
1. 国网上海能源互联网研究院有限公司,江苏,南京,210003
2. 国网河北省电力有限公司,河北,石家庄,050022
Published Online:23 October 2025,
Published:2025
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王德顺, 雷洁, 胡安平, 王冰, 冯鑫振, 王志辉. 基于多目标双层优化的台区分布式电源选址定容方法[J]. 中国电力, 2025, 58(10): 136-146.
WANG Deshun, LEI Jie, HU Anping, et al. Siting and Sizing of Distributed Generation in Distribution Transformer Areas Using Multi-objective Bi-level Optimization[J]. 2025, 58(10): 136-146.
王德顺, 雷洁, 胡安平, 王冰, 冯鑫振, 王志辉. 基于多目标双层优化的台区分布式电源选址定容方法[J]. 中国电力, 2025, 58(10): 136-146. DOI: 10.11930/j.issn.1004-9649.202505080.
WANG Deshun, LEI Jie, HU Anping, et al. Siting and Sizing of Distributed Generation in Distribution Transformer Areas Using Multi-objective Bi-level Optimization[J]. 2025, 58(10): 136-146. DOI: 10.11930/j.issn.1004-9649.202505080.
近年来,随着国家能源局“整县推进”屋顶光伏开发政策的持续推进,中国分布式光伏接入规模持续扩大,提升了可再生能源利用率。但是,低压配电网末端接入的大量光伏用户引发了局部电压越限和网损异常等问题,降低了系统的运行安全性,且经济性较低。针对以上问题,提出一种基于二阶锥规划松弛的分布式电源选址定容双层优化配置方法。首先,兼顾系统运行安全性与经济性,在考虑分布式储能老化、维护成本及运行安全等因素的基础上,构建以系统日综合运行成本最低和光伏利用率最高为目标的双层优化模型;然后,使用二阶锥规划松弛技术转换潮流模型,将原有非凸模型转换为凸模型以降低运算规模,并使用多目标粒子群算法求解模型;最后,以改进的IEEE 33节点及河北实际台区为算例,与传统规划方法对比,验证所提方法优越性。结果表明,所提方法能在保证经济性的同时,提高电能质量并降低网损,增加分布式光伏消纳能力。
In recent years
with the continuous implementation of the "county-wide rooftop distributed photovoltaic (DPV) development program" promoted by the National Energy Administration
the integration scale of PV in China has steadily expanded
enhancing the utilization efficiency of renewable energy. However
the large-scale integration of PV users
particularly at the ends of low-voltage distribution networks. has led to issues such as localized voltage violations and abnormal power losses
thereby compromising power system's operational security and economic efficiency. To address the aforementioned issues
this paper proposes a bi-level optimal allocation method for distributed generation siting and sizing based on second-order cone programming relaxation. Firstly
to balance system's operational security and economic efficiency
a bi-level optimization model is established with the dual objectives of minimizing the system's daily comprehensive operating cost and maximizing PV utilization
which takes account such factors as the aging
maintenance costs and operational safety of distributed energy storage systems. Then
the second-order cone programming relaxation technique is employed to transform the power flow model
converting the original non-convex model into a convex one to reduce computational complexity
and the multi-objective particle swarm optimization algorithm is used to solve the model. Finally
using the improved IEEE 33-bus system and an actual distribution network in Hebei for case study
a comparison with the traditional planning approaches is conducted to verify the superiority of the proposed method. The results indicate that the proposed method can enhance power quality
reduce network losses
and increase the DPV hosting capacity while ensuring economic efficiency of distribution networks.
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