考虑概率电压不平衡度越限风险的共享储能优化运行方法

doi:10.16183/j.cnki.jsjtu.2021.455

摘要/Abstract

摘要：

可再生能源单相分布式接入和发电不确定性提高了配电网的电压不平衡越限风险,随着可再生能源发电渗透率的不断提高,研究如何降低间歇性可再生能源发电对配电网电压不平衡越限风险的影响具有重要意义.提出了基于全局灵敏度分析(GSA)的共享储能配置策略与优化运行方法.首先,构建了基于反向传播神经网络的配电网概率电压不平衡度计算模型,定义了配电网概率电压不平衡度越限风险指标,快速、准确量化可再生能源发电不确定性对配电网概率电压不平衡度越限风险的影响.然后,提出了基于Wasserstein距离的GSA方法,辨识影响配电网电压不平衡度的关键可再生能源机组.最后,提出了基于GSA的共享储能配置策略与基于滚动预测优化的共享储能优化运行方法.通过IEEE 123节点配电网的仿真计算,验证了所提方法的有效性.

关键词: 可再生能源发电, 不确定性, 电压不平衡, 全局灵敏度分析, 共享储能

Abstract:

The distributed access with single-phase and uncertain generation of the renewable energy increase the risk of voltage unbalance limit violation in the distribution network. With the increasing penetration rate of the renewable energy generation, it is important to study the mitigation of the impacts of intermittent renewable energy generation on the risk of voltage unbalance limit violation in the distribution network. A shared energy storage allocation strategy and optimal operation method based on global sensitivity analysis (GSA) is proposed. First, a back propagation neural network (BPNN) based probabilistic voltage unbalance factor calculation model for the distribution network is constructed, and the risk index of the distribution network probabilistic voltage unbalance factor limit violation is defined, which can quickly and accurately quantify the impact of uncertain renewable energy generation on the risk of voltage unbalance limit violation in the distribution network. Then, a GSA method based on Wasserstein distance is proposed to identify the critical renewable energy sources affecting the distribution network voltage unbalance. Finally, the GSA-based shared energy storage allocation strategy and the rolling prediction optimization-based operation method of the shared energy storage are proposed. The effectiveness of the proposed method is verified through the simulation analysis of IEEE 123-bus distribution network.

Key words: renewable energy generation, uncertainty, voltage unbalance, global sensitivity analysis (GSA), shared energy storage

中图分类号:

TM715

方晓涛, 严正, 王晗, 徐潇源, 陈玥. 考虑概率电压不平衡度越限风险的共享储能优化运行方法[J]. 上海交通大学学报, 2022, 56(7): 827-839.

FANG Xiaotao, YAN Zheng, WANG Han, XU Xiaoyuan, CHEN Yue. A Shared Energy Storage Optimal Operation Method Considering the Risk of Probabilistic Voltage Unbalance Factor Limit Violation[J]. Journal of Shanghai Jiao Tong University, 2022, 56(7): 827-839.

图/表 16

图1

图2

图3

图4

表1

表2

图5

表3

共享ESD的参数

参数	数值	参数	数值
η_c	0.85	E_r/(kW·h)	125
η_disc	1.15	Δ $P m a x c$ /kW	100
$S m i n S O C$	0.20	Δ $P m a x d i s c$ /kW	100
$S m a x S O C$	1.00	$P t m i n$ /kW	0
τ	0.60	$P t m a x$ /kW	1000

表3

表4

表5

图6

表6

图7

图8

图9

图10

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风机	v_in/(m·s^-1)	v_out/(m·s^-1)	v_r/(m·s^-1)	P_r/kW
WT₁	3.5	20.0	14.5	300
WT₂	3.0	19.0	13.0	200
WT₃	3.5	20.0	15.5	300

光伏电池	A/m²	η/%
PV₁	5600	15
PV₂	4800	14

可再生能源机组	全局灵敏度指标
可再生能源机组	时段1	时段2	时段3	时段4
WT₁	0.197	0.110	0.036	0.191
WT₂	0.283	0.193	0.060	0.299
WT₃	0.520	0.305	0.084	0.510
PV₁	0.000	0.232	0.442	0.000
PV₂	0.000	0.160	0.378	0.000

可再生能源机组	全局灵敏度指标
可再生能源机组	时段1	时段2	时段3	时段4
WT₁	0.192	0.110	0.043	0.190
WT₂	0.271	0.185	0.061	0.288
WT₃	0.536	0.298	0.080	0.522
PV₁	0.000	0.241	0.446	0.000
PV₂	0.000	0.166	0.369	0.000

时段	配置共享ESD的可再生能源机组
时段1	WT₂,WT₃
时段2	WT₃,PV₁
时段3	PV₁,PV₂
时段4	WT₂,WT₃