{'fraction_non_alphanumeric': 0.010834926704907584, 'fraction_numerical': 0.0, 'mean_word_length': 5.330645161290323, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Simulation of disaggregated load profiles and construction of a proxy-microgrid for modeling purposes

Expanding the deployment of small scale renewable energy technologies such as photovoltaic has implications on how much of consumers' load has to be supplied by the electricity grid. The actual impact depends on the local resource potential as well as on the specific regional composition of consumers. It is therefore important to take into consideration geospatial aspects when modeling energy systems. However, both spatially explicit renewable energy supply data as well as spatially disaggregated load profiles are often unavailable. Hence, we propose a methodology which combines statistical data on the distribution of electricity consumers with standardized load profiles. We estimate the demand load profiles for the distribution grid on a grid cell level of one square kilometer. Due to lack of data on the actual distribution grid, we generate proxy-microgrids representing the distribution grid by using a heuristic which matches the known number of distribution grid transformers to grid cells. We apply the methodology to the Austrian region of Vorarlberg. It will enable researchers to use the results generated as an input into energy system models studying the integration of renewable energy technologies. In order to validate the methodology we estimate the load profiles for whole Austria and compare it to real data. The modeling approach can reproduce historically measured load profiles and the number of transformers in the distribution grid.