Article(id=1190684596426650613, tenantId=1146029695717560320, journalId=1189987059142926344, issueId=1190684594115589101, articleNumber=null, orderNo=null, doi=10.19457/j.1001-2095.dqcd26129, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1724342400000, receivedDateStr=2024-08-23, revisedDate=1727539200000, revisedDateStr=2024-09-29, acceptedDate=null, acceptedDateStr=null, onlineDate=1761810929638, onlineDateStr=2025-10-30, pubDate=1745078400000, pubDateStr=2025-04-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1761810929638, onlineIssueDateStr=2025-10-30, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1761810929638, creator=13701087609, updateTime=1761810929638, updator=13701087609, issue=Issue{id=1190684594115589101, tenantId=1146029695717560320, journalId=1189987059142926344, year='2025', volume='55', issue='4', pageStart='3', pageEnd='96', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1761810929087, creator=13701087609, updateTime=1761811258832, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1190685977225081530, tenantId=1146029695717560320, journalId=1189987059142926344, issueId=1190684594115589101, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1190685977225081531, tenantId=1146029695717560320, journalId=1189987059142926344, issueId=1190684594115589101, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=41, endPage=47, ext={EN=ArticleExt(id=1190684596762194935, articleId=1190684596426650613, tenantId=1146029695717560320, journalId=1189987059142926344, language=EN, title=Optimal Configuration of SOP in Flexible Distribution Network Based on Branch Power Sensitivity Analysis, columnId=null, journalTitle=Electric Drive, columnName=null, runingTitle=null, highlight=null, articleAbstract=

While a large number of distributed generator (DG) keep penetrating into distribution networks,the problems such as voltage violation and network power congestion become more and more serious. Soft open point(SOP) can quickly achieve flexible interconnection and accurate power flow control,effectively addressing the challenges caused by the integration of DG. Considering the installation priority of SOP on branches where active power is heavily affected by loads,an intelligent soft switch site slection and capacity determination strategy based on branch active power sensitivity analysis was proposed. Firstly,a load growth factor was introduced into the power flow equations,and the branch power sensitivity,which reflects time series variation of DG output and load,was theoretically derived. The selection of SOP sites was then ranked according to this sensitivity value. Secondly,the model of SOP site slection and capacity optimization was established,which was solved using a second-order cone algorithm. Finally,validation was conducted on the improved IEEE 33 node distribution system. Results show that the proposed method can affectively save annual comprehensive operation cost of distribution networks,reduce system network losses and improve node voltage deviation.

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大量分布式电源(DG)不断接入配电网中,易引发电压越限和网络阻塞等问题;智能软开关(SOP)可以快速实现柔性互联和功率调节,能够有效解决DG接入带来的问题。考虑优先在有功功率受负荷影响大的支路上装设SOP,提出一种基于支路有功功率灵敏度分析的智能软开关选址定容策略。首先在潮流方程中引入负荷增长因子,理论推导反映DG出力及负荷时序变化特性的支路功率灵敏度,按照其值大小进行SOP选址排序;其次建立了SOP选址定容优化模型,采用二阶锥算法求解;最后,在改进的IEEE 33节点配电系统上进行验证。算例结果表明,所提出的方法可有效节省配电网年度综合运行成本,降低系统网络损耗,改善节点电压偏差。

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孙嘉(1998—),女,硕士研究生,主要研究方向为柔性配电网运行与控制,Email:

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孙嘉(1998—),女,硕士研究生,主要研究方向为柔性配电网运行与控制,Email:

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孙嘉(1998—),女,硕士研究生,主要研究方向为柔性配电网运行与控制,Email:

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Comparison of screening results of flexible switches installed with distributed power access

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方法 待接入SOP支路排序(支路编号/指标)
本文方法 TS5/2.67 6043 TS4/1.487 738 TS1/0.815 747 TS3/0.608 716 TS2/0.163 963
改进节点电压灵敏度法[8] TS2/0.474 181 TS4/0.202 009 TS5/0.039 078 TS3/0.008 811 TS1/0.001 568
潮流介数法[10] TS5/0.276 600 TS3/0.235 200 TS1/0.145 700 TS4/0.123 000 TS2/0.024 300
), ArticleFig(id=1191113127212233319, tenantId=1146029695717560320, journalId=1189987059142926344, articleId=1190684596426650613, language=CN, label=表1, caption=

分布式电源接入情况下装设柔性开关筛选结果对比

, figureFileSmall=null, figureFileBig=null, tableContent=
方法 待接入SOP支路排序(支路编号/指标)
本文方法 TS5/2.67 6043 TS4/1.487 738 TS1/0.815 747 TS3/0.608 716 TS2/0.163 963
改进节点电压灵敏度法[8] TS2/0.474 181 TS4/0.202 009 TS5/0.039 078 TS3/0.008 811 TS1/0.001 568
潮流介数法[10] TS5/0.276 600 TS3/0.235 200 TS1/0.145 700 TS4/0.123 000 TS2/0.024 300
), ArticleFig(id=1191113127342256744, tenantId=1146029695717560320, journalId=1189987059142926344, articleId=1190684596426650613, language=EN, label=Tab.2, caption=

Cost comparison among various access methods

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接入方案 SOP
接入个数
SOP接入支路 SOP接入容量/(kV·A) 投资成本
/万元
运维成本
/万元
损耗成本
/万元
年综合最小成本
/万元
方案1 0 0 0 0 41.410 460 41.410 460
方案2 1 TS5 600 6.12 1.2 31.708 225 39.028 225
方案3 2 TS5,TS4 350/200 5.61 1.1 26.608 375 33.318 375
方案4 3 TS5,TS4,TS1 400/200/100 7.14 1.4 25.259 200 33.799 200
), ArticleFig(id=1191113127405171305, tenantId=1146029695717560320, journalId=1189987059142926344, articleId=1190684596426650613, language=CN, label=表2, caption=

不同接入方案成本对比

, figureFileSmall=null, figureFileBig=null, tableContent=
接入方案 SOP
接入个数
SOP接入支路 SOP接入容量/(kV·A) 投资成本
/万元
运维成本
/万元
损耗成本
/万元
年综合最小成本
/万元
方案1 0 0 0 0 41.410 460 41.410 460
方案2 1 TS5 600 6.12 1.2 31.708 225 39.028 225
方案3 2 TS5,TS4 350/200 5.61 1.1 26.608 375 33.318 375
方案4 3 TS5,TS4,TS1 400/200/100 7.14 1.4 25.259 200 33.799 200
), ArticleFig(id=1191113127497445994, tenantId=1146029695717560320, journalId=1189987059142926344, articleId=1190684596426650613, language=EN, label=Tab.3, caption=

Cost evaluation of the three optimal access methods for comparison

, figureFileSmall=null, figureFileBig=null, tableContent=
方法 接入
方案
SOP
个数
SOP接入支路 SOP接入容量/(kV·A) 投资成本/万元 运维成本
/万元
损耗成本
/万元
年综合最小成本/万元
本文方法 方案3 2 TS5,TS4 350/200 5.61 1.1 26.608 375 33.318 375
改进节点电压灵敏度法[8] 方案3 3 TS2,TS4,TS5 400/200/150 7.65 1.5 25.352 875 34.502 875
潮流介数法[10] 方案3 2 TS5,TS3 350/200 5.61 1.1 29.169 650 35.879 650
), ArticleFig(id=1191113127589720683, tenantId=1146029695717560320, journalId=1189987059142926344, articleId=1190684596426650613, language=CN, label=表3, caption=

3种方法最优接入方案成本对比

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方法 接入
方案
SOP
个数
SOP接入支路 SOP接入容量/(kV·A) 投资成本/万元 运维成本
/万元
损耗成本
/万元
年综合最小成本/万元
本文方法 方案3 2 TS5,TS4 350/200 5.61 1.1 26.608 375 33.318 375
改进节点电压灵敏度法[8] 方案3 3 TS2,TS4,TS5 400/200/150 7.65 1.5 25.352 875 34.502 875
潮流介数法[10] 方案3 2 TS5,TS3 350/200 5.61 1.1 29.169 650 35.879 650
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基于支路功率灵敏度分析的柔性配电网智能软开关优化配置
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孙嘉 , 韩顺天 , 倪良华 , 吕干云
电气传动 | 综合能源与现代电网 2025,55(4): 41-47
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电气传动 | 综合能源与现代电网 2025, 55(4): 41-47
基于支路功率灵敏度分析的柔性配电网智能软开关优化配置
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孙嘉 , 韩顺天, 倪良华, 吕干云
作者信息
  • 南京工程学院 电力工程学院,江苏 南京 211167
  • 孙嘉(1998—),女,硕士研究生,主要研究方向为柔性配电网运行与控制,Email:

Optimal Configuration of SOP in Flexible Distribution Network Based on Branch Power Sensitivity Analysis
Jia SUN , Shuntian HAN, Lianghua NI, Ganyun LÜ
Affiliations
  • School of Electric Power Engineering,Nanjing Institute of Technology,Nanjing 211167,Jiangsu,China
出版时间: 2025-04-20 doi: 10.19457/j.1001-2095.dqcd26129
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大量分布式电源(DG)不断接入配电网中,易引发电压越限和网络阻塞等问题;智能软开关(SOP)可以快速实现柔性互联和功率调节,能够有效解决DG接入带来的问题。考虑优先在有功功率受负荷影响大的支路上装设SOP,提出一种基于支路有功功率灵敏度分析的智能软开关选址定容策略。首先在潮流方程中引入负荷增长因子,理论推导反映DG出力及负荷时序变化特性的支路功率灵敏度,按照其值大小进行SOP选址排序;其次建立了SOP选址定容优化模型,采用二阶锥算法求解;最后,在改进的IEEE 33节点配电系统上进行验证。算例结果表明,所提出的方法可有效节省配电网年度综合运行成本,降低系统网络损耗,改善节点电压偏差。

柔性配电网  /  支路功率灵敏度  /  智能软开关  /  选址定容  /  二阶锥规划

While a large number of distributed generator (DG) keep penetrating into distribution networks,the problems such as voltage violation and network power congestion become more and more serious. Soft open point(SOP) can quickly achieve flexible interconnection and accurate power flow control,effectively addressing the challenges caused by the integration of DG. Considering the installation priority of SOP on branches where active power is heavily affected by loads,an intelligent soft switch site slection and capacity determination strategy based on branch active power sensitivity analysis was proposed. Firstly,a load growth factor was introduced into the power flow equations,and the branch power sensitivity,which reflects time series variation of DG output and load,was theoretically derived. The selection of SOP sites was then ranked according to this sensitivity value. Secondly,the model of SOP site slection and capacity optimization was established,which was solved using a second-order cone algorithm. Finally,validation was conducted on the improved IEEE 33 node distribution system. Results show that the proposed method can affectively save annual comprehensive operation cost of distribution networks,reduce system network losses and improve node voltage deviation.

flexible distribution network  /  branch power sensitivity  /  soft open point(SOP)  /  site selection and capacity determination  /  second-order cone planning
孙嘉, 韩顺天, 倪良华, 吕干云. 基于支路功率灵敏度分析的柔性配电网智能软开关优化配置. 电气传动, 2025 , 55 (4) : 41 -47 . DOI: 10.19457/j.1001-2095.dqcd26129
Jia SUN, Shuntian HAN, Lianghua NI, Ganyun LÜ. Optimal Configuration of SOP in Flexible Distribution Network Based on Branch Power Sensitivity Analysis[J]. Electric Drive, 2025 , 55 (4) : 41 -47 . DOI: 10.19457/j.1001-2095.dqcd26129
近年来,大量分布式电源(DG)不断渗透到配电网中[1]。由于其具有明显的随机性和波动性,易引发电压越限、双向潮流、网络阻塞等问题,严重威胁配电网安全稳定运行。新型电力电子器件智能软开关(SOP)应用到有源的配电网中[2],能灵活应对分布式电源出力的不确定性,改善系统运行状态。现阶段SOP投资成本高,合理配置SOP并发挥其调节能力具有重要意义[3]
就SOP选址与定容问题不少专家从不同角度作了研究。文献[4]采用基于机会约束规划方法建立SOP选址定容的模型。文献[5]提出含储能的三端SOP与需求侧响应的有功无功调节手段,将DG与无功补偿设备相结合对配电网进行优化。文献[6]基于快速失负荷风险理论,提出计及重要用户失负荷风险对多端SOP优化配置策略。文献[7]基于条件风险价值理论,提出考虑采用多种主动调节措施进行网络重构的SOP选址定容方法。以上研究均直接将SOP的安装位置容量作为决策变量,没有考虑分布式电源时序出力对系统运行状态产生的影响。
文献[8]考虑分布式电源出力变化影响电压波动,从改善电压分布的角度采用改进灵敏度分析方法优化SOP选址,采用二阶锥算法确定配置容量,但其无法全面反映DG波动与负荷变化导致系统功率产生的时序性变换。文献[9]提出了一种基于有功潮流调节灵敏度参数的SOP选址策略,并考虑投资运维成本建立双层优化模型确定SOP容量,不足之处在于计算功率灵敏度方法比较复杂,且对配电网的适用性差。文献[10]基于线路潮流介数的概念,采用潮流介数识别关键线路,避免大量寻优过程,但只确定了SOP的位置,没有考虑SOP安装容量对配网运行经济性的影响。
本文提出一种基于支路有功功率灵敏度的分析方法进行SOP选址定容的策略,充分发挥SOP对线路潮流调节能力强的功能[11]。方法全面考虑DG出力及负荷功率变化的时序特性,首先理论推导了待装支路有功功率对负荷增长率的灵敏度计算公式,按照其值由大到小确定SOP在配电网中的优先接入顺序,最大程度上避免了配电网受电源及负荷波动的影响;随后,构建了基于支路有功功率灵敏度的SOP定容优化数学模型,采用二阶锥规划算法求解;最后采用改进的IEEE 33节点配电系统进行分析,验证了所提出SOP选址定容策略的有效性。
本文采用背靠背电压源型换流器B2B VSC进行分析[11]。典型双端SOP结构示意图如图1所示。
双端SOP两端的换流器在结构上完全对称,通过合理的调度指令即可实现功率精准控制与灵活双向交换。SOP接入位置如图2所示。
本文采用双端SOP接入系统配置定容优化模型,研究SOP正常运行状态下的优化策略,控制模式选择 P Q V d c Q控制。其中PQ控制可实现交直流功率转化, V d c Q控制可维持恒定的直流电压,得到稳定平衡的有功功率。采用这种控制模式,能够使SOP独立控制其两端变流器的有功功率和无功功率传输。
DG出力具有随机性和不确定性,负荷波动亦具有时变特性。为反映节点注入功率时序变化特性对SOP选址定容的影响,故文中引入负荷增长参数λ。基于此,推导待装SOP支路的功率对节点负荷增长因子的灵敏度,其计算过程如下。
负荷型连续潮流的数学模型是引入节点负荷增长参数的潮流方程[12],可以简写为
f ( x , λ ) = 0
式中:x为系统状态变量; λ为节点负荷增长参数。
在极坐标下建立如下节点功率方程模型:
P G i P D i V i j i V j ( G i j c o s δ i j + B i j s i n δ i j ) = 0 i Ω P Q + P V
Q G i Q D i V i j i V j ( G i j s i n δ i j B i j c o s δ i j ) = 0 i Ω P Q
式中: P G i Q G i分别为电力系统发电机节点发出的有功与无功功率; P D i Q D i分别为负荷节点消耗的有功与无功功率; V i V j分别为节点i,j的电压幅值; G i j B i j分别为节点i,j间的互电导与互电纳; δ i j为节点间相角差值; Ω P QPQ节点集合; Ω P Q + P VPQ节点和PV节点的并集。
为简化分析,假设发电机节点与负荷节点功率随负荷增长因子变化,如下式所示:
P G i = 1 + λ P G i 0 Q G i = 1 + λ Q G i 0 P D i = 1 + λ P D i 0 Q D i = 1 + λ Q D i 0 i Ω P Q + P V
式中: P G i 0 Q G i 0 P D i 0 Q D i 0分别为节点i的有功、无功功率的初始潮流值。
节点功率方程式(2)、式(3)两边对 λ求一阶导数得:
d ( P G i P D i ) d λ = i = 1 n [ ( P G i P D i ) δ i d δ i d λ + ( P G i P D i ) V i d V i d λ ]
d ( Q G i Q D i ) d λ = i = 1 n [ ( Q G i Q D i ) δ i d δ i d λ + ( Q G i Q D i ) V i d V i d λ ]
式中:n为节点的个数; δ i为节点i的相角。
求导后的式(5)、式(6)中的 P / δ , P / V ,
Q / δ , Q / V符合潮流方程中的雅可比矩阵元素形式,为简化计算可将其转换为矩阵形式表示:
d ( P G i P D i ) d λ d ( Q G i Q D i ) d λ + J d δ i d λ d V i d λ = 0
式中:J为雅可比矩阵。
根据矩阵计算规则,即可求解出电压幅值及相角对负荷增长因子的导数矩阵,如下式所示:
d δ d λ d V d λ = J 1 P G 0 P D 0 Q G 0 Q D 0
式中: J 1为雅可比矩阵逆矩阵。
支路有功功率与无功功率对负荷增长因子的灵敏度可以表示为
d P i j d λ d Q i j d λ = A d δ i d λ d V i d λ d δ j d λ d V j d λ Τ
式中:A为灵敏度系数矩阵。
下面推导灵敏度系数矩阵A。
根据电路基本原理,由节点i向节点j注入的支路复功率可以表示为
S i j = V i I i j = V i ( V i V j ) / Z i j
式中: S i j 为支路ij的支路复功率; I i j 为支路ij的支路电流的共轭; V i V j 分别为节点i,j的电压向量; Z i j 为待装SOP支路ij的支路阻抗的共轭。
将式(10)转换为极坐标形式表示为
S i j = V i c o s δ i + j V i s i n δ i ( R i j + j X i j ) / R i j 2 + X i j 2 ( V i c o s δ i j V i s i n δ i ) V i c o s δ i + j V i s i n δ i ( R i j + j X i j ) / R i j 2 + X i j 2 ( V j c o s δ j j V j s i n δ j )
根据输电线路的潮流公式,节点 i , j间的传输复功率还可以表示为
S i j = P i j + j Q i j
计算化简式(11)后,将实数部分和虚数部分分列,与式(12)联立,即可得:
P i j = R i j / ( R i j 2 + X i j 2 ) [ ( V i c o s δ i ) 2 V i V j c o s δ i c o s δ j + ( V i s i n δ i ) 2 V i V j s i n δ i s i n δ j ] R i j R i j 2 + X i j 2 · [ V i V j c o s δ i s i n δ j V i 2 c o s δ i s i n δ i + V i 2 s i n δ i c o s δ i V i V j s i n δ i c o s δ j ]
Q i j = R i j R i j 2 + X i j 2 [ V i V j c o s δ i s i n δ j V i 2 c o s δ i s i n δ i + V i 2 s i n δ i c o s δ i V i V j s i n δ i c o s δ j ] + R i j R i j 2 + X i j 2 [ ( V i c o s δ i ) 2 V i V j c o s δ i c o s δ j + ( V i s i n δ i ) 2 V i V j s i n δ i s i n δ j ]
根据数学模型中复合函数的微分计算方法,线路ij有功功率、无功功率分别对 λ求导,得到:
d P i j d λ = P i j V i d V i d λ + P i j δ i d δ i d λ + P i j V j d V j d λ + P i j δ j d δ j d λ
d Q i j d λ = Q i j V i d V i d λ + Q i j δ i d δ i d λ + Q i j V j d V j d λ + Q i j δ j d δ j d λ
由此求得灵敏度系数矩阵A的表达式如下:
A = P i j V i P i j δ i P i j V j P i j δ j Q i j V i Q i j δ i Q i j V j Q i j δ j
式(13)、式(14)两侧对节点 i , j的电压幅值与相角分别求偏导,即可求解式(17)中的具体灵敏度系数。
配电网中DG与负荷随季节时刻的波动性会影响线路潮流分布,单一时刻的支路有功功率灵敏度并不能全面反映线路的实际情况。定义某一时段内的综合支路有功功率灵敏度 D i j
D i j = 1 T t = 0 T d P i j . t d λ d t
式中:T为总时长; d P i j . t / d λ为线路ij在t时刻的支路有功功率灵敏度。
D i j值越大,即该支路功率对负荷增长因子灵敏度越大,表明DG出力与负荷发生动态变化时,该支路受到的影响越大。在有功功率灵敏度大的联络支路安装SOP,可以最大程度实现SOP对于配电网的控制优化作用。
SOP的调节能力及经济性与其安装容量有着紧密的联系。因此,在确定选址后,需合理规划容量来充分发挥其性能。本文基于二阶锥规划模型提出了SOP优化定容策略。
以年综合成本最低为目标函数,表达式为
m i n F = C s o p T + C s o p W + C n e t l o s s
年综合成本包括以下3个部分:
1)SOP年度投资成本[13] C s o p T
C s o p T = d ( 1 + d ) y s o p ( 1 + d ) y s o p 1 i j Ω s o p C s o p S s o p . i j i j Ω s o p
式中: C s o p T为SOP单位容量投资成本; y s o p为使用年限; S s o p . i j 为安装在支路ij上SOP的容量;d为贴现率; Ω s o p为待装SOP支路集合。
2)SOP年度运维成本 C s o p W
C s o p W = α i = 1 j i n C s o p S s o p . i j i j Ω s o p
式中: α为SOP年度运维成本系数。
3)配电网年度损耗成本 C n e t l o s s
C n e t l o s s = β t = 1 24 ( I i j . t 2 · r i j . t · Δ t ) × 365 i j Ω L
式中: Ω L为配电线路支路集合; β为实时电价;t为供电时间; I i j . t t时刻线路ij的电流; r i j . t t时刻线路ij的电阻值; Δ t为每个时刻的持续时间。
1)SOP约束条件分别介绍如下:
SOP有功功率约束:
P i , t S O P + P i , t S O P , L + P j , t S O P + P j , t S O P , L = 0
P i , t S O P , L = α i S O P ( P i , t S O P ) 2 + ( Q i , t S O P ) 2
P j , t S O P , L = α j S O P ( P j , t S O P ) 2 + ( Q j , t S O P ) 2
式中: P i , t S O P , L P j , t S O P , L为损耗功率; P i , t S O P P j , t S O P Q i , t S O P Q j , t S O P分别为SOP在t时刻节点i,j对应的有功与无功功率; α i S O P α j S O P分别为节点i,j处传输过程中的损耗系数。
SOP无功功率约束:
β i S i , t S O P Q i , t S O P β i S i , t S O P
β j S j , t S O P Q j , t S O P β j S j , t S O P
式中: S i , t S O P S j , t S O P为SOP配置容量; β i β j分别为节点i,j处的无功约束系数。
SOP容量约束:
( P i , t S O P ) 2 + ( Q i , t S O P ) 2 S i S O P
( P j , t S O P ) 2 + ( Q j , t S O P ) 2 S j S O P
2)支路潮流约束[14]
U j , t 2 = U i , t 2 2 ( r i j P i j , t S + x i j Q i j , t S )   + ( r i j 2 + x i j 2 ) ( I i j , t ) 2
i j Ω 1 [ P i j , t S r i j ( I i j , t ) 2 ] + P j , t S = j k Ω 1 P j k , t S + j k Ω 2 σ j P j k , t S + P j , t S . L o a d i j Ω 1
i j Ω 1 [ Q i j , t S x i j ( I i j , t ) 2 ] + Q j , t S = j k Ω 2 Q j k , t S + j k Ω 2 σ j Q j k , t S + Q j , t S . L o a d i j Ω 1
( I i j , t ) 2 = ( P i j , t S ) 2 + ( Q i j , t S ) 2 ( U i , t ) 2 i j Ω 1
k = 0 1
式中: Ω 1为支路集合; Ω 2为联络开关支路集合; r i j x i j分别为支路ij对应的电阻、电抗; U i , t U j , t 分别为t时刻节点i,j的电压; P j , t S Q j , t S分别为t时刻节点j注入的有功、无功功率; P i j , t S Q i j , t S分别为t时刻支路ij首端的有功、无功功率; P j k , t S Q j k , t S分别为t时刻支路jk的有功与无功功率; P j , t S . L o a d Q j , t S . L o a d分别为t时刻节点j所接负荷的有功与无功功率;i,j为节点编号;k为接入联络开关状态量。
支路潮流模型如图3示。
3)节点电压与支路电流约束:
U m i n U i , t U m a x
I m i n I i j , t I m a x
式中: U m a x U m i n分别为节点电压运行最大值与最小值; I m a x I m i n分别为支路电流最大值与最小值。
4)DG出力约束[15]
m = 1 M S m , i S i , m a x i = 1 N m = 1 M S m , i η P m a x
式中: S m , i S i , m a x分别为节点i安装容量与其最大允许接入的DG容量; η为DG的渗透率; P m a x为配电网最大负荷。
本文基于支路有功功率灵敏度法,对SOP待装支路已进行了优化选址。因此,在运用二阶锥规划算法时,SOP的位置不再作为决策变量。当需要安装1个以上SOP时,即采用按支路有功灵敏度大小降序将SOP逐个接入系统的方法。二阶锥规划层的目的为优化SOP安装容量,求解SOP选址定容模型的流程如图4所示。
为了验证本文所提选址方法的有效性,以实际配电网为模型进行模拟。IEEE 33节点配电系统主要由32条常闭支路和5条联络开关支路构成,如图5所示。额定电压为12.66 kV,有功功率为5 084.26 kW,无功功率为2 547.32 kvar。
为更贴合实际运行状态,考虑DG渗透率的影响,采用在原始配电系统中接入两台光伏PV电源和两台风机WT的改进IEEE 33节点算例仿真。
光伏PV电源一台安装在16节点,容量为800 kW,另外一台安装在28节点,容量为600 kW;风机WT安装在14节点和18节点,对应容量为500 kW和300 kW。不考虑配电网重构,直接将原接入联络开关的位置作为SOP待装支路进行选址。
采用支路功率灵敏度分析法对4个季节全天24 h进行分析计算[16],得到4个季度每个时刻不同待装支路有功功率灵敏度结果,再计算综合支路有功功率灵敏度。
本文方法、改进节点电压灵敏度法[8]和潮流介数法[10]的SOP优化配置排序结果如表1所示。改进节点电压灵敏度法是首先计算反映DG出力时序变化特性的改进节点电压灵敏度,根据电压灵敏度大小先确定SOP配置位置,然后以配电网综合运行成本最低为目标确定SOP的容量。潮流介数法是计算可反映发电机出力和负荷功率变化的线路潮流介数值,选取潮流介数高的关键线路配置SOP。本文方法指标:支路功率灵敏度 D i j值;改进节点电压灵敏度法指标:节点改进灵敏度 S j i值;潮流介数法指标:综合线路潮流介数 K i j值。
表1的结果可以看出,本文方法待装支路排序为TS5,TS4,TS1,TS3,TS2;改进节点电压灵敏度分析法待装支路排序为TS2,TS4,TS5,TS3,TS1;潮流介数分析法待装支路排序为TS5,TS3,TS1,TS4,TS2。由本文方法与潮流介数法结果分析可知,首选TS5支路安装SOP,而改进节点电压灵敏度法首选TS2支路安装SOP。
SOP的经济性能参数和电价等参数为:年度投资成本中的单位安装容量为50 kV·A;贴现率设为8%;经济使用年限设为20 a;单位容量投资成本设为1 000元/(kV·A);年度损耗成本中的实时电价定为0.3 元/(kW·h);年度运维成本系数为0.02;DG渗透率为100%。节点电压约束中设定节点电压范围为额定电压的90%~105%,即视为不越限[17]
基于本文所提SOP的选址定容模型,在Matlab R2021a平台上利用YALMIP优化工具箱进行编程,并调用IBM ILOG CPLEX 12.9算法包进行仿真模拟。
本文设置SOP最大接入数为3个。SOP的接入方案分为以下4种:①不安装SOP;②一条支路安装1个SOP;③两条支路安装2个SOP;④3条支路安装3个SOP。采用本文方法,不同接入方案成本对比如表2所示。
表2的4种方案所对应的年综合最小成本对比可知,方案3为最优方案:支路TS5接入容量为350 kV·A的SOP,同时支路TS4上接入200 kV·A的SOP。从成本来看,未安装SOP的损耗成本远大于安装SOP后的成本,采用方案3所节省下的成本,约5.12 a就可以收回SOP的投资费用。在安装SOP的情况下,方案3相较于方案2、方案4而言,年度综合最小成本分别可以节省5.71 万元(14.63%)和0.48 万元(1.42%)。故合理配置SOP可以有效提高配电网经济性。
为进一步对比本文所提方法与其他方法的优劣性,研究改进节点电压灵敏度法和潮流介数法的SOP选址策略,采取不同方案进行仿真。3种方法对应的年综合成本最小的方案进行对比,结果如表3所示。
表3可以看出,若安装两个SOP,采用本文方法进行选址定容,损耗成本与年综合成本均低于改进节点电压灵敏度法与潮流介数法,且年综合最小成本与两种方法相比,分别节省了3.43%与7.14%。
综上表明,采用本文支路功率灵敏度分析方法对SOP进行选址定容策略,由于在有功功率受电源出力和负荷波动影响大的支路安装SOP,有效控制了配网功率分布,降低了配网损耗和年综合运行成本,提高了系统运行的经济性。
本文提出了优先在受电源和负荷影响大的支路安装SOP的选址定容策略;理论推导了待装支路有功功率灵敏度计算方法;建立了以年综合费用最小为目标的SOP容量规划模型,采用二阶锥方法求解。运用改进IEEE 33节点算例进行仿真分析,验证了所提出的选址定容策略的有效性,为SOP的规划应用奠定基础。
  • 江苏“六大人才高峰”创新团队项目(2019-TD-XNY004)
  • 江苏省高等学校自然科学研究重大项目(2019052)
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doi: 10.19457/j.1001-2095.dqcd26129
  • 接收时间:2024-08-23
  • 首发时间:2025-10-30
  • 出版时间:2025-04-20
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  • 收稿日期:2024-08-23
  • 修回日期:2024-09-29
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江苏“六大人才高峰”创新团队项目(2019-TD-XNY004)
江苏省高等学校自然科学研究重大项目(2019052)
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    南京工程学院 电力工程学院,江苏 南京 211167
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