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

Different energy systems are generally planned and operated independently, which result in the low energy utilization, weak self-healing ability, and low system reliability. Therefore, an adaptive clustering-based hierarchical layout optimization 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 optimization model is formulated as to find the modified minimum spanning tree of regional integrated energy system and multi-regional integrated energy systems respectively, to construct an economical and reliable interconnection network. Finally, the effectiveness of the optimization model and strategy is verified by simulations.