4.5 Article

Adaptive clustering-based hierarchical layout optimisation for large-scale integrated energy systems

期刊

IET RENEWABLE POWER GENERATION
卷 14, 期 17, 页码 3336-3345

出版社

INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-rpg.2020.0105

关键词

trees (mathematics); distributed power generation; optimisation; power system interconnection; power system simulation; power generation reliability; power distribution reliability; multiregional integrated energy systems; large-scale integrated energy system; low energy utilisation; low system reliability; energy balance; adaptive clustering partition method; energy hubs; multiple regional integrated energy systems; hierarchical layout optimisation; self-healing ability; transmission losses; construction costs; load moments; distributed generation; spanning tree; economical interconnection network; reliable interconnection network

资金

  1. National Key R&D Program of China [2017YFE0112400]
  2. European Union [734796]
  3. Marie Curie Actions (MSCA) [734796] Funding Source: Marie Curie Actions (MSCA)

向作者/读者索取更多资源

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.

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