电力系统自动化2026，Vol.50Issue(1)：29-38,10.DOI:10.7500/AEPS20241128002
面向经济高效的蜂巢状配电网优化布局与调度策略
Economically Efficient Optimization Layout and Scheduling Strategy for Honeycomb Distribution Networks
摘要
Abstract
With the advancement of the national"carbon emission peak and carbon neutrality"goal,a significant number of distributed energy sources,hybrid energy storage systems are being integrated into the distribution network.This integration has enriched the composition of distribution network elements,thereby making the exploration of new network architectures and functionalities increasingly relevant.Among these,the honeycomb distribution network has emerged as a promising new architecture due to its efficient energy dispatch and the synergistic operation of multiple microgrids.This paper proposes a streamlined hexagonal honeycomb distribution network(SHHDN)architecture optimized through the strategic placement of intelligent base stations(IBSs).Firstly,a structural model of SHHDN based on the non-Cartesian coordinate system(NCCS)is developed to determine the optimal siting of IBSs and their internal energy storage capacities.Secondly,an SHHDN dispatch model incorporating multiple IBSs is constructed based on the optimized IBS system layout.Finally,the proposed model is validated through simulation on a modified IEEE 33-bus system and a modified 97-bus system.The results demonstrate that the proposed approach effectively smooths load fluctuations,reduces network losses,and facilitates renewable energy source(RES)integration with minimal IBS investment.This study provides both theoretical support and practical guidance for the flexible planning and low-carbon operation of next-generation distribution networks.关键词
蜂巢状配电网/储能/可再生能源/选址定容/运行调度/负荷波动Key words
honeycomb distribution network/energy storage/renewable energy/siting and sizing/operation scheduling/load fluctuation引用本文复制引用
HAN Haiteng,XU Yiteng,ZU Guoqiang,CAO Shuyu,WU Chen,ZANG Haixiang..面向经济高效的蜂巢状配电网优化布局与调度策略[J].电力系统自动化,2026,50(1):29-38,10.基金项目
国家自然科学基金资助项目(52307090) （52307090）
江西省重大科技研发专项项目(20223AAE02011). This work is supported by National Natural Science Foundation of China(No.52307090)and the Major Research Special Project on Science and Technology of Jiangxi Province(No.20223AAE02011). （20223AAE02011）
