ISSN 1674-0629
CN 44-1643/TK
CN 44-1643/TK
Multi-Level Multi-Objective Collaborative Optimization Method for Distribution Network-Substation Area-End Users Considering Dynamic Comfort Intervals
Rui MA , Jiale LI , Chenhui SONG
›› 2025, Vol. 19 ›› Issue (11) : 11 -26.
Multi-Level Multi-Objective Collaborative Optimization Method for Distribution Network-Substation Area-End Users Considering Dynamic Comfort Intervals
Driven by the "dual carbon" goals and energy transition, distributed photovoltaic systems with their characteristics of "numerous points and extensive coverage" are connected to distribution networks, making power interactions between distribution network levels more complex. Traditional supply-side regulation methods struggle to meet the operational demands of multi-source collaboration and multi-objective coordination. To address this, a multi-level multi-objective collaborative optimization method for distribution networks-substation areas-users is proposed, considering dynamic comfort zones. Firstly, a multi-level structure and hierarchical scheduling framework for distribution networks, transformer areas, and users is established. The distribution network is divided into the distribution network layer, transformer area layer, and user layer. Within each layer, source-grid-load-storage resources achieve collaborative interaction, while bidirectional power transfer and information exchange occur between layers, promoting rational resource allocation and utilization. Secondly, a flexible resource model incorporating dynamic comfort zones is developed to quantify residential users′ resource regulation potential under varying electricity prices, enabling real-time adjustment of regulation boundaries. Then, a multi-level multi-objective collaborative optimization model for distribution networks-substation areas-users is formulated, comprehensively considering optimization objectives across different levels to establish a bottom-up coordination mechanism. Finally, the proposed strategy is validated through case simulations. The results demonstrate that the method effectively maximizes and utilizes source-grid-load-storage resources across all levels, significantly improving photovoltaic integration, optimizing load curves, reducing user electricity costs, and ensuring safe and economical distribution network operation
active distribution network / optimal scheduling / regulation potential / flexible resources / multi-lever scheduling
the National Natural Science Foundation of China(52307079)
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