Computer-implemented method for energy supply structure planning and arrangement for energy supply structure planning

Abstract

The invention relates to a computer-implemented method for energy supply structure planning for providing an energy supply, in particular power grid planning, to a multitude of consumers, especially those partially designed and operable for energy generation, in which a a) Forming a multitude of groups from at least parts of the consumers according to a geographical allocation such that a group of consumers is assigned to the same, in particular predeterminable, region, b) Connecting each group via at least one data interface in such a way that data is retrieved from heterogeneous data sources containing at least some correlation with the group and is structured and provided for the respective group. c) Feeding at least parts of the structured data to at least a first module providing a simulation, in particular of load profiles and / or generation profiles, for example of PV systems, and / or at least a second module providing an analysis, in particular at least a disaggregation of the consumers per group, algorithm. d) Generating a visualization at least based on the output of the first and / or second module on a display, e) Querying an input device to determine an input, f) Repeating steps a) to e) or terminating the process based on an evaluation of the input. Furthermore, the invention relates to an arrangement for energy supply structure planning with means for carrying out the method.

Description

[0001] The invention relates to a computer-implemented method for energy supply structure planning according to the preamble of claim 1 and an arrangement for energy supply structure planning according to the preamble of claim 12.

[0002] It is well known that energy systems are changing both in terms of their consumers, for example through the increasing number of electric vehicles and heat pumps, and in terms of their generation structure, for example through the increasing number of decentralized, volatile energy generation systems, especially photovoltaics (PV). Furthermore, more and more traditional consumers are using their own PV systems and battery storage systems, thus transforming themselves from consumers into a combination of producers and consumers, also known as "prosumers." Developments on the electricity customer side can be expected to be more disruptive in the future than in the past. The previous situation, in which new consumers and changes in the consumption structure were more predictable because significant changes in the consumption structure, for example, accompanied the construction of new buildings, will therefore no longer exist.For integration into the electricity grid and for energy supply and grid planning, planning for changes in consumption and generation patterns is crucial. The significantly more disruptive changes expected in the future due to electric vehicles, heat pumps, and batteries therefore bring with them considerable uncertainties regarding the location and timing of energy consumption.

[0003] The problem of long-term energy supply structure planning at the regional level is currently solved through processes based on manual research, such as determining where new buildings are being constructed or where industry is locating, at utility companies or network operators, as well as through the involvement of technical consultants. This is, among other things, a very time-consuming and also error-prone process.

[0004] The object underlying the invention is to provide a technical solution that overcomes the disadvantages of the prior art, in particular to enable an accurate and / or effective implementation of energy supply structure planning.

[0005] This problem is solved starting from the computer-implemented method for energy supply structure planning according to the preamble of claim 1 by its characterizing features and starting from the arrangement for energy supply structure planning according to the preamble of claim 12 by its characterizing features.

[0006] In the computer-implemented method according to the invention for energy supply structure planning for providing an energy supply, in particular power grid planning, to a large number of consumers, in particular some of which are designed and operable for energy generation, a: a) Forming a multitude of groups from at least parts of the consumers according to a geographical allocation such that a group of consumers is assigned to the same, in particular predeterminable, region, b) Connecting each group via at least one data interface in such a way that data is retrieved from heterogeneous data sources containing at least some correlation with the group and is structured and provided for the respective group. c) Feeding at least parts of the structured data to at least a first module providing a simulation, in particular of load profiles and / or generation profiles, for example of PV systems, and / or at least a second module providing an analysis, in particular at least a disaggregation of the consumers per group, algorithm. d) Generating a visualization at least based on the output of the first and / or second module on a display, e) Querying an input device to determine an input, f) Repeat steps a) to e) or terminate the process based on an evaluation of the input.

[0007] The invention allows, for example, data available from a geographic information system (GIS) for a given region to be automatically connected and processed via a data interface. Furthermore, additional input parameters for various algorithms can be integrated, such as the number of heat pumps or electric vehicles. The invention also advantageously triggers simulations and algorithms sequentially and ultimately allows for a visualization of the results, which then serve as a basis for decision-making, particularly for infrastructure development (see query- and input-dependent continuation b), and provides efficient and transparent communication of the decision-making basis as well as versioning of the results.The invention thus provides a coordination of algorithms and models for regional energy system planning and optimization, as well as the creation of a common data basis for the automation of the planning process.

[0008] The energy supply structure planning according to the invention is characterized by means for carrying out the computer-implemented method and / or one of its further developments, thereby contributing to the implementation and mutatis mutandis to the realization of the advantages mentioned in connection with the dismantling support method.

[0009] The computer program product according to the invention offers the same advantages, mutatis mutandis.

[0010] Further advantageous embodiments and developments of the invention are specified in the dependent claims.

[0011] According to a further development of the computer-implemented method for energy supply structure planning according to the invention, the connection functions as automated data onboarding, wherein the structured provision is carried out in such a way that it is based at least on processing, harmonization and / or synthesis of the determined data.

[0012] Preferably, the computer-implemented method according to the invention for energy supply structure planning can be further developed in such a way that the connection is made in such a way that the data interfaces to the heterogeneous data sources, in particular designed as databases, are connected in such a way that the data includes a combination of data from a geographic information system, such as the so-called "Open Street Map", "OSM", socio-economic data, technical data on the existing infrastructure, such as the electricity grid, energy generation, building stock and the like, data on movement patterns of vehicles, data on electricity consumption, and / or data from measurements in the electricity grid, for example energy meter measurements.

[0013] In particular, the combination of these two training courses creates a harmonized data basis from heterogeneous data sources through structured provision, enabling the status quo of data relevant for energy system planning, such as distribution network planning, to be determined, for example by integrating this advantageously into a database.

[0014] According to a further development of the computer-implemented procedure for energy supply structure planning, at least the structured data provided are fed to a third module for carrying out an algorithm for energy system optimization, in particular an energy system model, for example the so-called "European model", in such a way that the output of the third module is made available for visualization.

[0015] Energy system optimization, for example according to the European model, generates a projection of the generation fleet as well as sector-coupling components, such as the electrification of the heating and transport sectors.

[0016] In a further development of the computer-implemented method according to the invention for energy supply structure planning, a first data interface, in particular a web interface, for the third module for carrying out the algorithm, for inputting data correlating to scenarios, for example CO2 reduction, technology costs or similar, and a second data interface for the third module is operated in such a way that an automated data input of existing infrastructure, weather data and / or similar is made, wherein the third module is operated in such a way that it provides a technology mix scenario, for example a number of electric vehicles and PV systems for one or more related groups, such as a federal state, region, building data, parking spaces and / or similar, for visualization from the data of the first and second data interfaces.

[0017] In a further development of the computer-implemented method according to the invention for energy supply structure planning, the algorithm for the analysis is carried out as disaggregation in such a way that a third data interface, in particular a web interface for inputting consumer-related data, is used, and a fourth data interface is operated for the second module in such a way that automated data input is made from the technology mix scenarios output by the third module, wherein the first module performs a disaggregation of consumption, for example to building data and industrial sites, and provides projected locations according to technology, such as electric vehicle, photovoltaics, battery, heat pump, heat storage and / or comparable consumer technologies, for visualization.

[0018] In a further development, the computer-implemented method according to the invention for energy supply structure planning is further developed such that a fifth data interface, in particular a web interface, is used for the first module for performing the simulation of load profiles for inputting parameters, and a sixth data interface is operated for the first module in such a way that automated data input is made via the locations of consumers, in particular at the building level, traffic flow measurements and / or other parameters correlating with the load, wherein the third module is operated in such a way that it provides a load profile for each type of consumer and each location of the respective consumer for visualization as output from the data of the fifth and sixth data interfaces.

[0019] This allows for the simulation of load profiles, such as those for e-mobility, by inputting parameters such as assumed charging behavior, like tariff-optimized charging. In this context, as in the other advanced developments, "input" can mean that the respective data is transmitted and / or obtained from a source, particularly a temporarily connected one, at the instigation of a user. In conjunction with the automated data input via the data interface according to the invention, the system can then already know the locations of charging stations and other technologies, such as building-level heat pumps, traffic flow measurements, etc., so that an accurate projection of the load profiles for each technology and each technology location can be performed.

[0020] According to a further development of the computer-implemented method according to the invention, the connection is made via the at least one data interface such that, as data sources containing data that correlate with the group, at least parts of the outputs of the first, second, third, and / or fourth modules are also operated. This ultimately provides a unified data interface / data model to which, particularly after data onboarding, various algorithms can access modularly, and the results of the algorithms can also be stored centrally via the modules that operate the algorithms, particularly in an at least assigned and / or integrated database. This enables and supports further automation of the overall process.

[0021] According to a further development of the computer-implemented method for energy supply structure planning according to the invention, at least the structured data provided are fed to a fourth module for carrying out an algorithm for grid expansion planning, in particular a so-called "Grid Module", in such a way that the output of the third module is provided.

[0022] According to a further development of the computer-implemented method for energy supply structure planning according to the invention, the algorithm for network expansion planning is carried out in such a way that a seventh data interface, in particular a web interface for inputting cost-related data, especially technology costs, for example the investment expenditures also referred to as "Capital Expenditure", CAPEX, and / or the operating costs also referred to as "Operational Expenditure", OPEX, is used, and an eighth data interface for the fourth module is operated in such a way that automated data input is made from the technology mix scenarios output by the third module, wherein the fourth module determines network expansion proposals for each technology mix scenario and provides them as output for visualization.

[0023] In particular, combining these training programs enables at least partially automated network expansion planning, allowing planners to be provided with a suitable selection for visualization. This selection can be refined or directly chosen through user input, enabling the selection of the energy supply structure plan and its implementation. Key parameters for the plans, such as asset costs, are taken into account and used in conjunction with data from sources like data onboarding, data relating to the status quo of a network, and / or data projected through simulation, such as data from a Grid Model Builder. This results in a network layout plan for at least one scenario, thus providing a visualization of at least one energy supply structure plan for selection and / or fine-tuning.

[0024] According to a further development of the computer-implemented method for energy supply structure planning, the visualization is formed on the basis of the data in such a way that the structured data provided are obtained from the first, second, third and / or fourth module, whereby at least parts of the outputs of the first, second and / or third module are fed to the fourth module.

[0025] In a further development of the computer-implemented method for energy supply structure planning according to the invention, the visualization is generated in such a way that a ninth data interface is operated in such a way that an automated data input is obtained from the first, second, third and / or fourth module, wherein at least parts of the outputs of the first, second and / or third module are fed to the fourth module, and are provided as output for the visualization in such a way that the steps are repeated at least twice until the process is completed.

[0026] By repeating the process at least twice, the visualization according to the invention is provided in such a way that the simulations and analyses obtained through sequential calling of the modules can be used to present the results for interactive exploration via the automated data interface, for example, of network expansion measures and / or causes of problems, such as high simultaneity of heat pumps and electric vehicles in a network string without batteries, which can lead to thermal overload of the line or substation in the scenarios under consideration.

[0027] The further developments of the inventive method, or the inventive method itself, which are partly exemplified here for electricity distribution networks, are not limited to this. Rather, they can also be applied analogously to other infrastructure planning, for example, for heat networks, or carried out in conjunction with them.

[0028] Further advantages and details of the invention, as well as further developments of the invention, are explained in more detail below with reference to an exemplary embodiment shown in the single figure. It shows the Figure (FIG) schematically shows an exemplary process for controlling a large number of heat pumps operated locally distributed in a network according to one of the possible embodiments of the method according to the invention.

[0029] The embodiment described below in the figure (FIG) is a preferred embodiment, the advantages of which, as well as further embodiments or developments of the invention, are explained in more detail.

[0030] In particular, the following explanations merely show exemplary implementation possibilities of how such implementations of the teaching according to the invention could look, since it is impossible and also not helpful or necessary for understanding the invention to name all these implementation possibilities.

[0031] Furthermore, a person skilled in the art, with knowledge of the independent claims, will of course be aware of all the possibilities for realizing the invention that are customary in the prior art, so that in particular there is no need for a separate disclosure in the description.

[0032] In the exemplary embodiment(s), the described components of the embodiments each represent individual features of the invention that can be considered independently of one another, which further develop the invention independently of one another and can therefore be regarded as part of the invention individually or in a combination other than that shown.

[0033] Furthermore, the described embodiments can also be supplemented by further features of the invention already described.

[0034] The single figure FIG schematically shows a sequence of a first embodiment of the method as well as an embodiment of the arrangement of the invention carrying out the method.

[0035] It can be seen that, according to the exemplary embodiment, in a first step S1, data from various data sources 1 is onboarded. According to the exemplary embodiment, the data from the various sources converge at a data onboarding interface 2. This interface is functionally connected to, or used by, a data processing module 3, such that the data from the various sources are harmonized so that they are available in a database 4 for further steps of the exemplary embodiment of the method. For example, the further modules and steps are served via a data interface 5 or several, possibly distributed, data interfaces.

[0036] Another module, which is assigned to the first step S1 of the procedure according to the exemplary embodiment, is a network module planner 6, with which, via the data interface 5 and in particular with the harmonized data from the database 4, an integration of the data to an existing infrastructure, i.e. the status quo, is created, in particular through further data such as energy statistics (for example supply and demand).

[0037] Furthermore, it can be seen that in a second step S2, an energy demand and technology mix projection is carried out by an energy system modeling module 7, whereby any further data required for this can be provided for the modeling via an initial data input option 8, for example via a web interface. As can be seen, the second step S2 and its modules 7 and 8 access status quo data via data interface 5.

[0038] Via this data interface 5, the third step S3 also gains access to the status quo, and optionally also to the results stored in database 4 by the second step S2 via data interface 5, in order to begin the so-called disaggregation of the projection scenarios. For this purpose, the data, according to an exemplary embodiment of the method according to the invention, are made available to a module that executes an algorithm 1, which performs a disaggregation of the technologies, loads, generators, and other corresponding entities of the projection at the level of geographical regions, for example, the building level, so that they are available for a fourth step S4 for the simulation of load profiles, optionally alongside other modules.This fourth step S4 is performed, for example, on an agent-based simulation and can access database 4 via data interface 5, thus accessing further information necessary for this step S4. Furthermore, it may be provided, and in the exemplary embodiment is, that data can be entered via a second data input 9, in particular a web interface. This can, as with the first data input 8, be triggered by an input prompt and / or passed as a parameter, for example, when calling the module.

[0039] This is followed by a fifth step, S5, which can be described as a network expansion step. In this step, a model for distribution network expansion planning is generated based on at least some of the data previously generated via data interface 5 and database 4, as well as data determined through onboarding. Further data can also be entered here via the second data input, which is primarily implemented via a web interface.

[0040] This step S5 is followed by a sixth step S6, which visualizes the results from the fifth step S5, as well as, if applicable, results from other algorithms, simulations, and / or the status quo, all obtained via data interface 5. This can result in the visualization of several available options, from which a user can then trigger a selection and / or a further iteration of one or more of the steps S1...S5 by inputting a value, until ultimately a distribution network can be visualized and implemented.

[0041] The advantages will become clear below based on the details of the exemplary implementation, some of which are presented in different words, as well as on alternative further developments: The described embodiment, and thus at least partially also the arrangement and method according to the invention, are characterized by the fact that it enables the digitization of the planning process in order to make the best data-driven decisions for the expansion of the energy supply infrastructure.

[0042] The exemplary embodiments therefore disclose a platform or a computer-implemented method that automatically connects and processes data (including geographic information system data) for the respective region via a data interface. Further input parameters for various algorithms can be integrated, such as the number of heat pumps, the number of electric vehicles, etc. Simulations and algorithms are triggered sequentially, and the results are visualized. These results then serve as a basis for infrastructure development decisions and can provide efficient and transparent communication of the decision-making process, as well as versioning of the results. At the heart of the invention is the coordination of algorithms and models for regional energy system planning and optimization, and the creation of a common data foundation for automating the planning process.

[0043] The regional data can encompass any type of data, such as data from a geographic information system, socioeconomic data, technical data on existing infrastructure, particularly regarding the power grid, energy generation and / or building stock, etc., vehicle movement patterns, electricity consumption, measurements in the power grid, and increasingly, energy meter readings. According to the invention, this data is efficiently connected to the platform via, for example, an API, enabling automated data updates, such as when the number of electric vehicles in the region changes. For this purpose, an interface to the website of the Federal Motor Transport Authority or similar could be considered as part of the API. To achieve this, the invention has a modular design and is capable of connecting a wide variety of data sources through suitable data interfaces.The invention is also capable of working with incomplete data, and it allows for the continuous integration and updating of more data over time to improve the basis for decision-making. After processing, the data is stored in a database and made available to various algorithms via the data interface. This ensures a consistent data foundation for all tools, models, and algorithms involved in the planning process.

[0044] Regarding scenario-specific input parameters and / or input parameters for specific algorithms, such as a required minimum distance between public charging stations in the case of charging infrastructure allocation, these are also made available to the algorithms via a data interface. The user can enter these, for example, via a visualization interface within the visualization process, either alternatively or additionally via a web interface.

[0045] The invention, or its embodiments, combines various algorithms for regional energy system planning, which can access the common data basis via the data interface. Furthermore, according to the invention, the data output of one algorithm can be reused as input for the next.

[0046] The following algorithms, especially for simulation, can be included, among others: • Analysis algorithms for optimal decision-making in generation structure and grid expansion planning, • Algorithms for the spatial and temporal disaggregation of data / technologies, for example energy consumption, number of vehicles, etc., algorithms for the optimal placement of technologies (e.g. charging infrastructure), • Projection models for technology penetration rates, energy system optimization models, • Algorithms for data synthesis, for example for filling data gaps, simulations of energy consumption / generation, especially spatially and temporally resolved, “Grid Model Builder” (network model) • -Planner for modeling distribution network topologies, etc.

[0047] Finally, the last step of the visualization process provides an interface to the user in infrastructure planning, for example, at the municipal utility, energy supplier, or network operator. A change in parameters at this stage can trigger a new calculation to create an updated basis for decision-making with the updated input parameters.

[0048] A more detailed implementation example, specifically one related to e-mobility, could be presented as follows, or, in other words, expressed as follows: First step S1: Automated data onboarding, processing, harmonization and synthesis ◯ Input: Databases (e.g., "OpenStreetMap" / OSM) ◯ Output: Harmonised data basis that integrates the status quo of data relevant for energy system planning (here distribution network planning) into a database.

[0049] Second step S2: Energy system optimization (e.g. European model) provides a projection of the generation fleet, as well as sector-coupling components (electrification of the heating and transport sectors) ◯ Data input via web interface: Scenarios (e.g. CO2 reduction, technology costs) ◯ Automated data input via data interface: existing infrastructure, weather data, etc. ◯ Output: Technology mix scenario (e.g., number of electric vehicles and PV systems for an entire region (e.g., federal state))

[0050] Third step S3: Disaggregation ◯ Data input via web interface (e.g. minimum distance between public charging stations) ◯ Automated data input via data interface: Technology mix scenarios from the previous step for the region under consideration, building data, parking spaces, etc. ◯ Consumption disaggregation is carried out, for example, using building data and industrial sites (from GIS) ◯ Output: Projected locations of all technologies (e.g., EV, PV, battery, heat pump, heat storage) in the region

[0051] Fourth step S4: Simulation of load profiles (exemplified here only using eMobility as an example) ◯ Data input via web interface: Parameters for the assumed charging behavior (e.g. tariff-optimized charging) ◯ Automated data input via data interface: Locations of charging stations (and other technologies, e.g. heat pumps at building level), traffic flow measurements, etc. ◯ Output: Load profiles for each technology and technology location

[0052] Fifth step S5: Network expansion planning ◯ Data input via web interface: Costs for assets ◯ Automated data input via data interface: Network data (e.g., from Grid Model Builder or real data via data onboarding, technology locations, and associated load profiles from the previous step) ◯ Output: Network expansion proposals per scenario

[0053] Sixth step S6: Visualization ◯ Input from previous simulations via automated data interface ◯ Output: Presentation of the results of the interactive exploration of the grid expansion measures and the investigation of the causes (e.g. high simultaneity of heat pumps and EVs in a grid string without batteries, which usually leads to thermal overload of the line or substation in the scenarios considered)

[0054] The processing steps shown here as an example for electricity distribution networks can also be applied analogously to other infrastructure planning projects, such as heat networks, or carried out in conjunction with them.

[0055] Features and advantages of the exemplary embodiments include, among others: - Data-driven planning - Integration of many different data sources via a suitable interface - A platform that allows for continuous updates to the plan - Standardized solution for planning - Use of simulation tools and algorithms for planning - Visual presentation of the results - The planner can interact with the results in the platform, for example by selecting detailed views, initiating recalculations, and manually adding new data points (e.g., geodata points). - The invention makes available a digital representation of the energy system, including end consumers, decentralized producers, and prosumers. - Projection of the development of the energy system including end consumers, decentralized producers and prosumers (also broken down to building / street level) - High-resolution planning (street or building level) - Inclusion of statistical analyses to deal with the uncertainties of the projections.

[0056] Regardless of the grammatical gender of a particular term, persons with male, female or other gender identities are included.

Claims

[1] Computer-implemented method for energy supply structure planning for the provision of an energy supply, in particular electricity grid planning, to a large number of consumers, in particular some of which are designed and operable for energy generation, characterized by the following steps: a) Forming a multitude of groups from at least parts of the consumers according to a geographical allocation such that a group of consumers is assigned to the same, in particular predeterminable, region, b) Connecting each group via at least one data interface in such a way that data is retrieved from heterogeneous data sources containing at least some correlation with the group and is structured and provided for the respective group. c) Feeding at least parts of the structured data to at least a first module providing a simulation, in particular of load profiles and / or generation profiles, for example of PV systems, and / or at least a second module providing an analysis, in particular at least a disaggregation of the consumers per group, algorithm. d) Generating a visualization at least based on the output of the first and / or second module on a display, e) Querying an input device to determine an input, f) Repeat steps a) to e) or terminate the process based on an evaluation of the input. [2] Computer-implemented method for energy supply structure planning according to the preceding claim, characterized bythat the connection functions as automated data onboarding, whereby the structured provision is carried out in such a way that it is based at least on processing, harmonization and / or synthesis of the determined data. [3] Computer-implemented method for energy supply structure planning according to the preceding claim, characterized by, that the connection is made in such a way that the data interfaces to the heterogeneous data sources, in particular those designed as databases, are connected in such a way that the data includes a combination of data from a geographic information system, for example the so-called "Open Street Map", "OSM", socio-economic data, technical data on the existing infrastructure, for example the electricity grid, energy generation, building stock and the like, data on movement patterns of vehicles, data on electricity consumption, and / or data from measurements in the electricity grid, for example energy meter measurements. [4] Computer-implemented method for energy supply structure planning according to one of the preceding claims, characterized by, that at least the structured data provided are fed to a third module for carrying out an algorithm for energy system optimization, in particular an energy system model, for example according to the so-called “European model”, in such a way that the output of the third module is made available for visualization. [5] Computer-implemented method for energy supply structure planning according to the preceding claim, characterized by, that for the third module for implementing the algorithm, a first data interface, in particular a web interface for inputting data correlating to scenarios, for example CO2 reduction, technology costs or similar, and for the third module a second data interface is operated in such a way that an automated data input of existing infrastructure, weather data and / or similar is provided, wherein the third module is operated in such a way that it provides a technology mix scenario, for example a number of electric vehicles and PV systems for one or more related groups, such as a federal state, a region, building data, parking spaces and / or similar, for visualization from the data of the first and second data interfaces. [6] Computer-implemented method for energy supply structure planning according to the preceding claim, characterized by, that the algorithm for the analysis is carried out as disaggregation in such a way that a web interface for inputting consumer-related data is used as a third data interface, and a fourth data interface is operated for the second module in such a way that automated data input is made from the technology mix scenarios output by the third module, wherein the first module performs a disaggregation of consumption, for example into building data and industrial sites, and provides projected locations according to technology, such as electric vehicle, photovoltaics, battery, heat pump, heat storage and / or comparable consumer technologies, for visualization. [7] Computer-implemented method for energy supply structure planning according to the preceding claim, characterized by, that for the first module for carrying out the simulation of load profiles, a fifth data interface, in particular a web interface for inputting parameters, is used, and for the first module a sixth data interface is operated in such a way that automated data input about locations of consumers, in particular at building level, traffic flow measurements and / or other parameters correlating with the load, is provided, wherein the third module is operated in such a way that it provides a load profile for each type of consumer and each location of the respective consumer for visualization as output from the data of the fifth and sixth data interfaces. [8] Computer-implemented method for energy supply structure planning according to one of the preceding claims, characterized by, that at least the structured data provided are fed to a fourth module for carrying out an algorithm for network expansion planning, in particular a so-called “Grid Module”, in such a way that the output of the third module is provided. [9] Computer-implemented method for energy supply structure planning according to the preceding claim, characterized by, that the algorithm for network expansion planning is implemented in such a way that a seventh data interface, in particular a web interface, is used for inputting cost-related data, in particular technology costs, for example the investment expenditures also referred to as "Capital Expenditure", CAPEX, and / or the operating costs also referred to as "Operational Expenditure", OPEX, and for the fourth module an eighth data interface is operated in such a way that automated data input is made from the technology mix scenarios output by the third module, wherein the fourth module determines network expansion proposals for each technology mix scenario and provides them as output for visualization. [10] Computer-implemented method for energy supply structure planning according to one of the preceding claims, characterized by, that the connection is made via at least one data interface in such a way that, as data sources containing at least data correlating with the group, at least parts of the outputs of the first, second, third and / or fourth module are also operated. [11] Computer-implemented method for energy supply structure planning according to one of the preceding claims, characterized by , that the visualization is formed on the basis of the data in such a way that the structured data provided is obtained from the first, second, third and / or fourth module, whereby at least parts of the outputs of the first, second and / or third module are fed to the fourth module. [12] Computer-implemented method for energy supply structure planning according to the preceding claim, characterized by, that the visualization is generated in such a way that a ninth data interface is operated in such a way that an automated data input is obtained from the first, second, third and / or fourth module, whereby at least parts of the outputs of the first, second and / or third module are fed to the fourth module, and are provided as output for the visualization in such a way that the repetition of the steps until the end of the process occurs at least twice. [13] Order on energy supply structure planning characterized by Means for carrying out the computer-implemented method according to one of the preceding claims. [14] Computer program product which is executed in a processor and performs the method according to any one of claims 1 to 12.

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