配电网分布式电源经济可承载力评估

doi:10.11930/j.issn.1004-9649.202312019

摘要/Abstract

摘要：

基于鲁棒优化方法，考虑安全运行和经济性目标，对配网分布式电源和储能的容量进行优化配置。根据风光负荷的历史数据和分布特征生成多个运行场景，利用所生成的运行场景建立描述风光负荷的不确定集，然后基于该不确定集建立双层鲁棒优化模型。外层模型在不确定集中寻找经济性最差的运行场景；内层模型考虑配网运行的安全约束，在最差场景下优化风、光和储能的容量。相比于采用典型场景法的容量配置结果，提出的容量配置结果更小，并且可以满足配网的安全运行条件，具有更高的安全性和经济性。

关键词: 主动配电网, 分布式电源容量配置, 经济可承载力

Abstract:

Based on the robust optimization method, considering the safe operation and economic objectives, the capacity of distributed power generation and energy storage in the distribution network is optimized. According to historical data and probability distributions of the uncertain wind, solar and load, multiple scenarios of these uncertainties are generated, and the uncertainty set describing these uncertainties is established using these operation scenarios. Then, based on the uncertainty set, a two-level robust optimization model is established. The outer-level model searches for the economically worst operation scenario in the uncertainty set. The inner-level model optimizes the capacity of wind, solar and energy storage in the worst scenario, taking into account the security constraints of distribution network. Compared with the capacity allocation results of the traditional method using typical operation scenarios, the capacities allocated in this paper are smaller, and can meet the condition of safe operation in the distribution network, with higher economic performance.

Key words: active distribution network, capacity configuration of distributed generations, economic carrying capacity

凡鹏飞, 李宝琴, 侯江伟, 李嵘, 宋崇明, 林凯骏. 配电网分布式电源经济可承载力评估[J]. 中国电力, 2024, 57(7): 196-202.

Pengfei FAN, Baoqin LI, Jiangwei HOU, Rong LI, Chongming SONG, Kaijun LIN. Economic Capacity Assessment of Renewables in Distribution Networks[J]. Electric Power, 2024, 57(7): 196-202.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202312019

https://www.electricpower.com.cn/CN/Y2024/V57/I7/196

图/表 9

图 1 33节点配网系统

Fig.1 33-bus distribution network system

图 2 风电和光伏的波动范围

Fig.2 Fluctuation range of wind power and photovoltaic

图 3 负荷的波动范围

Fig.3 Fluctuation range of load

图 4 24时段电价变化

Fig.4 The change of electricity price during 24 hours

图 5 生成场景和真实场景的对比

Fig.5 Comparison of generated scenario and real scenario

图 6 泛化能力测试结果

Fig.6 The test result of generalization ability

表 1 不同方法的容量配置结果

Table 1 Capacity configuration results of different methods

方法	风电容量/MW	光伏容量/MW	储能容量/(MW·h)
本文方法	2.72	0	1.92
	1.26	0.93	0
	1.34	0	0
典型场景法	3.69	1.11	2.23
	1.75	2.30	1.19
	1.66	1.64	1.27

表 2 容量配置结果（两批10年期储能）

Table 2 Capacity configuration results with energy storage of 10 years

方法	风电容量/MW	光伏容量/MW	储能容量/(MW·h)
本文方法	2.19	0	1.57
	1.02	0.63	0
	1.34	0	0
典型场景法	3.18	0.77	1.85
	1.21	1.82	0.91
	1.30	1.33	1.07

表 3 不同方法的经济性对比

Table 3 Economic comparison of different methods

方法	平均综合费用/元	存在约束违反场景占比/%
本文	1.26×10⁸（盈利）	1.2
典型场景	1.26×10⁷（亏损）	17.3

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