WO2018074973A1

WO2018074973A1 - A method for controlling energy content and power flow in a local power grid

Info

Publication number: WO2018074973A1
Application number: PCT/SE2017/051023
Authority: WO
Inventors: Björn Bolund; Tobias REHNHOLM; Mikael NORDLANDER
Original assignee: Vattenfall Ab
Priority date: 2016-10-21
Filing date: 2017-10-17
Publication date: 2018-04-26
Also published as: EP3529773A1; EP3529773A4; DE212017000235U1

Abstract

The present disclosure relates to a method, performed in a control unit, for controlling energy content and power flow in a local power grid at least intermittently connected to an external power grid. The method comprises obtaining (S11) information regarding: power consumptions in controllable loads and non-controllable loads influencing energy content and power flow in the local power grid, current energy content in energy storage accessible to the local power grid, and market prices for energy related commodities and power related commodities available in the external power grid. The method further comprises: calculating (S13) energy content and power flow forecasts within the local power grid based on the obtained information, optimizing (S15) the energy content and power flow within the local power grid based on the forecasts, and applying (S16) the optimized energy content and power flow within the local power grid during a predetermined time interval.

Description

A method for controlling energy content and power flow in a local power grid TECHNICAL FIELD

The disclosure relates to a method, a control unit and a computer program for controlling energy content and power flow in a local power grid. More specifically, the disclosure relates to optimizing energy content and power flow in the local power grid based on obtained information and applying it to the local power grid.

BACKGROUND

Every entity, e.g. micro-grid, household, industry, commercial building, network station, may be viewed as a local power grid comprising Controllable Loads (CL), such as heating system, and Non-Controllable Loads (NCL), such as lighting. From a user perspective, the energy content and power flow within the local power grid is expected to be sufficient in order to deliver power to the loads. This is generally true provided access to an external power grid is fulfilled, but Locally Generated Energy (LGE) with or without local Energy Storage (ES), such as batteries, may provide the necessary energy content and power flow to establish an off-grid solution. An external power grid is defined as any type of grid that may supply energy to the local grid if connected. Examples of external power grids are national power grid, a regional power grid and another local power grid.

The introduction of energy storage in local power grids increases the possibility to be able to operate off-grid for a longer time, especially in combination with locally generated energy, such as solar energy or wind.

Figure 1 illustrates a local power grid 21 which under normal operating conditions is connected to an external power grid 22 via a meter 6. The meter records the amount of energy transferred from the local power grid 21 to the external power grid 22 and vice versa. The local power grid comprises controllable loads (CL) 12 and non-controllable loads (NCL) 13. Solar panels or windmills may be provided to provide locally generated energy (LGE) 17 and local energy storage ES 14, e.g. a battery bank or fuel cells, may be provided to store energy for later use. A control unit (CU) 5 is configured to handle energy content in the optional energy storage 14 and to control power flows inside the local grid. The CU 5 may be a separate unit or implemented in another device.

The purpose of the prior art system illustrated in figure 1 is to ensure sufficient energy is available for the local power grid. The cost for providing sufficient amount of power to the loads in the local power grid 21 is of less importance.

A drawback with the prior art system is that information is not shared between the user handling the functionality in the local power grid and the operators handling the functionality of the external power grid. Another drawback is the lack of control of energy and power flow from the local grid to the external power grid and vice versa. SUMMARY

An object of the present disclosure is to provide a method and control unit configured to execute the 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.

This object is obtained by a method, performed in a control unit, for controlling energy content and power flow in a local power grid at least intermittently connected to an external power grid. The method comprises obtaining information regarding power consumptions in controllable loads and non-controllable loads influencing energy content and power flow in the local power grid, current energy content in energy storage accessible to the local power grid, and market prices for energy related commodities and power related commodities available in the external power grid. The method further comprises calculating energy content and power flow forecasts within the local power grid based on the obtained information, optimizing the energy content and power flow within the local power grid based on the forecasts, and applying the optimized energy content and power flow within the local power grid during a predetermined time interval. An advantage with the disclosed method for controlling energy content and power flow is that energy storage may be decentralized and the energy stored may be used to deliver power to power related commodities, also known as ancillary services, in the external power grid. Another advantage with the disclosed method for controlling energy content and power flow is that energy production may be decentralized and the generated energy may be used for power related commodities in the external power grid.

Another advantage with the disclosed method for controlling energy content and power flow is that power to controllable loads may be reduced and available power within the local power grid may be used for power related commodities in the external power grid.

According to some aspects, the disclosure relates to a control unit for controlling energy content and power flow in a local power grid, at least intermittently connected to an external power grid. The control unit comprising a processing circuitry configured to obtain information regarding: power consumptions in controllable loads and non-controllable loads influencing energy content and power flow in the local power grid, current energy content in energy storage accessible to the local power grid, and market prices for energy related commodities and power related commodities available in the external power grid. The control unit is further configured to calculate energy content and power flow forecasts within the local power grid based on the obtained information, optimize energy content and power flow within the local power grid based on the forecasts, and apply the optimized energy content and power flow within the local power grid during a predetermined time interval.

BRIEF DESCRIPTION OF THE DRAWINGS

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.

Figure 1 illustrates a control unit within a local power grid according to the prior art;

Figure 2 illustrates a control unit within a local power grid according to some aspects of the disclosure;

Figure 3 illustrates a model hypothesis according to some aspects of the disclosure;

Figure 4 illustrates how a control unit can be integrated to support operations within a local power grid according to some aspects of the disclosure; Figure 5 is a flowchart that illustrates the method steps for controlling energy content and power flow within a local power grid;

Figure 6 is a partial flowchart that illustrates alternatives related to processing obtained information according to some aspects of the disclosure; and Figure 7 illustrates a control unit configured to perform the method steps illustrated in connection with figure 5.

Figure 8a illustrates power flow in a battery plotted as a function of total system power flow in an EV charging example.

Figure 8b illustrates power flow through the EV charger plotted as a function of the total system power flow in the EV charging example.

Figure 9 illustrates the forecasted power through the EV charger and the real time power in the EV charging example.

Figure 10 illustrates a 10 day run in a peak shaving example. DETAILED DESCRIPTION Aspects of the present disclosure will be described more fully hereinafter with reference to the accompanying drawings. The apparatus 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.

The terminology used herein is for the purpose of describing particular aspects of the disclosure only, and is not intended to limit the disclosure. 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.

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.

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.

In economic terms, electricity (both power and energy) is a commodity capable of being bought, sold, and traded. An electricity market is a system enabling purchases, through bids to buy; sales, through offers to sell; and short-term trades, generally in the form of financial or obligation swaps. Bids and offers use supply and demand principles to set the price. Long-term trades are contracts similar to power purchase agreements and generally considered private bi-lateral transactions between counterparties.

Wholesale transactions (bids and offers) in electricity are typically cleared and settled by the market operator or a special-purpose independent entity charged exclusively with that function. Market operators do not clear trades but often require knowledge of the trade in order to maintain generation and load balance. The commodities within an electric market generally consist of two types: power and energy. Power is the metered net electrical transfer rate at any given moment and is measured in watts (W). Energy is electricity that flows through a metered point for a given period and is measured in watt-hours (Wh).

Markets for energy-related commodities trade net generation output for a number of intervals usually in increments of five, fifteen or sixty minutes. Markets for power-related commodities required and managed by (and paid for by) market operators to ensure reliability, are considered ancillary services and include such names as spinning reserve, non-spinning reserve, operating reserves, responsive reserve, regulation up, regulation down, and installed capacity.

Consumers of energy will in the future be more active and more renewable energy systems, such as solar power and wind power, will be installed in local power grids which increase the need for power system flexibility and services. The term "local power grid" include any type of power grid, e.g. micro-grid, household, industry, commercial building, network station, connected to an external power grid via a meter. According to some aspects, batteries with high power/energy ratio are beneficial to offer short term flexibility, power related commodities and increase value for Photo Voltaic (PV) production. Furthermore, local energy storage in the form of batteries can offer technology hedging, e.g. secure a way to pay less per kWh on more volatile electricity markets.

A more variable and intermittent power system will increase the incentives to be more flexible in energy consumption for consumers. The possibility to offer local grid flexibility to the markets for power and energy related commodities will increase the incentives for customers investing in flexible solutions. Together, local production and flexibility offer the synergy of increased self-sufficiency. This will also increase the incentives for customers to decrease their environmental impact. The grid hosting capacity will grow due to increased decentralized flexibility in the distribution networks. The value of intermittent renewables will be better maintained under increasing penetration of VRE (Variable Renewable Energy), since larger deviations in supply and demand can be handled. The global trend for electricity systems is an increase of Variable Renewable Energy (VRE) in order to adapt to a more sustainable society. As a consequence conventional flexible production is being pushed out of the system, replaced by intermittent energy production with low capacity factor. Removing flexible production and adding VRE will substantially increase the need for system flexibility. There are four solutions to solve the production/demand balance:

• Flexible production - Decreasing when conventional production is decommissioned due to higher VRE penetration.

• Flexible demand - Digitalization, communication and sensors development offers more possibilities to control loads, and is a growing segment with large potential. • Storage - Large scale solutions like pumped hydro is a conventional technology, but solutions like batteries and hydrogen storage enables small scale storage solutions.

• Transmission - Increased connectivity and transmission capacity allows for production and demand balance to be solved within a larger geographical area, hence reducing impact of local flexibility constraints. However a number of factors such as long permit times, capital heavy investments and dimension for future peak capacity requirements results in a slow build out lagging the system needs.

To maintain or increase system flexibility, different electrical systems will need their own combination the above four mentioned solutions order to create flexibility in a cost effective manner.

The rapid cost decrease of PV combined with low economies of scale is leading to an increase in predominantly decentralized PV build out but also other decentralized production. One of main advantages for decentralized production such as PV is the ability to self-consume production, removing costs for transmission, energy taxes and VAT compared to sourcing from grid. An increase in self-consumption increases the value of local production. This can be done by introducing either controllable loads like heat pumps that can adapt to local production or storage solutions like batteries that can move production in time or a combination of both. Controllable loads and energy storage also adds additional benefits like reduced grid tariff and enable flexible consumption in time. Energy storage also offers resilience to grid failure and flexibility in time when producing to power grid, i.e. the battery introduces flexible consumption and production.

Active control of flexible assets enables local power grids to provide ancillary services. By taking the needs of local and external power grid into consideration when utilizing the available flexibility increased revenue can be created, thus increasing value of flexible assets. The electrical systems gain access to a distributed flexibility reserve that can aid the external power grid operation by performing power related commodities, also known as ancillary services.

Advantages with the power related commodities are distribution and transmission grid investment deferral and resource adequacy, thereby avoiding portfolio overinvestment. Another aspect is that coordination for demand of power related commodities, also known as ancillary services, such as: Spin/Non-spin reserve, e.g. synthetic inertia, Frequency Regulation, Strategic reserve, Voltage support through active and reactive power control, Black Start, Transmission congestion relief, Peak shaving, Phase balancing, Power control, etc., in the external power grid will be important in the future, and aggregators for demand side coordination may be desired.

The power need is different depending on demands in different parts of the power grid. For instance usage optimization, e.g. increased PV self-consumption, tariff reduction, load shifting, time of use and resilience to grid failures, is of high importance when considering local need. Ancillary services, e.g. frequency regulation, spin/non-spin reserve (e.g. synthetic inertia), strategic reserve and black start, are of high importance when considering centralized need in the power grid. Upstream grid functionality, e.g. voltage support through active and reactive power control, active power limitation, peak shaving, phase balancing and reactive power, is of high importance when considering regional need. Thus, optimal handling of power depends on local conditions, location in grid and regional markets for power and energy commodities. The strategic value lies in optimal prioritizing of the available resources, while considering the needs of the user, local power grid and external power grid

Figure 2 illustrates a local power grid 21 which is at least intermittently connected to an external power grid 22 via a meter 6. The meter records the amount of energy, i.e. power per time period, transferred from the local power grid 21 to the external power grid 22 and vice versa. The local power grid comprises controllable loads (CLj 12 and non-controllable loads (NCL) 13. A local energy source, such as fuel ceils, combined heat and power (CHP), hydro power, solar PV & solar heater or windmills, may be provided to provide locally generated energy (LGE) 17 and local energy storage ES 14, e.g. batteries, capacitors, hydrogen storage, etc. may be provided to store energy for later use. A detector 15 may be provided which is configured to detect accessibility to the external power grid 22.

A control unit 10 is provided for controlling energy content and power flow in the local power grid 21 and is described in more detail in connection with figure 7. The control unit 10 is configured to obtain information regarding certain key parameters, as described below, which may be obtained from information available in the cloud 23, or directly from operators 24, for instance Independent System Operators ISO and/or Regional Transmission Organizations RTO. The control unit 10 does not have to be a physical unit located within the local power grid, and some or all the functionality of the control unit may be distributed, e.g. in a cloud implementation, or even implemented at a remote location outside the local power grid.

The external power grid is defined as power grids not controlled by the control unit 10, and may be a national power grid, a regional power grid, or even another local power grid that have the ability to provide energy and power to the local power grid.

According to one aspect, capability to store energy in the local power grid is temporary and may be provided by electric vehicles (which are considered to be a controllable load within the local power grid 21). According to another aspect, energy storage may be provided outside the local power grid as long as the energy content is accessible to the local power grid.

Energy storage may be implemented as stationary battery banks, mobile battery banks such as electric vehicles (EV) or plug-in hybrid electric vehicles (PHEV), fly wheels, compressed air or thermal energy storage. In order to calculate the available energy content in the energy storage certain boundary conditions have to be defined such as maximum energy content level (above which charging is not an option), lower energy content level (below which discharge is not recommended), and charge/discharge rate (which determines how fast discharge and charge of the energy storage may be performed, i.e. the maximum power when charging/discharging the energy storage). Boundary conditions may also comprise fuse size of incoming lines, maximum discharge rate of local energy storage, battery cycling limitations etc.

Boundary conditions could also be user specified conditions, such as temperature ranges, charge levels in battery banks, etc. user location could also influence set boundary conditions. For instance, set boundary conditions at a property having a local power grid could be to maintain the indoor temperature at ten degrees Celsius, and if the user is approaching the property the indoor temperature is increased to twenty degrees Celsius.

Available energy content in each accessible energy storage is an important parameter when optimizing the energy content and power flow within the local power grid, but the decision to charge or discharge the energy storage may be based on the value of the available energy within the energy storage and the ability to receive power or deliver power. Therefore, according to some aspects, it is necessary to estimate available power, e.g. kilo Watts (kW), stored in the energy storage. This information may be used to determine the best use of the available energy and power in view of local energy production (if present), ancillary services available in the external power grid and the energy and power need within the local power grid during a predetermined time period.

The United States Federal Energy Regulatory Commission FERC defines the ancillary services as: "those services necessary to support the transmission of electric power from seller to purchaser given the obligations of control areas and transmitting utilities within those control areas to maintain reliable operations of the interconnected transmission system."

Ancillary services are the specialty services and functions provided by the electric grid that facilitate and support the continuous flow of electricity so that supply will continually meet demand. The term "ancillary services" is used to refer to a variety of operations beyond generation and transmission that are required to maintain grid stability and security. These services generally include frequency control, spinning reserves and operating reserves. Traditionally ancillary services have been provided by generators, however, the integration of intermittent generation and the development of smart grid technologies have prompted a shift in the equipment that can be used to provide ancillary services. Figure 3 illustrates a model hypothesis according to some aspects of the disclosure. The model hypothesis comprises three steps: Forecast 30, Optimizing 31 and Operation 32.

The basic principle of the Forecast 30 is to gather information that could be used when performing the next steps. Each local power grid is unique in its design and thus the operation of each local power grid depends on different parameters. The parameters include: power consumption in controllable loads as well as non-controllable loads, current energy content in energy storage which is accessible to the local power grid, and market prices for energy related commodities and power related commodities available in the external power grid. The energy related commodities include market price for purchasing energy from and selling energy to the external power grid (including tariffs and associated fees, such as taxes and distribution fees), and the power related commodities include ancillary services. The energy related commodities may comprise cost for power failure which may be used to choose between consumption within the local power grid and providing ancillary services when optimizing the energy content and power flow within the local power grid. The parameters may also include wind speed if wind mills are included in the local power grid, solar influx if solar PV or solar heaters are included in the local power grid, temperature information to better estimate power consumption for heating systems within the local power grid, accessibility to the external power grid and historic data that have an impact on the different parameters over time. Some information is available within the local power grid; other information may be retrieved from an external source, such as a cloud based information provider or directly from operators.

Historic data may relate to energy content of energy storage, measured discharge/charge rates, power consumptions in NCL over time, power consumption in CL as a function of external parameters (such as temperature). Historic data may also relate to previously applied optimized energy content and power flow within the local power grid. Energy content and power flow forecasts are calculated based on the obtained information in order to optimize and prioritize handling of energy and power within the local power grid. The calculating of forecasts may comprise calculating power consumption forecasts for controllable loads and non-controllable loads over at least a predetermined time interval, and/or calculating price per power unit in the external power grid based on the market price for power related commodities, and/or calculating available energy content in the energy storage, accessible to the local power grid and having a predefined lower energy content level, based on the current energy content and the predefined lower energy content level, and estimating available power stored in the energy storage.

The optimizing step 31 may comprise a linear optimizer, or machine learning algorithm implemented in a processor, that optimize the energy content and power flow within the local power grid based on the calculated forecasts. According to some aspects, the obtained information is processed and the optimizing is performed based on market prices for power and energy commodities, local energy production forecast, local heating need forecast, local consumption forecast, EV (or PHEV) availability and boundary conditions. The capability to be able to handle a power failure in the external power grid (since the external power grid is intermittently connected to the local power grid) may be taken into consideration when optimizing the energy content and power flow within the local power grid. This is especially important in certain markets where power failures happen often and at a regular basis. Historic data related to power failure occurrences in the external grid may be used to further optimize the energy content and power flow within the local power grid.

The Operation step 32 may comprise control loops to ensure that the process is within predetermined boundary conditions. The operation step is normally performed during a predetermined time interval, which may vary from a couple of minutes (e.g. five, fifteen or sixty minutes) up to several hours dependent on the specific conditions of the local power grid. According to some aspects, the optimizing step 31 comprises creating a utilization plan for the energy content and the power flow which may cover a time period of up to several days, wherein the utilization plan is regularly updated based on the obtained information and forecasts. According to some aspects, the optimizing step 31 further comprises creating an operation plan based on the utilization plan, which is applied within the local power grid during the predetermined time interval.

According to some aspects there is no optimization between the local power grid and the external power grid since no ancillary services are present. In those cases, the optimization step 31 only involves the local power grid, and could include the following services: own consumption of local energy production (if present), back-up power, resilience to external power grid failures, time of use, demand response and/or demand charge reduction through peak shaving and phase balancing.

Figure 4 illustrates how a control unit 10 can be integrated to support operations within a local power grid 21 according to some aspects of the disclosure. The local power grid 21 is in this embodiment divided into two parts, direct current DC power and alternating current AC power, and a sensor 15 is provided to detect accessibility to an external power grid 22. An inverter 25 converts the AC power into DC power and to controllable loads 12b and non- controllable loads 13b are connected to the DC power.

Controllable loads 12a and non-controllable loads 13a is in this example connected to the AC power. The local grid 21 optionally comprises locally generated energy production 17 and local energy storage 14, both connected to the DC power of the inverter 25 in this example. However, energy storage may be located outside the local power grid (not shown) and still be accessible to the local power grid via the external power grid 22. The accessible energy storage may be used for storing energy from local energy production. The control unit 10 is configured to receive information from the non-controllable loads 13a and 13b, controllable loads 12a and 12b, energy storage 14, local energy production 17, sensor 15, and also to receive external information from electricity operators 24 or information available from the cloud 23 regarding energy related commodities as well as power related commodities available in the external power grid. The control unit 10 obtains the available information and calculates energy content and power flow forecasts within the local power grid to optimize usage of available energy and power based on predetermined boundary conditions and/or user defined boundary conditions. The knowledge of market price for power related commodities, i.e. ancillary services, such as Spin/Non-spin reserve (e.g. synthetic inertia), Frequency Regulation, Strategic reserve, Voltage support through active and reactive power control, Black Start, Transmission congestion relief, Peak shaving, Phase balancing and/or Power control, requested by the operators in the external power grid is used to optimize how to use the available energy and power within the local power grid in the most effective way.

Figure 5 is a flowchart that illustrates the method steps for controlling energy content and power flow in a local power grid at least intermittently connected to an external power grid. The method is performed in a control unit, e.g. implemented in a heat pump or heat exchanger, and starts in step S10. The intention is not to limit the control unit to a physical unit, and the method may therefore be performed in a cloud implemented control unit, or other suitable configurations. In Sll, information related to the local power grid and external power grid is obtained, and the information may include user defined and/or user specified boundary conditions. The information is related to: power consumptions in controllable loads and non-controllable loads influencing energy content and power flow in the local power grid, current energy content in energy storage accessible to the local power grid, and market prices for energy related commodities and power related commodities available in the external power grid. An example of market price for energy related commodities is demand response, such as purchasing energy from the external power grid, and selling energy to the external power grid. An example of power related commodities (i.e. ancillary services) is peak shaving, i.e. keep import from/export to external power grid within certain power limits. According to one aspect the ancillary services further comprise Spin/Non-spin reserve (e.g. synthetic inertia), Frequency Regulation, Strategic reserve, Voltage support through active and reactive power control, Black Start, Transmission congestion relief, Peak shaving, Phase balancing and/or Power control,.

According to one aspect, information regarding historic data Slla is obtained and taken into consideration in the following steps.

According to one aspect, forecast data for market price for energy related commodities in the external grid is obtained and taken into consideration in the following steps.

According to one aspect, accessibility to the external power grid is detected S12 and taken into consideration in the following steps. Calculating S13 energy content and power flow forecasts within the local power grid based on the obtained information is performed, which is described in more detail in figure 6. The calculated forecasts are taken into consideration in the following steps.

According to some aspects, the local power grid comprises local energy production, such as solar power (PV), wind mills, hydro power, fuel cells etc. The method then comprises obtaining information regarding weather forecast to determine local energy production forecast S14, and information regarding local production forecast is taken into consideration in the following steps. The forecast is used to determine the local energy production over a time frame, which may be hours, days or weeks. The information may also include knowledge from local energy production at remote sites. For instance if the local energy production comprises solar panels, knowledge regarding the solar intensity at remote sites including wind direction (to determine cloud movements, etc.) may be used provided the physical location of each remote site is known. Furthermore, local and/or global solar forecasts may be used to generate local energy production forecasts, and it is also possible to compare earlier forecasts with actual production results to further improve future forecasts. In step S15, optimizing the energy content and power flow within the local power grid is performed based on the energy content and power flow forecasts. The forecasts are calculated based on the current status of power consumptions in controllable loads and non- controllable loads influencing energy content and power flow in the local power grid, current energy content in energy storage accessible to the local power grid, and market prices for energy related commodities and power related commodities available in the external power grid. According to some aspects, step S15 is based on accessibility to external power grid, historic data, and/or local production forecast.

According to one aspect, when historic data information is obtained, the step of calculating S13 the energy content and power flow forecasts are further based on the historic data information.

According to one aspect, when accessibility to the external power grid is detected, the step of optimizing S15 the energy content and power flow is further based on the accessibility to the external power grid. According to one aspect, the step of optimizing S15 of the energy content and power flow within the local power grid further comprises creating a utilization plan S15a for the energy content and the power flow, wherein the utilization plan is regularly updated based on the obtained information. The purpose of creating a utilization plan is to determine the best way of prioritizing the use of energy and power available within the local power grid. The optimizing may be based on predetermined boundary conditions, user specific boundary conditions, regularly updated real time status of energy content and estimated available power in energy storage, local power consumption, local energy production, etc.

According to one further aspect, the step of optimizing S15 of the energy content and power flow within the local power grid further comprises creating an operation plan S15b based on the utilization plan S15a. The operation plan is applied within the local power grid during the predetermined time interval. The operation plan typically covers a small time period compared to the utilization plan. For instance, if the utilization plan covers a time period over a couple of days, then the operation plan may be limited to cover only a fraction of an hour, e.g. fifteen minutes. In step S16, applying the optimized energy content and power flow within the local power grid is performed during a predetermined time interval. The time interval may be adapted to the situation, and may be as short as a couple of minutes up to several hours. During this time interval boundary conditions are observed in order to prevent unintentional discharge of the energy storage below a certain limit, lack of available energy and power within the local power grid causing unintentional shut-down of loads (CL and NCL), etc. The boundary conditions of the optimized energy content and power flow within the local power grid may be monitored in S17 and if deviation from the optimized energy content and power flow within the local power grid is detected, the process continues to step S15 for adjustment. However, if the applied optimized energy content and power flow within the local power grid is within the boundary conditions during the time interval, the process proceeds to step S18. When decided to continue the process, the process continues to step Sll and information is obtained in order to update the optimized energy content and power flow within the local power grid (e.g. update the utilization plan and thereafter create a new operation plan for the next time interval). If not, the flow ends in S19.

Figure 6 is a partial flowchart that illustrates alternatives related to calculating energy content and power flow forecasts based on the obtained information according to some aspects of the disclosure. According to one aspect, the step of calculating S13 the forecasts comprises calculating S13a power consumption forecasts for controllable loads and non-controllable loads over at least the predetermined time interval. This information will assist in determining the power need of the loads within the local power grid.

According to one aspect, the step of calculating S13 the forecasts comprises calculating S13b price per power unit in the external power grid based on the market price for power related commodities and also on market price forecasts if available. This information may be used to determine when to receive power from/deliver power to the external power grid.

Market prices for power related commodities, i.e. ancillary services, vary over time in response to available energy/power balances and reserves within the external power grid. Locally stored energy and/or locally generated energy may be used to deliver power to the external power grid provided the profit when delivering power to the external power grid is adequate. Another type of ancillary services is to receive power and consume it and/or store it in local energy storage provided the profit when receiving power from the external power grid is adequate.

According to some aspects, the step of calculating S13b price per power unit in the external power grid based on market price for power related commodities further comprises calculating S13bl profit when receiving power from the external power grid, and/or calculating S13b2 profit when delivering power to the external power grid. Then, the step of calculating S13 the energy content and power flow forecasts are based on the calculated profit when receiving power from the external power grid and/or profit when delivering power to the external power grid. According to one aspect, the step of calculating S13 the forecasts comprises calculating S13c available energy content in the energy storage, accessible to the local power grid and having a predefined lower energy content level, based on the current energy content and the predefined lower energy content level and estimating available power stored in the energy storage. Many types of energy storage have a lower energy content level below which it is unwise to discharge energy, unless introducing the risk to damage the energy storage. It should also be noted that the energy storage may be stationary energy storage, such as a large battery bank, fuel cells etc., or intermittently accessible energy storage, such as a PHEV, EV, fuel cell vehicles, etc., connected to the local power grid.

The value of the energy storage also includes the ability to deliver/receive power. This may be estimated based on the calculated available energy content in the energy storage from step S13c, or be estimated based on measured available energy content in the energy storage. For instance, it is possible to measure the amount of energy charge into and/or discharged from an energy storage realized with batteries using Coulomb counting.

Figure 7 illustrates a control unit 10 for controlling energy content and power flow in a local power grid 21, which is at least intermittently connected to an external power grid 22. The control unit 10 comprising processing circuitry, comprising one or multiple processor μΡ 11, configured to obtain information regarding a number of key parameters, to optimize energy content and power flow within the local power grid 21 based on the obtained information, and to apply the optimized energy content and power flow within the local power grid 21 during a predetermined time interval. The key parameters can be divided into two parts: local power grid information and external power grid information.

Local power grid information comprises power consumptions in controllable loads CL 12 and non-controllable loads NCL 13 influencing energy content and power flow in the local power grid 21 and current energy content in energy storage ES 14 accessible to the local power grid 21. External power grid information comprises market prices for energy related commodities and power related commodities 24 available in the external power grid 22 by different operators, such as Independent System Operator ISO, Regional Transmission Organization RTO, and Transmission System Operator TSO. A regional transmission organization RTO in the United States is an organization that is responsible for moving electricity over large interstate areas. Like the European transmission system operator TSO, an RTO coordinates, controls and monitors an electricity transmission grid. RTOs were created by the Federal Energy Regulatory Commission FERC in 1999.

An independent system operator ISO is an organization formed at the direction or recommendation of FERC. In the areas where an ISO is established, it coordinates, controls and monitors the operation of the electrical power system, usually within a single US State, but sometimes encompassing multiple states. RTOs typically perform the same functions as ISOs, but cover a larger geographic area.

The two are similar, with an RTO being more clearly defined and born out of the concept of electrical grid reliability. In short, an ISO operates a region's electricity grid, administers the region's wholesale electricity markets, and provides reliability planning for the region's bulk electricity system. Today's RTO's do the same thing with an added component of greater responsibility for the transmission network as established by FERC.

A transmission system operator TSO is an entity entrusted with transporting energy in the form of natural gas or electrical power on a national or regional level, using fixed infrastructure. The term is defined by the European Commission.

Due to the cost of establishing a transmission infrastructure, such as main power lines or gas main lines and associated connection points, a TSO is usually a natural monopoly, and as such is often subjected to regulations. In electrical power business, a TSO is an operator that transmits electrical power from generation plants over the electrical grid to regional or local electricity distribution operators.

The method described in connection with figure 5 and 6 may be implemented as a computer program comprising computer program code which, when executed, causes a control unit 10 as described in connection with figure 7 to execute the method. The control unit may be a standalone unit, integrated in other equipment or even realized completely, or partially, in a cloud implementation. According to some aspects, the processing circuitry 1 comprises multiple processors which are locally and/or remotely distributed, i.e. the processors may be implemented at a remote location (e.g.in a cloud environment) and/or be implemented locally.

According to one aspect, the control unit comprises a sensor 15 configured to detect accessibility to the external power grid 22, and the processing circuitry 11 is further configured to optimize energy content and power flow based on the accessibility to the external power grid 22. According to one aspect, the control unit further comprises a communication interface 16, or communication port, configured to obtain information regarding historic data, and wherein the processing circuitry 11 is further configured to optimize energy content and power flow based on the historic data information. According to one aspect, external power grid information is also accessible via the communication interface 16 and local power grid information is accessible via communication interface 19, I/O ports.

According to one aspect, the processing circuitry 11 of the control unit 10 is configured to process the obtained information and is further configured to optimize the energy content and power flow based on the processed obtained information. The obtained information as well as the result of the processing may be stored in a memory 18 for future use. The memory may be located anywhere, e.g. cloud based, locally or externally, provided the control unit has full access to the memory.

According to one aspect, the processing circuitry 11, when processing the obtained information, is further configured to perform one or more of the following tasks: calculate power consumption forecasts for each CL 12 and NCL 13; calculate price per power unit in the external power grid 22; calculate available energy content in the energy storage 14 and estimate available power in the energy storage 14.

The task to calculate power consumption forecasts for controllable loads 12 and non- controllable loads 13 is performed over at least the predetermined time interval. The task to calculate price per power unit in the external power grid 22 is based on the market price for power related commodities.

In order to be able to calculate available energy content in the energy storage 14, the energy storage has to be accessible to the local power grid 21. Furthermore, the energy storage has to have a predefined lower energy content level, below which discharge is not recommended. The task to calculate energy content in the energy storage is based on the current energy content and the predefined lower energy content level. The task to estimate available power in the energy storage 14 requires knowledge of available energy content in the energy storage as well as discharge and charge rate. However, the energy content can be obtained by continuously monitoring charge and discharge of the energy storage. According to one aspect, the processing circuitry 11, when calculating price per power unit in the external power grid 22 based on market price for power related commodities, is further configured to calculate profit when receiving power from the external power grid 22, and/or calculate profit when delivering power to the external power grid 22. Optimizing the energy content and power flow further is then based on the calculated profit when receiving power from the external power grid and/or profit when delivering power to the external power grid 22.

According to one aspect, the local power grid 21 comprises local energy production 17, and the control unit 10 is then further configured to obtain information regarding weather forecast to determine local energy production forecast. The processing circuitry is further configured to optimize the energy content and power flow based on the local production forecast.

According to one aspect, the processing circuitry 11, when optimizing energy content and power flow within the local power grid 21, is further configured to create a utilization plan for energy content and power flow, the utilization plan is regularly updated based on the obtained information. According to one aspect, the processing circuitry 11, when optimizing energy content and power flow within the local power grid 21, is further configured to create an operation plan based on the utilization plan, which is applied within the local power grid 21 during the predetermined time interval.

According to one aspect, the power related commodities, i.e. ancillary services, 24 comprises for example:

• Spin/Non-spin reserve, e.g. synthetic inertia

• Frequency regulation

• Strategic reserve

• Voltage support through active and reactive power control

• Black Start

• Transmission congestion relief

• Peak shaving

• Energy arbitrage

• Phase balancing

• Power control

Example related to controlling an EV charger to optimize the cost for the user

The solution described above can be used to minimize the cost for the energy and power use by steering/controlling the EV charger for a user (such as a customer or a local grid). The state of charge of one or more EVs are used as input (together with all other input such as PV production, storage status, Cost elements like tariffs and power price, consumption and other forecasts) when making a long term forecast (i.e. a utilization plan). Since the power consumption (load) can change at any time, e.g. by turning on the stove, starting a heat pump etc., the forecast is always going to deviate from the actual utilization, i.e. the forecast will always be inaccurate.

The short term plan (i.e. operation plan) is monitoring the deviations from the forecast and if necessary adjusts the utilization pattern for the EV (By controlling the EV charger). I this way the power drawn from the grid can be kept under a dynamically set value while simultaneously avoid high customer costs. This is illustrated in Figure 8a and 8b. Figure 8a illustrates power flow in a stationary battery arranged in a local grid plotted as a function of the total system power flow.

As illustrated, every time the operation plan preforms a check a new curve will be generated. The set points steering the battery input/output is obtained from the curve. In this example it can also be seen that behavior curve for the battery (battery power flow) changes every time the operation plan performs a check. Since the model may use several variables (tariffs, forecast, load, etc.) simultaneously when optimizing, the battery behavior as a function of system power flow can change when a new check is done. The new curve is the behavior of the battery that minimizes the cost while reaching the long term plan (utilization plan). The primary Time check is indicated by 80 (dotted line), the secondary check 1 is indicated by 81, the secondary check 2 is indicated by 82, the secondary check 3 is indicated by 83, the secondary check 4 is indicated by 84 and the secondary check 5 is indicated by 85.

Similarly in figure 8b the power flow through the EV charger is plotted as a function of the total system power flow. The additional constraint of when the EV needs to be charged is considered and a similar behavior as in figure 8a is detected. The operation plan minimizes the error in the utilization plan (forecast) by changing the power flow through the EV charger.

Figure 9 shows the forecasted power through the EV charger and the real time power. It can be clearly seen that the operation plan has gone in and changed the charging pattern to suit the overall system optimization. In this run the operation plan was updated every lOminutes. Example of system services illustrating the difference between utilization plan (estimated) and operation plan (continuously updated plan to execute)

The delivery of power from the battery storage is flexible according to the inventive concept. The flow of energy into the battery is adjusted based on the cost and availability from the main network. Here follows an example of when the model is used for peak shaving. This is to illustrate the difference between the forecasted utilization plan and continuously updated operation plan. A simple setup of a grid with tariffs, an industry consumer (load) and a battery is used together with the described controlling model. Based on measured and previously gathered data a 24h forecast of how to control the battery is created (the utilization plan). The forecast aims to minimize cost for the customer and thus takes into account the tariffs (electricity price €/kWh and power price€/kW). One of the parameters the model aims to minimize is the max power drawn from the grid over a predetermined time interval.

In this example the German grid code is used and the mean power drawn from grid during 15 minutes is kept under a dynamically set level. In Germany one is charged for the highest peak power of any 15 minute period throughout a year. In the model a dynamic setting of the average 15 minute power level is desired and this feature is given by a combination of the utilization plan and the operation plan.

The operation plan is monitoring the deviation from the utilization plan (forecast) and creates set points for the controller controlling the battery input/output power. Since the forecast will always be wrong (the load is stochastic), the operation plan will try to minimize the error. In this example the operation plan keeps the dynamic power price in mind and tries to minimize the average power bought from grid under a 15 minute period.

Figure 10 shows a 10 day run of the setup described. It can be seen that the load 100 (dotted line) is varying with high and low power peaks. The power bought from grid and the battery energy level is plotted as well, as indicated by 101 (dashed line). The dynamic feature can be seen by the 102 (solid line) showing the max power drawn from grid. The model keeps the highest mean power for 15 min mind and uses that as the dynamic level.

In this run it can be seen that the maximum average power drawn from grid steps up every time a higher average is detected. Furthermore it can be seen that the model compensates within every 15 min period to try and keep the mean power below the dynamic value. When a high peak power is bought from the grid the battery continuous to push down the power bought from grid and thereby lower the 15 min average. The battery energy level is indicated by 103 (solid line with rings). The dynamic power level enables the Utilization plan to better plan for longer power peaks. The operation plan is in this case updated every minute.

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. 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.

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.

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

1. A method, performed in a control unit, for controlling energy content and power flow in a local power grid at least intermittently connected to an external power grid, the method comprising: obtaining (Sll) information regarding:

• power consumptions in controllable loads and non-controllable loads influencing energy content and power flow in the local power grid,

• current energy content in energy storage accessible to the local power grid, and

• market prices for energy related commodities and power related commodities available in the external power grid, calculating (S13) energy content and power flow forecasts within the local power grid based on the obtained information, optimizing (S15) the energy content and power flow within the local power grid based on the forecasts, and applying (S16) the optimized energy content and power flow within the local power grid during a predetermined time interval, wherein, the step of calculating (S13) energy content and power flow forecasts comprises:

• calculating (S13a) power consumption forecasts for controllable loads and non- controllable loads over at least the predetermined time interval, and/or

• calculating (S13b) price per power unit in the external power grid based on the market price for power related commodities, and/or

« calculating (S13c) available energy content in the energy storage, accessible to the local power grid and having a predefined lower energy content level, based on the current energy content and the predefined lower energy content level, and estimating available power in the energy storage; and wherein the step of optimizing (S15) of the energy content and power flow within the local power grid further comprises: creating a utilization plan (515a) for the energy content and the power flow, wherein the utilization plan is regularly updated based on the obtained information and forecasts.

The method according to claim 1, wherein the step of optimizing the energy content and power flow within the local power grid is based on: back-up power and/or resilience to external power grid failures and/or time of use and/or demand response and/or demand charge reduction through peak shaving and phase balancing.

The method according to claim 1 or 2, further comprising detecting accessibility (S12) to the external power grid, and the step of optimizing (S15) the energy content and power flow is further based on the accessibility to the external power grid.

The method according to any of claims 1-3, wherein the method further comprises obtaining information regarding historic data (Slla), and the step of calculating (S13) the energy content and power flow forecasts is further based on the historic data information.

The method according to any of claims 1-4, wherein the step of calculating (513b) price per power unit in the external power grid based on market price for power related commodities further comprises:

• calculating (S13bl) profit when receiving power from the external power grid, and/or

• calculating (S13b2) profit when delivering power to the external power grid, wherein calculating (S13) the energy content and power flow forecasts further is based on the calculated profit when receiving power from the external power grid and/or profit when delivering power to the external power grid. The method according to any of claims 1-5, wherein the local power grid comprises local energy production, and wherein the method further comprises obtaining information regarding weather forecast to determine local energy production forecast (S14), and the step of calculating (S13) the energy content and power flow forecasts is further based on the local energy production forecast, and the step of optimizing the energy content and power flow within the local power grid further is based on consumption of local energy production.

The method according to any of claims 1-6, wherein the step of optimizing (S15) of the energy content and power flow within the local power grid further comprises:

• creating an operation plan (S15b) based on the utilization plan, which is applied within the local power grid during the predetermined time interval.

The method according to claim 7, wherein the local power grid comprises a controllable charger adapted to charge the energy storage accessible to the local power grid, wherein the method further comprises, when the local power grid is connected to the external power grid:

• monitoring deviations between the operation plan and the utilization plan, and

• dynamically controlling the charger to optimize the power flow from the external power grid.

The method according to any of claims 1-8, wherein the power related commodities comprises any of the group:

• Spin/Non-spin reserve,

• Frequency regulation

• Strategic reserve

• Voltage support through active and reactive power control

• Black start

• Transmission congestion relief

• Peak shaving

• Energy arbitrage

• Phase balancing • Power control

A control unit (10) for controlling energy content and power flow in a local power grid (21), at least intermittently connected to an external power grid (22), the control unit comprising processing circuitry (11) configured to: obtain information regarding:

• power consumptions in controllable loads (12) and non-controllable loads (13) influencing energy content and power flow in the local power grid (21),

• current energy content in energy storage (14) accessible to the local power grid (21), and

• market prices for energy related commodities and power related commodities (24) available in the external power grid (22), calculate energy content and power flow forecasts within the local power grid based on the obtained information, optimize energy content and power flow within the local power grid (21) based on the forecasts, and apply the optimized energy content and power flow within the local power grid (21) during a predetermined time interval, wherein the processing circuitry (11), when calculating energy content and power flow forecasts, further is configured to:

• calculate power consumption forecasts for controllable loads (12) and non- controllable loads (13) over at least the predetermined time interval, and/or

• calculate price per power unit in the external power grid (22) based on the market price power related commodities, and/or

• calculate available energy content in the energy storage (14), accessible to the local power grid (21) and having a predefined lower energy content level, based on the current energy content and the predefined lower energy content level, and estimate available power in the energy storage (14); and wherein the processing circuitry (11), when optimizing energy content and power flow within the local power grid (21), is further configured to: create a utilization plan for energy content and power flow, wherein the utilization plan is regularly updated based on the obtained information and forecasts. 11. The control unit according to claim 10, wherein the processing circuitry (11) comprises multiple processors which are locally and/or remotely distributed.

12. The control unit according to claim 10 or 11, wherein the processing circuitry (11) further is configured to optimize the energy content and power flow within the local power grid is based on: - back-up power and/or resilience to external power grid failures and/or time of use and/or demand response and/or demand charge reduction through peak shaving and phase balancing. 13. The control unit according to any of claims 10-12, further comprising a detector (15) configured to detect accessibility to the external power grid (22), and wherein the processing circuitry (11) is further configured to calculate energy content and power flow forecasts based on the accessibility to the external power grid (22).

14. The control unit according to any of claims 10-13, wherein the control unit further comprises a communication interface (16) configured to obtain information regarding historic data, and wherein the processing circuitry (11) is further configured to calculate energy content and power flow forecasts based on the historic data.

15. The control unit according to any of claims 10-14, wherein the processing circuitry (11), when calculating price per power unit in the external power grid (22) based on market price for power related commodities, further is configured to:

• calculate profit when receiving power from the external power grid (22), and/or • calculate profit when delivering power to the external power grid (22), wherein calculating the energy content and power flow forecasts further is based on the calculated profit when receiving power from the external power grid and/or profit when delivering power to the external power grid (22). 16. The control unit according to any of claims 10-15, wherein the local power grid (21) comprises local energy production (17), and wherein the control unit (10) is further configured to obtain information regarding weather forecast to determine local energy production forecast, and the processing circuitry is further configured to: calculate the energy content and power flow forecasts based on the local energy production forecast and optimize the energy content and power flow within the local power grid further is based on consumption of local energy production.

17. The control unit according to any of claims 10-16, wherein the processing circuitry (11), when optimizing energy content and power flow within the local power grid (21), is further configured to:

• create an operation plan based on the utilization plan, which is applied within the local power grid (21) during the predetermined time interval.

18. The control unit according to claim 17, wherein the local power grid comprises a controllable charger adapted to charge the energy storage accessible to the local power grid, further configured to, when the local power grid is connected to the external power grid:

• monitor deviations between the operation plan and the utilization plan, and

• dynamically control the charger to optimize the power flow from the external power grid. 19. The control unit according to any of claims 10-18, wherein the power related commodities (24) comprises any of the group:

• Spin/Non-spin reserve • Frequency Regulation

• Strategic reserve

• Voltage Support through active and reactive power control

• Black Start

· Transmission congestion relief

• Peak shaving

• Energy arbitrage

• Phase balancing

• Power control

20. A computer program comprising computer program code which, when executed, causes a control unit (10) according to any of claims 10-19 to execute the method according to any of claims 1-9.

21. A method, performed in a control unit, for controlling energy content and power flow in a local power grid at least intermittently connected to an external power grid, the method comprising: obtaining (Sllj information regarding:

• market prices for energy related commodities and power related commodities available in the external power grid, calculating (S13) energy content and power flow forecasts within the local power grid based on the obtained information, optimizing (S15) the energy content and power flow within the local power grid based on the forecasts, and applying (S16) the optimized energy content and power flow within the local power grid during a predetermined time interval, wherein, the step of optimizing (S15) of the energy content and power flow within the local power grid further comprises:

• creating a utilization plan (S15a) for the energy content and the power flow, wherein the utilization plan is regularly updated based on the obtained information and forecasts, and

• creating an operation plan (S15b) based on the utilization plan, which is applied within the local power grid during the predetermined time interval wherein the local power grid comprises a controllable charger adapted to charge the energy storage accessible to the local power grid, wherein the method further comprises, when the local power grid is connected to the external power grid:

The method according to claim 21, wherein the step of optimizing the energy content and power flow within the local power grid is based on: back-up power and/or resilience to external power grid failures and/or time of use and/or demand response and/or demand charge reduction through peak shaving and phase balancing.

The method according to claim 21 or 22, further comprising detecting accessibility (S12) to the external power grid, and the step of optimizing (S15) the energy content and power flow is further based on the accessibility to the external power grid.

The method according to any of claims 21-23, wherein the method further comprises obtaining information regarding historic data (Slla), and the step of calculating (S13) the energy content and power flow forecasts is further based on the historic data information. The method according to any of claims 21-24, wherein and the step of calculating (S13) energy content and power flow forecasts comprises:

• calculating (S13c) available energy content in the energy storage, accessible to the local power grid and having a predefined lower energy content level, based on the current energy content and the predefined lower energy content level, and estimating available power in the energy storage.

The method according to claim 25, wherein the step of calculating (S13b) price per power unit in the external power grid based on market price for power related commodities further comprises:

• calculating (S13b2) profit when delivering power to the external power grid, wherein calculating (S13) the energy content and power flow forecasts further is based on the calculated profit when receiving power from the external power grid and/or profit when delivering power to the external power grid.

The method according to any of claims 25-26, wherein the local power grid comprises local energy production, and wherein the method further comprises obtaining information regarding weather forecast to determine local energy production forecast (S14), and the step of calculating (S13) the energy content and power flow forecasts is further based on the local energy production forecast, and the step of optimizing the energy content and power flow within the local power grid further is based on consumption of local energy production.

The method according to any of claims 21-27, wherein the power related commodities comprises any of the group: • Spin/Non-spin reserve,

• Frequency regulation

• Strategic reserve

• Voltage support through active and reactive power control

• Black start

• Transmission congestion relief

• Peak shaving

• Energy arbitrage

• Phase balancing

• Power control

• market prices for energy related commodities and power related commodities (24) available in the external power grid (22), calculate energy content and power flow forecasts within the local power grid based on the obtained information, optimize energy content and power flow within the local power grid (21) based on the forecasts, and apply the optimized energy content and power flow within the local power grid (21) during a predetermined time interval, wherein the processing circuitry (11), when optimizing energy content and power flow within the local power grid (21), is further configured to: create a utilization plan for energy content and power flow, wherein the utilization plan is regularly updated based on the obtained information and forecasts, and create an operation plan (S15b) based on the utilization plan, which is applied within the local power grid during the predetermined time interval, wherein the local power grid comprises a controllable charger adapted to charge the energy storage accessible to the local power grid, wherein the processing circuitry (11), when the local power grid is connected to the external power grid, is further configured to:

• monitor deviations between the operation plan and the utilization plan, and

• dynamically control the charger to optimize the power flow from the external power grid.

The control unit according to claim 29, wherein the processing circuitry (11) comprises multiple processors which are locally and/or remotely distributed.

The control unit according to claim 29 or 30, wherein the processing circuitry (11) further is configured to optimize the energy content and power flow within the local power grid is based on: back-up power and/or resilience to external power grid failures and/or time of use and/or demand response and/or demand charge reduction through peak shaving and phase balancing.

The control unit according to any of claims 29-31, further comprising a detector (15) configured to detect accessibility to the external power grid (22), and wherein the processing circuitry (11) is further configured to calculate energy content and power flow forecasts based on the accessibility to the external power grid (22).

33. The control unit according to any of claims 29-32, wherein the control unit further comprises a communication interface (16) configured to obtain information regarding historic data, and wherein the processing circuitry (11) is further configured to calculate energy content and power flow forecasts based on the historic data. 34. The control unit according to any of claims 29-33, wherein the processing circuitry (11), when calculating energy content and power flow forecasts, further is configured to:

• calculate power consumption forecasts for controllable loads (12) and non-controllable loads (13) over at least the predetermined time interval, and/or

• calculate available energy content in the energy storage (14), accessible to the local power grid (21) and having a predefined lower energy content level, based on the current energy content and the predefined lower energy content level, and estimate available power in the energy storage (14). 35. The control unit according to claim 34, wherein the processing circuitry (11), when calculating price per power unit in the external power grid (22) based on market price for power related commodities, further is configured to:

• calculate profit when receiving power from the external power grid (22), and/or

• calculate profit when delivering power to the external power grid (22), wherein calculating the energy content and power flow forecasts further is based on the calculated profit when receiving power from the external power grid and/or profit when delivering power to the external power grid (22).

36. The control unit according to any of claims 34-35, wherein the local power grid (21) comprises local energy production (17), and wherein the control unit (10) is further configured to obtain information regarding weather forecast to determine local energy production forecast, and the processing circuitry is further configured to: calculate the energy content and power flow forecasts based on the local energy production forecast and optimize the energy content and power flow within the local power grid further is based on consumption of local energy production.

The control unit according to any of claims 29-36, wherein the power related commodities (24) comprises any of the group:

• Spin/Non-spin reserve

• Frequency Regulation

• Strategic reserve

• Voltage Support through active and reactive power control

• Black Start

• Transmission congestion relief

• Peak shaving

• Energy arbitrage

• Phase balancing

• Power control

A computer program comprising computer program code which, when executed, causes a control unit (10) according to any of claims 29-37 to execute the method according to any of claims 21-28.