Open AccessAdaptive clustering‐based hierarchical layout optimisation for large‐scale integrated energy systems
Author(s) -
Guo Hui,
Shi Tianling,
Wang Fei,
Zhang Lijun,
Lin Zhengyu
Publication year - 2020
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/iet-rpg.2020.0105
Subject(s) - cluster analysis , computer science , partition (number theory) , interconnection , energy (signal processing) , distributed computing , scale (ratio) , reliability (semiconductor) , hierarchical clustering , reliability engineering , mathematical optimization , engineering , mathematics , artificial intelligence , quantum mechanics , computer network , power (physics) , statistics , physics , combinatorics
Different energy systems are generally planned and operated independently, which result in the low energy utilisation, weak self‐healing ability and low system reliability. Therefore, an adaptive clustering‐based hierarchical layout optimisation method is proposed for a large‐scale integrated energy system, considering energy balance, transmission losses and construction costs. First, an adaptive clustering partition method based on energy balance and load moments is proposed to determine the optimal location of energy hubs and to allocate each distributed generation and load to different energy hubs, forming multiple regional integrated energy systems adaptively. Then, the proposed hierarchical layout optimisation model is formulated as to find the modified minimum spanning tree of the regional integrated energy system and multi‐regional integrated energy systems, respectively, to construct an economical and reliable interconnection network. Finally, the effectiveness of the optimisation model and strategy is verified by simulations.