Introduction

The Helmholtz Association and its partners have developed ground-breaking modeling tools to research future energy systems. These tools are collected and made openly available to fellow researchers and to the open public by the Helmholtz Energy Computing Initiative (HECI).

Transforming the energy system so that it is secure, sustainable, and affordable is an enormous technical and societal challenge that requires complicated computer models of everything from buildings, transportation, and industry through to energy grids, energy storage, and socio-economic interactions. HECI makes the Helmholtz modeling software, data, and benchmarking datasets available to everyone for inspection, reuse, modification, and distribution following the Helmholtz Open Science principles

An open ecosystem for energy modeling has several advantages: Openness improves the transparency and reproducibility of research, thereby enhancing its scientific credibility. Energy policy can be a highly politicized and sometimes controversial area, and openness can help to build trust among policymakers and the public about the modeling results. Openness allows research institutes to share models more easily between each other, which enhances cooperation and avoids duplication of work, thus freeing resources for productive research. Finally, openness can improve the quality of models, by allowing the possibility for feedback and correction by a broad audience. 

The tools below are divided into three categories: software, data, and benchmarks. Software includes energy model frameworks and libraries for preparing and processing data. Data refers to the raw and processed datasets used by the models. Finally, benchmarks provide model data for testing different simulation and optimization methodologies.

    HECI – Model Compendium, Data and Optimization Benchmarks

    The publication HECI – Model Compendium, Data and Optimization Benchmarks provides model equations for common components of campus-scale energy supply systems. In addition, specific optimization benchmarks as well as realistic example values for all occurring model parameters and inputs, e.g., energy demand and weather data, are given. This publication is meant as a basis for model development with respect to applications related to the energy transition.

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