• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:
    The present invention relates to a method of allocating electrical power from one or more energy sources to one or more energy sinks comprising acts of receiving electrical power from one or more energy sources to a distribution unit, distributing electrical power to one or more energy sinks from a distribution unit, and balancing the distributed electrical power to the received electrical power.
    公开号:DK201670958A1
    申请号:DKP201670958
    申请日:2016-12-05
    公开日:2018-06-14
    发明作者:Poul Anker Skaarup Lübker
    申请人:Udviklingsselskabet Gh As；
    IPC主号:
    专利说明:

    [Self-regulated distribution of power from energy sources]
    Field of the Invention
    The present invention relates to a method of allocating electrical power from one or more energy sources to one or more energy sinks comprising acts of receiving electrical power from one or more energy sources to a distribution unit, distributing electrical power to one or more energy sinks from a distribution unit, and balancing the distributed electrical power to the recei ved electrical power.
    Background of the Invention
    In countries like Denmark and Germany renewable energy sources now provide more than 30% of the power on an average basis. In some cases renewable energy sources based on solar and wind power supplied more than 100%· of peak power demand at specific times of the day. So far these countries have managed to integrate and balance these high shares of renewable energy with very modest changes to its public electricity network system. The major reasons are: The existing strength of its public electricity network system with a high security of power supply, and the flexible operation of coal and nuclear plants to dynamically increase power production to meet peak power demand or reduce power production when the power consumption is low. The modest changes to its public electricity network system include implementations of better system control software and day-ahead weather forecasting.
    In the future, a variety of additional measures will be required on public electricity network systems to improve handle energy storage, power demand response, smart inverters, two-way energy flow's, virtual power plants combining generation of power with flexible loads, integration of heat supply and heat storage, and other developments yet to be encountered on public electricity network systems.
    Energy storage has played almost no role in integrating and balancing renewable energy production so far. Innovations and changes specifically in this field will be necessary in the future to improve the ability to integrate and balance renewable energy production.
    Object of the Invention
    It is an objective of this invention to overcome one or more of the aforementioned shortcomings of the prior art.
    Description of the Invention
    An object of the invention may be achieved by a method of allocating electrical power from one or more energy sources to one or more energy sinks comprising acts of receiving electrical power from one or more energy sources to a distribution unit, distributing electrical power to one or more energy sinks from a distribution unit, and balancing the distributed electrical power to the received electrical power. A method where the distribution unit may be connected to the one or more energy sources and the one or more energy sinks, where the distribution unit may be configured with controlling means to control the acts of receiving and distributing electrical power, and where the distribution unit may be configured to execute the act of balancing according to one or more algorithms (A1.JM) executable in the distribution unit.
    The one or more algorithms for balancing electrical power, Al_Bal may each include several algorithms working dependent on each other or comprise a cluster of algorithms.
    The controlling means to control the acts of receiving and distributing electrical power may operate as a switch, a regulator or to divert the electrical power. The controller means may also operate by adjusting the individual energy sinks to regulate the power output.
    The energy sources may include renewable energy sources such as wind turbines, solar panel, systems for thermal energy and systems for wave energy amongst others.
    An effect of this method is that fluctuations in produced and demanded energy are levelled out or balanced thereby achieving reduced energy loss due to surplus production of energy.
    An effect of this method is that a local network electrical power centre may be established where the local energy production may be adjusted to the local electrical power demand thus avoiding surplus energy production, The energy production may be regulated by adjusting the output from local conventional energy sources with the advantage of minimizing the use of fossil fuels.
    The energy production may further be regulated by receiving electrical power from renewable energy sources located at a distance which necessitates using the public electricity power system to transport this electricity power with the advantage of minimizing the use of fossil fuels.
    The energy production may further be regulated by adjusting the output from local renewable energy sources with the advantage of minimizing the tear and wear of these. This could be the case for wind turbines, where these may be adjusted to a lower output than maximum to balance the received power of the distributing centre to the demanded electrical power and thereby reduce the load on the wind turbines. For solar panels a similar situation may be the case, where the solar irradiation input is reduced by regulating the inflow angle of solar radiation for the benefit of reducing the heat induced in the panels. Thus, environmental benefits due to reduced use of fossil fuels may be achieved and increased life span of the equipment for renewable energy may be achieved.
    An object of the invention may be achieved by a method of allocating electrical power comprising the further acts of collecting and storing one or more data sets comprising actual electrical power production of each energy source, and providing executing means configured for executing one or more algorithms, which algorithm(s) (Al_Rec) regulates the level of received electricity power trom each energy source to the distribution unit.
    In general, when referring to one or more algorithms in the described method the algorithm may each include several algorithms working dependent on each other or the multiple algorithms may comprise a cluster of algorithms which may be referred to by a single reference, for example: Al-Bal, Al_R.ee, algorithm for electrical power output to mention a few.
    An object of the invention may be achieved by a method of allocating electrical power comprising the further acts of collecting and storing one or more data sets comprising actual electrical power demand for each energy sink, and providing one or more controllers configured for executing one or more algorithms, which algorithm(s) (Al__Dist) regulates the level of distributed electricity power to each energy sink from the distribution unit.
    One effect of the above mentioned methods are in line with the previous mentioned effect of regulating the output from local conventional energy sources and local renewable energy sources with the advantage of minimizing the use of fossil fuels and minimizing the tear and wear of these. One effect may also be to regulate the demand for electrical power of one or more individual energy sinks to a later timer, where the general demand are lower or where the energy output from renewable energy sources are high without exploiting the energy sources to a maximum output. And thus as previously mentioned achieving environmental benefits due to reduced use of fossil fuels may be achieved and increased life span of the equipment for renewable energy.
    An object of the invention may be achieved by a method of allocating electrical power comprising the further act of storing electrical power for balancing the distributed electrical power to the received electrical power from the one or more energy sources wherein the distributed electrical power comprises an actual electrical power demand.
    One effect of this embodiment is that the fluctuations in received energy and distributed energy may be more easily accommodated without causing rapid changes in the energy production or energy demand. An advantage of this may be that a sudden increase in energy demand may be met without using fossil fuel, A sudden increase in energy demand in energy supply systems are often met by increasing the conventional energy production as this is often the fastest way of regulating energy production. In this method, due to energy storage facilities, the regulation may be achieved by a slower increase and thus over a longer time period and thus, the increase may be achieved by regulating the power output from the renewable energy sources. A further object of the invention may be achieved by a method of allocating electrical power wherein the act of receiving electrical power from one or more energy sources to the distribution unit comprise the further acts of collecting and storing data sets comprising time stamped data sets of received electrical power from each energy source, and synchronizing and processing the said time stamped data sets of received electrical power with time stamped data sets of predicted electrical power output from each energy source. A method wherein the act of receiving electrical power from the one or more energy sources to the distribution unit may be controlled by an algorithm (Al_Rec).
    Yet a further object of the invention may be achieved by a method of allocating electrical power wherein the act of distributing electrical power from the distribution unit to one or more energy sinks comprise the further acts of collecting and storing data sets comprising time stamped data sets of distributed electrical power to each, energy sink, and synchronizing and processing the said time stamped data sets of predicted electrical power demand trom each power sink. A method wherein the act of distributing electrical power from the distribution centre to the one or more energy sinks may be controlled by an algorithm (Al_Dist).
    For this invention by synchronizing is meant that the data is time synchronized based on a time stamp on the individual data. This means that the data may be extrapolated in time to achieve synchronization.
    Thus, one effect of time stamping the data is that synchronization of the data may be performed. Synchronisation ensures synchronized data prior to processing and thus advantageously allow' for implementation of calibration of parameters.
    An object of the invention may be achieved by a method of allocating electrical power wherein the act of collecting data synchronized is performed using at least one synchronization system, and wherein the synchronization system transmits a trigger signal activating synchronized measurement of data from one or more sensors.
    The effect of this embodiment is that the data is synchronization due to that data are measured in parallel on a trigger signal and thus is synchronized in real time. In this case the data may still be time stamped for further use in case of synchronization of other measurements not performed in parallel.
    Thus, one effect of time stamping the data is that synchronization of the data may be performed. Synchronisation ensures synchronized data prior to processing and thus advantageously allow for implementation of calibration of parameters.
    An object of the invention may be achieved by a method of allocating electrical power comprising the further act of calibrating at least one algorithm from the one or more time stamped and synchronized data sets.
    The calibrating process may involve an automatic self-calibrating process. The calibrating process may have the effect of improving the accuracy of the algorithm based on measured data. Calibration of one or more algorithms based on local measurements may be advantageous in regard to achieving an adjusted and optimised algorithm for the individual allocating system with all the energy sinks, sources and storage facilities which may be different for each individual system. Furthermore, the individual energy sources and sinks may perform differently under the same meteorology conditions if placed in different terrains.
    An object of the invention may be achieved by a method of allocating electrical power comprising the further acts of collecting and storing actual meteorology data, collecting and storing weather forecast data, and collecting and storing predicted meteorology data, wherein the actual meteorology data and the predicted meteorology data are time stamped and synchronized.
    One effect of this embodiment is that that meteorology data may be used to predict electrical power output from the renewable energy sources and to predict electrical power demand, as the demand may be dependent on environmental conditions such as temperature, wind speed or others. For example in the case of power demand for heating is dependent on the ambient temperature. Thus this is advantageous in regard to predicting the amount of received electrical power and the demand for electrical energy. Furthermore, it may be advantageous in regard to manage the energy storage facilities.
    An object of the invention may be achieved by a method of allocating electrical power energy sinks are performed by frequency power sampling in the time scale of milliseconds to seconds.
    The frequency power sampling may also be performed as high frequency power sampling. A fast sampling rate and real-time data recording of current, voltage, frequency, power, power factor, phase angle, grid harmonics and/or the like enables use for operational measurement as well as for condition monitoring of the overall electrical power applications.
    The measuring intervals on several devices have to be time synchronized in order to evaluate the collected energy data consistently. This also simplifies and speeds up the engineering, enabling comprehensive diagnostics and fault analysis.
    An object of the invention may be achieved by a method of allocating electrical power wherein the one or more algorithms perform an act of calibrating by comparing actual meteorology data to predicted meteorology data, wherein the predicted meteorology data is extrapolated and estimated from short-term and/or long-term local weather forecast, by comparing actual electrical power production to predicted electrical power production, by comparing actual electrical power demand to predicted electrical power demand, and/or by comparing actual electrical power storage capacity to predicted electrical power storage capacity. A method wherein the predicted data may be extrapolated and estimated from predicted meteorology data, and databases of collected and stored data.
    An object of the invention may be achieved by a method of allocating electrical power wherein the one or more algorithms (Al._Bal) for balancing the distributed electrical power to the received electrical power evaluates the state of operation of the individual energy sources, energy sinks and/or meteorology sensors.
    An object of the invention may be achieved by a method of allocating electrical power wherein machine learning is used for calibrating the one or more algorithms.
    Machine learning centres on the de velopment and use of algorithms that can learn to make predictions based on past data. The recent advances in machine learning lets people take very large data sets and analyse them using large-scale computing systems or neural networks.
    Thus, using machine learning may govern for a continuous and rapid calibration of the algorithms wherein the amount of historical data to be handle and used for calibrating the individual algorithms may be enormous. Furthermore, using machine learning may enable calibration of inter-dependent algorithms in a manageable way, which is basically impossible in practice without employing machine learning.
    The calibration of the algorithm(s) may be based on historical data of weather, electrical power production from individual energy sources, electrical power demand of the individual energy sink(s) and capacity of any storage facilities and may take into account a weather forecast for prediction of basically the same parameters but present and future values of the electrical power production, electrical power demand and capacity of any storage facilities A person skilled in the field of artificial intelligence and machine learning will know how to apply and implement machine learning in a beneficial way. A skilled person in the art may be inspired from the approach and implementation presented by Microsoft using machine learning for predicting weather patterns in the coming 24 hours.
    Unlike more typical weather forecasting approaches, which have traditionally relied on physical simulations, Microsoft’s research took a data-centric approach: They just looked at the data and didn’t try to make restrictive assumptions about how nature tends to act. The researchers used historical data for several w'eather variables — atmospheric pressure, temperature, dew point and vrinds — to train their systems to make predictions about future weather patterns based on past data.
    This invention may be using smart-grid technologies, new monitoring and data acquisition systems and better systems for day-ahead and/or week-ahead weather forecasting to forecast output from local renewables and local demand to self-regulate the distribution of electrical power from different energy sources on a local electricity network system. This local electricity network system will automatically perform balancing and peak-shaving by storing excess power and distributing it as needed by managing the electrical power supply to short term energy storage technology systems like for example local combined-heat-and-power plants and their heat storage facilities and to long term energy storage technology systems like for example production of hydrogen facilities.
    Example of a method (which including renewables) for predicting and balancing incoming and outgoing electricity, and a method (which includes renewables) using energy storage for balancing predicted supply and predicted demand for short- and long term fluctuations. The method described herein may encompass a system which includes renewable energy sources.
    The input to the method may encompass manual data from operators and measured data. The data may be time stamped and synchronize. The data may be stored in a number of databases.
    The method of allocating electrical power may provide a regulated electrical power output which is based on predicting and balancing electrical power output from energy sources and storage facilities, wherein the electrical power output from renewables may be predicted in consideration of short- and long term fluctuations. The regulated electrical power output may further be regulated in consideration of short- and long term fluctuations in predicted electrical power demand of the consumers.
    The allocating of electrical power may require multiple algorithms for performing the relevant analysis on actual and predicted data. The algorithms may be multidimensional self-learning and self-calibrating algorithms.
    The example is illustrated schematically, wherein the main algorithm is the algorithm for balancing electrical power in the system, Al„Bal. Al__Bal communicates with the algorithms Al_Rec, the algorithm for controlling the receiving of electricity power and Al_Dist, the algorithm for controlling the actual distribution of all available electrical power, Al Bal further receives and transmit data regarding meteorology data and data from all clients collected in a database: Database for all clients. Here clients are energy sources, energy sinks and energy storage facilities.
    Database for all clients: Database for all clients delivering and receiving electricity directly to/from the distribution centre and for all clients connected to a heating pump. The database may comprise information on priority code of the client, agreed prices, minimum and maximum sale/purchase, special expectations to variations, and other rele vant informa lion.
    Al_R.ec: This algorithm communicates yet with another algorithm Algorithm for electrical power output and receives data regarding predicted electrical power demand from internal conventional energy source and predicted electrical power demand from public electricity network.
    The predicted electrical power demand from internal conventional energy source and from public electricity network may be long-term and/or short-term forecasts.
    Algorithm for electrical power output: Self-calibrating algorithm checking actual electrical power output and predicting electrical power output from renewable energy sources on a short-range time scale and on a long-range time scale,
    The short-range time scale may be measured in hours.
    The long-range time scale may be measured in days.
    The long-range time scale may define the planning period.
    The predicted and actual measured data is constantly evaluated using an alarm and a level indicator. The level indicator (L) and alarm (A) is used for calibrating the algorithm^). The level indicator rates the level by which the predicted and measured data agree and the impact of the data in the calibration algorithm. The alarm indicator is used when the predicted and measured data is inconsistent which extends beyond a given threshold value.
    Algorithm, predicting renewable energy source output may predict the output from each renewable source in the planning period.
    Database “Actual meteorology” may comprise time-stamped and synchronized data from a meteorology station.
    Database “produced electrical power” may comprise high frequency power measurements from each renewable source.
    High frequency power measurements may include current, voltage and power output characteristics.
    The short-range weather forecast may be a weather forecast on a short-range time scale. The long-range weather forecast may be a weather forecast on a long-range time scale. The weather forecasts may be updated on an hourly basis.
    Database: Price (Intern produced) - with price in planning period for electricity produced on actual internal conventional energy source.
    In the above the work expectations are abbreviated to exp.
    Algorithm constantly updating expected need for electricity to internal clients for direct use in their operation - (in this example large consumers / large companies) -based on data bases with time stamped and time synchronized data and manual input related to special expectations / variations from normal and specific requirements
    Algorithm for balancing a renewable energy storage system (in this case a hot water storage system) - Algorithm constantly updating expected electricity need distributed to (in this case) to a large heat pump system producing hot water to INTERNAL, storage system in the planning period - based on algorithms and analysis of data in data bases with time stamped and time synchronized data and manual input related to expectations / requirements from operators.
    Description of the Drawings
    Figure 1 illustrates an electrical power allocation system.
    Figure 2 illustrates a method for balancing received and distributed electrical power in a connected system.
    Figure 3 show's a top-level hardware and implementation view7 of one embedded computer system.
    Figure 4 illustrates an embodiment of a system for performing the method of allocating electrical energy.
    Figure 5 illustrates an embodiment of the method of allocating electrical energy.
    In figure 6 is illustrated an embodiment of electrical power measurements on energy sources and energy sinks by frequency sampling.
    Figure 7 illustrates an embodiment in which the electrical power is allocated to drive pumps to drive a water heating system.
    Figure 8 illustrates another embodiment in which the electrical power is allocated to drive pumps to drive a water heating system and a cooling water system.
    Figure 9 i llustrates an embodiment in which the electrical power is allocated to drive a cooker system.
    Figure 10 illustrates a cooling water buffer system and storage tanks.
    Figure 11 illustrates an embodiment of a meteorology station.
    Figure 12 illustrates another embodiment of a system for performing the method of allocating electrical energy.
    Figure 13 illustrates the legends used in figure 12.
    Detailed Description of the Invention
    Figure l illustrates a system 100 in which one or more energy sources 20 are connected 110 to a distribution unit 10, The energy sources 20 may consist of conventional energy sources and/or renewable energy sources, The system may also be connected to a public electricity network 50 (not illustrated) which in that case may comprise one energy source 20. The distribution unit 10 is then further connected 110 to one or more energy sinks 30. The energy sinks 30 may be internal consumers, external consumers. Again, in the case of energy sinks 30 the system 100 may be connected to a public electricity network 50 (not illustrated) which in that case may comprise one energy sink 30. The distribution centre 10 allocates electrical power 40 from the energy source(s) 20 to the energy sink(s) 30. Where the electrical power 40 from the energy source(s) 20 are received electrical power 42, and the electrical power 40 to the energy sink(s) 30 are distributed electrical power 44.
    The renewable energy source(s) may comprise wind turbines, solar cells, thermal solar panels, units for harvesting wave energy or thermal energy from the underground, any other existing or future renewable energy source, or a combination of these. The energy produced by the energy source(s) 30 are converted to electrical power 40 before reaching the distribution centre which then distributes the received electrical power 42 to the one or more energy sinks 30. In case of thermal energy this is used through heat exchange systems driven by the electrical power allocated by the distribution centre. Thus, the harvested thermal energy is not converted to electrical power and back and thus, energy losses of such conversion are avoided.
    The system may also comprise energy storage facilities. The storage facilities may act as both an energy source 20 and energy sink 30.
    Figure 2 illustrates an embodiment of the method 400 of allocating 410 electrical power 40 from one or more energy sources 20 to one or more energy sinks 30. The distribution center receives 412 electrical power from one or more energy sources 20 and then allocates 410 the received electrical power by distributing 414 the electrical power to the energy sink(s) 30 which has an actual demand for electrical power 40. The allocating 410 of electrical energy may be balanced 440 using one or more algorithms 450 executable in the distribution unit 10. The algorithm(s) (Al_Bal 452) for balancing the allocated electrical power may be further dependent on other algorithms which regulates the level of received electrical power 42 (Al_Rec 454) from each energy source 20 to the distribution unit (10) and regulates the level of distributed electrical power 42 (Al_Dist 456) from the distribution unit 10 to each energy sink 30.
    Figure 3 shows one embodiment of a hardware implementation of one embedded computer system 310 used for condition monitoring. On the left side is shown the interfaces relating to input 350 from sensors 320 and databases 330.
    In this embodiment a range of sensors 320 measuring meteorology data are illustrated comprising wind speed sensors, temperature sensors, rain sensors, humidity sensors, air pressure sensors, wind direction sensors, UV sensors, solar irradiation sensors.
    Furthermore, sensors measuring electrical power are illustrated along with sensors measuring on liquid parameters, which may comprise flow, temperature, density or other relevant parameters. These sensors may measure on energy sinks, sources and storage facilities to monitor the produced, consumed and stored energy.
    All data collected by these sensors or a selected number of the sensors may be time stamped (430) and synchronized (432). Alternatively the data collected from the sensors may be time stamped (430) and subsequently synchronized (432).
    Additionally, optional input is illustrated which may consist of additional relevant condition monitoring and measurement instruments which can be added to extend the invention to support an improved condition monitoring. This may include fault detection and instant alarm system for other key components in the electrical power allocation system.
    Furthermore, the input 350 to the embedded computer system 310 may comprise data sets 200 from various databases 330. These databases 330 may comprise meteorology data sets, data sets on electrical power from energy sources, sinks and storage facility. The data sets may both be predicted values and actual measured values.
    The embedded computer system 310 in figure 3 may comprise at least one processor for processing said input. There is at least one storage means for the storing of collect- ed measured and calculated values etc. to be used in the algorithms comprised in the method.
    The output interfaces 340 are also illustrated in figure 3. These may comprise at least one power backup with sufficient capacity to safely shut down all software in the embedded computer system 310 and attached systems in case of sudden loss of permanent power supply, at least one power supply to the embedded computer system 310 and attached systems, at least one terminal interface and one USB interface option, and at least one communication interface providing option to transfer larger data amounts - could be WAN interface, GPRS / 3G / 4G / 5G interface, or any other communication interface that may become relevant in the future to be able to transfer larger data amounts.
    Thus the output from the embedded computer system controls the distribution of the available electrical power based on the received input.
    Figure 4 illustrates an embodiment of a system 100 for performing the method 400 of allocating electrical energy 40. In this embodiment wind turbines 22 acts as energy sources 20 and a hardware setup, acting as the distribution centre 10 receives the electrical power from the wind turbines and distributes electrical power 42 to large consumers 70 and energy storage facilities 60. The distribution centre 10 either receives or distributes electrical power to the public electricity network 50 depending on if there is a surplus or deficit of received electrical power compared to the distributed electrical power. Thus a balancing of received and distributed electrical powder 40 is performed.
    Figure 5 illustrates an embodiment of the method 400 of allocating electrical energy 40. In this embodiment is illustrated how software, algorithms and artificial intelligence are used to balance the received and distributed electrical power in a balancing algorithm. The balancing algorithm recei ves data input of actual and predicted electrical power production and demand, where the predicted data is based on weather forecasts and historical data on electrical power demand and production. Figure 5 further more illustrates how the hardware and software in the distribution unit are arranged such that the allocating of electrical power may be performed in a balanced way.
    In figure 6 is illustrated an embodiment of collecting data on energy 20 sources and energy sinks 30 by high frequency sampling on the connections transferring electrical energy to and from the distribution centre 10. The data may be collected synchronized by collecting data from all connections on a trigger signal transmitted from the distribution centre 10. By high frequency sampling it is possible to retrieve a broad range of data of the individual energy sources 20 and/or energy sinks 30.
    Figure 7 illustrates an embodiment in which the electrical power is allocated to drive pumps to drive a water heating system wherein heat from warm seawater is extracted to district heating or other methods of distributing heated water to consumers. In this embodiment, high frequency sampling is used for measuring on the pumps and retrieve data on their performance.
    In figure 8 another embodiment is illustrated wherein the electrical power also is allocated to drive pumps to drive a water heating system. The embodiment in figure 8 is an extended version of the embodiment illustrated in figure 7. In this embodiment an additional cooling exchanger is added to provide cooling w'ater to consumers.
    Figure 9 illustrates an embodiment in which the electrical power is allocated to drive a cooker system for heating water to distributed heating water for consumers. In this embodiment high frequency sampling is used for measuring on the cooker system and retrieve data on the performance of the electrical components.
    In figure 10 a buffer system and storage tanks comprising cold water is illustrated. Figure 9 and figure 10 both illustrates water storage systems which may be connected to the distribution centre 10 through electrical components working as energy sinks of electrical power but storage facilities of thermal or mechanical energy. Furthermore, the water storage systems may be connected to the distribution centre 10 through sensors. The sensors may be temperature sensors, flow sensors, level sensors or the like, which may provide the method 100 with data regarding the state of the storage facilities.
    In figure 11 an embodiment of a meteorology station (90) is illustrated. The meteorology station may be localized on the premises or on the close vicinity of the system 100 thereby providing the method 400 with accurate data of the actual meteorology state where the renewable energy source(s) 20 and the energy sink(s) 30 are positioned.
    Figure 12 illustrates an embodiment of a system 100 for performing the method 400 of allocating electrical energy 40. The arrows in the figure illustrate how the energy is allocated from the energy sources to energy sinks. The types of energy sinks, energy-sources and storage facilities illustrate in figure 12 are illustrated and explained in figure 13.
    Figure 13 contains the legends of figure 12 A: Renewable energy source 22, wind turbine B: Meteorology station, 90 C: Energy sink 30, pump based on sea water D: Energy storage facility 60, storage tank for hot water E: Energy storage facility 60, storage tank for cold water F: Energy storage facility 60, hydrogen production plant G: Energy storage facility 60, hydrogen filling station H: Energy sink 30, electrically powered ferry I: Public electricity network 50 J: Large consumer 70, heating plant K: Energy sink 30, city 1..: Distribution unit 10 M: Energy sink 30, hydrogen powered car
    N: Energy sink 30, industrial plant A
    O: Energy sink 30 industrial plant B P: Renewable energy source 22, solar panels.
    权利要求:
    Claims (13)
    [1] 1. A method (400) of allocating (410) electrical power (40) from one or more energy sources (20) to one or more energy sinks (30) comprising acts of - receiving (412) electrical power (40) from one or more energy sources (20) to a distribution unit (10); - distributing (414) electrical powder (40) to one or more energy sinks (20) from a distribution unit (10); and balancing (416) the distributed electrical power (44) to the received electrical power (42), and where the distribution unit (10) is connected (110) to the one or more energy sources (20) and the one or more energy sinks (30); configured (112) with controlling means (120) to control the acts of receiving (420) and distributing (414) electrical power; and configured (112) to execute (418) the act of balancing (416) according to one or more algorithms (Al_bal) executable in the distribution unit (10).
    [2] 2. The method (400) according to claim 1 comprising the further acts of Collecting (420) and storing (422) one or more data sets (200) comprising actual electrical power production (210) of each energy source (20); and Providing (424) executing means (122) configured for executing (418) one or more algorithms (Al_rec) which algorithm(s) (Aljrec) regulates the level of received electricity power (42) from each energy source (20) to the distribution unit (10).
    [3] 3. The method (400) according to claim 1 or 2 comprising the further acts of - Collecting (420) and storing (422) one or more data sets (200) comprising actual electrical power demand (220) for each energy sink (30): and Providing (424) one or more control lers (124) configured for executing one or more algorithms (Al__dist), which algorithm(s) (Al__dist) regulates the level of distributed electricity power (44) to each energy sink (30) from the distribution unit (10).
    [4] 4. The method (400) according to any one or more of claim i to 3 comprising a further act of storing (422) electrical power (40) for balancing (416) the distributed electrical power (44) to the received electrical power (42) from the one or more energy sources (20) wherein the distributed electrical power (44) comprises an actual electrical power demand (220),
    [5] 5. The method (400) according to any one or more of claim 1 to 4 wherein the act of receiving (412) electrical power (40) from one or more energy sources (20) to the distribution unit (10) comprise the further acts of: Collecting (420) and storing (422) data sets (200) comprising time stamped data sets (130) of received electrical power (42) from each energy source (20); and Synchronizing (432) and processing (434) the said time stamped data sets (130) of recei ved electrical power (42) with time stamped data sets (130) of predicted electrical power output (212) from each energy source (20), and wherein the act of receiving (412) electrical power (40) from the one or more energy sources (20) to the distribution unit (10) is controlled by an algorithm (Al_Rec).
    [6] 6, The method (400) according to any one or more of claim 1 to 5 wherein the act of distributing (414) electrical power (40) from the distribution unit (10) to one or more energy sinks (30) comprise the further acts of: - Collecting (420) and storing (422) data sets(200) comprising time stamped data sets (130) of distributed electrical power (44) to each energy sink (30); and Synchronizing (432) and processing (434) the said time stamped data sets (130) of predicted electrical power demand (222) from each, power sink (30), and wherein the act of distributing (414) electrical power (40) from the distribution centre (10) to the one or more energy sinks (30) is controlled by an algorithm (Al_Dist).
    [7] 7, The method (400) according to any one or more of claim 1 to 6 wherein the act of collecting data synchronized is performed using at least one synchronization system (360) wherein said synchronization system (360) transmits a trigger signal activating synchronized measurement of data from one or more sensors.
    [8] 8. The method (400) according to any one or more of claim 1 to 7 comprising the fur ther act of calibrating at least one algorithm from the one or more time stamped (130) and synchronized (140) data sets (200).
    [9] 9. The method (400) according to any one or more of claim 1 to 8 comprising the further acts of - collecting (420) and storing (422) actual meteorology data (240); - collecting (420) and storing (422) weather forecast data (244), and - collecting (420) and storing (422) predicted meteorology data (242), wherein the actual meteorology data (240) and the predicted meteorology data (242) are time stamped (130) and synchronized(140).
    [10] 10. The method (400) according to any one or more of claim 1 to 9 wherein electrical power measurements on one, more or all energy sources (20) and/or energy sinks (30) are performed by frequency power sampling in the time scale of milliseconds to seconds.
    [11] 11.1’he method (400) according to any one or more of claim 1 to 10 wherein the one or more algorithms perform an act of calibrating by comparing - actual meteorology data (240) to predicted meteorology data (242), wherein the predicted meteorology data (242) is extrapolated and estimated from shortterm and/or long-term local weather forecast (242A,242B), - actual electrical power production (210) to predicted electrical power production (212), - actual electrical power demand (220) to predicted electrical power demand (222), and/or - actual electrical power storage capacity (230) to predicted electrical power storage capacity (232), wherein the predicted data are extrapolated and estimated from predicted meteorology data (242), and databases of collected and stored data.
    [12] 12. The method (400) according to any one or more of claim 1 to 11 wherein the one or more algorithms (Al_bal) for balancing (416) the distributed electrical power (44) to the received electrical power (42) evaluates the state of operation of the individual energy sources (20), energy sinks (30) and/or meteorology sensors.
    [13] 13. The method (400) according to any one or more of claim 1 to 12 wherein machine learning is used for calibrating the one or more algorithms.
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    DK179419B9|2018-08-15|
    DK179419B1|2018-06-18|
    引用文献:
    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    US20050165511A1|2004-01-23|2005-07-28|Matthew Fairlie|Energy network|
    US20130043725A1|2009-07-31|2013-02-21|Mogen Birkelund|Method and Apparatus for Managing Transmission of Power in a Power Transmission Network|
    US20110082598A1|2009-10-02|2011-04-07|Tod Boretto|Electrical Power Time Shifting|
    WO2012078433A2|2010-12-06|2012-06-14|Sandia Corporation|Computing architecture for autonomous microgrids|
    EP3002848A1|2014-09-30|2016-04-06|Schneider Electric USA, Inc.|Demand-side grid-level load balancing aggregation system|
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    申请号 | 申请日 | 专利标题
    DKPA201670958A|DK179419B9|2016-12-05|2016-12-05|Self-regulated distribution of power from energy sources|DKPA201670958A| DK179419B9|2016-12-05|2016-12-05|Self-regulated distribution of power from energy sources|
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