Open Power System Data - Frictionless data for electricity system modelling

The quality of electricity system modelling heavily depends on the input data used. Although a lot of data is publicly available, it is often dispersed, tedious to process and partly contains errors. We argue that a central provision of input data for modelling has the character of a public good: it reduces overall societal costs for quantitative energy research as redundant work is avoided, and it improves transparency and reproducibility in electricity system modelling. This paper describes the Open Power System Data platform that aims at realising the efficiency and quality gains of centralised data provision by collecting, checking, processing, aggregating, documenting and publishing data required by most modellers. We conclude that the platform can provide substantial benefits to energy system analysis by raising efficiency of data pre-processing, providing a method for making data pre-processing for energy system modelling traceable, flexible and reproducible and improving the quality of original data published by data providers.Comment: This is the postprint version of the articl

Integrated Techno-Economic Power System Planning of Transmission and Distribution Grids

The energy transition towards renewable and more distributed power production triggers the need for grid and storage expansion on all voltage levels. Today’s power system planning focuses on certain voltage levels or spatial resolutions. In this work we present an open source software tool eGo which is able to optimize grid and storage expansion throughout all voltage levels in a developed top-down approach. Operation and investment costs are minimized by applying a multi-period linear optimal power flow considering the grid infrastructure of the extra-high and high-voltage (380 to 110 kV) level. Hence, the common differentiation of transmission and distribution grid is partly dissolved, integrating the high-voltage level into the optimization problem. Consecutively, optimized curtailment and storage units are allocated in the medium voltage grid in order to lower medium and low voltage grid expansion needs, that are consequently determined. Here, heuristic optimization methods using the non-linear power flow were developed. Applying the tool on future scenarios we derived cost-efficient grid and storage expansion for all voltage levels in Germany. Due to the integrated approach, storage expansion and curtailment can significantly lower grid expansion costs in medium and low voltage grids and at the same time serve the optimal functioning of the overall system. Nevertheless, the cost-reducing effect for the whole of Germany was marginal. Instead, the consideration of realistic, spatially differentiated time series led to substantial overall savings

Indicator for the current and future socio-ecological burden caused by the expansion of wind energy in German districts - auxiliary values

The table contains the population and the size of the total area for each German district as of 2013. Furthermore it contains the size of those areas per district, that potentially could be used for wind energy. The data on the population is provided by the Federal Statistical Office and the statistical Offices of the Länder: © Federal Statistical Office and the statistical Offices of the Länder, Regionaldatenbank Deutschland, December 2014, Datenlizenz by-2-0 (https://www.govdata.de/dl-de/by-2-0) (data was changed). The total district area is derived from geo data provided by the Federal Agency for Cartography and Geodesy: © GeoBasis-DE / BKG 2014 (data was changed). For further information on potential areas see VerNetzen Degel, M., Christ, M., Grünert, J., Becker, L., Wingenbach, C., Soethe, M., Bunke, W.-D., Mester, K., und Wiese, F. (2016). VerNetzen: Sozial-ökologische und technisch-ökonomische Modellierung von Entwicklungspfaden der Energiewende. IZT Berlin, Europa-Universität Flensburg, Deutsche Umwelthilfe e.V., pp. 105-109. Deutsch: Die Tabelle umfasst die Bevölkerungsanzahl und Flächengröße je deutschem Landkreis für das Jahr 2013. Außerdem ist die Größe jener Fläche angegeben, die potentiell für die Windenergie genutzt werden könnte. Die Bevölkerungszahlen werden von den Statistischen Ämtern des Bundes und der Länder zur Verfügung gestellt: © Statistische Ämter des Bundes und der Länder, Regionaldatenbank Deutschland, Dezember 2014, Datenlizenz by-2-0 (https://www.govdata.de/dl-de/by-2-0) (Daten geändert). Die Landkreisflächen werden auf Grundlage von Geodaten des Bundesamtes für Kartographie und Geodäsie berechnet: © GeoBasis-DE / BKG 2014 (Daten geändert). Für weitere Informationen bzgl. der Potentialflächen siehe VerNetzen Degel, M., Christ, M., Grünert, J., Becker, L., Wingenbach, C., Soethe, M., Bunke, W.-D., Mester, K., und Wiese, F. (2016). VerNetzen: Sozial-ökologische und technisch-ökonomische Modellierung von Entwicklungspfaden der Energiewende. IZT Berlin, Europa-Universität Flensburg, Deutsche Umwelthilfe e.V., S. 105-109

(Fl)ensburg (En)ergy (S)cenarios - open_eGo Scenarios for 2014/2035/2050

This Dataset includes scenarios for Germany and its electrically neighbouring countries for the application renpassG!S in order to calculate an electrical power system on a hourly basis. For the project open_eGo (Open Electricity Grid Optimization) three scenarios are defined and used for a following power flow simulations. Apart from one SQ scenario representing the electrical energy system in Germany in 2014, two future scenarios are defined via exogenous assumptions for the German power system in 2035 and at 100% renewable energy. The 2035 scenario is based on publicly available information and methods of the Netzentwicklungsplan (NEP) Strom 2025, erster Entwurf. Out of several NEP scenarios, the so-called "B1-2035" is chosen, which is characterized by a high renewable energy expansion and an increased share of natural gas. The third scenario pictures a future electrical energy system powered by 100% from renewable energy and is mainly based on the 100% RES scenario of the eHighway2050 - Modular Development Plan of the Pan-European Transmission System 2050. A detailed description of the scenarios, assumptions and sources is part of the readme file