EP4470085A1 - Procédé pour faire fonctionner une source d'énergie - Google Patents

Procédé pour faire fonctionner une source d'énergie

Info

Publication number
EP4470085A1
EP4470085A1 EP23705200.6A EP23705200A EP4470085A1 EP 4470085 A1 EP4470085 A1 EP 4470085A1 EP 23705200 A EP23705200 A EP 23705200A EP 4470085 A1 EP4470085 A1 EP 4470085A1
Authority
EP
European Patent Office
Prior art keywords
energy source
energy
temperature
battery
data sets
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP23705200.6A
Other languages
German (de)
English (en)
Inventor
Christoph SAGEWKA
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Viessmann Holding International GmbH
Original Assignee
Viessmann Climate Solutions SE
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Viessmann Climate Solutions SE filed Critical Viessmann Climate Solutions SE
Publication of EP4470085A1 publication Critical patent/EP4470085A1/fr
Pending legal-status Critical Current

Links

Classifications

    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or discharging batteries or for supplying loads from batteries
    • H02J7/80—Circuit arrangements for charging or discharging batteries or for supplying loads from batteries including monitoring or indicating arrangements
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for AC mains or AC distribution networks
    • H02J3/28—Arrangements for balancing of the load in networks by storage of energy
    • H02J3/32—Arrangements for balancing of the load in networks by storage of energy using batteries or super capacitors with converting means
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or discharging batteries or for supplying loads from batteries
    • H02J7/90—Regulation of charging or discharging current or voltage
    • H02J7/971—Regulation of charging or discharging current or voltage the charge cycle being controlled or terminated in response to non-electric parameters
    • H02J7/975—Regulation of charging or discharging current or voltage the charge cycle being controlled or terminated in response to non-electric parameters in response to temperature
    • H02J7/977—Regulation of charging or discharging current or voltage the charge cycle being controlled or terminated in response to non-electric parameters in response to temperature of the battery

Definitions

  • the present invention relates to a method for operating an energy source at an installation site in a building, the energy source being intended to supply the building with energy.
  • a thermal model is to be created that describes a thermal interaction between the energy source and the installation site in the building.
  • the situation is similar for buildings (e.g. residential or commercial buildings) with decentralized energy sources, such as a fuel cell, a photovoltaic system (PV system) or other energy sources that supply electricity, for example.
  • decentralized energy sources such as a fuel cell, a photovoltaic system (PV system) or other energy sources that supply electricity, for example.
  • PV system photovoltaic system
  • battery storage devices are generally used, which store energy when there is an oversupply of locally generated electricity and release it again when required by local consumers.
  • a memory that can be used to feed electrical energy into a power grid and remove it from it is disclosed, for example, in DE 10 2010 001 874 Al.
  • the memory described therein includes a controller that controls the delivery to the power grid and the absorption of energy from the power grid. With such a storage system, energy can be absorbed in times of oversupply and released again in times of increased demand. Accordingly, the memory can also be used, for example, to smooth out voltage peaks or valleys.
  • Such a battery store for a building is an example of an energy source within the meaning of the present invention.
  • it is important to know or predict an internal temperature or operating temperature, since a deviation of the operating temperature from an optimal temperature range can lead to a reduction in the power of the energy source.
  • the environmental conditions of the energy source are usually not sufficiently known, it is difficult to make predictions about the operating temperature of the energy source.
  • the present invention is based on the object of specifying an improved method for operating an energy source at an installation site that solves the problems mentioned above. According to a first aspect of the invention, the object is achieved by a method according to claim 1. Further aspects of the invention emerge from the dependent claims, the figures and the following description of exemplary embodiments.
  • An energy source within the meaning of the invention is an energy-related end device or a device that provides energy to a building, for example in the form of electrical energy and/or heat and/or cold.
  • the energy source can be a battery store for a building, which stores electrical energy and can deliver this to a power grid in the building to supply consumers.
  • An energy source within the meaning of the invention can also be a local energy generator such as a fuel cell, a heat pump or a heat generator such as a condensing boiler, a combined heat and power plant or the like, although this list is neither restrictive nor complete.
  • an energy source or “the energy source”, this can mean at least one energy store and/or at least one energy generator.
  • the at least one energy source can be part of an energy system that also includes an internal power grid, at least one consumer connected to the internal power grid, a grid connection point and a control device.
  • Such an energy source is often installed in a basement of a building. Other locations are also possible.
  • the exact geometry, thermal conductivity, other heat sources, influence of the outside temperature and the like are often not exactly known or are difficult to determine, so that it would usually be very time-consuming to adequately calculate and/or model the thermodynamic properties of the installation site. It is therefore an aim of the present Invention to specify a method for performing a qualitative and / or quantitative assessment of the installation site in terms of thermodynamic properties.
  • the purpose here is in particular to avoid a power reduction of the energy source, for example an effect referred to as thermal derating in battery storage devices.
  • An installation site can, for example, be evaluated based on an average room temperature.
  • Other criteria include, for example, possible heat emission to the environment.
  • Such properties can depend on many parameters, such as the geometrical conditions, including a distance to walls and a ceiling of the room, the material of the walls and ceiling, the surface finish of the walls and ceiling, etc.
  • Different energy sources work differently efficiently at different temperatures.
  • aging of the energy source can depend on an internal temperature or an external temperature. It is therefore important to be able to calculate the relationships between the inside temperature or outside temperature and the power output of the energy source. If the energy source is operated under optimal conditions, resources and costs can also be saved.
  • a thermal model is to be generated that describes a thermal interaction between a considered energy source and its installation site.
  • a large number of data sets from a large number of similar energy sources are recorded and statistically evaluated.
  • Each data set can include a large number of measured temperature values, which are measured, for example, by a large number of temperature sensors at a large number of different positions on and in a housing of the energy source.
  • a big data analysis of measured values from a large number of devices in operation should be carried out in order to determine the thermal influence of the environment or the installation site.
  • a statistical evaluation of the large number of data sets is carried out. For example, a regression analysis can be performed. In particular, the statistical evaluation can include performing a linear regression.
  • the installation site of an individual energy source can then be evaluated on the basis of the generated thermal model. For this purpose, data sets of the individual energy sources are compared with the thermal model and a deviation is determined. A signal can be output depending on the deviation.
  • Each data set can preferably include a time profile of an internal temperature of the respective energy source and a time profile of an external temperature of the respective energy source.
  • the terms internal temperature and external temperature can be understood relative to a housing of the energy source, for example.
  • an internal temperature is measured at at least one position in a battery stack (stack) of a battery storage device.
  • the outside temperature is preferably measured at or near the housing.
  • a temperature measured on the inside of a housing can also be referred to as the outside temperature. Measuring on the inside has the advantage that the corresponding temperature sensor protected from external influences can be arranged inside the housing.
  • the outside temperature can be measured on an outside of the housing. For example, if the housing is made of thin sheet metal, the difference between a measurement on the inside and a measurement on the outside can be very small or negligible.
  • the data sets can be evaluated depending on the inside temperature and the outside temperature. If measured values for the internal temperature and external temperature are available, a temperature gradient from the inside to the outside can be determined in particular. For example, it can be determined whether the environment around the energy source can cause cooling, or how efficient the cooling effect is.
  • Each data set preferably includes geographic information and/or weather information about the installation site.
  • the geographic information can be stored in the data record, for example, as GPS coordinates or something similar.
  • the geographic information is used in particular to select a group of similar energy sources in similar climatic conditions, so that the thermal model for all energy sources is as accurate as possible, because external parameters of the building’s surroundings, such as the outside temperature of the building, can also have an impact on the temperature in and /or have at the power source.
  • the geographical information can preferably also include a geodetic height.
  • Weather information can also preferably be used to select data sets with similar climatic conditions for generating the thermal model.
  • the data sets can then be adjusted according to the Geographical information and / or weather information are evaluated.
  • the thermal model preferably describes a heat transfer resistance of the energy source and/or a heat transfer resistance of the energy source and/or a thermal capacity of the energy source. These parameters can describe the thermodynamic interaction of the energy source with the installation site and advantageously allow the internal temperature of the energy source to be predicted as a function of a power output and/or power input.
  • the energy sources are battery storage devices for storing and providing electrical energy in a household.
  • the outside temperature is preferably measured by a sensor on a housing of the battery storage unit.
  • the internal temperature is preferably measured by a large number of sensors inside the battery storage unit.
  • Each data set preferably includes a time profile of a power output from the energy source in each case, in particular an electrical power output from the energy source. Accordingly, the data sets can be evaluated depending on the electrical power output. Since the power output of the energy source can be reduced as a function of the operating temperature of the energy source, in particular in relation to an optimal range of the operating temperature, for example by a control device of the energy source, the measured power output is a good indicator of the course of the operating temperature. In this way, a thermal model could be generated even without measuring temperature values. If both measured temperature values and measured power values are available, it is possible to draw conclusions about properties such as the heat transfer resistance of the energy source and/or the heat transfer resistance of the energy source and/or the heat capacity of the energy source.
  • the thermal model preferably describes a dependency of a state of charge and/or battery aging of the battery store on the internal temperature and/or the external temperature.
  • the aim of the procedure is to prevent a decrease in the performance of the battery storage.
  • the operation of the battery storage is preferably regulated so that the Internal temperature and / or the outside temperature remain in a range that has no or the least possible negative effect on the state of charge and / or the battery aging of the battery storage.
  • the signal can be output in different ways.
  • the signal can be transmitted in the form of a message to a terminal of a user and/or operator of the energy source. Additionally or alternatively, the signal may be displayed as an indication on a display device at or near the energy source.
  • the signal can be a control signal or control signal that is output to the energy source by a control device of the energy source or a control device of an energy system of the building, in particular in order to carry out a control intervention.
  • the signal that is output can preferably include at least one instruction to reduce a maximum output power of the individual battery storage device.
  • the internal temperature and/or the external temperature of the energy source can be reduced, or a further increase can be avoided.
  • the reduced maximum output power can advantageously be greater than an output power of the battery store that is limited due to excessive temperature.
  • An above-described early preventive power reduction of the energy source, in particular of the energy store, can advantageously lead to higher energy storage or to a higher energy transfer over a period under consideration, compared to a case in which no preventive power reduction is carried out.
  • the power reduction is only carried out when a limit temperature is reached, so that the power reduction then turns out to be more drastic compared to the method of the present invention.
  • the same or similar method steps can be implemented correspondingly for a different type of energy source, such as a fuel cell or a heat pump.
  • the signal that is output can preferably include an error message to a user and/or operator of the battery storage device.
  • the error message can be output on a mobile terminal of the user and/or operator.
  • the signal that is output can preferably include a recommendation for action to be taken by the user and/or operator of the battery storage device. Possible actions are, for example: If the room temperature at the installation site is too high for optimal operation of the battery storage, a request to reduce the room temperature by a certain value can be issued. Accordingly, if the room temperature at the installation site is too low for optimal operation of the battery storage system, a request to increase the room temperature by a certain value can be issued. If thermal barriers are detected in the immediate vicinity of the battery storage, a request can be issued to free the immediate vicinity of the battery storage from negative influences. Possible causes of a negative influence can be, for example, other energy sources, pieces of furniture such as cupboards or the like, stored goods, etc.
  • the signal that is output can preferably include at least one instruction for carrying out a control intervention on the individual energy source. Possible control interventions include a reduction in the power of the energy source.
  • the instruction can be output to a control device of the energy source, which can adjust the control of the operating state of the energy source accordingly.
  • the method includes a step of calculating a prediction of a data set of the individual energy source for a predetermined period of time.
  • an actual data record of the specified period is recorded.
  • the predicted data set is then compared with the actual data set and a deviation can be determined.
  • the thermal model can be adjusted. In this way, the thermal model for the individual energy source can be iteratively improved so that more accurate predictions can be made.
  • the method includes a step of transmitting the multiplicity of data sets from the multiplicity of similar energy sources to a cloud or a server.
  • the cloud or server may be geographically remote from the plurality of power sources.
  • the data sets can be stored in the cloud or in a storage device on the server in order to be used for an evaluation.
  • the cloud or the server can evaluate the data sets, with the calculations described above being able to be carried out.
  • the advantage of a cloud or a server that is communicatively connected to the multitude of energy sources via a network and suitable interfaces is that data from a large number of energy sources, which can be set up in a wide variety of locations, can be received and evaluated. Furthermore, procedural steps of the evaluation and the calculations carried out with the data can be adapted centrally.
  • a signal can be output by the cloud or the server, for example to a mobile device of a user or operator of the energy source.
  • the mobile terminal can receive the signal in particular via an Internet connection.
  • Each energy source can be connected to a network via a suitable interface, for example to the Internet via a gateway, and can transmit data sets to a server or a cloud or receive them from the server or the cloud.
  • a suitable interface for example to the Internet via a gateway
  • This enables remote control, remote maintenance, remote analysis, etc. of the energy source.
  • this means that computationally intensive processes (e.g. machine learning algorithms) and/or the storage of large amounts of data can be outsourced to a server, a computing cluster or a cloud.
  • the transmission of datasets via a communication network for example a cellular network, a telephone network, an intranet and/or the Internet, may be possible.
  • Figure 1 illustrates a building with an energy system.
  • FIG. 2 illustrates a method according to an embodiment of
  • the energy system 1 shown in FIG. 1 comprises a photovoltaic system 3 (hereinafter also abbreviated to PV system) as the first energy source for electric power, which converts radiant energy from the sun into electrical energy.
  • a PV system photovoltaic system 3
  • the energy system 1 can have other (renewable) energy sources, such as a wind turbine, a fuel cell, a heat pump, a combined heat and power plant and/or a condensing boiler.
  • An inverter converts the direct current generated by the PV system 3 into alternating current and feeds it into an internal power grid (not shown) of the building.
  • a large number of consumers (not shown) that consume electrical energy can be connected to the internal power supply system.
  • at least one battery store is connected to the power grid as an energy source 2 connected.
  • the battery store 2 can, for example, store electrical energy generated by the PV system 2 or taken from a public power grid.
  • the battery store 2 includes an inverter that can convert alternating current from the utility grid to charge the battery store 2 into direct current. Furthermore, the inverter can convert direct current from the battery storage 2 into alternating current for the internal power grid in the building. To charge the battery store 2 with energy from the PV system 3, a direct power line (not shown) can also be provided between the PV system 3 and the battery store 2, so that there is no need to convert between direct current and alternating current when charging the battery store 2.
  • the energy system 1 also includes a control device 10 for regulating and/or controlling the PV system 3 or the inverter of the PV system 3 and for regulating and/or controlling the battery store 2 or the inverter of the battery store. Dashed arrows in FIG. 1 illustrate signal lines for regulation and/or control signals or measurement signals from sensors and the like.
  • the energy system 1 includes an outside temperature sensor 4 for measuring an outside temperature of the building. Furthermore, a large number of temperature sensors can be arranged in the battery store 2 .
  • the control device 10 detects the measurement signals from the temperature sensors and regularly generates data sets that contain current temperature measurement values and current power values of the energy sources 2, 3, for example.
  • the control device 10 regularly transmits the data sets to a cloud 30 and/or a server 20 via a suitable communication interface.
  • the data sets are transmitted via a suitable network 40, which can be the Internet, for example.
  • a terminal T of a user or operator of the energy system 1 can communicate with the network 40 .
  • Also shown in FIG. 1 are a variety of other buildings, which may be geographically distant from one another.
  • Each of these buildings includes an energy system with a similar battery storage 2 as an energy source. Furthermore, each energy system in these buildings includes a control device that transmits data sets from the battery storage device 2 to the network 40 .
  • the cloud 30 and/or the server 20 can thus record and evaluate a large number of data sets from a large number of energy sources 2 of the same type.
  • a cloud 30 (or a server 20) records a large number of data sets from a large number of similar energy sources 2 via a network 40.
  • the energy sources 2 can be arranged geographically remote from one another in different buildings.
  • Each energy source 2 is connected in particular to a control device 10 which outputs data sets to the network 40 in each case.
  • step S2a a statistical evaluation of the large number of data sets from the large number of energy sources is carried out and a thermal model is generated which describes a thermal interaction between the energy sources and the respective installation site.
  • step S2b one of the plurality of power sources is selected.
  • a dynamic thermal model can be generated from the large number of data sets from all recorded energy sources.
  • a heat transfer resistance, a heat transfer resistance and a heat capacity of the components of the energy source are calculated using a linear regression of the data sets.
  • a general thermal model preferably enables the thermal properties of internal components of any of the plurality of energy sources to be determined.
  • the thermal model can describe the following variables: thermal parameters of an inverter of a battery storage as an energy source, thermal parameters of the battery depending on the state of charge, the battery temperature and battery aging including resistance and capacity loss, and thermal parameters of the housing of the battery storage.
  • Environmental conditions of the respective geographic location can preferably be taken into account when generating the thermal model.
  • thermal parameters of the mean environment can be taken into account.
  • weather data can be included when creating the model.
  • the weather data can include, for example, an outside temperature of the building. This is advantageous because the environmental conditions of the energy source in the room can be strongly influenced by high or low outside temperatures.
  • weather data with regard to solar radiation can be taken into account. For example, high levels of irradiation can lead to higher power losses due to an inverter in a PV system.
  • a subset of data sets can be selected, preferably based on predetermined criteria, in order to improve the accuracy of the thermal model for the selected energy source.
  • the data sets may preferably be sorted based on the geographic location of the respective energy sources. That generated
  • the thermal model enables a heat transfer resistance of convection and thermal radiation to be determined from the linear regression of the data sets.
  • a geographic model can be generated using the geographic location data.
  • a thermal model which was generated as a function of the geographical location data is thus referred to as a geographical model.
  • a thermal model, for example, which can be generated by averaging all geographic models, is referred to as an average model.
  • a data set of the selected energy source is compared with the thermal model.
  • the installation location of the selected energy source can be evaluated with regard to its thermal properties using a decision tree. Details of the decision tree are described below.
  • step S4 a discrepancy between the data set of the selected energy source and the thermal model is determined.
  • a large number of optimized control parameters for operating the energy source can be determined as a function of the deviation.
  • the mean model described above can be compared with the considered energy source, preferably in combination with the geographically associated model. Excessive deviations can be identified by analyzing data sets from several days. Furthermore, suspected deviations can be identified by predictive calculations and comparison of the prediction with the actual stationary and dynamic behavior of the energy source.
  • deviations in the prediction or the actual data sets can be evaluated with the thermal model by comparing the model parameters of the energy source under consideration.
  • possible Reasons for the determined deviation are determined.
  • a frequency of the occurrence of deviations can be used below as a criterion for decisions (for example using a decision tree).
  • a signal is generated and output as a function of the deviation determined.
  • a message in particular an error message, is output to a user and/or an operator of the energy source.
  • the message can be output, for example, by transmitting the message to a mobile terminal T of the user and/or operator.
  • the message transmitted to the user and/or an operator of the energy source can preferably contain suggestions for optimizing the energy system. For example, temporal restrictions on the battery power and/or the state of charge can be suggested.
  • the proposals serve in particular to optimize the operation of the energy source in such a way that an impairment of the power output of the energy source can be minimized.
  • step S6 the optimized control parameters can be transmitted from the cloud 30 or the server 20 via the network 40 to the control device 10 of the energy source 2.
  • This transmission of optimized control parameters is also referred to as "control engineering intervention”.
  • Exemplary control interventions include a permanent or partial derating of the battery power and/or an optimization of a derating of a PV system.
  • step S3 A possible decision tree in step S3 will now be described.
  • the following example relates to an energy system as in FIG. 1 with a battery store 2 and a PV system 3 which charges the battery store 2 .
  • the server 20 or the cloud 30
  • the server 20 can, for example, recognize that the battery could not be optimally charged or discharged during the course of the day and especially in the evening hours due to thermal derating and the battery compared to other energy sources (other battery storage systems in other buildings) required longer standing times at night to cool down to an ambient temperature of the energy source.
  • the large number of temperature sensors in the battery store 2 has, for example, measured an increased surface temperature of the housing in comparison with corresponding temperature sensors of other battery stores that are geographically similar. A discrepancy in the data sets of the battery store 2 under consideration from other battery stores of the same type was thus identified.
  • a possible deviation of the temperatures due to characteristics of the battery is excluded.
  • Determining the deviations can now be analyzed using the thermal model and the data sets of the energy source under consideration.
  • the heat loss emitted by the PV system 3 can be reduced by adapting the dynamic PV derating, ie reducing the feed power of the inverter (active power limitation).
  • the possible and necessary active power limitation is analyzed with the data sets of the PV system 3 and the battery storage 2 and only reduced to the extent that a higher self-consumption compensation of the building is achieved despite a possibly lower PV yield due to grid feed-in or battery charging power.
  • dynamic PV derating and active power limitation come from solar technology. For example, they refer to a 70% rule that reduces the PV feed-in power into the grid to 70% of the maximum installed PV power according to the EEG. With dynamic active power limitation, in the case of a pending maximum PV power, only this 70% would be fed into the grid and the remaining 30% would flow into the battery storage, i.e. from the point of view of the PV system, 100% of the solar generated energy would be used.
  • the adjustment could mean that the PV system is set to a dynamic 60% active power limit, so that 60% is fed into the grid and the rest is stored in the battery.
  • the PV system By reducing the power consumption of the battery store 2, it can be achieved, for example, that the PV system generates less heat loss.
  • the data sets also show a deviation in the cooling of battery storage 2 in the late evening hours and at night and in comparison to other battery storage systems and the thermal model, it follows that the dynamic thermal behavior is also carrier at lower battery temperatures, both in the comparison result between the day with high solar radiation and the day with medium solar radiation in the evening hours compared to other battery storage systems.
  • the data sets can show that the energy system 1 is not operated at optimal efficiency on very sunny autumn or winter days because a high PV power heats up the battery storage during charging and the boiler that is switched on in the evening hours heats up the housing surface of battery storage 2.
  • maximum battery power could be reduced or PV derating implemented.
  • information regarding the interaction with the boiler at the installation site can or can be issued to the user or operator the PV power and battery power parameters can be adjusted via a control intervention.

Landscapes

  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)

Abstract

Un procédé pour faire fonctionner une source d'énergie au niveau d'un site d'installation comprend une étape de collecte d'une pluralité d'ensembles de données à partir d'une pluralité de sources d'énergie du même type, chaque ensemble de données comprenant une pluralité de valeurs de mesure de température. Dans une autre étape, un ensemble de données provenant d'une source d'énergie unique est sélectionné parmi la pluralité de sources d'énergie du même type et un calcul est effectué. Dans une étape du calcul, la pluralité d'ensembles de données est évaluée statistiquement, et un modèle thermique est généré qui décrit une interaction thermique entre les sources d'énergie et le site d'installation en question. L'ensemble de données provenant de la source d'énergie unique est comparé au modèle thermique et un écart est déterminé. Un signal est émis en fonction de l'écart déterminé.
EP23705200.6A 2022-01-25 2023-01-18 Procédé pour faire fonctionner une source d'énergie Pending EP4470085A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102022101709.5A DE102022101709A1 (de) 2022-01-25 2022-01-25 Verfahren zum Betreiben einer Energiequelle
PCT/EP2023/051090 WO2023143978A1 (fr) 2022-01-25 2023-01-18 Procédé pour faire fonctionner une source d'énergie

Publications (1)

Publication Number Publication Date
EP4470085A1 true EP4470085A1 (fr) 2024-12-04

Family

ID=85239007

Family Applications (1)

Application Number Title Priority Date Filing Date
EP23705200.6A Pending EP4470085A1 (fr) 2022-01-25 2023-01-18 Procédé pour faire fonctionner une source d'énergie

Country Status (3)

Country Link
EP (1) EP4470085A1 (fr)
DE (1) DE102022101709A1 (fr)
WO (1) WO2023143978A1 (fr)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102024206261A1 (de) 2024-07-03 2026-01-08 Robert Bosch Gesellschaft mit beschränkter Haftung Verfahren zur Klassifizierung einer Eignung einer automobilen Batterie

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE19834740C2 (de) 1998-08-01 2003-03-13 Iq Battery Res & Dev Gmbh Kraftfahrzeugbatterie mit integrierter Überwachungsvorrichtung und Verfahren zur Überwachung einer Kraftfahrzeugbatterie
DE102010001874A1 (de) 2010-02-12 2011-08-18 Holzner, Stephan, 82069 Speicher für elektrische Energie
US9864016B2 (en) * 2014-10-31 2018-01-09 GM Global Technology Operations LLC Battery system pack life estimation systems and methods
US10742055B2 (en) * 2015-10-08 2020-08-11 Con Edison Battery Storage, Llc Renewable energy system with simultaneous ramp rate control and frequency regulation
DE102018213991A1 (de) 2018-08-20 2020-02-20 Audi Ag Verfahren zur Ermittlung einer Lebensdauer einer Batterie sowie Fahrzeug mit einer Batterie
EP3826102A1 (fr) * 2019-11-20 2021-05-26 Vestas Wind Systems A/S Surveillance de système de batterie basée sur un modèle
DE102020108365A1 (de) 2020-03-26 2021-09-30 Bayerische Motoren Werke Aktiengesellschaft Verfahren und Vorrichtung zur Ermittlung von Lebensdauerinformation für einen elektrischen Energiespeicher

Also Published As

Publication number Publication date
WO2023143978A1 (fr) 2023-08-03
DE102022101709A1 (de) 2023-07-27

Similar Documents

Publication Publication Date Title
DE102016214332B4 (de) Aggregierte und optimierte virtuelles-kraftwerk-steuerung
EP3590169B1 (fr) Procédé de gestion d'énergie pour système énergétique et système énergétique
EP2628231B1 (fr) Commande d'un réseau de distribution d'énergie électrique
EP3561983B1 (fr) Procédé de fonctionnement d'un système d'alimentation en énergie
EP3161928B1 (fr) Système de gestion d'énergie permettant de commander un dispositif, produit-programme d'ordinateur et procédé de commande d'un dispositif
DE102015101738A1 (de) Verfahren zum Betrieb einer Energieerzeugungsanlage und Energieerzeugungsanlage
Bebic et al. The sun also rises
EP2843788A2 (fr) Procédé destiné au fonctionnement d'un système de centrale
EP3284152B1 (fr) Commande de transfert d'énergie entre un réseau d'alimentation en énergie et des dispositifs d'utilisateur final sur la base du flux d'énergie et de la qualité du réseau
DE102021214816A1 (de) Verfahren und System zur Steuerung eines Stromnetzes
DE102016225787A1 (de) Verfahren zum Betrieb eines Energie-Management-Systems eines Gebäudes und Energie-Management-System
EP3667851B1 (fr) Création de modèles dynamiques de noeuds de réseau dans un réseau de distribution à faible et / ou moyenne tension à l'aide d'un algorithme d' apprentissage automatique
WO2023143978A1 (fr) Procédé pour faire fonctionner une source d'énergie
DE112016004377T5 (de) Verbesserte Leistungsregelung eines Satzes von Fotovoltaik-Modulen zur Teilnahme an der Frequenzregelung ohne Verwendung eines Speichermediums
WO2016131885A1 (fr) Injection par précaution d'énergie emmagasinée temporairement dans un réseau d'alimentation en énergie, basée sur la prévision de disponibilité de l'énergie et de la sécurité d'alimentation en énergie
DE102014222687A1 (de) Steuerung eines Energienetzes
DE102015102430A1 (de) Autonom und kooperativ gesteuertes Energieeinspeisen in einem virtuellen Kraftwerk
EP3382841A1 (fr) Utilisation hybride d'accumulateurs d'énergie
EP2834898B1 (fr) Procédé de détermination de points de mesure dans des réseaux à basse tension et sous-système de gestion de réseau servant à mettre en oeuvre ce procédé
WO2019072541A1 (fr) Utilisations multiples d'accumulateurs d'énergie
EP3906522B1 (fr) Processus de gestion de l'énergie assisté par ordinateur et système de gestion de l'énergie
DE102017100639B4 (de) Speichergeführte Anlagensteuerung für eine Kraftwärmekopplungsanlage
DE102023102702A1 (de) Eigenverbrauchsoptimierung für haushaltsnetze mit batteriespeicher
CN117081153A (zh) 光伏发电本地消纳方法、装置及电子设备
EP3664243B1 (fr) Planification de fonctionnement prédictive dans un micro-réseau en fonction des fenêtres temporelles de charge élevé d'un réseau électrique principal

Legal Events

Date Code Title Description
STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: UNKNOWN

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE INTERNATIONAL PUBLICATION HAS BEEN MADE

PUAI Public reference made under article 153(3) epc to a published international application that has entered the european phase

Free format text: ORIGINAL CODE: 0009012

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: REQUEST FOR EXAMINATION WAS MADE

17P Request for examination filed

Effective date: 20240821

AK Designated contracting states

Kind code of ref document: A1

Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC ME MK MT NL NO PL PT RO RS SE SI SK SM TR

DAV Request for validation of the european patent (deleted)
DAX Request for extension of the european patent (deleted)
RAP1 Party data changed (applicant data changed or rights of an application transferred)

Owner name: VIESSMANN HOLDING INTERNATIONAL GMBH