
1.上海交通大学电气工程学院,上海市 200240
2.上海交通大学国家电投智慧能源创新学院,上海市 200240
Received:20 January 2026,
Revised:2026-06-15,
Online First:29 September 2026,
Published:10 December 2026
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朱宇潇,谢宁,宋依群等.多时间尺度场景下考虑多维柔性负荷响应的源荷储协同规划[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20260120005.
ZHU Yuxiao,XIE Ning,SONG Yiqun,et al.Source-Load-Storage Coordinated Planning Considering Multi-dimensional Flexible Load Responses in Multi-time-scale Scenarios[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20260120005.
朱宇潇,谢宁,宋依群等.多时间尺度场景下考虑多维柔性负荷响应的源荷储协同规划[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20260120005. DOI:
ZHU Yuxiao,XIE Ning,SONG Yiqun,et al.Source-Load-Storage Coordinated Planning Considering Multi-dimensional Flexible Load Responses in Multi-time-scale Scenarios[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20260120005. DOI:
为了在新型配电系统规划中兼顾不同时间尺度的场景,考虑不同柔性负荷的运行特点,文中基于多时间尺度场景,提出考虑多维柔性负荷响应的新型配电系统源荷储协同规划方法。根据负荷时空自相似性生成规划年负荷场景,结合风光出力场景,构建了基于分形理论的规划场景生成方法。通过序列分段特征表示方法,根据年持续净负荷曲线生成运行场景。综合考虑3类柔性负荷,构建了计及多维柔性负荷响应的源荷储协同容量规划模型。上层以储能容量投资成本最小为目标,以储能装机容量为约束;下层以变电站运维成本、购电成本、储能运行成本、弃风弃光惩罚成本及需求响应补偿成本之和最小为目标,以功率平衡、储能和柔性负荷运行特性为约束。通过对实际地区配电网的算例研究,验证了所提方法的有效性。
In order to balance different time-scale scenarios in the planning of the new distribution system
and considering the operation characteristics of various flexible loads
this article proposes a new source-load-storage coordinated planning method for the distribution system based on multi-time-scale scenarios
which takes into account the responses of multi-dimensional flexible loads. According to the spatiotemporal self-similarity of the load
the planning annual load scenarios are generated
and combined with the wind and solar power output scenarios
a planning scenario generation method based on fractal theory is constructed. Through the sequence segmentation feature representation method
the operation scenarios are generated based on the annual continuous net load curve. Considering three types of flexible loads comprehensively
a source-load-storage coordinated capacity planning model considering the responses of multi-dimensional flexible loads is constructed. The upper layer aims to minimize the investment cost of energy storage capacity
with the installed energy storage capacity serving as a constraint. The lower layer aims to minimize the sum of substation operation and maintenance costs
electricity purchase costs
energy storage operating costs
penalties for curtailed wind and solar power
and demand response compensation costs
with power balance
energy storage
and flexible load operating characteristics serving as constraints. The effectiveness of the proposed method is verified through case studies of actual regional distribution networks.
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