Determining a measurement-based digital image of a local substation network

Abstract

The invention relates to a method (200) for determining a measurement-based digital at least partial image of a local substation network (100) with multiple local substations (102). The method (200) comprises determining (204) state data of at least one local substation (102) of the local substation network (100) and generating (206) a digital at least partial image of the local substation network (102) on the basis of at least a part of the determined state data. The state data are based on measurements and measurement-equivalent data from at least one local substation (102).

Description

[0001] DETERMINING A MEASUREMENT-BASED DIGITAL IMAGE OF A LOCAL NETWORK STATION NETWORK

[0002] TECHNICAL FIELD

[0003] The present invention relates generally to the technical field of electrical power engineering and its digitalization and in particular to methods, devices, computer programs and data structures for determining a measured value-based digital at least partial image of a local network station network.

[0004] BACKGROUND

[0005] Power grids are used to transmit and distribute electrical energy. In particular, power grids are used to transport electrical energy from energy producers, such as power plants, to energy consumers.

[0006] To reduce transmission losses in power grids, electrical energy is typically transmitted at different voltage levels. The higher the voltage during transmission, the lower the transmission losses. The extra-high voltage and high voltage levels, where the voltage can range from 50 kV to several hundred kV, are used to distribute electrical energy over long distances. The medium-voltage grid, which typically has a voltage of 1 kV to 35 kV, is used for the regional transmission of electrical energy over shorter distances. The shortest transmission distances are bridged by the low-voltage grid, which typically has a voltage of less than 1 kV, in particular 230 V or 400 V.

[0007] In order to shift energy between the voltage levels of the power grid, the electrical energy is transformed from a higher voltage to a lower voltage and vice versa. Local network substations, for example, are used for this purpose. For example, a local network substation can transform energy between a medium-voltage network and a low-voltage network, but transformation can also take place between other voltage levels. In many areas, the power grid in its current form is the result of historical development, with the expansion of the power grid and the equipment and planning of the local network substations historically taking place primarily with a view to distributing electrical energy from central generators with relatively high output, for example coal-fired or nuclear power plants, to decentralized consumers.

[0008] Today, however, the energy system is increasingly geared toward decentralized energy generation. Energy is generated, for example, by wind turbines or solar power plants, which can provide significantly less electrical power than large power plants. Furthermore, many of the energy sources used for decentralized energy generation, such as wind and solar, are volatile in their availability, dependent on local conditions, and cannot be predicted with sufficient precision.

[0009] An embodiment of a local network substation is known from DE 102018 102 394 A1. The local network substation has a fault detection device for detecting a network fault in a low-voltage network connected to the local network substation. For this purpose, the fault detection unit has a monitoring unit for monitoring the network current of the low-voltage network and for monitoring the network voltage of the low-voltage network. A detection device is configured to detect a network fault based on a stored fault criterion and the detected network current or the detected network voltage.

[0010] DE 102016 110 188 A1 discloses a method for operating a low-voltage grid that can be implemented in a local network substation. In this method, an actual power is measured in a distribution line of the low-voltage grid. A feed-in value from electrical feeders in the distribution line and a load value from electrical loads in the distribution line are determined. A target power is then compared with the actual power, and an error signal is output if the deviation between the target power and the actual power exceeds a limit.

[0011] EP 3 968212 A1 describes a method for providing switching state data, which can also be carried out in a local network substation. The switching state data describe a switching state of a power distribution device with outgoing devices for a low-voltage network. A trained pattern recognition function is applied to a photo of the power distribution device, which shows optically detectable switching states of switching elements of the power distribution device. In this way, the switching state of the switching elements of the power distribution device is determined and provided. Existing local network substations are designed to be "intelligent" to varying degrees, i.e., they are equipped with means for controlling and regulating the distribution of electrical energy, for example, with various sensors, actuators, and communication means. The equipment of a local network substation is usually adapted to the task performed by the local network substation.Equipment requirements can be derived, for example, from the location, size, equipment, and / or function of a local network substation. Consequently, the selection and dimensioning of the technical components of a local network substation, the installation and commissioning of the local network substations, the monitoring and control of operating states, the performance of tests and repairs, and the documentation and analysis of operating data depend on the specific intended use of the local network substations.

[0012] This results in inconsistencies in the information collected by different distribution substations. Some distribution substations can only provide limited measurement data, while others can provide comprehensive information about the status of the components of the distribution substation itself, as well as about the power grid connected to the distribution substation. This uneven distribution of information density can lead to problems in grid planning, grid expansion, and the integration of renewable energies into the grid.

[0013] As a result, existing energy systems suffer from several technical disadvantages. Due to the inadequate information provided by some local grid stations, reliable control and distribution of electrical currents in the power grid cannot be achieved. This can lead to inefficient operation and negatively impact supply security and grid stability. To ensure a high level of supply security in the provision of electrical energy despite changing conditions, the structure of the power grid must be adapted.

[0014] It is therefore an object of the present invention to provide techniques for optimizing, monitoring and / or controlling local network stations and / or power grids and thus to at least partially overcome the above-mentioned disadvantages of the prior art.

[0015] SUMMARY OF THE INVENTION

[0016] In its most general form, the invention provides methods, apparatus, computer programs, and data structures for determining a measured-value-based digital representation of a local network. The described methods can be computer-implemented.

[0017] According to one aspect of the present invention, a method is provided for determining a measured value-based digital at least partial image of a local network station network having a plurality of local network stations. A “local network station” can be used to transform electrical energy between different voltage levels of a power grid. For example, local network stations can be used for transformation between a medium-voltage grid and a low-voltage grid, i.e., for transforming voltage between the medium-voltage level and the low-voltage level. However, the present invention is not limited to application in the medium- or low-voltage range, but can also be used for other voltage levels. Local network stations can have various technical components, i.e., hardware, such as a power transformer, a switchgear, a voltage distribution system, and / or secondary technology.The secondary technology may include, for example, automation and telecontrol technology, energy meters and / or communication devices.

[0018] A "local network substation network" can be an electrical power grid to which several local network substations are connected. For example, several local network substations connected to a common medium- or low-voltage grid can be assigned to the same local network substation network. In principle, the voltage level of the grid connecting the local network substations can be freely selected. For example, the local network substations of a local network substation can be connected by a medium-voltage grid and / or a low-voltage grid.

[0019] Various designs of a local network substation network are conceivable. For example, a local network substation network can be designed as a spur line, with a local network substation connected to the end of a power line. This variant has the advantage of being cost-effective and easy to implement due to its simple structure. A local network substation network can, for example, be designed as a ring network, with several local network substations connected to a power line in the form of a closed ring. A ring network offers a high level of supply security, as the ring network can be closed at another location in the event of a fault in a line or the failure of a local network substation, so that the supply of electrical energy can be maintained despite the outage.For example, a secondary distribution network can be designed as a parallel feeder, with several secondary distribution stations connected in parallel to a power line. In general, a secondary distribution network designed as a parallel feeder provides a high supply quality because the voltage at the stations is kept at a substantially constant level by the parallel feeder.

[0020] The method may include a step of determining status data of at least one local network station of the local network station network. The "status data" may, for example, describe the status of a local network station and / or the status of one or more connections of the local network station and / or the status of a network to which the local network station is connected. The status data may be based on measured values ​​of at least one local network station. The status data may be based on measured-value-equivalent data of at least one local network station.

[0021] The method may include a step of generating a digital image of at least a partial substation network (hereinafter referred to simply as a "digital image") based on at least a portion of the determined status data. The digital image of the substation network may, for example, be a digital twin of at least a portion of the substations of the substation network and thus represent the characteristics of the substation network in the form of a digital model.

[0022] Creating a digital image of at least part of the local network substation based on status data brings several technical advantages:

[0023] A digital twin enables the monitoring of the status and utilization of the distribution substations and the power grids connected to them with improved transparency. Furthermore, a digital twin enables faster and more precise fault detection and troubleshooting at distribution substations and in the distribution substation network.

[0024] Furthermore, a digital twin can support the planning and operation of substations and substation networks by simulating various scenarios and thus predicting the impact of measures. This can reduce costs in the planning, operation, and maintenance of substation networks, increase efficiency, and extend the service life of the substations.

[0025] According to one aspect of the present invention, the status data is based on measured values ​​and measured-value-equivalent data from at least one local network station. Determining the status data from a combination of measured values ​​and measured-value-equivalent data, e.g., indirectly derived data, offers several technical advantages over the approach of using only measured values:

[0026] Supplementary information: Measured value equivalent data can provide additional insights into the substation network that cannot be derived directly from the measured values. This information can help develop a more comprehensive understanding of the substation network.

[0027] Reducing measurement errors: Measurement values ​​are not always perfect and may contain measurement errors. Equivalent data can help correct or compensate for such errors to achieve more accurate results.

[0028] Flexibility: Equivalent measurement data can be used when measurements are difficult or expensive to perform. This enables continuous monitoring and analysis of the distribution substation network, even when direct measurements are limited.

[0029] Improved modeling: Integrating measured-value equivalent data into models can help improve their accuracy and predictive capability. This is especially important in complex technical substation networks.

[0030] Anomaly detection: Measured value equivalent data can be used to detect and explain deviations or anomalies in the measured data. This enables early identification of problems in the substation network.

[0031] Cost savings: The use of measurement-equivalent data can help reduce the costs of data collection and / or monitoring, as not all information needs to be captured through expensive measurements.

[0032] Reduction of metering devices: In some cases, the use of metered-value data can reduce the number of required meters and / or sensors, which can reduce the complexity and maintenance costs of the substation network. Data fusion: By combining measured values ​​and metered-value data, different data sources can be merged to obtain a more holistic picture of the substation network.

[0033] Overall, the integration of metered value equivalent data into the analysis and monitoring of a local network substation network and / or individual local network substations enables a more comprehensive and accurate assessment, which can lead to improved decisions, efficiency gains and / or cost savings.

[0034] According to a further aspect of the present invention, the measured values ​​can be recorded by a measuring device assigned to the local network station. Different local network stations can be equipped with different measuring devices, in particular sensors. In this respect, not all local network stations of a local network station usually record the same measured values. For example, a measuring device of a local network station can be designed to determine measured values ​​that are suitable for describing the condition of components of the local network station, such as the transformer. The measured values ​​can relate, for example, to protection, control and / or monitoring devices of the local network station. For example, the grid voltage curve and / or grid current curve received by the local network station can be measured.For example, the grid voltage and / or current curve provided by the transformer substation can be measured. Using status data based on measured values ​​when creating a transformer substation network has the advantage that the resulting digital representation corresponds very closely to the actual transformer substation network.

[0035] According to a further aspect of the present invention, the measured value-equivalent data can be derived from data describing the local network station and / or one or more connections, in particular peripheral data. "Peripheral data" can be understood to mean all information that is available or can be collected from the environment of the local network station, for example, from the power grids to which the local network station is connected. However, measured value-equivalent data can be derived not only from peripheral data. Measured value-equivalent data can also be derived from data describing the local network station itself.

[0036] According to a further aspect of the present invention, the peripheral data may comprise low-voltage network-side peripheral data. According to a further aspect of the present invention, the peripheral data may comprise medium-voltage network-side peripheral data. This may be the case, for example, if the local network station is connected to a medium-voltage network and a low-voltage network, and voltage is transformed between the medium-voltage level and the low-voltage level by means of a transformation device of the local network station.

[0037] The low-voltage network-side peripheral data may in particular include consumer data and / or electricity meter status data and / or consumption statistics data and / or environmental condition data such as temperature data, solar radiation data, wind speed and / or direction data.

[0038] The medium-voltage network-side peripheral data can in particular include connection variant data and / or line resistance data and / or network infrastructure data and / or environmental condition data such as temperature data, solar radiation data, wind speed and / or direction data.

[0039] As already mentioned above, the use of measured value-equivalent data can expand and / or supplement the database from which the digital image of the local network substation network is derived. Consequently, it is not necessary to derive all the status data required to create the digital image from measured values. Particularly when only limited data is available for a local network substation, the status data required to create the digital image can be based on measured value-equivalent data, which can in particular be derived from peripheral data describing the environment of the local network substation. From the peripheral data, measured value-equivalent data can be calculated, which can serve as the basis for the digital image of the local network substation network, even though no corresponding measured values ​​can actually be recorded.

[0040] According to a further aspect of the present invention, the condition data may comprise historical condition data and / or geodesics and / or data provided by a user.

[0041] By linking data from various sources, such as sensors, simulations, geoinformation, and historical data, a digital twin can provide valuable insights that can be used to optimize, monitor, and / or control the real secondary grid substation. Historical status data can, for example, be time series of measured values ​​or data equivalent to measured values, in particular, trends of the physical quantities relevant to a power grid, such as current flow or voltage. According to a further aspect of the present invention, the method can comprise a step of providing at least one target pattern that defines target status data for an analysis of the secondary grid substation network, in particular an operation, maintenance, and / or planning analysis.

[0042] Such an analysis of the local network substation network can, for example, examine issues related to operational reliability, such as the prevention of blackouts. Analyses can also be conducted regarding the planning of the local network substations and / or the local network substation network, for example, regarding the expansion of the local network substation network or the connection of new generators or consumers, such as charging stations. Additionally or alternatively, questions regarding maintenance, such as component replacement and / or predictive maintenance, can be investigated.

[0043] A target pattern can define which status data is required for an analysis of the local network substation network and thus must be determined to create a meaningful digital image of the local network substation network. A target pattern can additionally or alternatively define a target status data range within which the required status data may be located. For example, the target status data range can be defined such that a local network substation is functioning properly if the status data is within the target status data range. For example, a target pattern can describe a certain corridor for a voltage and / or current curve provided by a local network substation.

[0044] For example, the target state data of the target pattern can be defined by grid connection conditions specified by grid operators. For example, the target state data can be specified by typical load profiles of generators and / or consumers and / or by technical restrictions of the components of a distribution substation.

[0045] The target pattern can be selected from a pool of existing target patterns, provided manually, and / or generated automatically, for example, by an artificial intelligence-based algorithm such as a neural network. Whether a target pattern is selected, provided, or generated, and the nature of the target pattern, can depend in particular on the analysis of the local network substation network to be performed. When determining status data of at least one local network station of the local network substation network as explained above, the status data can be determined that correspond to the target status data described by the target pattern in order to obtain a digital image of the local network substation network that is suitable for analysis according to the target pattern.

[0046] The local network substations in a local network substation network may be equipped with different levels of intelligence, i.e., different measuring devices and control systems. Therefore, it may not be possible for all local network substations to provide the required status data defined by the target status data.

[0047] According to a further aspect of the present invention, the method may therefore comprise a step of determining that the digital image of the local network station network comprises insufficient status data for analysis according to the at least one target pattern.

[0048] To prevent an analysis according to the target pattern from being performed due to insufficient, for example, incomplete, data, the method may include a step of selecting a completion algorithm from an algorithm database. The method may include a step of completing the status data using the selected completion algorithm. Depending on which status data can and cannot be provided by the local distribution network, other algorithms may be suitable for filling in the gaps in the status data.

[0049] A variety of algorithms are available for completing state data. Data completion is commonly referred to as "imputation" in statistics. For example, simple statistical algorithms can be used, such as calculating an average or median of a state data series and inserting the calculated average or median into all gaps in the state data series. These simple algorithms are characterized by particularly low computational effort.

[0050] In other exemplary embodiments, interpolation, LOCF (Last Observation Carried Forward), or moving average may be used. In particular, when completing time series, Kalman smoothing or seasonal decomposition may be used. When completing clustering data, K-Nearest Neighbor or K-Means clustering may be used. These somewhat more complex algorithms can complete the missing data with improved accuracy.

[0051] By completing the specific status data of the digital image, the quality of the digital image is improved, allowing for meaningful analyses of the secondary substation network even when the data basis is insufficient. The accuracy and significance of the analyses performed are improved.

[0052] According to a further aspect of the present invention, completing the state data using the selected completion algorithm may comprise a step of comparing local exchange stations of the local exchange station network.

[0053] Comparing local substations in the local substation network represents an efficient and at the same time robust way to supplement the status data of a digital image, especially when comparing local substations that have similar components and / or are connected to similar power grids.

[0054] For example, distribution substations that transform electrical energy between a medium-voltage level and a low-voltage level can have a comparable number of low-voltage outgoing devices, in particular 4 to 17 low-voltage outgoing devices. Furthermore, the structures downstream of the low-voltage outgoing devices in the low-voltage network, which are characteristic of the behavior of the respective distribution substation, can be comparable.

[0055] For example, if only street lighting is connected to a low-voltage outgoing system, the connection characteristics are different than if many different households, which may even feed electricity into the low-voltage network, are connected to a low-voltage network.

[0056] According to a further aspect of the present invention, completing the state data using the selected completion algorithm may comprise a step of deriving measured value equivalent data of at least one local network station of the local network station network from peripheral data.

[0057] As already explained above, supplementing the status data with measurement data derived from peripheral data enables the creation of a particularly efficient, yet simultaneously meaningful, digital image. According to a further aspect of the present invention, the method can comprise a step of comparing the target status data of the target template with status data of the digital image of the local network substation network. According to a further aspect of the present invention, the method can comprise a step of deriving at least one measure if the comparison reveals that the status data of the digital image of the local network substation network deviate from the target status data of the target template by more than a threshold value.

[0058] Measures can be understood as actions that can be initiated in the event that at least one of the status data threatens to leave the legitimate range of the target pattern, in order to keep the system within the legitimate range. Measures can, for example, have an informational and / or control character.

[0059] According to a further aspect of the present invention, the method may include a step of simulating a development of the state data of the digital image of the local network station network compared to the target state data of the target pattern. According to a further aspect of the present invention, the method may include a step of deriving at least one measure if the simulation reveals that the state data of the digital image of the local network station network will deviate from the target state data of the target pattern by more than a threshold value.

[0060] By simulating the development of the status data, especially a future-oriented development of the status data, future scenarios can also be incorporated into the derivation of measures. For example, electricity generation in a low-voltage grid to which many photovoltaic systems are connected can differ significantly during the day or in summer from electricity generation at night or in winter due to the changing duration of sunshine. By simulating the development of the status data, such diverse scenarios can also be incorporated into the analysis of the secondary grid substation network, enabling a particularly robust analysis.

[0061] According to a further aspect of the present invention, the generated digital image of the local network station network may comprise a digital image of at least some of the local network stations, preferably all of the local network stations of the local network station network.

[0062] Thus, a particularly comprehensive digital image of the local network substation network is generated, which can be used to perform meaningful analyses and improve predictions. In a further aspect of the present invention, a data processing device configured to carry out the method according to any of the aspects disclosed herein is provided. For this purpose, the data processing device may comprise means for carrying out the method according to any of the aspects disclosed herein.

[0063] In a further aspect of the present invention, a computer program is provided. The computer program comprises instructions that, when executed by a data processing device, cause the device to perform the method according to any of the aspects disclosed herein.

[0064] In a further aspect of the present invention, a computer-readable medium is provided on which such a computer program is stored.

[0065] In a further aspect of the present invention, a computer-readable data structure is provided which represents a measured-value-based digital, at least partial, image of a local network station network having a plurality of local network stations. The data structure can comprise status data of at least one local network station of the local network station network, which data is based on measured values ​​and measured-value-equivalent data of at least one local network station. In a decentralized architecture, such a data structure can be provided on a server of a local network station. In a centralized architecture, the data structure can be provided on a central server assigned to the local network station network. Hybrid forms of these two architectures are also possible.

[0066] Some of the status data can be statically configured in the data structure. Static status data can, for example, be fixedly parameterized, meaning it cannot change over time. This can apply, for example, to status data relating to the structural design of the local network substations or the local network substation network. Some status data can be dynamically configured in the data structure, so that they can change over time, for example, if the status data refers to measured values, averages, or similar.

[0067] A local network substation can have a controller for locally controlling the technical components of the local network substation, i.e., the technical hardware of the local network substation. For example, the controller can receive measured values ​​from measuring devices and send control signals to technical components. The controller can have an external interface that includes a server, for example, an OPC-IIA server. The server can have the aforementioned data structure or a portion of the aforementioned data structure.

[0068] A local network substation network can comprise multiple local network substations, each of which can have a controller for local control of the local network substations. Since the controller of each local network substation controls the technical components of the local network substation locally—and autonomously within a certain framework specified by the network operator—the control effort of the entire local network substation network is reduced.

[0069] The servers provided by the controllers' external interfaces enable simple and uniform communication with the local network stations, for example, via a dedicated communication network. In particular, status data can be provided individually via the server(s) and queried specifically by other local network stations, a user, and / or a network control system.

[0070] The external interfaces can be designed as bidirectional data interfaces, allowing access to status data from the individual local network stations. Furthermore, it may also be possible to send data to the individual local network stations via the external interfaces.

[0071] The external interface of the control system of the secondary network substation can have an administration shell configured to publish status data via a communications network. The status data can be published via the administration shell using standardized metadata.

[0072] By providing static and dynamic status data in the server of the external interface, a local network substation can provide a type of module type package that forms part of an administration shell. The provided status data can be retrieved when determining the status data and / or when generating the digital image of the local network substation.

[0073] Preferably, the data structure, which may be provided, for example, on the server of a local network substation and / or a central server associated with the local network substation network, may comprise a number of objects. The objects may comprise a real-time value and a description of the real-time value. The real-time values ​​are stored in objects of the data structure so that they can be easily retrieved, identified, or referenced. The real-time values ​​can be continuously updated by the controller.

[0074] The controller can be configured so that the server can be queried dynamically, especially for each object individually. This allows only the status data that is currently of interest to be retrieved from the outside. Uninteresting status data therefore does not need to be transmitted, minimizing data transfer within a network or on a bus via which the local network stations can exchange status data or via which status data is requested by a higher-level controller.

[0075] BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Preferred embodiments of the present disclosure are described below with reference to the following figures:

[0077] Fig. 1 : A local network station network 100 according to an embodiment of the

[0078] invention

[0079] Fig. 2: A local network station 102 according to an embodiment of the invention

[0080] Fig. 3: A method 200 according to an embodiment of the invention

[0081] DETAILED DESCRIPTION

[0082] Various aspects of a method for determining a measured-value-based digital image of a secondary distribution network are described below. Overall, the aspects of the present invention disclosed herein provide a more efficient solution for analyzing and / or controlling energy networks.

[0083] Fig. 1 shows an overview of a local network station network 100 in which embodiments of the invention can be practiced. In this highly simplified example, the local network station network 100 comprises three local network stations 102a, 102b, and 102c, which are also collectively designated by the reference numeral 102. Each of the local network stations 102 is arranged between at least one medium-voltage network 104 and at least one low-voltage network 106 (see the low-voltage networks 106a, 106b, 106c), for example, a local network. By means of the local network stations 102, voltage can be transformed between the medium-voltage level of the medium-voltage network 104 and the low-voltage level of the low-voltage network 106.

[0084] The illustrated low-voltage networks 106a, 106b, 106c are typically designed taking technical and local requirements into account and can therefore be constructed differently. For example, the low-voltage networks 106a, 106b, 106c can have consumers and / or generators with different power outputs. The low-voltage networks 106a, 106b, 106c can extend over different distances, so the resistances caused by the power lines are configured differently.

[0085] The local network stations 102a, 102b, and 102c also typically have at least partially different structures, in particular different equipment with technical hardware, in particular with measuring devices 122. This results in different data being provided by the local network stations 102a, 102b, and 102c. Some of the local network stations 102a, 102b, and 102c provide many measured values, while others of the local network stations 102a, 102b, and 102c provide fewer measured values.

[0086] Overall, a local network station network 100 represents a heterogeneous network of local network stations 102 that are connected by at least one power grid and that do not provide a completely uniform database of measured values.

[0087] Figure 2 shows a local network substation 102 according to an exemplary embodiment of the invention. Local network substation 102 has a transformer device 108, by means of which voltage can be transformed from a medium-voltage level 104 to a low-voltage level 106, and vice versa. The exemplary low-voltage level distribution line 106 has three phases fed by a power distribution busbar 107. Each of the phases of the low-voltage network 106 is protected by a fuse 109.

[0088] The local network station 102 has a controller 110, which can be designed for local control of the local network station 102. For this purpose, the controller 110 can have I / O modules 116, 118. The I / O modules 116, 118 can be signal-connected to technical components of the local network station 102, i.e., to the technical hardware of the local network station 102. For example, measured values ​​from sensors can be transmitted to the I / O modules 116, 118 of the controller 110. Control signals can be sent from the I / O modules 116, 118 to actuators. In one exemplary embodiment, the controller 110 is signal-connected to the transformer device 108 via the I / O module 116, so that measured values ​​from the transformer device 108 can be provided to the controller 110. At the same time, control signals can be sent to the transformer device 108.

[0089] Via the I / O module 118, the controller 110 can, for example, be in signal communication with a measuring device 122. The measuring device 122 has a current measuring device 124 and a voltage measuring device 126 for monitoring the electrical current and voltage on the power distribution busbar 107. The measured values ​​thus determined can be sent from the measuring device 122 to the controller 110 or retrieved by the controller 110.

[0090] Of course, the controller 110 can have additional I / O modules, which can be connected, for example, to other technical components of the secondary network station 102. However, the controller 110 can also be configured to receive peripheral data and calculate measured value-equivalent data based on this peripheral data. For example, the controller 110 can be signal-connected to a weather station 114, which sends environmental condition data such as temperature data, solar radiation data, and / or wind speed and / or direction data to the controller 110 or makes it available for retrieval. Measured value-equivalent data can be calculated from the environmental condition data, which, for example, forecast power generation by photovoltaic systems or wind turbines.

[0091] The peripheral data may include low-voltage grid-side data suitable for describing the low-voltage grid 106 connected to the local grid station 102 or the energy system connected thereto. Additionally or alternatively, the peripheral data may include medium-voltage grid-side data suitable for describing the medium-voltage grid 104 connected to the local grid station 102 or the energy system connected thereto.

[0092] The controller 110 may further comprise an external interface 112, which is designed for communication between the controller 110 and systems outside the local network station 102, for example with a higher-level controller or with other local network stations 102. For this purpose, the external interface 112 may comprise a server 120, which may be configured, for example, as an OPC-UA server.

[0093] The server 120 can have a fixed data structure comprising static and / or dynamic status data of the local network station 102 based on measured values ​​and / or measured-value-equivalent data. The static status data can, for example, describe non-changing properties of technical components of the local network station 102, such as properties of the transformer device 108. The dynamic status data can change over time and can, for example, be based on measured values ​​and / or measured-value-equivalent data of one or more local network stations 102.

[0094] Consequently, the local network substation 102 can communicate with the outside world via the server 120 and can also provide or exchange dynamic status data during operation. The dynamic status data can be written into the data structure of the server 120 by the controller 110 so that it can be retrieved by other local network substations or a higher-level controller.

[0095] Figure 3 shows a method 200 for determining a measured value-based digital at least partial image of a local network station network with a plurality of local network stations according to an embodiment of the invention.

[0096] The method 200 can be carried out, for example, by a central controller of a local network station network 100, in particular a network control system or a network control center of the local network station network 100. However, the method can additionally or alternatively also be carried out decentrally by the controller 110 of at least one local network station 102 of the local network station network 100.

[0097] Essentially, method 200 comprises step 204, in which status data from at least one local network station 102 of a local network station network 100 is determined. Based on at least part of this status data, a digital, at least partial, image of the local network station network 100 is generated in step 206. The status data can be based on measured values ​​and measured-value-equivalent data from at least one local network station 102.

[0098] Optionally, in step 202, which can be executed, for example, before steps 204 and 206, a target pattern can be provided which defines target state data for an analysis of the local network substation network, in particular an operation, maintenance and / or planning analysis.

[0099] In an optional step 208, which can be performed, for example, after step 204 and / or step 206, it is determined that the digital image of the local network substation network includes insufficient status data for analysis according to the at least one target pattern. The missing status data can be completed in an optional step 210. The completion of the status data can be performed using a completion algorithm. For this purpose, a suitable completion algorithm can be selected from an algorithm database.

[0100] When completing the status data in step 210, for example, different local network stations 102 of the local network station network 100 can be compared with each other. Additionally or alternatively, measured value-equivalent data from at least one local network station 102 can be derived from peripheral data.

[0101] If, during the investigation as to whether the digital image of the local network substation network 100 contains insufficient status data, it is determined that the status data of the digital image are already available in sufficient form, steps 208 and 210 can be skipped.

[0102] In an optional step 212, the target state data of the target pattern are compared with state data of the digital image of the local network substation network 100. Thus, an analysis specified by the target state data of the target pattern is performed.

[0103] In an optional step 214, at least one measure can be derived. For example, a measure can be derived if the comparison in step 212 reveals that the state data of the digital image of the local network substation network 100 deviates by more than a threshold value from the target state data of the target pattern.

[0104] An exemplary embodiment of method 200 is explained below using a planning analysis concerning the expansion of charging infrastructure or charging stations. The analysis is intended to answer the question of whether it is feasible to install a certain number of charging stations in a specific region.

[0105] Based on this, a target pattern is provided in step 202. The target pattern can be selected from a pool of existing target patterns, which are stored, for example, in a target pattern database. The target pattern can be generated manually or automatically by an artificial intelligence-based algorithm, or it can be modified from an existing target pattern.

[0106] This defines which target status data are necessary to perform the analysis. Target status data for the charging infrastructure is defined here to ensure that sufficient electricity is available to operate charging stations in the desired region. The amount of electricity that can be provided is approximated, for example, by the maximum power that local grid stations 102 can deliver and the available capacity reserve in an area. Status data on the utilization of local grid stations 102 can provide information about the current load on the power grid. This makes it possible to determine whether the operation of additional charging stations, which represent additional loads on the power grid, would overload the power grid.

[0107] Power quality status data, such as voltage fluctuations or voltage stability, can be used to ensure that charging stations are functioning properly and that electric vehicles can be charged safely. Grid configuration status data provides information about the distribution of power lines and transformers in the vicinity of the distribution substation network. This information can help identify where additional power lines or transformer upgrades might be needed during charging infrastructure planning.

[0108] Load profiles, i.e., the temporal distribution of load in the power grid, can provide information about how electricity demand is distributed throughout the day. This is important for identifying peak loads and adjusting charging station capacity accordingly. Furthermore, the availability of power connections and the condition of the cabling can be incorporated into the analysis. Legal regulations and standards are also important to ensure that the planning of charging stations complies with the applicable regulations in the target region.

[0109] After the target pattern has been created, the target state data specified by the target pattern are determined in step 204. For example, status data of the individual local network stations 102 can be acquired based on measured values ​​using measuring devices 122, such as sensors. Furthermore, measured value-equivalent data, based, for example, on low-voltage and / or medium-voltage network peripheral data, can also be used for this purpose. Based on this, a digital image of at least part of the local network station network 100 can be generated in step 206.

[0110] The determined status data are compared with the target status data in step 208, and it is examined whether all necessary information is available. It may happen that status data necessary for an analysis, for example, concerning the utilization of a local network substation 102, is not available or could not be determined. In response, in step 210, an algorithm suitable for calculating the missing status data can be selected from an algorithm database. For example, peripheral data is checked and loaded by the algorithm. Based on the peripheral data, the algorithm completes the load flows to be completed in the requested region, thereby supplementing the digital image of the local network substation network 100.

[0111] After repeating the simulation and comparing the target state data with the state data of the digital image in step 212, it can be determined, for example, that a particular local grid station 102 cannot feed in enough power to install a certain number of charging stations in a specific region. There is therefore a discrepancy between the target state data and the state data of the digital image. Consequently, measures are proposed in step 214. One possible measure is to control a neighboring local grid station 102 to compensate for the insufficient feed-in by one local grid station 102. Another measure could be to control a completely different local grid station 102 that can provide more power.

[0112] One of these measures can be selected to enable the installation of the desired number of charging stations in a specific region. The results of the analysis can be provided to a user via a user interface, such as a smartphone application or a web interface. Based on the analysis results, the user can decide whether to implement the selected measure or whether to install fewer or no charging stations.

[0113] Although some aspects have been described in the context of a device, it is clear that these aspects also represent a description of the corresponding method, with a block or device corresponding to a method step or a function of a method step. Analogously, aspects described in the context of a method step also represent a description of a corresponding block, element, or property of a corresponding device.

[0114] Embodiments of the invention may be implemented in a computer system. The computer system may be a local computing device (e.g., a personal computer, laptop, tablet computer, or mobile phone) having one or more processors and one or more memory devices. The computer system may be a distributed computing system (e.g., a cloud computing system having one or more processors or one or more memory devices distributed at different locations, for example, at a local client and / or one or more remote server farms and / or data centers). The computer system may include any circuitry or combination of circuits. In one embodiment, the computer system may include one or more processors, which may be of any type.The term "processor" is understood to mean any type of computing circuit, such as a microprocessor, a microcontroller, a complex instruction set microprocessor (CISC), a reduced instruction set microprocessor (RISC), a very long instruction word (VLIW) microprocessor, a graphics processor, a digital signal processor (DSP), a multi-core processor, a field-programmable gate array (FPGA), or any other type of processor or processing circuit. Other types of circuitry that may be included in the computer system may be a custom-built circuit, an application-specific integrated circuit (ASIC), or the like, such as one or more circuits (e.g., a communications circuit) for use in wireless devices such as cellular phones, tablet computers, laptop computers, two-way radios, and similar electronic systems.The computer system may include one or more storage devices, which may include one or more storage elements suitable for the particular application, such as main memory in the form of random access memory (RAM), one or more hard disks, and / or one or more drives handling removable media such as CDs, flash memory cards, DVDs, and the like. The computer system may also include a display device, one or more speakers, and a keyboard and / or controller, which may include a mouse, trackball, touchscreen, voice recognition device, or any other device that allows a system user to input information to and receive information from the computer system.

[0115] Some or all of the method steps may be performed by (or using) a hardware device, such as a processor, a microprocessor, a programmable computer, or an electronic circuit. In some embodiments, one or more of the key method steps may be performed by such a device.

[0116] Depending on specific implementation requirements, embodiments of the invention may be implemented in hardware or software. The implementation may be performed using a non-volatile storage medium, such as a digital storage medium, such as a floppy disk, DVD, Blu-ray, CD, ROM, PROM and EPROM, EEPROM, or FLASH memory, on which electronically readable control signals are stored that interact (or can interact) with a programmable computer system to perform the respective method. Therefore, the digital storage medium may be computer-readable.

[0117] Some embodiments according to the invention comprise a data carrier with electronically readable control signals that can interact with a programmable computer system so that one of the methods described herein is carried out.

[0118] In general, embodiments of the present invention can be implemented as a computer program product with a program code, wherein the program code is effective for executing one of the methods when the computer program product is running on a computer. The program code can, for example, be stored on a machine-readable medium.

[0119] Further embodiments include the computer program for carrying out one of the methods described herein, which is stored on a machine-readable carrier.

[0120] In other words, an embodiment of the present invention is therefore a computer program having a program code for carrying out one of the methods described herein when the computer program runs on a computer.

[0121] Another embodiment of the present invention is a storage medium (or a data carrier or a computer-readable medium) comprising a computer program stored thereon for performing one of the methods described herein when executed by a processor. The data carrier, digital storage medium, or recorded medium is typically tangible and / or non-seamless. Another embodiment of the present invention is an apparatus as described herein, comprising a processor and a storage medium.

[0122] A further embodiment of the invention is a data stream or a signal sequence representing the computer program for carrying out one of the methods described herein. The data stream or signal sequence can, for example, be configured to be transmitted or transmittable via a data communication connection, for example, via the Internet. A further embodiment comprises a processing means, for example, a computer or a programmable logic device, configured or adapted to carry out one of the methods described herein.

[0123] A further embodiment comprises a computer on which the computer program for carrying out one of the methods described herein is installed.

[0124] A further embodiment according to the invention comprises a device or system configured to transmit (e.g., electronically or optically) a computer program for carrying out one of the methods described herein to a recipient. The recipient may, for example, be a computer, a mobile device, a storage device, or the like. The device or system may, for example, comprise a file server for transmitting the computer program to the recipient.

[0125] In some embodiments, a programmable logic device (e.g., a field-programmable gate array, FPGA) may be used to perform some or all of the functionality of the methods described herein. In some embodiments, a field-programmable gate array may cooperate with a microprocessor to perform any of the methods described herein. In general, the methods may preferably be performed by any hardware device.

Claims

CLAIMS 1. A method (200) for determining a measured value-based digital at least partial image of a local network station network (100) with a plurality of local network stations (102), the method (200) comprising: Determining (204) status data of at least one local network station (102) of the Local network substation network (100); and Generating (206) a digital at least partial image of the Local network station network (102) based on at least part of the determined status data; wherein the status data is based on measured values ​​and measured value-equivalent data of at least one local network station (102).

2. The method (200) according to claim 1, wherein the measured values ​​can be detected by a measuring device (122) assigned to the local network station (102).

3. The method (200) according to claim 1 or 2, wherein the measured value equivalent data can be derived from data describing the local network station (102) and / or one or more connections, in particular peripheral data.

4. The method (200) according to claim 3, wherein the peripheral data comprises low-voltage network-side and medium-voltage network-side peripheral data; wherein the low-voltage network-side peripheral data in particular comprises: consumer data; and / or Electricity meter reading data; and / or Consumption statistics data; and / or Environmental condition data such as temperature data, solar radiation data, wind speed and / or direction data; the medium-voltage network peripheral data includes in particular: Connection variant data; and / or Line resistance data; and / or Network infrastructure data; and / or Environmental condition data such as temperature data, solar radiation data, wind speed and / or direction data.

5. The method (200) according to any one of the preceding claims, wherein the Condition data includes: historical status data; and / or Geodesics; and / or data provided by a user.

6. The method (200) according to any one of the preceding claims, further comprising: Providing (202) at least one target pattern which defines target state data for an analysis of the local network station network (100), in particular an operation, maintenance and / or planning analysis.

7. The method (200) of claim 6, further comprising: Determining (208) that the digital image of the local network station network (100) includes insufficient status data for analysis according to the at least one target pattern; Selecting a completion algorithm from an algorithm database; and Completing (210) the state data using the selected completion algorithm.

8. The method (200) of claim 7, wherein completing the state data using the selected completion algorithm comprises: Comparing local network stations (102) of the local network station network (100).

9. The method (200) of claim 7 or 8, wherein completing the state data using the selected completion algorithm comprises: Deriving measured value equivalent data of at least one local network station (102) of the local network station network (100) from peripheral data.

10. The method (200) according to any one of the preceding claims 6-9, further comprising: Comparing (212) the target state data of the target pattern with state data of the digital image of the local network station network (100); and Deriving (214) at least one measure if the comparison shows that the status data of the digital image of the local network station network (100) deviate from the target status data of the target pattern by more than a threshold value.

11. The method (200) according to any one of the preceding claims 6-10, further comprising: Simulating a development of the status data of the digital image of the local network station network (100) compared to the target status data of the target pattern; and deriving at least one measure if the simulation shows that the status data of the digital image of the local network station network (100) will deviate from the target status data of the target pattern by more than a threshold value.

12. The method (200) according to any one of the preceding claims, wherein the generated digital image of the local network station network (100) comprises a digital image of at least some of the local network stations (102), preferably all of the local network stations (102) of the local network station network (100).

13. A data processing device configured to carry out the method (200) according to any one of claims 1-12.

14. A computer program or a computer-readable medium on which the computer program is stored, the computer program comprising instructions which, when the program is executed by a data processing device, cause the device to carry out the method (200) according to any one of claims 1-12.

15. A computer-readable data structure which represents a measured-value-based digital at least partial image of a local network station network (100) having a plurality of local network stations (102), wherein the data structure comprises status data of at least one local network station (102) of the local network station network (100), which status data are based on measured values ​​and measured-value-equivalent data of at least one local network station (102).

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