农村新型电力系统精细化时序生产模拟方法

doi:10.11930/j.issn.1004-9649.202503066

中国电力 ›› 2025, Vol. 58 ›› Issue (10): 71-81.DOI: 10.11930/j.issn.1004-9649.202503066

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农村新型电力系统精细化时序生产模拟方法

郑永乐¹(), 韦仁博²(), 冯宇昂², 张艺涵¹, 崔世常²(), 武振宇¹, 蒋小亮¹, 李慧璇¹, 艾小猛², 方家琨²

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

收稿日期:2025-03-20 发布日期:2025-10-23 出版日期:2025-10-28
作者简介:
郑永乐（1992），女，硕士，从事能源电力研究，E-mail：851086152@qq.com
韦仁博（1999），男，硕士，从事电力系统规划运行研究，E-mail：weirenbo@hust.edu.cn
崔世常（1994），男，通信作者，副研究员，从事分布式智能电网优化与需求响应、电力系统规划研究，E-mail：shichang_cui@hust.edu.cn
基金资助:
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）。

A Refined Time-Series Production Simulation Method for New Rural Power Systems

ZHENG Yongle¹(), WEI Renbo²(), FENG Yuang², ZHANG Yihan¹, CUI Shichang²(), WU Zhenyu¹, JIANG Xiaoliang¹, LI Huixuan¹, AI Xiaomeng², FANG Jiakun²

1. State Grid Henan Economic and Technical Research Institute, Zhengzhou 450052, China
2. State Key Laboratory of Advanced Electromagnetic Technology (Huazhong University of Science and Technology), Wuhan 430074, China

Received:2025-03-20 Online:2025-10-23 Published:2025-10-28
Supported by:
This work is supported by National Natural Science Foundation of China (General Program) (No.52177088), Science and Technology Project of State Grid Henan Electric Power Company (Research on the Evolutionary Technology of High-Proportion Renewable Energy Consumption in Lankao, No.5217L0240012).

摘要/Abstract

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。

关键词: 农村电力系统, 时序生产模拟, 新能源, 消纳能力评估, 二阶锥松弛

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.

Key words: rural power systems, time-series production simulation, renewable energy, accommodation capacity evaluation, second-order cone relaxation

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, ZHANG Yihan, CUI Shichang, WU Zhenyu, JIANG Xiaoliang, LI Huixuan, AI Xiaomeng, FANG Jiakun. A Refined Time-Series Production Simulation Method for New Rural Power Systems[J]. Electric Power, 2025, 58(10): 71-81.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202503066

https://www.electricpower.com.cn/CN/Y2025/V58/I10/71

图/表 14

图 1 二阶锥松弛示意

Fig.1 Illustration of second-order cone relaxation

图 2 时序生产模拟时段分解

Fig.2 Time-series production simulation period decomposition

图 3 某农村县域电力系统接线

Fig.3 Electrical single-line diagram of a county-level rural power system

图 4 年度负荷序列

Fig.4 Annual load sequence

图 5 风电全年时序出力序列

Fig.5 Annual time-series output sequence of wind power

图 6 光伏全年时序出力序列

Fig.6 Annual time-series power output sequence of photovoltaic

表 1 时序运行相关参数

Table 1 Parameters related to time-series operation

参数	数值	参数	数值
生物质发电成本/(元·(MW·h)^–1)	750	储能充放电效率/%	90
弃风弃光惩罚系数/(元·(MW·h)^–1)	100	生物质机组最小启停时间/h	12
生物质机组启停成本/(元·次^–1)	40000	购电成本/ (元·(MW·h)^–1)	850
燃料热值/(kJ·kg^–1)	12736	生物质机组发电效率/%	17

表 2 基于精细化潮流的时序生产模拟结果

Table 2 Detailed power flow-based time-series production simulation results

指标		时序生产模拟运行结果
目标函数/万元		9.43×10⁴
风电消纳率/%		83.69
光伏消纳率/%		93.98
生物质发电量占比/%		13.25
可再生能源供电量占比/%		64.75
外来输电量占比/%		38.97
线损率/%		3.61
生物质机组平均年利用小时数/h		7299
光伏发电机组平均年利用小时数/h		1096
风力发电机组平均年利用小时数/h		1892

图 7 光伏逐月消纳情况

Fig.7 Monthly photovoltaic accommodation

图 8 风电逐月消纳情况

Fig.8 Monthly wind power accommodation

图 9 二阶锥约束松弛验证

Fig.9 Verification of second-order cone constraint relaxation

表 3 基于直流潮流与基于交流潮流的时序生产模拟运行结果对比

Table 3 Comparison of time-series production simulation results between DC power flow-based and AC power flow-based models

指标	基于直流潮流的时序生产模拟模型	基于精细化交流潮流的时序生产模拟模型
目标函数/万元	9.05×10⁴	9.43×10⁴
生物质发电量占比/%	11.67	13.25
可再生能源供电量占比/%	61.60	64.75
外来输电量占比/%	38.48	38.97
生物质机组平均年利用小时数/h	6429	7299
光伏发电机组平均年利用小时数/h	1110	1096
风力发电机组平均年利用小时数/h	1814	1892

表 4 基于直流潮流与基于交流潮流的时序生产模拟运行时长对比

Table 4 Comparison of runtime between DC and AC power flow-based time-series production simulations

指标		基于直流潮流的时序生产模拟模型		基于精细化交流潮流的时序生产模拟模型
计算时长/s		45.95		591.09

图 10 不同子时段长度的时序生产模拟结果

Fig.10 Time-series production simulation results for different time-step lengths

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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

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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

RichHTML

PDF (PC)

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摘要/Abstract

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参考文献 32

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