Article(id=1154038488010842884, tenantId=1146029695717560320, journalId=1146031654075715584, issueId=1154038481564197598, articleNumber=null, orderNo=null, doi=10.13234/j.issn.2095-2805.2024.2.242, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1617033600000, receivedDateStr=2021-03-30, revisedDate=1622390400000, revisedDateStr=2021-05-31, acceptedDate=1623168000000, acceptedDateStr=2021-06-09, onlineDate=1753073816540, onlineDateStr=2025-07-21, pubDate=1711728000000, pubDateStr=2024-03-30, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1753073816540, onlineIssueDateStr=2025-07-21, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1753073816540, creator=13701087609, updateTime=1753073816540, updator=13701087609, issue=Issue{id=1154038481564197598, tenantId=1146029695717560320, journalId=1146031654075715584, year='2024', volume='22', issue='2', pageStart='1', pageEnd='455', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1753073815003, creator=13701087609, updateTime=1753780998609, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1157004624629683026, tenantId=1146029695717560320, journalId=1146031654075715584, issueId=1154038481564197598, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1157004624629683027, tenantId=1146029695717560320, journalId=1146031654075715584, issueId=1154038481564197598, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=242, endPage=249, ext={EN=ArticleExt(id=1154038488623211271, articleId=1154038488010842884, tenantId=1146029695717560320, journalId=1146031654075715584, language=EN, title=Research on Improving Voltage Transient Characteristics of Energy Storage System with Improved MPC, columnId=1152281491788100462, journalTitle=Journal of Power Supply, columnName=Battery and Energy Storage, runingTitle=null, highlight=null, articleAbstract=

The grid-connected operation of an energy storage system is realized by a converter. Due to the low switching frequency of the conventional converter, there exists time delay in sampling and calculation, which will lead to poor transient characteristics of the energy storage system and even instability of the whole power grid. In this paper, model predictive control(MPC) is used to achieve a fast power response of energy storage system and avoid the influence of time delay. A power weight value function is introduced to calculate the optimal output voltage of energy storage converter in the MPC control of active and reactive power. To solve the problem of inaccurate MPC model caused by the parameter deviation of filter inductor, inductance error compensation control is used to improve the model accuracy. Through Matlab/Simulink simulations and experimental results, it is verified that the proposed scheme can improve the transient characteristics of energy storage system and effectively eliminate the influence of error on the MPC control performance.

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储能系统通过换流器实现并网运行,常规换流器因为其开关频率低,在采样、计算环节存在延时导致储能系统暂态特性差,甚至引起整个电网不稳定。本文采用模型预测控制 MPC(model predictive control)来实现储能系统功率快速响应,避免延时影响。引入功率权重价值函数在有功、无功 MPC控制中,计算储能换流器输出电压最优值。针对因为滤波电感参数偏移导致的MPC模型不准确问题,本文采用电感误差补偿控制来提高模型精度。通过Matlab/Simulink仿真和实验来验证本文所提方案可提高储能系统暂态特性,有效消除误差对MPC控制性能的影响。

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鲍建(1962-),男,硕士,讲师。研究方向:储能相关电气技术,企业供配电系统技术,电机与电力拖动等。E-mail: 736654229@qq.com。

杨沛豪(1993-),男,通信作者,博士,工程师。研究方向:电力系统自动化。E-mail: 44960280@qq.com。

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鲍建(1962-),男,硕士,讲师。研究方向:储能相关电气技术,企业供配电系统技术,电机与电力拖动等。E-mail: 736654229@qq.com。

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鲍建(1962-),男,硕士,讲师。研究方向:储能相关电气技术,企业供配电系统技术,电机与电力拖动等。E-mail: 736654229@qq.com。

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杨沛豪(1993-),男,通信作者,博士,工程师。研究方向:电力系统自动化。E-mail: 44960280@qq.com。

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杨沛豪(1993-),男,通信作者,博士,工程师。研究方向:电力系统自动化。E-mail: 44960280@qq.com。

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参数 数值 参数 数值
直流母线电压/V 700 交流线电压/V 380
开关频率$/\mathrm{{kHz}}$ 10 额定角频率/rad$\cdot {\mathrm{s}}^{-1}$ 314
滤波电感/mH 1 滤波电容/μF 4700
等效电阻/$\Omega$ 0.5 直流侧电容/mF 1.5
), ArticleFig(id=1154038577995440275, tenantId=1146029695717560320, journalId=1146031654075715584, articleId=1154038488010842884, language=CN, label=表1, caption=系统仿真参数, figureFileSmall=null, figureFileBig=null, tableContent=
参数 数值 参数 数值
直流母线电压/V 700 交流线电压/V 380
开关频率$/\mathrm{{kHz}}$ 10 额定角频率/rad$\cdot {\mathrm{s}}^{-1}$ 314
滤波电感/mH 1 滤波电容/μF 4700
等效电阻/$\Omega$ 0.5 直流侧电容/mF 1.5
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采用改进 MPC 提高储能系统电压暂态特性研究
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鲍建 1 , 杨沛豪 2
电源学报 | 电池与储能 2024,22(2): 242-249
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电源学报 | 电池与储能 2024, 22(2): 242-249
采用改进 MPC 提高储能系统电压暂态特性研究
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鲍建1 , 杨沛豪2
作者信息
  • 1 山东职业学院 智能制造学院 济南 250104
  • 2 西安热工研究院有限公司 西安 710054
  • 鲍建(1962-),男,硕士,讲师。研究方向:储能相关电气技术,企业供配电系统技术,电机与电力拖动等。E-mail: 736654229@qq.com。

    杨沛豪(1993-),男,通信作者,博士,工程师。研究方向:电力系统自动化。E-mail: 44960280@qq.com。

Research on Improving Voltage Transient Characteristics of Energy Storage System with Improved MPC
Jian BAO1 , Peihao YANG2
Affiliations
  • 1 Intelligent Manufacturing College Shandong Polytechnic Jinan 250104 China
  • 2 Xi'an Thermal Power Research Institute Co., Ltd. Xi'an 710054 China
出版时间: 2024-03-30 doi: 10.13234/j.issn.2095-2805.2024.2.242
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储能系统通过换流器实现并网运行,常规换流器因为其开关频率低,在采样、计算环节存在延时导致储能系统暂态特性差,甚至引起整个电网不稳定。本文采用模型预测控制 MPC(model predictive control)来实现储能系统功率快速响应,避免延时影响。引入功率权重价值函数在有功、无功 MPC控制中,计算储能换流器输出电压最优值。针对因为滤波电感参数偏移导致的MPC模型不准确问题,本文采用电感误差补偿控制来提高模型精度。通过Matlab/Simulink仿真和实验来验证本文所提方案可提高储能系统暂态特性,有效消除误差对MPC控制性能的影响。

储能系统  /  暂态特性  /  模型预测控制  /  功率权重价值函数  /  电感误差电压补偿

The grid-connected operation of an energy storage system is realized by a converter. Due to the low switching frequency of the conventional converter, there exists time delay in sampling and calculation, which will lead to poor transient characteristics of the energy storage system and even instability of the whole power grid. In this paper, model predictive control(MPC) is used to achieve a fast power response of energy storage system and avoid the influence of time delay. A power weight value function is introduced to calculate the optimal output voltage of energy storage converter in the MPC control of active and reactive power. To solve the problem of inaccurate MPC model caused by the parameter deviation of filter inductor, inductance error compensation control is used to improve the model accuracy. Through Matlab/Simulink simulations and experimental results, it is verified that the proposed scheme can improve the transient characteristics of energy storage system and effectively eliminate the influence of error on the MPC control performance.

Energy storage system  /  transient characteristics  /  model predictive control(MPC)  /  power weight value function  /  inductance error voltage compensation
鲍建, 杨沛豪. 采用改进 MPC 提高储能系统电压暂态特性研究. 电源学报, 2024 , 22 (2) : 242 -249 . DOI: 10.13234/j.issn.2095-2805.2024.2.242
Jian BAO, Peihao YANG. Research on Improving Voltage Transient Characteristics of Energy Storage System with Improved MPC[J]. Journal of Power Supply, 2024 , 22 (2) : 242 -249 . DOI: 10.13234/j.issn.2095-2805.2024.2.242
作为我国能源变革关键技术之一的储能技术, 因为其可以为电网提供调峰、调频、应急响应等多种辅助服务,近年来受到了业内的广泛关注[1-2]。为了实现储能系统友好型并网, 为电网提供稳定电压、 频率支撑,需要开展储能换流器控制策略研究[3]
目前在储能换流器控制领域, 大多采用双闭环控制、无差拍控制来实现储能电压、频率动态响应[45]。 但常规控制策略无法维持分布式电源高渗透率下储能换流器控制系统稳定。文献[6]分析 P-Q 下垂控制模式下, 换流器的负导纳特性, 引入补偿控制环节来提高其控制系统稳定性。文献[7]研究分布式电源点无出力时, 各个电源点有功功率分配和母线电压偏差之间的联系,对下垂控制进行优化,将电压偏差引入控制系统中, 提高系统稳态性能。文献[8] 提出一种基于虚拟转矩、虚拟励磁的 VSG 控制在微网换流器功率调节控制中, 使得换流器控制系统具备阻尼特性,增强功率调节能力。
当储能换流器面对电压、频率频繁调节工况, 开关频率较高,此时因为采样、计算、零阶保持和脉宽调制 PWM(pulse width modulation) 会引起控制延时。如果控制系统不能将此延时及时抑制, 会极大降低系统带宽,造成整个控制系统失稳[9-10]。MPC (model predictive control)是一种状态变量预测算法, 通过预测算法降低对控制系统延时的影响, 因无需考虑开关状态数量, 不影响系统的控制带宽, 进而降低了运算需求, 在储能换流器控制系统中得到了广泛应用[11]。但在 MPC 实际运行过程中,常常因为建模不准确、网侧电压波形等原因,导致控制系统暂态特性较差。文献[12]在 MPC 电压控制环节添加延时负反馈模块, 在不改变控制模型输出的基础上, 增加系统带宽。文献[13]设计多目标离散型 MPC 系统,通过自适应算法匹配最优控制目标值,增加控制系统精度。文献[14]应用 MPC 在逆变装置电流控制系统中, 添加最小电流误差评价函数来消除稳态电流误差, 提高系统动态响应能力。文献[15]在传统 MPC 中引入扰动转矩观测器和死区电压扰动观测器, 实时估计因为扰动转矩和死区效应所产生的电压误差, 将此电压误差作为负反馈引入电压控制环节中,有效减少预测误差。
本文首先根据储能逆变换流器数学模型建立瞬时有功、无功功率表达式, 进一步得到输出功率 MPC 模型分析; 然后构建功率权重价值函数, 计算两相静止坐标系下储能换流器输出电压最优值。接着分析 MPC 中误差由来, 建立预测误差函数表达式, 以提高预测精度为目标, 构建电感误差补偿模块。最后将上述控制策略通过 Matlab/Simulink 仿真和实验来验证所提方案有效性。
本文以带 LC 滤波电路的储能换流器为研究对象, 储能换流器 LC 型逆变电路拓扑如图1 所示。
图1 中:${U}_{\mathrm{{dc}}}$ 为储能直流侧母线电压;${U}_{\mathrm{{abc}}}$${i}_{\mathrm{{abc}}}$ 为储能换流器输出交流三相电压、电流;${e}_{\mathrm{{abc}}}$ 为网侧三相电压;${R}_{\mathrm{f}}\text{、}{L}_{\mathrm{f}}\text{、}{C}_{\mathrm{f}}$ 构成 LC 滤波电路;${L}_{\mathrm{g}}\text{、}{R}_{\mathrm{g}}$ 为等效负载。考虑网侧电动势为三相平衡正弦特性,则在两相静止${a\beta }$ 坐标系下储能换流器数学模型为
$\left\{\begin{array}{l}\frac{\mathrm{d}{i}_{\alpha }}{\mathrm{d}t}= \frac{1}{{L}_{\mathrm{f}}}\left({{U}_{\alpha }- {R}_{\mathrm{f}}{i}_{\alpha }- {e}_{\alpha }}\right)\\\frac{\mathrm{d}{i}_{\beta }}{\mathrm{d}t}= \frac{1}{{L}_{\mathrm{f}}}\left({{U}_{\beta }- {R}_{\mathrm{f}}{i}_{\beta }- {e}_{\beta }}\right)\end{array}\right.$
式中,${i}_{\alpha }\text{、}{i}_{\beta }\text{、}{U}_{\alpha }\text{、}{U}_{\beta }\text{、}{e}_{\alpha }\text{、}{e}_{\beta }$ 为两相静止${a\beta }$ 坐标系下储能换流器输出电流、电压, 网侧电压。理想情况下网侧电压可表示为
$\left\{\begin{array}{l}{e}_{\alpha }= \left| E\right|\sin \left({\omega t}\right)\\{e}_{\beta }= -\left| E\right|\cos \left({\omega t}\right)\end{array}\right.$
式中:$E$ 为网侧电压幅值;$\omega$ 为电网角频率。两相静止${a\beta }$ 坐标系下网侧电压变化率为
$\left\{\begin{array}{l}\frac{\mathrm{d}{e}_{\alpha }}{\mathrm{d}t}= \omega \left| E\right|\cos \left({\omega t}\right)= -\omega {e}_{\beta }\\\frac{\mathrm{d}{e}_{\beta }}{\mathrm{d}t}= \omega \left| E\right|\sin \left({\omega t}\right)= \omega {e}_{\alpha }\end{array}\right.$
根据瞬时功率理论可以得到两相静止${a\beta }$ 坐标系下瞬时有功、无功功率表达式为
$\left\{\begin{array}{l} P =\frac{3}{2}\left({{e}_{\alpha }{i}_{\alpha }+ {e}_{\beta }{i}_{\beta }}\right)\\ Q =\frac{3}{2}\left({{e}_{\beta }{i}_{\alpha }- {e}_{\alpha }{i}_{\beta }}\right)\end{array}\right.$
瞬时有功、无功功率变化率表达式为
$\left\{\begin{array}{l}\frac{\mathrm{d}P}{\mathrm{\;d}t}= \frac{3}{2}\left({{e}_{\alpha }\frac{\mathrm{d}{i}_{\alpha }}{\mathrm{d}t}+ {e}_{\beta }\frac{\mathrm{d}{i}_{\beta }}{\mathrm{d}t}+ {i}_{\alpha }\frac{\mathrm{d}{e}_{\alpha }}{\mathrm{d}t}+ {i}_{\beta }\frac{\mathrm{d}{e}_{\beta }}{\mathrm{d}t}}\right)\\\frac{\mathrm{d}Q}{\mathrm{\;d}t}= \frac{3}{2}\left({{e}_{\beta }\frac{\mathrm{d}{i}_{\alpha }}{\mathrm{d}t}- {e}_{\alpha }\frac{\mathrm{d}{i}_{\beta }}{\mathrm{d}t}+ {i}_{\alpha }\frac{\mathrm{d}{e}_{\beta }}{\mathrm{d}t}- {i}_{\beta }\frac{\mathrm{d}{e}_{\alpha }}{\mathrm{d}t}}\right)\end{array}\right.$
将式(2)、式(3)代入式(5)中,可以得到
$\left\{\begin{array}{l}\frac{\mathrm{d}P}{\mathrm{\;d}t}= \frac{3}{2{L}_{\mathrm{f}}}\left({{U}_{\alpha }{e}_{\alpha }+ {U}_{\beta }{e}_{\beta }- {e}_{\alpha }^{2}- {e}_{\beta }^{2}}\right)- \frac{{R}_{\mathrm{f}}}{{L}_{\mathrm{f}}}P -{\omega Q}\\\frac{\mathrm{d}Q}{\mathrm{\;d}t}= \frac{3}{2{L}_{\mathrm{f}}}\left({{U}_{\alpha }{e}_{\beta }- {U}_{\beta }{e}_{\alpha }}\right)- \frac{{R}_{\mathrm{f}}}{{L}_{\mathrm{f}}}Q +{\omega P}\end{array}\right.$
为了得到储能换流器功率$\mathrm{{MPC}}$ 数学模型,将式 (6) 做离散化处理,可以得到$k + 1$ 时刻储能换流器有功、无功 MPC 数学模型为
$\left\{\begin{matrix} P\left({k + 1}\right)= {T}_{\mathrm{s}}\frac{3}{2{L}_{\mathrm{f}}}\left\lbrack {{U}_{\alpha }{e}_{\alpha }\left( k\right)+ {U}_{\beta }{e}_{\beta }\left( k\right)- {e}_{\alpha }^{2}\left( k\right)- }\right.\\\left.{{e}_{\beta }^{2}\left( k\right)}\right\rbrack -{T}_{\mathrm{s}}\left\lbrack {\frac{{R}_{\mathrm{f}}}{{L}_{\mathrm{f}}}P\left( k\right)+ {\omega Q}\left( k\right)}\right\rbrack + P\left( k\right)\\ Q\left({k + 1}\right)= {T}_{\mathrm{s}}\frac{3}{2{L}_{\mathrm{f}}}\left\lbrack {{U}_{\alpha }{e}_{\beta }\left( k\right)- {U}_{\beta }{e}_{\alpha }\left( k\right)}\right\rbrack -\\{T}_{\mathrm{s}}\left\lbrack {\frac{{R}_{\mathrm{f}}}{{L}_{\mathrm{f}}}Q\left( k\right)- {\omega P}\left( k\right)}\right\rbrack + Q\left( k\right)\end{matrix}\right.$
式中,${T}_{\mathrm{s}}$ 为采样控制周期。离散数学模型标准形式为
$ x\left({k + 1}\right)= \mathbf{G}x\left( k\right)+ \mathbf{H}u\left( k\right)$
式中,$\mathbf{G}$$\mathbf{H}$ 为系数矩阵。将式(7)转换为如式 (8) 所示离散数学模型矩阵形式
$\left\lbrack \begin{array}{l} P\left({k + 1}\right)\\ Q\left({k + 1}\right)\end{array}\right\rbrack =\left\lbrack \begin{matrix} 1 -{T}_{\mathrm{s}}\frac{{R}_{\mathrm{f}}}{{L}_{\mathrm{f}}}& -{T}_{\mathrm{s}}\omega \\{T}_{\mathrm{s}}\omega & 1 -{T}_{\mathrm{s}}\frac{{R}_{\mathrm{f}}}{{L}_{\mathrm{f}}}\end{matrix}\right\rbrack \left\lbrack \begin{array}{l} P\left( k\right)\\ Q\left( k\right)\end{array}\right\rbrack +\\{T}_{\mathrm{s}}\frac{3}{2{L}_{\mathrm{f}}}\left\lbrack \begin{matrix}{U}_{\alpha }- {e}_{\alpha }\left( k\right)& {U}_{\beta }- {e}_{\alpha }\left( k\right)\\- {U}_{\beta }& {U}_{\alpha }\end{matrix}\right\rbrack \left\lbrack \begin{array}{l}{e}_{\alpha }\left( k\right)\\{e}_{\beta }\left( k\right)\end{array}\right\rbrack $
为了实现储能换流器有功、无功快速响应, 提高控制系统暂态特性, 本文采用有功、无功相同权重价值函数, 使换流器与网侧交换的功率实时跟随参考值, 功率权重价值函数可表示为
${J}_{k + 1}= {\left\lbrack {P}^{* }\left( k + 1\right)- P\left( k + 1\right)\right\rbrack }^{2}+ {\left\lbrack {Q}^{* }\left( k + 1\right)- Q\left( k + 1\right)\right\rbrack }^{2}$
式中,${P}^{* }\left({k + 1}\right)\text{、}{Q}^{* }\left({k + 1}\right)$$k + 1$ 时刻有功、无功功率参考值。
进一步的在储能换流器实际应用中, 在采样、 计算环节存在周期延时导致储能系统暂态特性差, 即在$k$ 时刻交流侧端电压采样值不能应用于当前采样周期,而是应用于$k + 1$ 时刻的采样周期,误差累计导致控制系统出现较大偏差。为了抑制周期延时带来的控制偏差, 本文采用两步模型预测方法即两周期延时补偿策略对系统变量进行预测, 以获得超前控制效果, 从而抵消延时影响, 根据式 (9) 可以得到$k + 2$ 时刻储能换流器功率$\mathrm{{MPC}}$ 数学模型为
$\left\lbrack \begin{array}{l} P\left({k + 2}\right)\\ Q\left({k + 2}\right)\end{array}\right\rbrack =\left\lbrack \begin{matrix} 1 -{T}_{\mathrm{s}}\frac{{R}_{\mathrm{f}}}{{L}_{\mathrm{f}}}& -{T}_{\mathrm{s}}\omega \\{T}_{\mathrm{s}}\omega & 1 -{T}_{\mathrm{s}}\frac{{R}_{\mathrm{f}}}{{L}_{\mathrm{f}}}\end{matrix}\right\rbrack \left\lbrack \begin{array}{l} P\left({k + 1}\right)\\ Q\left({k + 1}\right)\end{array}\right\rbrack +\\{T}_{\mathrm{s}}\frac{3}{2{L}_{\mathrm{f}}}\left\lbrack \begin{matrix}{U}_{\alpha }- {e}_{\alpha }\left({k + 1}\right)& {U}_{\beta }- {e}_{\alpha }\left({k + 1}\right)\\- {U}_{\beta }& {U}_{\alpha }\end{matrix}\right\rbrack .\\\left\lbrack \begin{array}{l}{e}_{\alpha }\left({k + 1}\right)\\{e}_{\beta }\left({k + 1}\right)\end{array}\right\rbrack $
根据式 (10) 可得两步模型预测下功率权重价值函数为
${J}_{k + 2}= {\left\lbrack {P}^{* }\left( k + 2\right)- P\left( k + 2\right)\right\rbrack }^{2}+ {\left\lbrack {Q}^{* }\left( k + 2\right)- Q\left( k + 2\right)\right\rbrack }^{2}$
为了实现储能换流器功率$\mathrm{{MPC}}$ 精确控制,使有功、无功的期望值与预测值误差最小,需要使功率权重价值函数值最小,${J}_{k + 2}$${U}_{\alpha }$${U}_{\beta }$ 求偏导为 0,即
$\left\{\begin{array}{l}\frac{\partial {J}_{k + 2}}{\partial {U}_{\alpha }}= 0 \\\frac{\partial {J}_{k + 2}}{\partial {U}_{\beta }}= 0 \end{array}\right.$
将式(13)代入式(12),可以得到两相静止${a\beta }$ 坐标系下储能换流器输出电压最优值为
$\left\{\begin{matrix}{U}_{\alpha }\left({k + 1}\right)= {e}_{\alpha }\left({k + 1}\right)- 2{R}_{\mathrm{f}}{i}_{\alpha }\left({k + 1}\right)+ {2\omega }{L}_{\mathrm{f}}{i}_{\beta }\left({k + 1}\right)- \\\frac{2{L}_{\mathrm{f}}}{3{T}_{\mathrm{s}}}\frac{\left\lbrack {\varepsilon }_{P}\left( k + 1\right){e}_{\alpha }\left( k + 1\right)+ {\varepsilon }_{Q}\left( k + 1\right){e}_{\beta }\left( k + 1\right)\right\rbrack }{{\varepsilon }_{\alpha }^{2}\left({k + 1}\right)} -\\{U}_{\beta }\left({k + 1}\right)= {e}_{\beta }\left({k + 1}\right)- 2{R}_{\mathrm{f}}{i}_{\beta }\left({k + 1}\right)+ {2\omega }{L}_{\mathrm{f}}{i}_{\alpha }\left({k + 1}\right)- \\\frac{2{L}_{\mathrm{f}}}{3{T}_{\mathrm{s}}}\left\lbrack {{\varepsilon }_{P}\left({k + 1}\right){e}_{\beta }\left({k + 1}\right)+ {\varepsilon }_{Q}\left({k + 1}\right){e}_{\alpha }\left({k + 1}\right)}\right\rbrack \\- \frac{2{L}_{\mathrm{f}}}{3{T}_{\mathrm{s}}}\left\lbrack {{\varepsilon }_{P}\left({k + 1}\right){e}_{\alpha }\left({k + 1}\right)- {\varepsilon }_{Q}\left({k + 1}\right)}\right\rbrack \end{matrix}\right.$
式中,${\varepsilon }_{P}\left({k + 1}\right)\text{、}{\varepsilon }_{Q}\left({k + 1}\right)$$k + 1$ 时刻有功、无功控制误差在 MPC 价值函数中所占的权重, 可表示为
$\left\{\begin{array}{l}{\varepsilon }_{P}\left({k + 1}\right)= {P}^{* }\left({k + 1}\right)- P\left({k + 1}\right)\\{\varepsilon }_{Q}\left({k + 1}\right)= {Q}^{* }\left({k + 1}\right)- Q\left({k + 1}\right)\end{array}\right.$
储能换流器 MPC 控制系统对于参数误差较为敏感,参数误差主要来自于滤波电感${L}_{\mathrm{f}}$ 参数偏移, 滤波电感实际值可表示为
${L}_{\mathrm{{fg}}}= {L}_{\mathrm{{fm}}}+ \Delta {L}_{\mathrm{f}}$
式中:${L}_{\mathrm{{fm}}}$ 为滤波电感参数设定值;$\Delta {L}_{\mathrm{f}}$ 为滤波电感偏差量。根据式 (12),因为${L}_{\mathrm{f}}$ 参数偏移造成的输出电压最优值偏差为
$\left\{\begin{matrix}\Delta {U}_{\alpha }\left({k + 1}\right)= \Delta {L}_{\mathrm{f}}{i}_{\beta }\left({k + 1}\right)- \frac{{2\Delta }{L}_{\mathrm{f}}}{3{T}_{\mathrm{s}}}.\\\frac{\left\lbrack {\varepsilon }_{P}\left( k + 1\right){e}_{\alpha }\left( k + 1\right)+ {\varepsilon }_{Q}\left( k + 1\right){e}_{\beta }\left( k + 1\right)\right\rbrack }{{e}_{\alpha }^{2}\left({k + 1}\right)+ {e}_{\beta }^{2}\left({k + 1}\right)} \\\Delta {U}_{\beta }\left({k + 1}\right)= \Delta {L}_{\mathrm{f}}{i}_{\alpha }\left({k + 1}\right)- \frac{2{L}_{\mathrm{f}}}{3{T}_{\mathrm{s}}}.\\\frac{\left\lbrack {\varepsilon }_{P}\left( k + 1\right){e}_{\beta }\left( k + 1\right)+ {\varepsilon }_{Q}\left( k + 1\right){e}_{\alpha }\left( k + 1\right)\right\rbrack }{{e}_{\alpha }^{2}\left({k + 1}\right)+ {e}_{\beta }^{2}\left({k + 1}\right)} \end{matrix}\right.$
由式 (17) 可知:滤波电感参数偏差会引起最优控制变量偏差, 造成储能换流器输出错误电压矢量,严重影响 MPC 控制精度。尤其是$\Delta {L}_{\mathrm{f}}> 0$,即滤波电感参数设定值小于实际值时, 将对 MPC 最优控制造成更大影响。
根据式 (11)、式 (16),可以得到电感误差补充后的$k + 2$ 时刻储能换流器功率$\mathrm{{MPC}}$ 数学模型为
$\left\lbrack \begin{array}{l}{P}_{\mathrm{m}}\left({k + 2}\right)\\{Q}_{\mathrm{m}}\left({k + 2}\right)\end{array}\right\rbrack =\left\lbrack \begin{matrix} 1 -{T}_{\mathrm{s}}\frac{{R}_{\mathrm{f}}}{{L}_{\mathrm{{fg}}}}& -{T}_{\mathrm{s}}\omega \\{T}_{\mathrm{s}}\omega & 1 -{T}_{\mathrm{s}}\frac{{R}_{\mathrm{f}}}{{L}_{\mathrm{{fm}}}}\end{matrix}\right\rbrack \left\lbrack \begin{array}{l} P\left({k + 1}\right)\\ Q\left({k + 1}\right)\end{array}\right\rbrack +\\{T}_{\mathrm{s}}\frac{3}{2{L}_{\mathrm{{fm}}}}\left\lbrack \begin{matrix}{U}_{\alpha }- {e}_{\alpha }\left({k + 1}\right)& {U}_{\beta }- {e}_{\alpha }\left({k + 1}\right)\\- {U}_{\beta }& {U}_{\alpha }\end{matrix}\right\rbrack .\\\left\lbrack \begin{array}{l}{e}_{\alpha }\left({k + 1}\right)\\{e}_{\beta }\left({k + 1}\right)\end{array}\right\rbrack $
式中,${P}_{\mathrm{m}}\left({k + 2}\right)$${Q}_{\mathrm{m}}\left({k + 2}\right)$ 为电感误差补充后的有功、 无功功率预测值。以有功功率为例, 用式 (18) 中电感误差补充后$k + 2$ 时刻有功功率减去式 (11) 中$k + 2$ 时刻有功功率,可以得到
${L}_{\mathrm{f}0}= {L}_{\mathrm{{fg}}}= {L}_{\mathrm{{fm}}}\left\lbrack \frac{{P}_{\mathrm{m}}\left({k + 2}\right)- P\left({k + 1}\right)+ {T}_{\mathrm{s}}{\omega Q}\left({k + 1}\right)}{P\left({k + 2}\right)- P\left({k + 1}\right)+ {T}_{\mathrm{s}}{\omega Q}\left({k + 1}\right)}\right\rbrack $
式中,${L}_{\mathrm{f}0}$ 为电感观测值。储能换流器$\mathrm{{MPC}}$ 控制系统在当前时刻即$k$ 时刻电感观测值为
${L}_{\mathrm{f}0}= {L}_{\mathrm{{fm}}}\left\lbrack \frac{{P}_{\mathrm{m}}\left( k\right)- P\left({k - 1}\right)+ {T}_{\mathrm{s}}{\omega Q}\left({k - 1}\right)}{P\left( k\right)- P\left({k - 1}\right)+ {T}_{\mathrm{s}}{\omega Q}\left({k - 1}\right)}\right\rbrack $
根据上述分析,可以通过${L}_{\mathrm{f}0}$$\mathrm{{MPC}}$ 控制系统电感参数进行实时修正, 减少预测误差保证控制精度。电感观测控制框图如图2 所示。
图2 中:限幅和低通滤波 LPF (low pass filter) 可以有效克服高频脉冲对控制系统的影响。电感观测控制通过两步预测得到的功率与前一时刻功率差值对参数误差进行修正。在 MPC 系统中, 因为其他参数误差引起的输出电压最优值偏差, 均可以折算为电感参数, 得到统一补偿。
为了验证本文所提储能换流器改进功率模型预测控制有效性。在 Matlab/Simulink 平台搭建如图1 所示的储能换流器系统。系统仿真参数如表1 所示。
设置仿真工况为$0 \sim {0.2}\mathrm{\;s}$ 空载运行,${0.2}\mathrm{\;s}$ 突加${80\Omega }$ 负载,本文在 PI 控制和改进 MPC 中采用滞环限幅控制, 使得到的储能换流器输出有功、无功波形更加平滑, 更好的反应负载突变情况下, 有功功率、无功功率的变化情况。采用 PI 控制得到的储能换流器输出有功、无功波形如图3 所示, 采用本文所提改进 MPC 得到的储能换流器输出有功、无功波形如图4 所示。
图3 可知:当面对突加负载工况,不管是有功功率还是无功功率在调节过程中, 存在超调和功率振荡现象,无法实现功率快速响应。
图3(a)中,当${0.2}\mathrm{\;s}$ 时刻有功功率突增至${0.3}\mathrm{\;{kW}}$, 传统$\mathrm{{PI}}$ 控制超调量最大达到${0.15}\mathrm{\;{kW}}$图3(b)中, 当${0.2}\mathrm{\;s}$ 时刻无功功率突降至$-{0.08}\mathrm{{kVar}}$,传统$\mathrm{{PI}}$ 控制超调量最大达到${0.05}\mathrm{{kVar}}$。在储能换流器控制系统中,传统PI 控制无法实现负荷突变功率快速、精确跟踪。
图4 可知:当采用本文所提改进 MPC 控制得到的有功、无功功率超调量减少很多,且没有功率振荡现象,可以实现快速跟踪功率指令值。图4(a) 中, 当${0.2}\mathrm{\;s}$ 时刻有功功率突增至${0.3}\mathrm{\;{kW}}$,改进 MPC 控制超调量可以控制在${0.02}\mathrm{\;{kW}}$ 内。图4 (b) 中,当${0.2}\mathrm{\;s}$ 时刻无功功率突降至$-{0.08}\mathrm{{kVar}}$,改进 MPC 控制超调量可以控制在${0.01}\mathrm{{kVar}}$ 内。相较于传统$\mathrm{{PI}}$ 控制, 储能换流器改进 MPC 控制具有更加快速和精确的功率控制能力。
图5图6 为储能系统空载运行,分别采用常规 MPC 和本文所提含有电感误差补偿 MPC 得到的${a\beta }$ 坐标系下换流器输出电压与参考电压波形。
图5 可知: 当滤波电感标称值与实际值不匹配时,储能换流器输出两相电压${U}_{\alpha }\text{、}{U}_{\beta }$ 无法实时跟踪目标电压,与目标电压存在周期延时且波形产生畸变, 暂态特性差, 控制效果不理想。
图6 可知: 当采用本文所提含有电感误差补偿模块的 MPC 得到的两相电压${U}_{\alpha }\text{、}{U}_{\beta }$ 可以快速跟踪目标电压, 且波形正弦特性良好。这是因为电感误差补偿模块可以准确获取滤波电感参数变化, 对参数偏差实时补偿, 有效提高储能换流器控制系统精度, 具有良好的暂态特性。
为了验证采用改进 MPC 控制算法后储能换流器对输出电压的动态控制性能, 搭建了 DSP+FPGA 的 LC 型储能换流器实验平台, 其中 DSP 选择 T MS320F28335、FPGA 选择 Spartan-7 以及相关外围电路、IGBT 选择 K40T120、示波器选择 MDO4104B-3 型示波器, 谐波测试选择 MAVOWATT 谐波测试器。 储能换流器参数与仿真一致。
图7 为采用常规 MPC 控制和本文所提改进 MPC 控制得到的储能换流器输出 A 相电压波形 (截取一段)。
图8 为两种控制方式下通过谐波测试仪得到的 A 相电压 THD 分析。
根据图7(a)可得:采用常规 MPC 得到的储能换流器输出$\mathrm{A}$ 相电压波形毛刺较多,在峰值和谷值处叠加了许多高次谐波分量,谐波畸变率高。
根据图7(b)可得:采用改进 MPC 控制得到的储能换流器输出$\mathrm{A}$ 相电压波形无畸变,正弦特性良好。
根据图8(a)可得:采用常规MPC 得到的储能换流器输出$\mathrm{A}$ 相电压$\mathrm{{THD}}= {7.71}\%$,谐波含量较高, 尤其是奇次谐波,暂态特性差,控制效果不理想。
根据图8(b)可得:采用改进 MPC 控制得到的储能换流器输出$\mathrm{A}$ 相电压$\mathrm{{THD}}= {2.03}\%,5$ 次、 7 次谐波明显降低,控制系统精度较高。
本文在储能换流器控制系统中采用 MPC 控制,为了实现储能换流器有功、无功快速响应,提高控制系统暂态特性, 本文采用有功、无功相同权重价值函数, 进一步得到输出电压最优值。针对滤波电感参数偏移导致的模型精度不高问题, 本文提出一种电感误差补偿模块来补偿控制偏差, 提高模型预测准确度。
仿真和实验结果表明:采用本文所提改进 MPC 控制储能换流器有更加快速和精确的功率控制能力, 可以实现功率实时、准确跟踪。电感误差补偿模块可以对滤波电感参数进行实时补偿, 有效提高储能换流器控制系统精度, 所提改进功率模型预测可以有效提高储能系统暂态特性, 具有一定工程应用价值。
  • 国家重点研发计划“973”资助项目(2017YFB0902102)
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2024年第22卷第2期
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doi: 10.13234/j.issn.2095-2805.2024.2.242
  • 接收时间:2021-03-30
  • 首发时间:2025-07-21
  • 出版时间:2024-03-30
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  • 收稿日期:2021-03-30
  • 修回日期:2021-05-31
  • 录用日期:2021-06-09
基金
National Key R & D Plan"973"(2017YFB0902102)
国家重点研发计划“973”资助项目(2017YFB0902102)
作者信息
    1 山东职业学院 智能制造学院 济南 250104
    2 西安热工研究院有限公司 西安 710054
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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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