EN农村新型电力系统精细化时序生产模拟方法
A Refined Time-Series Production Simulation Method for New Rural Power Systems
- 中国电力 2025年58卷第10期 页码：71-81
- 作者机构：
1. 国网河南省电力公司经济技术研究院,河南,郑州,450052
2. 强电磁技术全国重点实验室（华中科技大学）,湖北,武汉,430074
- 作者简介：
- 基金信息：国家自然科学基金面上项目（52177088）;国网河南省电力公司科技项目（兰考高比例新能源消纳演进技术研究，5217L0240012）。
DOI：10.11930/j.issn.1004-9649.202503066
中图分类号：-
网络出版：2025-10-23，
纸质出版：2025
- 稿件说明：
移动端阅览
郑永乐, 韦仁博, 冯宇昂, 张艺涵, 崔世常, 武振宇, 蒋小亮, 李慧璇, 艾小猛, 方家琨. 农村新型电力系统精细化时序生产模拟方法[J]. 中国电力, 2025, 58(10): 71-81.
ZHENG Yongle, WEI Renbo, FENG Yuang, et al. A Refined Time-Series Production Simulation Method for New Rural Power Systems[J]. 2025, 58(10): 71-81.
郑永乐, 韦仁博, 冯宇昂, 张艺涵, 崔世常, 武振宇, 蒋小亮, 李慧璇, 艾小猛, 方家琨. 农村新型电力系统精细化时序生产模拟方法[J]. 中国电力, 2025, 58(10): 71-81. DOI： 10.11930/j.issn.1004-9649.202503066.
ZHENG Yongle, WEI Renbo, FENG Yuang, et al. A Refined Time-Series Production Simulation Method for New Rural Power Systems[J]. 2025, 58(10): 71-81. DOI： 10.11930/j.issn.1004-9649.202503066.
摘要
准确评估农村电力系统的新能源消纳能力，对于农村新型电力系统的规划与发展具有重要指导意义。然而，由于农村电力系统普遍存在电压等级较低、阻抗比大、网损比例较高等特点，传统基于直流潮流的时序生产模拟在评估其消纳能力时容易产生偏差。对此，提出一种基于精细化交流潮流的时序生产模拟模型与求解方法。首先，考虑电压和网损特性，建立了基于交流潮流模型的农村电力系统精细化运行模型。然后，针对该模型在年度时序生产模拟时的计算难点，通过二阶锥松弛技术将交流潮流凸化松弛处理以降低模型复杂度，基于此提出兼顾电网规模和计算效率的时段分割策略，将时序生产模型拆分为多个子问题，并通过滚动优化求解提升计算效率。最后，以某实际县域农村电力系统为例进行仿真测试，仿真结果验证了所提方法的有效性。
Abstract
Accurately assessing the renewable energy accommodation capacity of rural power systems is of significant guidance for the planning and development of new rural power systems. However
due to the low voltage levels
large impedance ratios
and higher network loss ratios in rural power systems
the traditional DC power flow-based time-series production simulations are prone to inaccuracies when evaluating their accommodation capacity. Therefor this paper proposes a time-series production simulation model and solution method based on refined AC power flow. Firstly
considering the voltage and network loss characteristics
a refined operational model for rural power systems based on AC power flow model is established. Then
to address the computational challenges of this model in annual time-series production simulation
the AC power flow is convexified and relaxed using second-order cone relaxation techniques to reduce model complexity. Furthermore
a time segmentation strategy that balances both grid scale and computational efficiency is introduced
It decomposes the time-series production model into multiple subproblems solved via rolling optimization
drastically improving computational performance. Finally
a county-level rural power system was used as an example for simulation testing. and the results verified the effectiveness of the method in accurately assessing the capacity for renewable energy integration.
关键词
Keywords
references
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