CN104242318A - 基于模型预测控制理论的直流近区电压自动控制方法 - Google Patents

基于模型预测控制理论的直流近区电压自动控制方法 Download PDF

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CN104242318A
CN104242318A CN201410437080.7A CN201410437080A CN104242318A CN 104242318 A CN104242318 A CN 104242318A CN 201410437080 A CN201410437080 A CN 201410437080A CN 104242318 A CN104242318 A CN 104242318A
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CN104242318B (zh
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孙宏斌
郭庆来
王彬
张伯明
吴文传
徐峰达
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Tsinghua University
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    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
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    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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    • HELECTRICITY
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    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
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    • F03D7/042Automatic control; Regulation by means of an electrical or electronic controller
    • F03D7/043Automatic control; Regulation by means of an electrical or electronic controller characterised by the type of control logic
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Abstract

本发明涉及基于模型预测控制理论的直流近区电压控制方法,属于电力系统直流近区电压控制技术领域,该方法包括采集系统当前各类电量实测值作为各类电量的预测值的初始值,根据采集的数据建立由目标函数和约束条件组成的MPC优化控制模型,对该MPC优化控制模型进行简化,再利用优化工具求解MPC优化控制简化模型,获得发电机电压设定值在MPC时间窗内的解序列;将解序列中首个值作为控制目标下发给参与电压控制的发电机,以实现直流近区电压的自动控制。本方法能够在过程中实现多种连续离散无功设备协调,以适应目前直流方式改变时近区多种无功设备的协调。

Description

基于模型预测控制理论的直流近区电压自动控制方法
技术领域
本发明属于电力系统直流近区电压控制方法。
背景技术
随着国民经济的不断发展,传统重负荷用电量持续增长,我国负荷发电中心相隔较远的现状决定目前需要在大区电网间进行大功率输送。交流、直流超特高压长距离输电,直流背靠背等电网互联方式已得到普遍应用。
现场运行中发现,直流联网系统中存在受端直流近区网络薄弱的情况,该区域电压水平由系统潮流决定,域内电气联系紧密。大网间直流传输方式变化时,近区有功潮流将发生巨大变化,另外换流站通常配有大容量滤波电容,电容投切时将产生无功大扰动。在两者混合作用下,直流近区变电站电压出现大幅波动的状况,对系统安全运行十分不利。
目前直流近区参与区域自动电压控制的手段较为有限,主要包括邻近发电厂无功及变电站内容抗器投切等,换流站内一般只进行本地电压控制。运行数据表明直流传输功率变化时段,换流站滤波电容动作频繁,容易造成系统电压大幅波动。传统电压控制的多基于单时间断面系统状态展开,难以有效应对较长过程中区域内多种无功补偿设备间相互影响。
模型预测控制(MPC,Model Predictive Control)是过程控制理论中一种重要方法,广泛应用于石油、化工、冶金、机械等多个行业。在电力系统中主要应用于电网电压控制、电压稳定、有功调度、储能管理等领域,具有控制效果良好、鲁棒性强的优点。模型预测控制的当前控制动作是在每一个采样瞬间通过求解一个有限时域开环最优控制问题而获得。过程的当前状态作为最优控制问题的初始状态,解得的最优控制序列只实施第一个控制作用。这是它与那些使用预先计算控制律的算法的最大不同。
发明内容
本发明的目的是克服现有技术的不足之处,提出一种基于模型预测控制理论的直流近区电压控制方法,本方法能够在过程中实现多种连续离散无功设备协调,以适应目前直流方式改变时近区多种无功设备的协调。
本发明提出的基于模型预测控制理论的直流近区电压控制方法,用于主站AVC系统控制中,其特征在于,当一个控制周期开始时进行以下步骤:
1)采集系统当前各类电量实测值作为各类电量的预测值的初始值,预测值包括:中枢母线电压预测值变电站母线电压预测值变电站负荷有功预测值变电站负荷无功预测值变电站容抗器投入量发电机端电压预测值发电机有功预测值和发电机无功预测值并根据发电计划和负荷预测为MPC控制时间窗内变量赋值;
2)根据采集的数据建立由目标函数和约束条件组成的MPC优化控制模型:
2.1)MPC优化控制模型的目标函数如式(1):
min V G set Σ i = 0 N - 1 Σ j = 0 M - 1 ρ t i , j F 1 - - - ( 1 )
式(1)中,为优化变量,含义为参与电压控制发电机机端电压设定值;N为时间窗覆盖控制周期的个数;M为单个控制周期下含预测点的个数;时间变量ti,j=(Mi+j)Δt意义为当前时刻起第i个控制周期内的第j个预测点,ρ为衰减系数,取值ρ<1,Δt为预测点间隔;
式(1)中F1为中枢母线电压与设定值的偏差,具体表达式如下:
F 1 ( t i , j ) = [ V Pilot pre ( t i , j ) - V Pilot ref ] 2 - - - ( 2 )
式(2)中表示区域中枢母线电压的参考值;
2.2)优化模型的约束条件:
2.2.1)发电机无功预测约束条件:
对发电机无功参考值预测的约束如式(3)所示:
Q G ref ( t i , j ) = K P [ V G pre ( t i , j ) - V G set ( t i , 0 ) ] + K I Δt Σ k = 0 i × M + j [ V G pre ( t i , j - k ) - V G set ( t i , - k ) ] + Q G pre ( t 0,0 ) - K P [ V G pre ( t 0,0 ) - V G set ( t 0 , 0 ) ] - - - ( 3 )
式(3)中表示发电机机端电压的预测值,KI和KP分别为比例环节和积分环节的系数,由发电机励磁调节器控制系数确定;
对发电机无功预测值的约束如式(4)所示:
Q G pre ( t i , j ) = Q G ref ( t i , j - 1 ) + [ Q G pre ( t i , j - 1 ) - Q G ref ( t i , j - 1 ) ] e - ( t i , j - t i , j - 1 ) / T d - - - ( 4 )
式(4)中时间常数Td为发电机励磁调节器动作时延;
2.2.2)电压预测约束条件:
v pre ( t i , j ) - v pre ( t 0,0 ) = s P G pre ( t i , j ) - P G pre ( t 0,0 ) Q G pre ( t i , j ) - Q G pre ( t 0,0 ) - P St pre ( t i , j ) + P St pre ( t 0,0 ) - Q St pre ( t i , j ) + Q St pre ( t 0,0 ) + Q St C [ N St pre ( t i , j ) - N St pre ( t 0,0 ) ] - - - ( 5 )
式(5)中Vpre为中枢母线、变电站和发电机电压预测值构成的向量,S为灵敏度矩阵;为发电机有功预测值,由发电计划的得到;分别为变电站负荷有功和无功预测值,可查询计划值得到;整数变量分别为变电站电容器单组容量和投入组数;
2.2.3)变电站容抗器投入量预测的约束条件:
如式(6):
v ^ pre ( t i , j ) - v pre ( t 0,0 ) = s P G pre ( t i , j ) - P G pre ( t 0,0 ) Q G pre ( t i , j ) - Q G pre ( t 0,0 ) - P St pre ( t i , j ) + P St pre ( t 0,0 ) - Q St pre ( t i , j ) + Q St pre ( t 0,0 ) + Q St C [ N St pre ( t i , j - 1 ) - N St pre ( t 0,0 ) ] - - - ( 6 )
式(6)中为容抗器动作前中枢母线、变电站和发电机电压构成的向量,为其分量;
容抗器投入组数的约束条件如式(7)所示:
N St pre ( t i , j ) = N St pre ( t i , j - 1 ) - 1 , V ^ St pre > V St max N St pre ( t i , j - 1 ) + 1 , V ^ St pre < V St min N St pre ( t i , j - 1 ) , else - - - ( 7 )
式(7)中分别为变电站电压上下限值;
2.2.4)换流站定无功模式下滤波电容投入量预测的约束条件:
滤波电容动作前换流站注入电网总无功的约束条件如式(8)所示:
Q ^ St , out pre = - Q St pre ( t i , j ) + Q St C N St pre ( t i , j - 1 ) - - - ( 8 )
容抗器投入组数的约束条件如式(9)所示:
N St pre ( t i , j ) = N St pre ( t i , j - 1 ) - 1 , Q ^ St , out pre > Q St , out max N St pre ( t i , j - 1 ) + 1 , Q ^ St , out pre < Q St , out min N St pre ( t i , j - 1 ) , else - - - ( 9 )
式(8)中分别为滤波电容动作前换流站注入电网总无功上下限值;
2.2.5)容抗器动作次数约束的约束条件:
容抗器动作量预测的约束条件如式(10)所示,该动作量为0-1变量:
- O St pre ( t i , j ) &le; N St pre ( t i , j ) - N St pre ( t i , j - 1 ) &le; O St pre ( t i , j ) - - - ( 10 )
MPC优化时间窗内容抗器动作次数限制的约束条件如式(11)所示:
&Sigma; i = 0 N - 1 &Sigma; j = 0 M - 1 O St pre ( t i , j ) 1 &le; O St max - - - ( 11 )
式(11)中为动作次数上限;
2.2.6)系统电压、发电机运行和变电站容抗器组数的约束条件:
v min &le; v pre ( t i , j ) &le; v max Q G min &le; Q G pre ( t i , j ) &le; Q G max N St min &le; N St pre ( t i , j ) &le; N St max - - - ( 12 )
式(12)中Vmax和Vmin分别为由中枢母线、变电站和发电机电压构成系统电压向量的上限和下限,分别为发电机无功运行上下限,分别为变电站容抗器组数上下限;
2.3)式(1)优化目标函数与式(2-12)约束条件构成MPC优化控制模型;
3)对MPC优化控制模型进行简化:
删去式(3)对发电机无功参考值预测的约束,和式(4)中对发电机无功预测的约束条件,并在原目标函数中增加式(13):
min &Sigma; i = 0 N - 1 &Sigma; j = 0 M - 1 &rho; t i , j F 2 - - - ( 13 )
式(13)中F2含义为发电机机端电压预测值与设定值偏差:
F 2 = [ V G pre ( t i , j ) - V G set ( t i , 0 ) ] 2 - - - ( 14 )
简化后的MPC优化控制模型的目标函数如式(15)所示:
min &Sigma; i = 0 N - 1 &Sigma; j = 0 M - 1 &rho; t i , j ( F 1 + w T F 2 ) - - - ( 15 )
式(15)中F2为各发电机机端电压预测值与设定值偏差F2组成的向量,w为对应权重向量,权重值取中枢母线电压对发电机机端电压灵敏度的平方;
由式(15)优化目标函数与式(2)、(5-12)、(14)约束条件构成MPC优化控制简化模型;
4)利用优化工具求解MPC优化控制简化模型,获得发电机电压设定值在MPC时间窗内的解序列
5)将解序列中首个值作为控制目标下发给参与电压控制的发电机,以实现直流近区电压的自动控制。
本发明特点和效果:
本发明方法中设计了发电机无功和变电站容抗器投切预测模型,可以预估一段时间直流近区电压状态变化。相比于传统的仅以当前状态作为控制判据的控制方法,能够在过程中实现多种连续离散无功设备协调。本发明方法,可集成在调度中心现场运行的自动电压控制系统中,使该系统能够实时应对直流近区负荷波动及直流方式变化。
具体实施方式
本发明提出的基于模型预测控制理论的直流近区电压控制方法,用于主站AVC系统控制中,其特征在于,当一个控制周期(根据通信条件确定,实施例中设为5min)开始时进行以下步骤:
1)采集系统当前各类电量实测值作为各类电量的预测值的初始值,预测值包括:中枢母线电压预测值变电站母线电压预测值变电站负荷有功预测值变电站负荷无功预测值变电站容抗器投入量发电机端电压预测值发电机有功预测值和发电机无功预测值并根据发电计划和负荷预测为MPC控制时间窗内变量赋值;
2)根据采集的数据建立由目标函数和约束条件组成的MPC优化控制模型:
2.1)MPC优化控制模型的目标函数如式(1):
min V G set &Sigma; i = 0 N - 1 &Sigma; j = 0 M - 1 &rho; t i , j F 1 - - - ( 1 )
式(1)中,为优化变量,含义为参与电压控制发电机机端电压设定值;N为时间窗覆盖控制周期的个数(典型主站AVC系统控制周期为5min,实施例中N取值为6),MPC优化的时间窗长度据直流方式转换耗时确定(约30min);M为单个控制周期下含预测点的个数(用以精细化系统状态变化过程);时间变量ti,j=(Mi+j)Δt意义为当前时刻起第i个控制周期内的第j个预测点,ρ为衰减系数,取值ρ<1,Δt为预测点间隔(根据计算量设定,间隔越小描述越精细但计算量越大,实施例中设置为1min,M取值为5);
式(1)中F1为中枢母线电压与设定值的偏差,具体表达式如下:
F 1 ( t i , j ) = [ V Pilot pre ( t i , j ) - V Pilot ref ] 2 - - - ( 2 )
式(2)中表示区域中枢母线电压的参考值(人工设定,不超过区域中枢母线电压确定的上下限值);
2.2)优化模型的约束条件:
2.2.1)发电机无功预测约束条件:
对发电机无功参考值预测的约束如式(3)所示:
Q G ref ( t i , j ) = K P [ V G pre ( t i , j ) - V G set ( t i , 0 ) ] + K I &Delta;t &Sigma; k = 0 i &times; M + j [ V G pre ( t i , j - k ) - V G set ( t i , - k ) ] + Q G pre ( t 0,0 ) - K P [ V G pre ( t 0,0 ) - V G set ( t 0 , 0 ) ] - - - ( 3 )
式(3)中表示发电机机端电压的预测值,KI和KP分别为比例环节和积分环节的系数,由发电机励磁调节器控制系数确定(当发电机无功参考值超出发电机无功上下限范围时,取贴近的上限或下限值;
对发电机无功预测值的约束如式(4)所示:
Q G pre ( t i , j ) = Q G ref ( t i , j - 1 ) + [ Q G pre ( t i , j - 1 ) - Q G ref ( t i , j - 1 ) ] e - ( t i , j - t i , j - 1 ) / T d - - - ( 4 )
式(4)中时间常数Td为发电机励磁调节器动作时延;
2.2.2)电压预测约束条件:
v pre ( t i , j ) - v pre ( t 0,0 ) = s P G pre ( t i , j ) - P G pre ( t 0,0 ) Q G pre ( t i , j ) - Q G pre ( t 0,0 ) - P St pre ( t i , j ) + P St pre ( t 0,0 ) - Q St pre ( t i , j ) + Q St pre ( t 0,0 ) + Q St C [ N St pre ( t i , j ) - N St pre ( t 0,0 ) ] - - - ( 5 )
式(5)中Vpre为中枢母线、变电站和发电机电压预测值构成的向量,S为灵敏度矩阵(潮流方程线性化后得到);为发电机有功预测值,由发电计划的得到;分别为变电站负荷(包括换流站直流端极等值负荷)有功和无功预测值,可查询计划值得到;整数变量分别为变电站电容器单组容量和投入组数(投入电抗时取负值);
2.2.3)变电站容抗器投入量预测的约束条件:
该约束为在具备本地电压控制策略的变电站中,将在电压越上限/下限时投入/切除一组电抗器,电容器控制与之相反;必须首先计算容抗器动作前电压水平如式(6):
v ^ pre ( t i , j ) - v pre ( t 0,0 ) = s P G pre ( t i , j ) - P G pre ( t 0,0 ) Q G pre ( t i , j ) - Q G pre ( t 0,0 ) - P St pre ( t i , j ) + P St pre ( t 0,0 ) - Q St pre ( t i , j ) + Q St pre ( t 0,0 ) + Q St C [ N St pre ( t i , j - 1 ) - N St pre ( t 0,0 ) ] - - - ( 6 )
式(6)中为容抗器动作前中枢母线、变电站和发电机电压构成的向量,为其分量;
容抗器投入组数的约束条件如式(7)所示:
N St pre ( t i , j ) = N St pre ( t i , j - 1 ) - 1 , V ^ St pre > V St max N St pre ( t i , j - 1 ) + 1 , V ^ St pre < V St min N St pre ( t i , j - 1 ) , else - - - ( 7 )
式(7)中分别为变电站电压上下限值(式中逻辑约束在优化计算时将被转化为含整数变量的线性约束);
2.2.4)换流站定无功模式下滤波电容投入量预测的约束条件:
滤波电容动作前换流站注入电网总无功的约束条件如式(8)所示:
Q ^ St , out pre = - Q St pre ( t i , j ) + Q St C N St pre ( t i , j - 1 ) - - - ( 8 )
容抗器投入组数的约束条件如式(9)所示:
N St pre ( t i , j ) = N St pre ( t i , j - 1 ) - 1 , Q ^ St , out pre > Q St , out max N St pre ( t i , j - 1 ) + 1 , Q ^ St , out pre < Q St , out min N St pre ( t i , j - 1 ) , else - - - ( 9 )
式(8)中分别为滤波电容动作前换流站注入电网总无功上下限值(式中逻辑约束在优化计算时被转化为含整数变量的线性约束);
2.2.5)容抗器动作次数约束的约束条件:
容抗器动作量预测的约束条件如式(10)所示,该动作量为0-1变量:
- O St pre ( t i , j ) &le; N St pre ( t i , j ) - N St pre ( t i , j - 1 ) &le; O St pre ( t i , j ) - - - ( 10 )
MPC优化时间窗内容抗器动作次数限制的约束条件如式(11)所示:
&Sigma; i = 0 N - 1 &Sigma; j = 0 M - 1 O St pre ( t i , j ) 1 &le; O St max - - - ( 11 )
式(11)中为动作次数上限(在优化前结合当日容抗器已动次数确定);
2.2.6)系统电压、发电机运行和变电站容抗器组数的约束条件:
v min &le; v pre ( t i , j ) &le; v max Q G min &le; Q G pre ( t i , j ) &le; Q G max N St min &le; N St pre ( t i , j ) &le; N St max - - - ( 12 )
式(12)中Vmax和Vmin分别为由中枢母线、变电站和发电机电压构成系统电压向量的上限和下限,分别为发电机无功运行上下限,分别为变电站容抗器组数上下限(上限等于电容器组数,下限等于电抗器组数的相反数);
2.3)式(1)优化目标函数与式(2-12)约束条件构成MPC优化控制模型;
3)对MPC优化控制模型进行简化:
(应用时在MPC模型的预测点间隔Δt内,发电机通常已进入稳态,发电机已无功调节到位使机端电压达到设定值,或发电机无功达到限值,因此可以将步骤2.3)的优化模型进行简化;)
删去式(3)对发电机无功参考值预测的约束,和式(4)中对发电机无功预测的约束条件,并在原目标函数中增加式(13):
min &Sigma; i = 0 N - 1 &Sigma; j = 0 M - 1 &rho; t i , j F 2 - - - ( 13 )
式(13)中F2含义为发电机机端电压预测值与设定值偏差:
F 2 = [ V G pre ( t i , j ) - V G set ( t i , 0 ) ] 2 - - - ( 14 )
简化后的MPC优化控制模型的目标函数如式(15)所示:
min &Sigma; i = 0 N - 1 &Sigma; j = 0 M - 1 &rho; t i , j ( F 1 + w T F 2 ) - - - ( 15 )
式(15)中F2为各发电机机端电压预测值与设定值偏差F2组成的向量,w为对应权重向量,权重值取中枢母线电压对发电机机端电压灵敏度的平方;
由式(15)优化目标函数与式(2)、(5-12)、(14)约束条件构成MPC优化控制简化模型;
4)利用优化工具(如Cplex、Mosek等)求解MPC优化控制简化模型,获得发电机电压设定值在MPC时间窗内的解序列(该模型为混合整数二次规划问题,可以快速求解);
5)将解序列中首个值作为控制目标下发给参与电压控制的发电机,以实现直流近区电压的自动控制。

Claims (1)

1.一种基于模型预测控制理论的直流近区电压控制方法,用于主站AVC系统控制中,其特征在于,当一个控制周期开始时进行以下步骤:
1)采集系统当前各类电量实测值作为各类电量的预测值的初始值,预测值包括:中枢母线电压预测值变电站母线电压预测值变电站负荷有功预测值变电站负荷无功预测值变电站容抗器投入量发电机端电压预测值发电机有功预测值和发电机无功预测值并根据发电计划和负荷预测为MPC控制时间窗内变量赋值;
2)根据采集的数据建立由目标函数和约束条件组成的MPC优化控制模型:
2.1)MPC优化控制模型的目标函数如式(1):
min V G set &Sigma; i = 0 N - 1 &Sigma; j = 0 M - 1 &rho; t i , j F 1 - - - ( 1 )
式(1)中,为优化变量,含义为参与电压控制发电机机端电压设定值;N为时间窗覆盖控制周期的个数;M为单个控制周期下含预测点的个数;时间变量ti,j=(Mi+j)Δt意义为当前时刻起第i个控制周期内的第j个预测点,ρ为衰减系数,取值ρ<1,Δt为预测点间隔;
式(1)中F1为中枢母线电压与设定值的偏差,具体表达式如下:
F 1 ( t i , j ) = [ V Pilot pre ( t i , j ) - V Pilot ref ] 2 - - - ( 2 )
式(2)中表示区域中枢母线电压的参考值;
2.2)优化模型的约束条件:
2.2.1)发电机无功预测约束条件:
对发电机无功参考值预测的约束如式(3)所示:
Q G ref ( t i , j ) = K P [ V G pre ( t i , j ) - V G set ( t i , 0 ) ] + K I &Delta;t &Sigma; k = 0 i &times; M + j [ V G pre ( t i , j - k ) - V G set ( t i , - k ) ] + Q G pre ( t 0,0 ) - K P [ V G pre ( t 0,0 ) - V G set ( t 0 , 0 ) ] - - - ( 3 )
式(3)中表示发电机机端电压的预测值,KI和KP分别为比例环节和积分环节的系数,由发电机励磁调节器控制系数确定;
对发电机无功预测值的约束如式(4)所示:
Q G pre ( t i , j ) = Q G ref ( t i , j - 1 ) + [ Q G pre ( t i , j - 1 ) - Q G ref ( t i , j - 1 ) ] e - ( t i , j - t i , j - 1 ) / T d - - - ( 4 )
式(4)中时间常数Td为发电机励磁调节器动作时延;
2.2.2)电压预测约束条件:
v pre ( t i , j ) - v pre ( t 0,0 ) = s P G pre ( t i , j ) - P G pre ( t 0,0 ) Q G pre ( t i , j ) - Q G pre ( t 0,0 ) - P St pre ( t i , j ) + P St pre ( t 0,0 ) - Q St pre ( t i , j ) + Q St pre ( t 0,0 ) + Q St C [ N St pre ( t i , j ) - N St pre ( t 0,0 ) ] - - - ( 5 )
式(5)中Vpre为中枢母线、变电站和发电机电压预测值构成的向量,S为灵敏度矩阵;为发电机有功预测值,由发电计划的得到;分别为变电站负荷有功和无功预测值,可查询计划值得到;整数变量分别为变电站电容器单组容量和投入组数;
2.2.3)变电站容抗器投入量预测的约束条件:
如式(6):
v ^ pre ( t i , j ) - v pre ( t 0,0 ) = s P G pre ( t i , j ) - P G pre ( t 0,0 ) Q G pre ( t i , j ) - Q G pre ( t 0,0 ) - P St pre ( t i , j ) + P St pre ( t 0,0 ) - Q St pre ( t i , j ) + Q St pre ( t 0,0 ) + Q St C [ N St pre ( t i , j - 1 ) - N St pre ( t 0,0 ) ] - - - ( 6 )
式(6)中为容抗器动作前中枢母线、变电站和发电机电压构成的向量,为其分量;
容抗器投入组数的约束条件如式(7)所示:
N St pre ( t i , j ) = N St pre ( t i , j - 1 ) - 1 , V ^ St pre > V St max N St pre ( t i , j - 1 ) + 1 , V ^ St pre < V St min N St pre ( t i , j - 1 ) , else - - - ( 7 )
式(7)中分别为变电站电压上下限值;
2.2.4)换流站定无功模式下滤波电容投入量预测的约束条件:
滤波电容动作前换流站注入电网总无功的约束条件如式(8)所示:
Q ^ St , out pre = - Q St pre ( t i , j ) + Q St C N St pre ( t i , j - 1 ) - - - ( 8 )
容抗器投入组数的约束条件如式(9)所示:
N St pre ( t i , j ) = N St pre ( t i , j - 1 ) - 1 , Q ^ St , out pre > Q St , out max N St pre ( t i , j - 1 ) + 1 , Q ^ St , out pre < Q St , out min N St pre ( t i , j - 1 ) , else - - - ( 9 )
式(8)中分别为滤波电容动作前换流站注入电网总无功上下限值;
2.2.5)容抗器动作次数约束的约束条件:
容抗器动作量预测的约束条件如式(10)所示,该动作量为0-1变量:
- O St pre ( t i , j ) &le; N St pre ( t i , j ) - N St pre ( t i , j - 1 ) &le; O St pre ( t i , j ) - - - ( 10 )
MPC优化时间窗内容抗器动作次数限制的约束条件如式(11)所示:
&Sigma; i = 0 N - 1 &Sigma; j = 0 M - 1 O St pre ( t i , j ) 1 &le; O St max - - - ( 11 )
式(11)中为动作次数上限;
2.2.6)系统电压、发电机运行和变电站容抗器组数的约束条件:
v min &le; v pre ( t i , j ) &le; v max Q G min &le; Q G pre ( t i , j ) &le; Q G max N St min &le; N St pre ( t i , j ) &le; N St max - - - ( 12 )
式(12)中Vmax和Vmin分别为由中枢母线、变电站和发电机电压构成系统电压向量的上限和下限,分别为发电机无功运行上下限,分别为变电站容抗器组数上下限;
2.3)式(1)优化目标函数与式(2-12)约束条件构成MPC优化控制模型;
3)对MPC优化控制模型进行简化:
删去式(3)对发电机无功参考值预测的约束,和式(4)中对发电机无功预测的约束条件,并在原目标函数中增加式(13):
min &Sigma; i = 0 N - 1 &Sigma; j = 0 M - 1 &rho; t i , j F 2 - - - ( 13 )
式(13)中F2含义为发电机机端电压预测值与设定值偏差:
F 2 = [ V G pre ( t i , j ) - V G set ( t i , 0 ) ] 2 - - - ( 14 )
简化后的MPC优化控制模型的目标函数如式(15)所示:
min &Sigma; i = 0 N - 1 &Sigma; j = 0 M - 1 &rho; t i , j ( F 1 + w T F 2 ) - - - ( 15 )
式(15)中F2为各发电机机端电压预测值与设定值偏差F2组成的向量,w为对应权重向量,权重值取中枢母线电压对发电机机端电压灵敏度的平方;
由式(15)优化目标函数与式(2)、(5-12)、(14)约束条件构成MPC优化控制简化模型;
4)利用优化工具求解MPC优化控制简化模型,获得发电机电压设定值在MPC时间窗内的解序列
5)将解序列中首个值作为控制目标下发给参与电压控制的发电机,以实现直流近区电压的自动控制。
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