SimBench—A Benchmark Dataset of Electric Power Systems to Compare Innovative Solutions Based on Power Flow Analysis

Steffen Meinecke, Džanan Sarajlić, Simon Ruben Drauz, Annika Klettke, Lars-Peter Lauven, Christian Rehtanz, Albert Moser and Martin Braun
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Steffen Meinecke: Department of Energy Management and Power System Operation (e 2 n), University Kassel, 34121 Kassel, Germany
Džanan Sarajlić: Institute for Energy Systems, Energy Efficiency and Energy Economy (ie 3 ), TU Dortmund University, 44227 Dortmund, Germany
Simon Ruben Drauz: Fraunhofer Institute for Energy Economics and Energy System Technology (IEE), 34119 Kassel, Germany
Annika Klettke: Institute of Power Systems and Power Economics (IAEW), RWTH Aachen University, 52062 Aachen, Germany
Lars-Peter Lauven: Department of Energy Management and Power System Operation (e 2 n), University Kassel, 34121 Kassel, Germany
Christian Rehtanz: Institute for Energy Systems, Energy Efficiency and Energy Economy (ie 3 ), TU Dortmund University, 44227 Dortmund, Germany
Albert Moser: Institute of Power Systems and Power Economics (IAEW), RWTH Aachen University, 52062 Aachen, Germany
Martin Braun: Department of Energy Management and Power System Operation (e 2 n), University Kassel, 34121 Kassel, Germany

Energies, 2020, vol. 13, issue 12, 1-19

Abstract: Publicly accessible, elaborated grid datasets, i.e., benchmark grids, are well suited to publish and compare methods or study results. Similarly, developing innovative tools and algorithms in the fields of grid planning and grid operation is based on grid datasets. Therefore, a general methodology to generate benchmark datasets and its voltage level dependent implementation is described in this paper. As a result, SimBench, a comprehensive dataset for the low, medium, high and extra-high voltage level, is presented. Besides grids that can be combined across several voltage levels, the dataset offers an added value by providing time series for a whole year as well as future scenarios. In this way, SimBench is applicable for many use cases and simplifies reproducing study results. As proof, different automated algorithms for grid planning are compared to show how to apply SimBench and make use of it as a simulation benchmark.

Keywords: benchmark grid; grid planning; grid operation; grid generation methodology; comparability; reproducibility; time series; future scenarios (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

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