基于压缩开关候选集合的分布鲁棒配电网重构方法

doi:10.11930/j.issn.1004-9649.202403022

中国电力 ›› 2024, Vol. 57 ›› Issue (10): 12-24, 35.DOI: 10.11930/j.issn.1004-9649.202403022

• 面向现代智慧配电网的二次系统规划 • 上一篇下一篇

基于压缩开关候选集合的分布鲁棒配电网重构方法

杜浩程¹(), 李世龙²^,⁴(), 巨云涛³(), 张晋奇⁵()

1. 中国农业大学信息与电气工程学院，北京　100083
2. 电力物联网四川省重点实验室，四川成都　610095
3. 北方工业大学电气与控制工程学院，北京　100144
4. 国网四川省电力公司电力科学研究院，四川成都　610095
5. 山西省能源互联网研究院，山西太原　030000

收稿日期:2024-03-06 出版日期:2024-10-28 发布日期:2024-10-25
作者简介:杜浩程（1995—），男，硕士，从事配电网运行与优化技术研究，E-mail：595523633@qq.com
李世龙（1989—），男，博士，工程师，从事配电网运行与控制技术研究，E-mail：981163632@qq.com
巨云涛（1985—），男，通信作者，教授，从事高比例可再生能源系统的分布自律-集中协同的稳定分析与优化调控技术、分布式协同能量管理系统研究，E-mail：juyuntaomail@163.com
基金资助:
电力物联网四川省重点实验室开放课题项目（PIT-F-202205）。

A Distributional Robust Distribution Network Reconfiguration Method Based on Compressed Switch Candidate Set

Haocheng DU¹(), Shilong LI²^,⁴(), Yuntao JU³(), Jinqi ZHANG⁵()

1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
2. Power Internet of Things Key Laboratory of Sichuan Province, Chengdu 610095, China
3. School of Electrical and Control Engineering, North China University of Technology, Beijing 100144, China
4. State Grid Sichuan Electric Power Research Institute, Chengdu 610095, China
5. Shanxi Energy Internet Research Institute, Taiyuan 030000, China

Received:2024-03-06 Online:2024-10-28 Published:2024-10-25
Supported by:
This work is supported by the Opening Fund of Power Internet of Things Key Laboratory of Sichuan Province (No.PIT-F-202205).

摘要/Abstract

摘要：

在大规模多时刻配电网重构（distribution network reconfiguration，DNR）问题中，大量待优化的开关严重降低了配电网重构的求解效率。针对此问题，提出了一种压缩开关候选集合的分布鲁棒配电网重构模型，该模型分为2个阶段，第1阶段以最小化系统有功网损为目标函数，使用最优匹配回路流法压缩开关候选集合，第2阶段以最小化取电成本和开关动作成本之和为目标函数，并构建以电源点容量为限值的机会约束，采用基于Wasserstein球的分布鲁棒方法处理分布式电源的不确定性，利用对偶转换方法对目标函数中的最坏情况期望和机会约束进行确定性转换，将模型转化为一个混合整数二阶锥规划问题。最后，对33节点和辽宁盘锦45节点系统进行了数值实验，证明了所提模型能够有效提升计算效率，与鲁棒模型和随机规划模型相比，决策者可以通过改变样本数量和置信度来调整模型的经济性和保守性。

关键词: 配电网重构, 最优匹配回路流, 分布鲁棒优化, Wasserstein球, 机会约束

Abstract:

In the large-scale multi-moment distribution network reconfiguration (DNR) problem, a large number of switches to be optimized seriously reduces the solution efficiency of distribution network reconfiguration. To address this problem, a distributional robust distribution network reconfiguration model based on a compressed switch candidate set was proposed, which was divided into two stages. The first stage took the minimization of active network loss of the system as the objective function and used the optimal matching loop flow method to compress the switch candidate set; the second stage took the minimization of the sum of the power purchase cost and the switch action cost as the objective function, constructed the chance constraints on the capacity limits of the power point, and adopted a Wasserstein ball-based distributional robust method to deal with the uncertainty of distributed generation. It transformed the model into a mixed-integer second-order conic planning problem by deterministically transforming the worst-case expectation and chance constraints in the objective function by using a dual transformation method. Finally, numerical experiments were conducted on the 33 node and Liaoning Panjin 45 node systems, which proved that the model proposed in this paper could effectively improve the computational efficiency, and the decision maker could adjust the economy and conservatism of the model by changing the number of samples and the confidence level, compared with the robust model and the stochastic planning model.

Key words: distribution network reconfiguration, optimal matching loop flow, distributional robust optimization, Wasserstein ball, chance constraint

杜浩程, 李世龙, 巨云涛, 张晋奇. 基于压缩开关候选集合的分布鲁棒配电网重构方法[J]. 中国电力, 2024, 57(10): 12-24, 35.

Haocheng DU, Shilong LI, Yuntao JU, Jinqi ZHANG. A Distributional Robust Distribution Network Reconfiguration Method Based on Compressed Switch Candidate Set[J]. Electric Power, 2024, 57(10): 12-24, 35.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202403022

https://www.electricpower.com.cn/CN/Y2024/V57/I10/12

图/表 19

参考文献 32

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回路	场景1（12:00）		场景2（20:00）		场景3（04:00）		开关候选集合
回路	最小残留电流 (p.u.)	开关	最小残留电流 (p.u.)	开关	最小残留电流 (p.u.)	开关	开关候选集合
1	$ \begin{aligned} & 0.133 + \\& \rm j0.030\end{aligned} $	7-8	$\begin{aligned} & 0.020 +\\ & \rm j0.006 \end{aligned}$	6-7	$ \begin{aligned} &0.048 +\\& \rm j0.012\end{aligned} $	6-7	6-7、7-8、6-26、26-27、30-31、32-33、8-9、11-12、12-22、13-14、14-15
2	$\begin{aligned} & 0.021 - \\ & \rm j0.001\end{aligned} $	26-27	$\begin{aligned} &0.008 - \\ & \rm j0.011\end{aligned} $	6-26	$ \begin{aligned} &0.016 - \\& \rm j0.003 \end{aligned}$	26-27
3	$ \begin{aligned} &0.032 + \\& \rm j0.001\end{aligned} $	32-33	$\begin{aligned} & 0.032 +\\&\rm j0.009\end{aligned} $	30-31	$ \begin{aligned} &0.016 +\\& \rm j0.004\end{aligned} $	30-31
4	$ \begin{aligned} &- 0.066 + \\& \rm j0.026\end{aligned} $	12-22	$ \begin{aligned} &- 0.008 + \\& \rm j0.002\end{aligned} $	11-12	$\begin{aligned} & - 0.020 + \\& \rm j0.018 \end{aligned}$	8-9
5	$ \begin{aligned} &- 0.049 +\\& \rm j0.005\end{aligned} $	13-14	$\begin{aligned} & - 0.014 +\\&\rm j0.021\end{aligned} $	13-14	$ \begin{aligned} &- 0.006 + \\& \rm j0.009\end{aligned} $	14-15

回路	场景1（12:00）		场景2（20:00）		场景3（04:00）		开关候选集合
回路	最小残留电流 (p.u.)	开关	最小残留电流 (p.u.)	开关	最小残留电流 (p.u.)	开关	开关候选集合
1	$ \begin{aligned} & 0.133 + \\& \rm j0.030\end{aligned} $	7-8	$\begin{aligned} & 0.020 +\\ & \rm j0.006 \end{aligned}$	6-7	$ \begin{aligned} &0.048 +\\& \rm j0.012\end{aligned} $	6-7	6-7、7-8、6-26、26-27、30-31、32-33、8-9、11-12、12-22、13-14、14-15
2	$\begin{aligned} & 0.021 - \\ & \rm j0.001\end{aligned} $	26-27	$\begin{aligned} &0.008 - \\ & \rm j0.011\end{aligned} $	6-26	$ \begin{aligned} &0.016 - \\& \rm j0.003 \end{aligned}$	26-27
3	$ \begin{aligned} &0.032 + \\& \rm j0.001\end{aligned} $	32-33	$\begin{aligned} & 0.032 +\\&\rm j0.009\end{aligned} $	30-31	$ \begin{aligned} &0.016 +\\& \rm j0.004\end{aligned} $	30-31
4	$ \begin{aligned} &- 0.066 + \\& \rm j0.026\end{aligned} $	12-22	$ \begin{aligned} &- 0.008 + \\& \rm j0.002\end{aligned} $	11-12	$\begin{aligned} & - 0.020 + \\& \rm j0.018 \end{aligned}$	8-9
5	$ \begin{aligned} &- 0.049 +\\& \rm j0.005\end{aligned} $	13-14	$\begin{aligned} & - 0.014 +\\&\rm j0.021\end{aligned} $	13-14	$ \begin{aligned} &- 0.006 + \\& \rm j0.009\end{aligned} $	14-15

回路	场景4（16:00）		场景5（06:00）		开关候选集合
回路	最小残留电流 (p.u.)	开关	最小残留电流 (p.u.)	开关	开关候选集合
1	$ 0.148 +\rm j0.040 $	6-7	$ 0.030 +\rm j0.008 $	6-7	6-7、26-27、27-28、32-33、30-31、11-12、13-14
2	$ 0.035 -\rm j0.002 $	27-28	$ 0.007 -\rm j0.000 $	26-27
3	$ 0.058 +\rm j0.003 $	32-33	$ 0.012 +\rm j0.000 $	30-31
4	$ - 0.078 +\rm j0.021 $	11-12	$ - 0.016 +\rm j0.004 $	11-12
5	$ - 0.047 +\rm j0.004 $	13-14	$ - 0.004 +\rm j0.009 $	13-14

回路	场景4（16:00）		场景5（06:00）		开关候选集合
回路	最小残留电流 (p.u.)	开关	最小残留电流 (p.u.)	开关	开关候选集合
1	$ 0.148 +\rm j0.040 $	6-7	$ 0.030 +\rm j0.008 $	6-7	6-7、26-27、27-28、32-33、30-31、11-12、13-14
2	$ 0.035 -\rm j0.002 $	27-28	$ 0.007 -\rm j0.000 $	26-27
3	$ 0.058 +\rm j0.003 $	32-33	$ 0.012 +\rm j0.000 $	30-31
4	$ - 0.078 +\rm j0.021 $	11-12	$ - 0.016 +\rm j0.004 $	11-12
5	$ - 0.047 +\rm j0.004 $	13-14	$ - 0.004 +\rm j0.009 $	13-14

方法	成本/ 千元	计算时间/s	打开过的开关
经过压缩	3.8318	923	6-7、11-12、13-14、 26-27、30-31、32-33
未经压缩	3.8318	4002	6-7、11-12、13-14、 26-27、30-31、32-33

基于压缩开关候选集合的分布鲁棒配电网重构方法

A Distributional Robust Distribution Network Reconfiguration Method Based on Compressed Switch Candidate Set

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图/表 19

参考文献 32

相关文章 15

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Metrics

参数	不同优化模型下的成本/千元
参数	RO	DRO	SP	CM
$ \beta = 0.70 $	3.9254	3.8104	3.7886	3.7733
$ \beta = 0.80 $	3.9254	3.8203	3.7886	3.7733
$ \beta = 0.90 $	3.9254	3.8318	3.7886	3.7733
$ \varepsilon = 0.10 $	3.9254	3.8318	3.7943	3.7733
$ \varepsilon = 0.20 $	3.9254	3.8226	3.7871	3.7733
$ \varepsilon = 0.30 $	3.9254	3.8144	3.7854	3.7733

方法	成本/ 元	计算时间/s	打开过的开关
经过压缩	5764.2	1419	4-5、5-6、7-8、 16-17、18-19、19-20、23-26、26-27、18-38
未经压缩	5764.2	3202	4-5、5-6、7-8、 16-17、18-19、19-20、23-26、26-27、18-38

时段	断开的开关
时段	CM	DRO
$ {t_1}\sim {t_7} $	4-5, 5-6, 18-19, 18-38, 26-27	4-5, 5-6, 18-19, 18-38, 26-27
$ {t_8} \sim {t_{10}} $	4-5, 6-7, 18-19, 18-38, 23-26	4-5, 5-6, 18-19, 18-38, 26-27
$ {t_{11}} \sim {t_{13}} $	4-5, 7-8, 18-19, 16-17, 26-27	4-5, 7-8, 18-19, 16-17, 26-27
$ {t_{14}} \sim {t_{24}} $	4-5, 5-6, 19-20, 18-38, 23-26	4-5, 6-7, 19-20, 18-38, 23-26

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参数	不同优化模型下的成本/千元
参数	RO	DRO	SP	CM
$ \beta = 0.70 $	5.8426	5.7403	5.7250	5.6888
$ \beta = 0.80 $	5.8426	5.7529	5.7250	5.6888
$ \beta = 0.90 $	5.8426	5.7642	5.7250	5.6888
$ \varepsilon = 0.10 $	5.8426	5.7642	5.7219	5.6888
$ \varepsilon = 0.20 $	5.8426	5.7503	5.7142	5.6888
$ \varepsilon = 0.30 $	5.8426	5.7479	5.7018	5.6888

参数	不同优化模型下的成本/千元
参数	RO	DRO	SP	CM
$ \beta = 0.70 $	5.8426	5.7403	5.7250	5.6888
$ \beta = 0.80 $	5.8426	5.7529	5.7250	5.6888
$ \beta = 0.90 $	5.8426	5.7642	5.7250	5.6888
$ \varepsilon = 0.10 $	5.8426	5.7642	5.7219	5.6888
$ \varepsilon = 0.20 $	5.8426	5.7503	5.7142	5.6888
$ \varepsilon = 0.30 $	5.8426	5.7479	5.7018	5.6888

样本容量		计算时间/s
100		239
300		232
500		242
700		245

样本容量		计算时间/s
100		239
300		232
500		242
700		245

模态框（Modal）标题

基于压缩开关候选集合的分布鲁棒配电网重构方法

A Distributional Robust Distribution Network Reconfiguration Method Based on Compressed Switch Candidate Set

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