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Heuristic optimisation for automated distribution system planning in network integration studies
Author(s) -
Scheidler Alexander,
Thurner Leon,
Braun Martin
Publication year - 2018
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
ISSN - 1752-1424
DOI - 10.1049/iet-rpg.2017.0394
Subject(s) - computer science , smart grid , control reconfiguration , probabilistic logic , system integration , grid , network planning and design , heuristic , distributed computing , systems engineering , artificial intelligence , engineering , embedded system , computer network , mathematics , geometry , electrical engineering , operating system
Network integration studies try to assess the impact of future developments, such as the increase of Renewable Energy Sources or the introduction of Smart Grid Technologies, on large‐scale network areas. Goals can be to support strategic alignment in the regulatory framework or to adapt the network planning principles of Distribution System Operators. This study outlines an approach for the automated distribution system planning that can calculate network reconfiguration, reinforcement and extension plans in a fully automated fashion. This allows the estimation of the expected cost in massive probabilistic simulations of large numbers of real networks and constitutes a core component of a framework for large‐scale network integration studies. Exemplary case study results are presented that were performed in cooperation with different major distribution system operators. The case studies cover the estimation of expected network reinforcement costs, technical and economical assessment of smart grid technologies and structural network optimisation.

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