occur out of the order noted in the operational illustrations. For example, two blocks shown in succession can in fact be executed substantially concurrently or the blocks can sometimes be executed in the reverse order, depending upon the functionality / acts involved. Also, the functions or steps noted in the blocks can according to some aspects of the disclosure be executed continuously in a loop.

[0095] In the drawings and specification, there have been disclosed exemplary aspects of the disclosure. However, many variations and modifications can be made to these aspects without substantially departing from the principles of the present disclosure. Thus, the disclosure should be regarded as illustrative rather than restrictive, and not as being limited to the particular aspects discussed above. Accordingly, although specific terms are employed, they are used in a generic and descriptive sense only and not for purposes of limitation.

[0096] The description of the example embodiments provided herein have been presented for purposes of illustration. The description is not intended to be exhaustive or to limit example embodiments to the precise form disclosed, and modifications and variations are possible in light of the above teachings or may be acquired from practice of various alternatives to the provided embodiments. The examples discussed herein were chosen and described in order to explain the principles and the nature of various example embodiments and its practical application to enable one skilled in the art to utilize the example embodiments in various manners and with various modifications as are suited to the particular use contemplated. The features of the embodiments described herein may be combined in all possible combinations of methods, apparatus, modules, systems, and computer program products. It should be appreciated that the example embodiments presented herein may be practiced in any combination with each other.

[0097] It should be noted that the word “comprising” does not necessarily exclude the presence of other elements or steps than those listed and the words “a” or “an” preceding an element do not exclude the presence of a plurality of such elements. It should further be noted that any reference signs do not limit the scope of the claims, that the example embodiments may be implemented at least in part by means of both hardware and software, and that several “means”, “units” or “devices” may be represented by the same item of hardware.

[0098] The various example embodiments described herein are described in the general context of method steps or processes, which may be implemented in one aspect by a computer program product, embodied in a computer-readable medium, including computer-executable instructions, such as program code, executed by computers in networked environments. A computer-readable medium may include removable and non-removable storage devices including, but not limited to, Read Only Memory (ROM), Random Access Memory (RAM), compact discs (CDs), digital versatile discs (DVD), etc. Generally, program modules may include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. Computer-executable instructions, associated data structures, and program modules represent examples of program code for executing steps of the methods disclosed herein. The particular sequence of such executable instructions or associated data structures represents examples of corresponding acts for implementing the functions described in such steps or processes. In the drawings and specification, there have been disclosed exemplary embodiments. However, many variations and modifications can be made to these embodiments. Accordingly, although specific terms are employed, they are used in a generic and descriptive sense only and not for purposes of limitation, the scope of the embodiments being defined by the following claims.

Claims

CLAIMS1 . A local system to manage power distribution in a local power grid having a local energy management system, EMS, provided with a local energy storage and a hybrid inverter, the hybrid inverter being connected to the energy storage, controllable loads, and a main power grid via fuses, the local EMS being configured to at least optimize power consumption at a site by:- controlling power consumed by selected controllable loads- monitoring power received from the main power grid, and- controlling power from the energy storage, wherein the optimization is provided by a core node within the local EMS based on:- predicted power consumption for a time period,- available power capacity in energy storage, and- power that can be received from the main power grid without exceeding a set power level of the fuses.

2. The local system according to claim 1 , wherein the local EMS further comprises an energy production plant which is connected to the hybrid inverter, and the local EMS is further configured to at least optimize power consumption by monitoring locally produced power from the energy production plant based on weather conditions to predict power production for the time period.

3. The local system according to any of claims 1 or 2, wherein the local EMS is configured to operate in back-up mode if no power is available from the main power grid, and wherein the core node is further configured to randomly reconnect to the main power grid when power is available again to reduce the risk of power surges in the main power grid when many loads are reconnected at once.

4. The local system according to any of the preceding claims, wherein the time period is selected to be the next 24 hours, divided into hourly slots.

5. The local system according to any of the preceding claims, wherein the optimization is performed by an Al based algorithm.

6. A system to manage power distribution in a main power grid, the main power grid being connected to a plurality of local systems with a local energy management system, EMS, according to any of claims 1 -5, and the local EMS is further configured to predict available power that can be distributed to the main power grid, wherein a control system is used to control the power distribution in the main power grid, and data regarding available power within the plurality of EMSs is aggregated and the control system controls the amount of power provided from the aggregated power to the main power grid based on power needs.

7. A method to control power distribution in a local power grid with a local energy management system, EMS, according to any of claims 1 -5, wherein a core node in the local EMS controls the power distribution in the local power grid while performing the following steps: e) predicting power consumption for a time period, based on weather conditions and historic data, f) calculating available power capacity in energy storage, g) determining the amount of power that can be received from the main power grid without exceeding a set power level, h) optimizing power distribution based on the predicted power consumption in step a), available power capacity in step b) and amount of power from main grid in step c) by o controlling power consumed by selected controllable loads o monitoring power received from the main power grid, and o controlling power from the energy storage.

8. A method to manage power distribution in a main power grid, the main power grid being connected to a plurality of local systems with a local energy management system, EMS, according to any of claims 1 -5 each EMS is further configured to predict available power that can be distributed to the main power grid, wherein a control system controls the power distribution in the main power grid and the following steps are performed by the control system to manage the power distribution: receiving data regarding available power from each local EMS, aggregating the received data to determine aggregated power for the plurality of local EMSs, and- controlling the amount of power provided from the aggregated power to the main power grid based on power needs.

9. A computer program product comprising computer program code to perform, when executed on a computer, the method according to claim 7 or 8.

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