Article(id=1153695649024434672, tenantId=1146029695717560320, journalId=1146031654075715584, issueId=1153695641046864317, articleNumber=null, orderNo=null, doi=10.13234/j.issn.2095-2805.2024.5.193, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1627142400000, receivedDateStr=2021-07-25, revisedDate=null, revisedDateStr=null, acceptedDate=1629993600000, acceptedDateStr=2021-08-27, onlineDate=1752992077356, onlineDateStr=2025-07-20, pubDate=1727625600000, pubDateStr=2024-09-30, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1752992077356, onlineIssueDateStr=2025-07-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1752992077356, creator=13701087609, updateTime=1752992077356, updator=13701087609, issue=Issue{id=1153695641046864317, tenantId=1146029695717560320, journalId=1146031654075715584, year='2024', volume='22', issue='5', pageStart='1', pageEnd='330', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1752992075453, creator=13701087609, updateTime=1753780969288, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1157004501661078352, tenantId=1146029695717560320, journalId=1146031654075715584, issueId=1153695641046864317, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1157004501661078353, tenantId=1146029695717560320, journalId=1146031654075715584, issueId=1153695641046864317, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=193, endPage=202, ext={EN=ArticleExt(id=1153695649947181555, articleId=1153695649024434672, tenantId=1146029695717560320, journalId=1146031654075715584, language=EN, title=Dual-factor Droop Control Strategy for DC Microgrid Based on Adaptive Characteristics, columnId=1152281492550987902, journalTitle=Journal of Power Supply, columnName=Renewable Energy System, runingTitle=null, highlight=null, articleAbstract=

The inconsistency of line parameters at the outlet of distributed generator(DG) and its random output disturbance lead to a decrease in load power distribution accuracy of DC microgrid and grid-side voltage fluctuation. Aimed at these problems, a double-factor droop control strategy based on adaptive characteristics is proposed with the consideration of the transient-and steady-state of DG operation. First, the influence of line impedance is taken into account during the steady-state operation, a voltage regulation coefficient is introduced, and the steady-state component of double-factor droop coefficient is established. The exact distribution of load power can be realized when the impedance value is unknown, and the grid-side voltage can be raised to reduce the difference with the rated voltage. Second, the influence of random disturbance of DG output is considered in the transient process, and the distributed consistency iterative algorithm is introduced to establish the double-factor droop coefficient free component, which can quickly suppress the power disturbance and grid-side voltage fluctuation while maintaining the balanced output from DG, thus improving the system stability. Finally, a DC microgrid model is built in PSCAD, and simulation results show the effectiveness of the proposed strategy.

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分布式电源 DG(distributed generator)出口线路参数不一致及其出力随机扰动引起了直流微电网负荷功率分配精度下降与网侧电压波动。针对上述问题,计及DG运行暂稳态工况,提出1种基于自适应特性的双因子下垂控制策略。首先,稳态运行时考虑线路阻抗的影响并引入电压调节系数,建立双因子下垂系数稳态分量,在阻抗值未知的情况下即可实现负荷功率的精确分配,同时抬升网侧电压,减小与额定电压的差值;其次,暂态过程中考虑DG出力随机扰动的影响并引入分布一致性迭代算法,建立双因子下垂系数自由分量,可在维持DG均衡出力的前提下快速抑制功率扰动与网侧电压波动,提高系统的稳定性;最后,在PSCAD 中搭建直流微电网模型,仿真结果证明了所提策略的有效性。

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董旭(1997-),男,硕士研究生。研究方向:直流微电网优化控制。E-mail: 1071896623@qq.com。

徐永海(1966-),男,通信作者,博士,教授。研究方向:面向电网的电力电子技术、电压暂降耐受分析与抑制。E-mail: yonghaixu@263.net。

马宁(1996-),男,硕士研究生。研究方向:分布式发电与储能系统控制。E-mail: maningdsx@163.com。

何志轩(1996-),男,硕士研究生。研究方向:交直流混合微电网运行控制。E-mail: 398553148@qq.com。

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董旭(1997-),男,硕士研究生。研究方向:直流微电网优化控制。E-mail: 1071896623@qq.com。

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董旭(1997-),男,硕士研究生。研究方向:直流微电网优化控制。E-mail: 1071896623@qq.com。

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徐永海(1966-),男,通信作者,博士,教授。研究方向:面向电网的电力电子技术、电压暂降耐受分析与抑制。E-mail: yonghaixu@263.net。

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徐永海(1966-),男,通信作者,博士,教授。研究方向:面向电网的电力电子技术、电压暂降耐受分析与抑制。E-mail: yonghaixu@263.net。

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马宁(1996-),男,硕士研究生。研究方向:分布式发电与储能系统控制。E-mail: maningdsx@163.com。

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马宁(1996-),男,硕士研究生。研究方向:分布式发电与储能系统控制。E-mail: maningdsx@163.com。

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何志轩(1996-),男,硕士研究生。研究方向:交直流混合微电网运行控制。E-mail: 398553148@qq.com。

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何志轩(1996-),男,硕士研究生。研究方向:交直流混合微电网运行控制。E-mail: 398553148@qq.com。

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基于自适应特性的直流微电网双因子下垂控制策略研究
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董旭 , 徐永海 , 马宁 , 何志轩
电源学报 | 新能源系统 2024,22(5): 193-202
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电源学报 | 新能源系统 2024, 22(5): 193-202
基于自适应特性的直流微电网双因子下垂控制策略研究
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董旭 , 徐永海 , 马宁 , 何志轩
作者信息
  • 华北电力大学 新能源国家重点实验室 北京 102206
  • 董旭(1997-),男,硕士研究生。研究方向:直流微电网优化控制。E-mail: 1071896623@qq.com。

    徐永海(1966-),男,通信作者,博士,教授。研究方向:面向电网的电力电子技术、电压暂降耐受分析与抑制。E-mail: yonghaixu@263.net。

    马宁(1996-),男,硕士研究生。研究方向:分布式发电与储能系统控制。E-mail: maningdsx@163.com。

    何志轩(1996-),男,硕士研究生。研究方向:交直流混合微电网运行控制。E-mail: 398553148@qq.com。

Dual-factor Droop Control Strategy for DC Microgrid Based on Adaptive Characteristics
Xu DONG , Yonghai XU , Ning MA , Zhixuan HE
Affiliations
  • State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing 102206 China
出版时间: 2024-09-30 doi: 10.13234/j.issn.2095-2805.2024.5.193
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分布式电源 DG(distributed generator)出口线路参数不一致及其出力随机扰动引起了直流微电网负荷功率分配精度下降与网侧电压波动。针对上述问题,计及DG运行暂稳态工况,提出1种基于自适应特性的双因子下垂控制策略。首先,稳态运行时考虑线路阻抗的影响并引入电压调节系数,建立双因子下垂系数稳态分量,在阻抗值未知的情况下即可实现负荷功率的精确分配,同时抬升网侧电压,减小与额定电压的差值;其次,暂态过程中考虑DG出力随机扰动的影响并引入分布一致性迭代算法,建立双因子下垂系数自由分量,可在维持DG均衡出力的前提下快速抑制功率扰动与网侧电压波动,提高系统的稳定性;最后,在PSCAD 中搭建直流微电网模型,仿真结果证明了所提策略的有效性。

直流微电网  /  下垂控制  /  线路阻抗  /  随机扰动  /  功率均衡分配  /  电压波动抑制

The inconsistency of line parameters at the outlet of distributed generator(DG) and its random output disturbance lead to a decrease in load power distribution accuracy of DC microgrid and grid-side voltage fluctuation. Aimed at these problems, a double-factor droop control strategy based on adaptive characteristics is proposed with the consideration of the transient-and steady-state of DG operation. First, the influence of line impedance is taken into account during the steady-state operation, a voltage regulation coefficient is introduced, and the steady-state component of double-factor droop coefficient is established. The exact distribution of load power can be realized when the impedance value is unknown, and the grid-side voltage can be raised to reduce the difference with the rated voltage. Second, the influence of random disturbance of DG output is considered in the transient process, and the distributed consistency iterative algorithm is introduced to establish the double-factor droop coefficient free component, which can quickly suppress the power disturbance and grid-side voltage fluctuation while maintaining the balanced output from DG, thus improving the system stability. Finally, a DC microgrid model is built in PSCAD, and simulation results show the effectiveness of the proposed strategy.

DC microgrid  /  droop control  /  line impedance  /  random disturbance  /  balanced power distribution  /  voltage fluctuation suppression
董旭, 徐永海, 马宁, 何志轩. 基于自适应特性的直流微电网双因子下垂控制策略研究. 电源学报, 2024 , 22 (5) : 193 -202 . DOI: 10.13234/j.issn.2095-2805.2024.5.193
Xu DONG, Yonghai XU, Ning MA, Zhixuan HE. Dual-factor Droop Control Strategy for DC Microgrid Based on Adaptive Characteristics[J]. Journal of Power Supply, 2024 , 22 (5) : 193 -202 . DOI: 10.13234/j.issn.2095-2805.2024.5.193
电力电子技术的迅速发展大大推动了直流微电网技术的研究与进步。相较于交流微电网, 直流微电网可以更加高效地接纳各种 DG (distributed generator)单元,实现对负荷的可靠供电[1-2]。同时,直流微电网无需考虑无功、相位和频率问题,其供电容量大、控制结构简单,大大提高了供电系统的可控性与稳定性[3-4]。因此,直流微电网的发展受到了高度关注。
电压下垂控制作为功率调度与电压调节的有效方式广泛应用于直流微电网, 它不需要微电网集中控制器,能够使各$\mathrm{{DG}}$ 单元按照自身下垂系数参与电网调节,分配负荷不平衡功率,简化了控制系统的复杂程度[5]。但下垂控制在功率与电压调节上仍存在以下 2 个问题。
一是, 直流微电网内线路阻抗的存在干扰了负荷功率在$\mathrm{{DG}}$ 间的均衡分配[6-8],且阻抗上的电压降会进一步降低母线的电压质量。文献[9]提出 1 种直流微电网换流站的有功-电压二级优化控制策略, 通过相邻控制器的稀疏通信, 将各换流站的功率偏差转化为电压参考值补偿量加入下垂控制,实现功率的均衡分配, 但未考虑线路阻抗的影响; 文献[10] 提出 1 种适用于柔性直流输电系统的下垂控制策略,引入换流站间电压误差,使各换流站按功率裕度分配负荷, 但同样未考虑线路阻抗的影响; 文献 [11]提出 1 种分散式下垂控制方法以消除线路阻抗的影响, 但该方法的实现依赖于对阻抗的精确测量, 在实际工程中的应用受测量误差影响严重; 文献[12]提出 1 种计及电压变化率的改进下垂控制策略,改善负荷分配精度,但随着分配精度越高,母线电压偏差越严重。
二是, 由于 DG 出力具有随机性与波动性, 其输出功率扰动同样会对负荷分配与电压稳定产生不利影响[13-14]。文献[15]建立直流电网状态空间模型, 基于此分析下垂控制作用机理, 提出了下垂系数稳态约束范围,保证了系统电压不越限;文献[16-17]考虑储能与光伏的协同作用, 提出改进下垂控制方法, 保证了功率分配均衡与微电网的稳定运行; 文献[18-19]分析了电压电流的耦合关系,通过 DG 下垂系数的闭环反馈实现在不同工况下电压的稳定调节。以上方法从不同角度对下垂控制进行了必要改进, 但均未考虑 DG 随机扰动对微网功率与电压调节的影响。实际直流微电网中 DG 随机扰动客观存在, 因此有必要对其进行分析。
综合上述 2 个方面问题, 本文提出了基于自适应特性的直流微电网双因子下垂控制策略。首先, 建立下垂系数稳态分量, 补偿线路阻抗引起的功率分配偏差, 同时引入电压调节系数, 可有效减小下垂控制导致的母线电压与额定值的偏差; 其次, 建立下垂系数自由分量,消除$\mathrm{{DG}}$ 随机扰动对其出力均衡的破坏, 同时减小了 DG 功率与网侧电压波动量;最后,在 PSCAD/EMTDC 中搭建直流微电网模型进行仿真,仿真结果证明了所提策略的有效性和可靠性。
为便于分析各 DG 有功出力与网侧电压间的关系,本文采用 “电压-功率” 下垂控制策略。其关系式为
${u}_{\mathrm{{dc}}i}= {u}_{\text{ref }}- {k}_{i}{P}_{\mathrm{{dc}}i}$
式中:${u}_{\mathrm{d}{ci}}$${P}_{\mathrm{d}{ci}}$ 分别为第$i$$\mathrm{{DG}}$ 的端口电压与输出功率,$i = 1,2,\cdots, m;{u}_{\text{ref }}$ 为输出电压参考值;${k}_{i}$ 为第$i$ 组 DG 的下垂系数。
直流微电网稳定运行时, 若不考虑线路阻抗, 各 DG 单元输出功率与其额定功率成正比,下垂系数与额定功率成反比,所述关系可表示为
$\frac{{P}_{\mathrm{{dc}}i}}{{P}_{\mathrm{{dc}}j}}= \frac{{P}_{\text{dciref }}}{{P}_{\text{dciref }}}$
$\frac{{k}_{i}}{{k}_{j}}= \frac{{P}_{\text{doiref }}}{{P}_{\text{doiref }}}$
式中:${P}_{\mathrm{{dc}}i}\text{、}{P}_{\mathrm{{dc}}j}\text{、}{P}_{\text{dciref }}\text{、}{P}_{\text{dciref }}$ 分别为第$i\text{、}j$ 组单元的实际输出功率与额定输出功率;${k}_{j}$ 为第$j$ 组单元的下垂系数。
实际微电网中线路阻抗的存在加大了下垂控制中电压与电流的耦合关系, 使功率分配的精度降低。图1给出了含 2 组 DG 的直流微电网简化模型。
图1可见,$\mathrm{{DG}}$ 输出功率${P}_{\mathrm{{dc}}i}$$\mathrm{{DG}}$ 端电压${u}_{\mathrm{d}{ci}}$ 、线路阻抗${R}_{\text{line }i}$ 、直流母线电压${u}_{\text{load }}$ 的关系[20]
$\frac{{P}_{\mathrm{{dc}}i}}{{u}_{\mathrm{{dc}}i}}= \frac{{u}_{\mathrm{{dc}}i}- {u}_{\text{load }}}{{R}_{\text{line }i}}$
将式(1)代入式(4)右侧可得
${P}_{\mathrm{{dc}}i}= \frac{{u}_{\text{ref }}- {u}_{\text{load }}}{{R}_{\text{line }i}/{u}_{\mathrm{{dc}}i}+ {k}_{i}}$
考虑线路阻抗后, 2 组 DG 输出功率不再满足式(2),由式(5)可知,其功率分配偏差${E}_{\mathrm{a}}$
${E}_{\mathrm{a}}= \frac{{P}_{\mathrm{{dc}}i}}{{P}_{\mathrm{{dc}}j}}- \frac{{P}_{\mathrm{{dc}}i\text{ ref }}}{{P}_{\mathrm{{dc}}j\text{ ref }}}= \frac{{R}_{\mathrm{{line}}j}/{u}_{\mathrm{{dc}}j}+ {k}_{j}}{{R}_{\mathrm{{line}}i}/{u}_{\mathrm{{dc}}i}+ {k}_{i}}- \frac{{P}_{\mathrm{{dc}}i\text{ ref }}}{{P}_{\mathrm{{dc}}j\text{ ref }}}$
只有当${E}_{\mathrm{a}}= 0$ 时,2 组 DG 才能均衡分配负荷功率。
由第 1 节分析可知, 对于采用传统下垂控制方式的 DG,线路阻抗的存在影响功率分配的精度,同时, 线路阻抗的电压降进一步导致网侧电压降低。 针对上述问题,本文首先建立了双因子下垂控制系数的稳态分量${k}_{\mathrm{a}i}\left({i = 1,2,\cdots, m}\right)$,能够消除线路阻抗的影响,使各$\mathrm{{DG}}$ 单元精确分配负荷功率,同时抬升网侧电压,减小它与其额定值的差值。
由式 (6) 可知,当${E}_{\mathrm{a}}= 0$ 时,各单元按照自身额定功率分配负荷。将式(6)整理为
${E}_{\mathrm{a}}= \frac{{P}_{\text{dcjref }}\left({{R}_{\text{linej }}/{u}_{\mathrm{d}{cj}}+ {k}_{\mathrm{a}j}}\right)- {P}_{\text{dciref }}\left({{R}_{\text{linei }}/{u}_{\mathrm{{dc}}i}+ {k}_{\mathrm{a}i}}\right)}{{P}_{\text{dcjref }}\left({{R}_{\text{linei }}/{u}_{\mathrm{{dc}}i}+ {k}_{\mathrm{a}i}}\right)} $
式中,${k}_{\mathrm{a}i}$${k}_{\mathrm{a}j}$ 分别为第$i\text{、}j$ 个单元的双因子下垂系数稳态分量。将式(3)代入式(7)可得
${E}_{\mathrm{a}}= \frac{{k}_{i}\left({{R}_{\text{linej }}/{u}_{\mathrm{d}j}+ {k}_{\mathrm{a}i}}\right)- {k}_{j}\left({{R}_{\text{linei }}/{u}_{\mathrm{{dc}}i}+ {k}_{\mathrm{a}i}}\right)}{{k}_{i}\left({{R}_{\text{linei }}/{u}_{\mathrm{{dc}}i}+ {k}_{\mathrm{a}i}}\right)} $
式(8)等号左右两侧同乘电压调节系数$\lambda (\lambda \neq$ $0)$,当${E}_{\mathrm{a}}= 0$ 时,式 (8) 的右侧可整理为
$\left\{\begin{array}{l}\frac{{R}_{\text{linej }}}{{u}_{\text{dej }}}+ {k}_{\mathrm{a}j}= \lambda {k}_{j}\\\frac{{R}_{\text{linei }}}{{u}_{\text{dei }}}+ {k}_{\mathrm{a}i}= \lambda {k}_{i}\end{array}\right.$
此时, 双因子下垂系数稳态分量取值为
$\left\{\begin{array}{l}{k}_{\mathrm{a}i}= \lambda {k}_{i}- \frac{{R}_{\text{line }i}}{{u}_{\mathrm{{dc}}i}}\\{k}_{\mathrm{a}j}= \lambda {k}_{j}- \frac{{R}_{\text{line }j}}{{u}_{\mathrm{d}{bj}}}\end{array}\right.$
考虑在实际系统中, 线路阻抗无法精确测量, 由式(4)可得
$\frac{{R}_{\text{line }i}}{{u}_{\mathrm{{dc}}i}}= \frac{{u}_{\mathrm{{dc}}i}- {u}_{\text{load }}}{{P}_{\mathrm{{dc}}i}}$
将式(11)代入式(10)可得
${k}_{\mathrm{a}i}= \lambda {k}_{i}- \frac{{u}_{\mathrm{{dc}}i}- {u}_{\text{load }}}{{P}_{\mathrm{{dc}}i}}$
由式 (12) 得到的${k}_{\mathrm{a}i}$ 即为$\mathrm{{DG}}$ 单元双因子下垂系数稳态分量。与原始下垂系数${k}_{i}$ 相比,应用${k}_{\mathrm{a}i}$ 可实现各 DG 均衡分配负荷功率,调节$\lambda$ 还可在不影响功率分配精度的前提下抬升网侧电压,减小与其额定电压的差值。
图2表示不同$\lambda$ 取值下的${\mathrm{{DG}}}_{i}$ 下垂控制特性曲线$\left({L}_{1}\right.$$\left.{L}_{2}\right)$${\mathrm{{DG}}}_{j}$ 下垂控制特性曲线$\left({L}_{3}\right.$$\left.{L}_{4}\right)$。 其中${L}_{2}$${L}_{4}$ 对应的电压调节系数小于${L}_{1}$${L}_{3}$ 对应的电压调节系数。横轴为$\mathrm{{DG}}$ 输出功率$P$,纵轴为网侧电压$U,{\mathrm{{DG}}}_{j}$ 的额定功率是${\mathrm{{DG}}}_{i}$ 的 2 倍。
初始时刻网侧电压为${U}_{0}$,应用所提下垂系数稳态分量后,虚线${L}_{1}$${L}_{3}$ 对应输出功率分别为${P}_{i}$$2{P}_{i}$,此时已消除线路阻抗的影响。令$\lambda$ 减小,${k}_{\mathrm{a}i}$${k}_{aj}$ 亦随之减小,虚线${L}_{1}$${L}_{3}$ 逆时针旋转至实线${L}_{2}$${L}_{4}$,此时两者的输出功率增大为$P$${2P},\lambda$ 的改变并不影响功率均衡分配, 两者的功率之比仍为$1 : 2$。为使输出功率维持恒定,稳定在${P}_{i}$$2{P}_{i}$,$\mathrm{{DG}}$ 运行点沿${L}_{2}$${L}_{4}$ 上移,再次稳定之后网侧电压变为${U}^{\prime }$,提升了$\Delta {U}^{\prime }$,减小了下垂控制固有存在的电压偏差${\Delta U}$
${L}_{1}$${L}_{2}$ 为例,易知$\lambda$ 取值越小,则${L}_{1}$ 逆时针旋转角度越大,稳定时${L}_{2}$ 对应电压提升效果越显著,但相应地,当电压波动量${\Delta U}$ 相同时,要求其输出功率越高,即${P}_{i}> {P}_{i}$。DG 输出功率不可能无限增大,因此$\lambda$ 不能过小,应在 DG 容量与额定功率允许范围内合理取值。
基于以上分析可知: 所提下垂系数稳态分量可以消除线路阻抗的影响, 在各功率单元间均衡分配负荷;稳态分量式的建立未使用线路阻抗信息,规避了阻抗检测误差, 因此可以提升功率分配的精度; 提出电压调节系数$\lambda$,在 DG 功率调节能力允许范围内减小$\lambda$ 的取值可以减小下垂控制固有存在的电压偏差。值得注意的是,式(12)中各项均为本地 DG 状态量, 不涉及与网侧其他 DG 信息交互, 降低了对通信系统的要求。
第 2.1 节讨论了线路阻抗对 DG 功率与网侧电压的影响, 并提出了应对方案。在实际直流微电网中,由于$\mathrm{{DG}}$ 出力具有波动性,当输出功率变化时, 会进一步干扰功率精确分配并增大网侧电压波动。 基于此, 本文建立了双因子下垂控制系数自由分量${k}_{\mathrm{u}i}\left({i = 1,2,\cdots, m}\right)$,能快速对扰动进行补偿,消除扰动对功率精确分配的破坏, 使各单元输出功率重新达到均衡, 同时减小网侧电压波动, 提高系统的稳定性。
稳态分量与自由分量的乘积作为完整的双因子下垂控制系数, 可表示为
${k}_{i}^{\prime }= {k}_{\mathrm{a}i}{k}_{\mathrm{u}i}$
DG 功率波动会对网侧其他 DG 出力产生影响 (总负荷不变),因此自由分量的取值须计及多 DG 状态量信息交互。采用分布一致性算法进行分析求解。 分布一致性算法不依靠中央处理器, 仅通过本地节点与相邻节点的信息交互,通过迭代计算,就可使网侧节点的状态量趋于一致, 降低了对通信系统的要求, 提高了通信的可靠性。分布一致性算法[21]可表示为
${x}_{i}\left\lbrack k\right\rbrack =\mathop{\sum }\limits_{{j = 1}}^{n}{d}_{ij}{x}_{j}\left\lbrack {k - 1}\right\rbrack \;i = 1,2,\cdots, m $
式中:${x}_{i}\left\lbrack k\right\rbrack$ 为节点$i$ 迭代$k$ 次的状态量,节点$j$ 为与节点$i$ 通信的相邻节点;${d}_{ij}$ 为节点$j$ 对节点$i$ 的状态转移因子;${x}_{j}\left\lbrack {k - 1}\right\rbrack$ 为节点$j$ 迭代$k - 1$ 次的状态量。
本文采用 Metropolis 方法构造${d}_{ij}{}^{\left\lbrack 9\right\rbrack }$,即
${d}_{ij}= \left\{\begin{array}{ll}\frac{1}{\max \left({{n}_{i},{n}_{j}}\right)+ 1}& j \in {N}_{i}\\ 1 -\mathop{\sum }\limits_{{j \in {N}_{i}}}\frac{1}{\max \left({{n}_{i},{n}_{j}}\right)+ 1}& i = j \\ 0 &\text{ 其他.} \end{array}\right.$
式中:${n}_{i}$${n}_{j}$ 分别为节点$i$ 与节点$j$ 的相邻节点数;${N}_{i}$ 为节点$i$ 的相邻节点集合。
当任意 2 个节点状态量${x}_{i}\left\lbrack k\right\rbrack$${x}_{j}\left\lbrack k\right\rbrack$ 的差值小于给定常数$\varepsilon$ 后,认为状态量收敛,迭代结束。本文中$\varepsilon$${10}^{-3}$ 数量级。收敛判据可表示为
$\left|{{x}_{i}\left\lbrack k\right\rbrack -{x}_{j}\left\lbrack k\right\rbrack }\right|< \varepsilon \;\varepsilon ={10}^{-3}$
通过分布式信息处理器监测 DG 输出功率,计算各 DG 的功率标幺值, 可表示为
${P}_{i}^{* }= \frac{{P}_{\mathrm{{dc}}i}}{{P}_{\text{deiref }}}$
将功率标幺值发送给相邻单元,并接收相邻单元的信息, 利用式(14)与(15)进行一致性迭代, 可得一致收敛之后的微网 DG 平均功率标幺值为
${P}_{\text{ave }}^{* }\left\lbrack k\right\rbrack =\mathop{\sum }\limits_{{i = 1}}^{m}{d}_{ij}{P}_{i}^{* }\left\lbrack k\right\rbrack $
${P}_{i}^{* }$${P}_{\text{ave }}^{* }\left\lbrack k\right\rbrack$ 两者作差再乘以收敛系数$\tau$ 作为指数, 得到以幂函数形式表示的自由分量为
${k}_{\mathrm{u}i}= \exp \left\lbrack {\tau \left({{P}_{i}^{* }- {P}_{\mathrm{{ave}}}^{* }\left\lbrack k\right\rbrack }\right)}\right\rbrack =\\\exp \left\lbrack {\tau \left({\frac{{P}_{\mathrm{{dc}}i}}{{P}_{\text{dciref }}}- \mathop{\sum }\limits_{{i = 1}}^{n}{d}_{ij}\frac{{P}_{\mathrm{{dc}}i}}{{P}_{\text{dciref }}}\left\lbrack k\right\rbrack }\right)}\right\rbrack $
由式 (19) 可知,当 DG 功率不存在扰动时,${P}_{i}^{* }=$ ${P}_{\mathrm{{ave}}}^{* }\left\lbrack k\right\rbrack \text{、}{k}_{ui}= 1$,从而${k}_{i}^{\prime }= {k}_{\mathrm{a}i}{k}_{\mathrm{u}i}= {k}_{\mathrm{a}i}$,各 DG 按稳态分量均衡分配负荷,如图3所示,设此时 DG 输出功率为${P}_{0}$, 电压为${U}_{0}$。当$\mathrm{{DG}}$ 受到正向功率扰动时,${P}_{i}^{* }> {P}_{\text{ave }}^{* }\left\lbrack k\right\rbrack$,${k}_{\mathrm{u}i}$ 增大以等效减小$\mathrm{{DG}}$ 输出功率,从而补偿扰动影响,即${\Delta P}< 0,\mathrm{{DG}}$ 输出功率由${P}_{0}$ 变为$P$,如图3(a)虚线所示; 当 DG 受到负向功率扰动时,${P}_{i}^{* }< {P}_{\mathrm{{ave}}}^{* }\left\lbrack k\right\rbrack,{k}_{\mathrm{u}i}$ 减小以等效增大$\mathrm{{DG}}$ 输出功率,从而补偿扰动影响,即${\Delta P}> 0,\mathrm{{DG}}$ 输出功率由${P}_{0}$ 变为$P$,如图3(b)虚线所示。
${k}_{\mathrm{u}i}$ 可补偿扰动,即减小$\mathrm{{DG}}$ 的功率波动量的绝对值, 由下垂特性可知, 此时网侧电压波动量也相应减小,也即应用自由分量${k}_{\mathrm{u}i}$ 在抵消$\mathrm{{DG}}$ 功率扰动影响的同时可改善网侧直流电压质量,相关内容及仿真分析见 3.2 节。
通过收敛系数$\tau$ 可调节${k}_{\mathrm{u}i}$ 的取值范围。取值过大会使自由分量波动频繁,影响系统的稳定性; 取值过小意味着$\mathrm{{DG}}$ 对功率扰动不敏感,不利于 DG 间协调控制。为防止出现以上情况,须在式(19) 的基础上增加限幅条件。
一般系统的备用容量占其额定容量的 15%~${20}{\%}^{\left\lbrack {22}\right\rbrack }$。基于此,本文考虑$\mathrm{{DG}}$ 最大功率扰动占其额定功率的 20%。为同时满足自由分量调节速度与收敛性能的要求,本文选取收敛系数$\tau$,使得
$- {0.3}< \tau \left({{P}_{i}^{* }- {P}_{\text{ave }}^{* }\left\lbrack k\right\rbrack }\right)< {0.3}$
${k}_{\mathrm{u}i}$ 的取值约束为
$\left\{\begin{array}{l}{k}_{\text{uimin }}< {k}_{\text{ui}}< {k}_{\text{uimax }}\\{k}_{\text{uimax }}= \exp \left({0.3}\right)= {1.35}\\{k}_{\text{uimin }}= \exp \left({-{0.3}}\right)= {0.74}\end{array}\right.$
当系统稳态运行时,${k}_{ui}= \exp \left( 0\right)= 1 \in \left\lbrack {{0.74},{1.35}}\right\rbrack$, 上述取值范围包括了 DG 稳态、扰动运行所有工况。
基于图1所示拓扑,${\mathrm{{DG}}}_{i}$${\mathrm{{DG}}}_{j}$ 在发生扰动后的功率调节量为
$\left|\frac{\Delta {P}_{i}}{\Delta {P}_{j}}\right|= \left|\frac{\Delta {U}_{i}/\left({{k}_{\mathrm{a}i}- {k}_{\mathrm{a}i}{k}_{\mathrm{u}i}}\right)}{\Delta {U}_{j}/\left({{k}_{\mathrm{a}j}- {k}_{\mathrm{a}j}{k}_{\mathrm{u}j}}\right)}\right|= \\\left|\frac{\Delta {U}_{i}/\left\lbrack {{k}_{\mathrm{a}i}\left({{k}_{\mathrm{u}i}- 1}\right)}\right\rbrack }{\Delta {U}_{j}/\left\lbrack {{k}_{\mathrm{a}j}\left({{k}_{\mathrm{u}j}- 1}\right)}\right\rbrack }\right|= \frac{\Delta {U}_{i}/{k}_{\mathrm{a}i}}{\Delta {U}_{j}/{k}_{\mathrm{a}j}}.\\\left|\frac{\exp \left\lbrack {\tau \left({{P}_{j}^{* }- {P}_{\text{ave }}^{* }\left\lbrack k\right\rbrack }\right)}\right\rbrack - 1}{\exp \left\lbrack {\tau \left({{P}_{i}^{* }- {P}_{\text{ave }}^{* }\left\lbrack k\right\rbrack }\right)}\right\rbrack - 1}\right|$
由于存在取值范围限定
$\left\{\begin{array}{l}- {0.3}< \tau \left({{P}_{i}^{* }- {P}_{\text{ave }}^{* }\left\lbrack k\right\rbrack }\right)< {0.3}\\- {0.3}< \tau \left({{P}_{j}^{* }- {P}_{\text{ave }}^{* }\left\lbrack k\right\rbrack }\right)< {0.3}\end{array}\right.$
由等价无穷小关系可将式(22)整理为
$\left|\frac{\Delta {P}_{i}}{\Delta {P}_{j}}\right|= \frac{\Delta {U}_{i}/{k}_{\mathrm{a}i}}{\Delta {U}_{j}/{k}_{\mathrm{a}j}}\left|\frac{\tau \left({{P}_{j}^{* }- {P}_{\mathrm{{ave}}}^{* }\left\lbrack k\right\rbrack }\right)}{\tau \left({{P}_{i}^{* }- {P}_{\mathrm{{ave}}}^{* }\left\lbrack k\right\rbrack }\right)}\right|= \frac{{P}_{\text{dciref }}}{{P}_{\text{dcjref }}}.\\\left|\frac{{P}_{j}^{* }- {P}_{\text{ave }}^{* }\left\lbrack k\right\rbrack }{{P}_{i}^{* }- {P}_{\text{ave }}^{* }\left\lbrack k\right\rbrack }\right|= \frac{{P}_{\text{dciref }}}{{P}_{\text{dcjref }}}$
即应用所提自由分量后, 计及扰动影响的 DG 仍然能均衡分配负荷功率。
由式 (19)、式 (24) 和图3可知:考虑自由分量后, 各 DG 的输出功率仍然与各自额定功率成正比,消除了 DG 扰动对其出力均衡的破坏;基于自由分量的调节可减小扰动功率的绝对值, 因此网侧电压的波动也相应减小,改善了电压质量;收敛系数$\tau$ 的大小影响功率调节的速度,但不会对最终的功率均衡分配产生影响; 因${k}_{\mathrm{u}i}$ 表示为指数形式,随扰动增大迅速增加,能有效抑制大扰动的影响,提高系统的稳定性;${k}_{\mathrm{u}i}$ 亦可作为功率单元的运行指标,通过检测${k}_{\mathrm{u}i}$ 可判断此时功率单元的运行状态,${k}_{\mathrm{u}i}\neq 1$ 时为受到扰动。
由上述分析,本文建立的双因子下垂系数表达式为
${k}_{i}^{\prime }= {k}_{\mathrm{a}i}{k}_{\mathrm{u}i}= \left({\lambda {k}_{i}- \frac{{u}_{\mathrm{{dc}}i}- {u}_{\text{load }}}{{P}_{\mathrm{{dc}}i}}}\right). \\\exp \left\lbrack {\tau \left({\frac{{P}_{\mathrm{{dc}}i}}{{P}_{\mathrm{{dc}}i\text{ ref }}}- \mathop{\sum }\limits_{{i = 1}}^{m}{d}_{ij}\frac{{P}_{\mathrm{{dc}}i}}{{P}_{\mathrm{{dc}}i\text{ ref }}}\left\lbrack k\right\rbrack }\right)}\right\rbrack $
双因子下垂控制框图如图4所示, 可见, 双因子下垂系数由稳态分量与自由分量 2 个部分组成。 通过自由分量能快速调节下垂控制系数, 弥补输出功率差额或削减过高功率,减小电压波动,提高了微电网对 DG 功率波动的鲁棒性; 通过稳态分量能确保各单元均衡分配负荷, 并且能有效提升网侧电压,当直流电压达到允许调节极限时,各分布式电源几乎同时达到满载, 提高各分布式电源有功输出的利用率,提高系统动态响应能力。
为验证本文所提控制策略的有效性, 在 PSCAD 中搭建了如图5所示的直流微电网模型。 为体现在所提方案下 DG 参与功率分配和电压调节的作用,微网孤岛运行。其中,设置直流母线额定电压为${750}\mathrm{\;V},{\mathrm{{DG}}}_{1}$${\mathrm{{DG}}}_{2}$ 的额定功率为${54}\mathrm{\;{kW}}$,${\mathrm{{DG}}}_{3}$${\mathrm{{DG}}}_{4}$ 的额定功率为${27}\mathrm{\;{kW}},4$ 个线路阻抗分别为${0.8}\text{、}{1.0}\text{、}{0.7}$${0.9\Omega },{\mathrm{{DG}}}_{1}$${\mathrm{{DG}}}_{2}$ 的下垂系数均为${0.011},{\mathrm{{DG}}}_{3}$${\mathrm{{DG}}}_{4}$ 的下垂系数均为${0.022},\lambda =$ ${0.8},\tau ={0.65}$。仿真对比所提双因子下垂控制方法与传统下垂控制方法、文献[11]所提控制方法作用下, DG 功率分配与网侧直流电压的变化情况。
在该算例中,初始时刻系统所接负荷为${90}\mathrm{\;{kW}}$,${2.0}\mathrm{\;s}$ 后增加到${140}\mathrm{\;{kW}},{3.6}\mathrm{\;s}$ 后减小到${116}\mathrm{\;{kW}}$。系统在不同控制策略下功率分配与系统电压响应如图6图7所示。由于线路阻抗存在损耗, 故 DG 单元的输出功率略多于负荷功率。
根据仿真系统参数,${\mathrm{{DG}}}_{1}$${\mathrm{{DG}}}_{2}$ 应提供相同的功率,${\mathrm{{DG}}}_{3}$${\mathrm{{DG}}}_{4}$ 应提供相同的功率,且前者为后者的 2 倍。但由图6可见, 应用传统下垂控制策略时,线路阻抗的存在影响了各功率单元对于负荷的分配,${2.0}\mathrm{\;s}$ 前,${\mathrm{{DG}}}_{1}\sim {\mathrm{{DG}}}_{4}$ 分别提供了${29.0}\text{、}{24.0}$ 、 22.5 和${18.0}\mathrm{\;{kW}}$ 的功率,功率分配偏差最大为${33.3}\%;{2.0}\sim {3.6}\mathrm{\;s}$ 功率分配偏差最大为${35.3}\%;{3.6}\sim$ ${6.0}\mathrm{\;s}$ 功率分配偏差最大为${34.5}\%$。文献[11]的功率分配策略依赖于线路阻抗的精确测量, 而实际电路中线路阻抗无法准确获取, 所以功率分配依然存在一定偏差。本文所提控制策略不需要计及阻抗数值,仅依靠网侧电压与$\mathrm{{DG}}$ 输出功率信息即可实现对负荷功率的精确分配,${\mathrm{{DG}}}_{1}$${\mathrm{{DG}}}_{2}$ 的输出功率为${\mathrm{{DG}}}_{3}$${\mathrm{{DG}}}_{4}$ 的 2 倍。
图7可见, 传统下垂控制使母线电压偏离额定值较严重,文献[11]所提方法并不能对其进行有效改善。本文所提控制策略通过减小$\lambda$ 的取值,即可在不干扰功率分配的前提下抬升网侧电压, 提高微电网电压质量,且电压偏移越严重,改善效果越显著。${2.0}\mathrm{\;s}$ 之前,应用文献[11]所提控制方法电压${734}\mathrm{\;V}$,与额定值偏差${16}\mathrm{\;V}$;应用本文所提方法电压 740 V,电压抬升 6 V,抬升比例 37.5%。2.0~3.6 s 应用 2 种控制方法电压分别为 712.5 和${729.0}\mathrm{\;V}$,抬升 16.5 V,抬升比例 44%。3.6~6.0 s应用 2 种控制方法电压分别为 724.0 和${735.0}\mathrm{\;V}$,电压抬升${11}\mathrm{\;V}$,抬升比例为 42.3%。
算例 1 已证明了所提控制策略相对于传统下垂控制策略的优越性,本算例验证所提策略在$\mathrm{{DG}}$ 功率扰动情况下的控制效果,与文献[11]所提策略作进一步对比分析。系统初始时刻所接负荷为${90}\mathrm{\;{kW}}$,为验证本文所提策略在 DG 发生扰动时依然能维持功率分配均衡,同时抑制网侧电压波动,${2.0}\mathrm{\;s}$ 时,模拟${\mathrm{{DG}}}_{1}$ 发生功率扰动,输出功率突增${14}\mathrm{\;{kW}},{3.0}\mathrm{\;s}$ 时扰动消失。系统在不同控制策略下功率分配与系统电压响应如图8图9所示。
图8(a)图9(a)可见,采用文献[11]所提控制策略,${\mathrm{{DG}}}_{1}$ 功率突增导致网侧电压波动严重,${2.0}\mathrm{\;s}$ 后由${734}\mathrm{\;V}$ 升高至${751}\mathrm{\;V}$,超过了额定运行电压,波动量为${17}\mathrm{\;V}$
而采用本文所提控制策略,如图8(b)所示, 发生功率突增瞬间,各单元平均输出功率标幺值${P}_{\text{ave }}^{* }\left\lbrack k\right\rbrack$ 未来得及变化,因而${P}_{{\mathrm{{DG}}}_{1}}^{* }> {P}_{\text{ave }}^{* }\left\lbrack k\right\rbrack,{\mathrm{{DG}}}_{1}$ 自由分量增大, 等效减小了输出功率, 补偿了功率扰动的影响。其余单元${P}_{i}^{* }< {P}_{\text{ave }}^{* }\left\lbrack k\right\rbrack,{\mathrm{{DG}}}_{2}\sim {\mathrm{{DG}}}_{4}$ 自由分量减小,等效增加输出功率,分担${\mathrm{{DG}}}_{1}$ 扰动功率,稳定时使各单元输出再次达到均衡, 消除了扰动对功率分配的影响。同时,因功率突增得到抑制,网侧电压波动也相应减小,如图9(a)所示,2.0~3.0 s 稳定电压为${745}\mathrm{\;V}$,未超过网侧电压额定值,波动量仅为$5\mathrm{\;V}$
图8(c)图9(b)${2.5}\sim {3.0}\mathrm{\;s}$ 时段所示,若在DG 功率扰动期间准确调节$\lambda$ 的大小,可实现各单元输出功率与网侧电压的无差调节。
不同$\lambda$ 取值时下垂控制特性如图10所示,$C$ 点为扰动前的$\mathrm{{DG}}$ 运行点,受扰动影响,$\mathrm{{DG}}$ 功率与网侧电压均有所提高,运行点由$C$ 点转移至$A$ 点,${L}_{1}$${2.0}\sim {2.5}\mathrm{\;s}$ 时段内$\mathrm{{DG}}$ 下垂控制曲线。增大电压调节系数$\lambda$,使下垂控制曲线由${L}_{1}$ 变为${L}_{2}$,在网侧电压不变的情况下运行点首先由$A$ 点左移至$B$ 点,而后沿${L}_{2}$ 下移至$C$ 点,即可实现在扰动未消除时的各单元输出功率与网侧电压的无差调节。
针对 DG 出口线路参数不一致及其出力随机扰动引起的直流微电网负荷功率分配精度下降, 以及网侧电压波动问题,本文提出了 1 种基于自适应特性的双因子下垂控制策略, 在 PSCAD 中搭建四端直流微电网模型, 并与不同策略的控制效果进行对比分析, 对不同工况的仿真结果证明了所提策略的有效性与可靠性。所得结论如下。
(1)基于下垂系数稳态分量可在线路阻抗未知的情况下消除其影响,使各 DG 精确分配负荷。在 DG 功率调节能力允许的范围内减小电压调节系数$\lambda$,可以有效抬升网侧电压,并减小与其额定值的差值。
(2)基于下垂系数自由分量可计及 DG 随机扰动实时对输出功率进行调节,消除扰动对$\mathrm{{DG}}$ 出力均衡的破坏, 同时快速对扰动功率与网侧电压波动进行抑制。通过收敛系数$\tau$ 可以方便地控制功率与电压调节的速度,适应系统的要求。综合应用暂稳态分量,自适应调节对$\lambda$ 进行整定还可实现$\mathrm{{DG}}$ 功率与网侧电压的无差调节,提高了系统的稳定性。
  • 北京市自然科学基金资助项目(3172036)
  • 新能源电力系统国家重点实验室(华北电力大学)自主研发课题基金资助项目(LAPS202124)
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2024年第22卷第5期
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doi: 10.13234/j.issn.2095-2805.2024.5.193
  • 接收时间:2021-07-25
  • 首发时间:2025-07-20
  • 出版时间:2024-09-30
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  • 收稿日期:2021-07-25
  • 录用日期:2021-08-27
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Beijing Municipal Natural Science Foundation(3172036)
北京市自然科学基金资助项目(3172036)
Independent Research Project Fund of the State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(LAPS202124)
新能源电力系统国家重点实验室(华北电力大学)自主研发课题基金资助项目(LAPS202124)
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    华北电力大学 新能源国家重点实验室 北京 102206
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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