TY  - JOUR
A1  - Bayer, Daniel
A1  - Pruckner, Marco
T1  - A digital twin of a local energy system based on real smart meter data
T2  - Energy Informatics
N2  - The steadily increasing usage of smart meters generates a valuable amount of high-resolution data about the individual energy consumption and production of local energy systems. Private households install more and more photovoltaic systems, battery storage and big consumers like heat pumps. Thus, our vision is to augment these collected smart meter time series of a complete system (e.g., a city, town or complex institutions like airports) with simulatively added previously named components. We, therefore, propose a novel digital twin of such an energy system based solely on a complete set of smart meter data including additional building data. Based on the additional geospatial data, the twin is intended to represent the addition of the abovementioned components as realistically as possible. Outputs of the twin can be used as a decision support for either system operators where to strengthen the system or for individual households where and how to install photovoltaic systems and batteries. Meanwhile, the first local energy system operators had such smart meter data of almost all residential consumers for several years. We acquire those of an exemplary operator and discuss a case study presenting some features of our digital twin and highlighting the value of the combination of smart meter and geospatial data.
KW  - digital twin
KW  - simulation
KW  - local energy system
KW  - decision support system
KW  - smart meter data utilization
KW  - future energy grid exploration
Y1  - 2023
UR  - https://opus.bibliothek.uni-wuerzburg.de/frontdoor/index/index/docId/35745
UR  - https://nbn-resolving.org/urn:nbn:de:bvb:20-opus-357456
VL  - 6
ER  -