WO2018014417A1 - 一种电力系统时滞稳定裕度快速求解方法 - Google Patents

一种电力系统时滞稳定裕度快速求解方法 Download PDF

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WO2018014417A1
WO2018014417A1 PCT/CN2016/097114 CN2016097114W WO2018014417A1 WO 2018014417 A1 WO2018014417 A1 WO 2018014417A1 CN 2016097114 W CN2016097114 W CN 2016097114W WO 2018014417 A1 WO2018014417 A1 WO 2018014417A1
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time
delay
power system
equation
mathematical model
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贾宏杰
董朝宇
姜懿郎
姜涛
王蕾
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天津大学
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • G06F17/11Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
    • G06F17/13Differential equations
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R21/00Arrangements for measuring electric power or power factor
    • G01R21/133Arrangements for measuring electric power or power factor by using digital technique
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • G06F17/16Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00Computer-aided design [CAD]
    • G06F30/20Design optimisation, verification or simulation
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00002Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/24Arrangements for preventing or reducing oscillations of power in networks
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00Details relating to CAD techniques
    • G06F2111/10Numerical modelling
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/02Reliability analysis or reliability optimisation; Failure analysis, e.g. worst case scenario performance, failure mode and effects analysis [FMEA]
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/06Power analysis or power optimisation
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/12Timing analysis or timing optimisation
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2207/00Indexing scheme relating to details of circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J2207/10Control circuit supply, e.g. means for supplying power to the control circuit
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04SSYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S40/00Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
    • Y04S40/20Information technology specific aspects, e.g. CAD, simulation, modelling, system security

Definitions

  • the invention relates to the field of linear matrix inequality (LMI) technology and stability analysis of time-delay systems, in particular to a fast solution method for stability margin of time-delay systems.
  • LMI linear matrix inequality
  • the Wide Area Measurement System is a real-time monitoring system based on synchronous vector measurement technology and aimed at dynamic process detection, analysis and control of power systems.
  • wide-area control using wide-area measurement information is beneficial to improve the operational stability of the entire power system and achieve safe and stable operation of the power system.
  • the wide-area measurement signals due to the need to use the remote signal for feedback control, the wide-area measurement signals have a certain time lag, and the existence of time lag may deteriorate the performance of the controller, resulting in instability of the system. Therefore, it is of great significance to study the influence of wide-area measurement time lag on the stability of power systems.
  • the present invention proposes a fast solution method for time-delay stability margin of a power system.
  • the method uses the Jordan standard transform to process the system model with time delay; further uses the Taylor series to the correlation separation process with state variables and time-delay state variables; and then use the Schur model to reduce the order
  • the equilibrium model is truncated, which greatly reduces the solution time of the delay stability margin.
  • the accuracy of the final judgment result is guaranteed.
  • the WSCC-3 machine 9-node power system with multiple time delays is utilized by the method of the present invention. The time-delay stability margin is quickly solved.
  • the invention provides a fast solution method for time-delay stability margin of power system.
  • a mathematical model of time-delay power system is constructed, and Jordan standard transformation, Taylor series separation, Schur model are applied.
  • the mathematical model of the time-delay power system is simplified by reducing the order, and the simplified time-delay power system is obtained.
  • the model in turn, quickly finds the time-delay stability margin of the time-delay power system, thereby obtaining the maximum time lag allowed for the stable operation of the power system.
  • the specific steps are as follows:
  • Step 1 Construct a mathematical model of the time-delay power system:
  • t represents a time variable
  • x(t) is a state variable
  • a 0 is the matrix of non-delay coefficients
  • m is the number of delays
  • ⁇ i >0 means that the time lag is greater than 0
  • h( t, ⁇ ) is the historical trajectory of the state variable x(t); ⁇ [-max( ⁇ i ), 0) indicates that the variable ⁇ varies between the opposite of the maximum value of ⁇ i and 0;
  • the above algebraic variables belong to The real number field R, the above vector variables belong to the n-dimensional real number vector R n ;
  • Step 3 Using the Taylor series to expand the time-delay state variable after the row-column transformation in step two Non-delay term in the mathematical model of time-delay power system after Jordan standard transformation and sparse row and column transformation And time-delay terms Interrelationship between
  • Step 4 Applying the Schur model to simplify the mathematical model of the time-delay power system after the Taylor series is separated in step 3. The number of state variables is reduced from n to r, and finally the simplified mathematical model of the time-delay power system is obtained.
  • Step 5 Under the time-delay stability criterion of the power system, use the simplified mathematical model of the time-delay power system obtained in step four to find the time-delay stability margin of the time-delay power system with m delays, and complete the power.
  • the fast solution of the system's time-delay stability margin provides the maximum time lag allowed to ensure stable operation of the power system.
  • the method of the invention proposes a fast solution for the time-delay stability margin of power system (referred to as JTS fast solution) for wide-area power systems with multiple time-delay.
  • JTS fast solution a fast solution for the time-delay stability margin of power system
  • the Jordan standard conversion, Taylor series separation, and Schur model reduction are implemented.
  • the model of the time-delay power system is simplified, and the simplified model can be applied to various time-delay stability criteria, which can greatly improve the calculation efficiency and improve the calculation performance.
  • Figure 1 is a boundary diagram of the delay stability domain of the 9-node power system of the WSCC-3 machine directly solved by three criteria;
  • FIG. 2 is a boundary diagram of a time-delay stability domain of a WSCC-3 machine 9-node power system solved by the JTS fast solution method of the present invention.
  • the invention provides a fast solution method for time-delay stability margin of power system.
  • a mathematical model of time-delay power system is constructed, and Jordan standard transformation, Taylor series separation, Schur model are applied.
  • the mathematical model of the time-delay power system is simplified by reducing the order, and the simplified mathematical model of the time-delay power system is obtained, and then the time-delay stability margin of the time-delay power system is quickly obtained, and the current operation is judged according to the time-lag stability margin. Whether the power system is stable, the specific steps are as follows:
  • Step 1 Construct a mathematical model of the time-delay power system: the specific steps are as follows:
  • Step 1-1 Consider the No. 2 and No. 3 generators in the WSCC-3 9-node system as the local grid equivalent unit with the wide-area control loop.
  • the terminal voltage measured on the No. 2 bus is fed back to the excitation.
  • s ⁇ R n is the original state variable of the system
  • y ⁇ R r is the original algebraic variable of the system
  • ⁇ i ⁇ R,i 1,2, is the time-delay constant of the system ;
  • Step 1-2 Linearize equation (2) at the equilibrium point (x e , y e ) to obtain:
  • Step 1-3 Without considering the singularity, G y , G yi in equation (2) is reversible, and the above formula (2) is expressed as:
  • Step 1-5 The mathematical model of the time-delay power system is expressed as follows:
  • t represents a time variable
  • x(t) is a state variable
  • It is the derivative of the state variable versus time
  • x(t- ⁇ i ), i 1, 2, which is the state variable of the time lag
  • h(t, ⁇ ) which is the historical trajectory of the state variable x(t)
  • ⁇ [- Max( ⁇ i ), 0) indicates that the variable ⁇ varies between the opposite of the maximum value of ⁇ i and 0
  • the above algebraic variables belong to the real number field R
  • the above vector variables belong to the 10-dimensional real number vector R 10 , non-time lag coefficient
  • the specific values of the matrix A 0 and the time-delay coefficient matrix A 1 , A 2 are as follows:
  • T is a matrix-column transformation matrix
  • Step 2-3 The first expression of the mathematical model of the power system with time-delay links established in Step 1: Perform a row transformation to get:
  • Step 2-5 Delay factor according to formula (11) in the matrix of the coefficients of sparsity Delay A iJ A iJ matrix for row and column, the principle of conversion is: for a variable z k, 1 ⁇ k ⁇ 10, If the element a a iJ iJ (i, j), or a iJ (j, i), 1 ⁇ i ⁇ 2,1 ⁇ j ⁇ 10, a iJ (i, j) and a iJ (j, i) of If the values are all zero, then the variable z k is sequentially moved to the end of the state variable sorting, and the state variables after the order rearrangement are obtained: among them, According to the above transformation principle:
  • Step 3 Using Taylor series to develop time-delay state variables Non-delay term in the mathematical model of time-delay power system after Jordan standard transformation and sparse row and column transformation And time-delay terms The relationship between them; the specific steps are as follows:
  • Step 3-1 Using the Taylor Series Expansion to Deviate the State Variables in Equation (13)
  • Step 3-2 Substituting equation (14) into the first expression in equation (13) get:
  • Step 3-3 Perform the same item combination on equation (15):
  • Step 4 Apply the Schur model to reduce the order.
  • the mathematical model of the time-delay power system after step 3 is separated by Taylor series is simplified.
  • the number of state variables is reduced from 10 to 4, and the simplified mathematical model of time-delay power system is obtained. ;
  • Specific steps are as follows:
  • Step 4-1 Input-output collation of the mathematical model of the time-delay power system after Taylor series separation is obtained:
  • Step 4-2 Apply the Schur model reduction method to reduce the 10 state variables in equation (18) to four:
  • Step 4-3 According to equation (18), Substitution (19):
  • Step 4-4 The second formula in equation (20) Substituting the first form Get:
  • Step 4-5 According to the Taylor series, expand each input component u i (t) of u(t) in equation (18):
  • Step 4-6 Substituting all input components into equation (21), and finally obtaining a simplified mathematical model of the time-delay power system:
  • Step 5 Under the time-delay stability criterion of the power system, the time-delay stability margin of the time-delay power system with two time-delay links is obtained by using the simplified mathematical model of the time-delay power system obtained in step four.
  • the power system time lag stability criterion includes one of the following two situations:
  • the time-delay stability margin of the 9-node power system of the WSCC-3 machine with double-delay is obtained, and the JTS fast solution method and the direct use criterion method are used to solve the problem.
  • the three typical criteria for the Layapunov stability criterion are as follows:
  • Criterion 1 gives a multi-delay stability criterion for power systems with a weight matrix.
  • Criterion 2 gives a multi-delay stability criterion for power systems without a weight matrix.
  • Criterion 3 introduces the integral quadratic form, and gives a multi-delay stability criterion for the power system with integral quadratic form.
  • a c [A 0 A 1 A 2 ... A m-1 A m O ... O],
  • Figure 1 shows the time-delay stability domain boundary obtained directly
  • Figure 2 shows the time-delay stability domain boundary obtained by applying the JTS fast solution method.
  • the WSCC-3 machine 9-node multi-time-delay power system is simplified by using the JTS fast solution method of the present invention, and the time-delay stability margin is calculated by the stability criterion, which can greatly reduce the solution time.
  • the CEIR value of criterion 1 can reach up to 40131.13%
  • the CEIR value of criterion 2 can reach up to 3266.67%
  • the CEIR value of criterion 3 can reach up to 4613.11%. It shows that the JTS method has a significantly fast effect.
  • the fast solution principle of the JTS method is described by using the criterion 1 to calculate the delay stability margin of the 9-node power system of the WSCC-3 machine. After using the JTS method, the variable matrix P, Q 1 , Q of the criterion 1 is determined.
  • N 1 , N 2 , N 3 , S 1 , S 2 , S 3 , T 1 , T 2 , T 3 , X 12 , X 13 , X 23 , Y 12 , Y 13 , Y 23 and Z 12 , Z 13 , Z 23 are 4 ⁇ 4 square matrix, N 1 , N 2 , N 3 , S 1 , S 2 , S 3 , T 1 , T 2 , T 3 , X 12 , X 13 , X 23 , Y 12 , Y 13 , Y 23 and Z 12 , Z 13 , Z 23 are For a suitable 4 ⁇ 4 matrix, the total number of variables to be determined N 1 is:
  • the total number of variables to be requested after using the JTS method is about 1/6 of the non-use case, which is significantly smaller than the direct calculation, and therefore has higher calculation efficiency.
  • the analysis of the other two criteria is similar.
  • the reduction rates of the variables to be determined from criterion 1 to criterion 3 are 83.31%, 81.82% and 83.16%, respectively. It is obvious that the JTS fast solution method can greatly reduce the Find the number of variables and improve the efficiency of the solution.

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Abstract

本发明公开了一种电力系统时滞稳定裕度快速求解方法,以Jordan标准变换、Taylor级数分离和Schur模型降阶三个步骤为核心,重构新的时滞系统,降低系统维数。该方法首先将时滞系统模型用Jordan标准变换进行处理;进一步将Taylor级数展开的思想应用到含有时滞状态变量和不含时滞状态变量的分离过程中;再利用Schur模型降阶方法实现均衡模型截断;最后,利用多时滞的WSCC-3机9节点电力系统对所提出发明方法分别在几种典型判据下进行验证。本发明通过简化系统模型,大幅降低时滞稳定裕度的求解时间,完成电力系统时滞稳定裕度的快速求解,解决多维、多时滞系统求解困难的问题,扩大了稳定判据的应用范围。

Description

一种电力系统时滞稳定裕度快速求解方法 技术领域
本发明涉及线性矩阵不等式(LMI)技术和时滞系统稳定性分析领域,尤其涉及一种时滞系统稳定裕度快速求解方法。
背景技术
广域测量系统(Wide Area Measurement System,WAMS)是以同步向量测量技术为基础,以电力系统动态过程检测、分析和控制为目标的实时监控系统。在广域量测系统中,利用广域量测信息进行广域控制有利于改善整个电力系统的运行稳定性,实现电力系统的安全稳定运行。但是在基于WAMS的电力系统广域控制中,由于需要利用远方信号进行反馈控制,广域量测信号均存在一定的时滞,而时滞的存在有可能恶化控制器性能,导致系统出现失稳,因此,研究广域量测时滞对电力系统稳定性的影响具有十分重要的意义。
为研究时滞对电力系统的影响,同时考虑到时滞随机变动、参数不连贯和存在切换环节等情况,基于Lyapunov稳定性理论和LMI技术的直接法已被广泛应用,它通过构造能量函数可以直接求解时滞系统稳定裕度,进行时滞系统控制器设计等。
但是,将直接法应用到广域系统时滞问题的分析与处理时,该方法待求解变量数与系统中状态变量的数量近似呈平方关系,当系统中状态变量较多时,求解时滞系统稳定裕度就会面临待求变量过多,计算时间过长的困难,因此如何减少待求变量的数目、降低计算求解时间就变得尤为重要。目前已经有一些模型简化的方法,如:均衡截断利用均方根对复杂模型进行简化;对非最小系统,运用Hankel最小度逼近简化系统,以及运用互质因子实现的模型截断,这些方法已经在复杂动态系统分析中获得成功应用。然而,上述简化方法大多数针对的是不含时滞的系统,由于时滞系统的特征方程含有超越项,将现有的简化方法直接应用到时滞稳定的求解过程仍然存在较大的困难。
发明内容
为解决上述问题,本发明提出了一种电力系统时滞稳定裕度快速求解方法。该方法通过将含有时滞的系统模型用Jordan标准变换进行处理;进一步将Taylor级数用于到含时滞状态变量和不含时滞状态变量的关联分离过程;再利用Schur模型降阶方法实现均衡模型截断,大幅降低时滞稳定裕度的求解时间,同时,保证了最后判断结果的精确性,在Layapunov稳定性判据下,利用本发明方法对多时滞的WSCC-3机9节点电力系统进行时滞稳定裕度快速求解。
本发明提出的一种电力系统时滞稳定裕度快速求解方法,对于含有m个时滞环节的时滞电力系统,构建时滞电力系统数学模型,应用Jordan标准变换、Taylor级数分离、Schur模型降阶对所述时滞电力系统数学模型进行简化,得到简化后的时滞电力系统数学 模型,进而快速求出时滞电力系统的时滞稳定裕度,从而得到保证电力系统稳定运行所允许的最大时滞,具体步骤如下:
步骤一、构建时滞电力系统数学模型:
Figure PCTCN2016097114-appb-000001
式中:t表示时间变量;x(t)为状态变量;
Figure PCTCN2016097114-appb-000002
为状态变量对时间的导数;A0为非时滞系数矩阵;Ai,i=1,2,…,m,为时滞系数矩阵,m表示时滞环节数目;τi,i=1,2,…,m,为系统的时滞常数;τi>0表示时滞均大于0;x(t-τi),i=1,2,…,m,为时滞状态变量;h(t,ξ),为状态变量x(t)的历史轨迹;ξ∈[-max(τi),0)表示变量ξ在τi最大值的相反数和0之间变化;上述代数变量均属于实数域R,上述向量变量均属于n维实数向量Rn
步骤二、利用时滞系数矩阵Ai的稀疏性,对步骤一构建的时滞电力系统数学模型中的时滞系数矩阵Ai,i=1,2,…,m之和进行Jordan标准变换,并根据稀疏性对时滞电力系统数学模型进行行列变换;
步骤三、利用Taylor级数展开步骤二中行列变换后的时滞状态变量
Figure PCTCN2016097114-appb-000003
分离经过Jordan标准变换和稀疏性行列变换后的时滞电力系统数学模型中的非时滞项
Figure PCTCN2016097114-appb-000004
和时滞项
Figure PCTCN2016097114-appb-000005
之间的相互关联;
步骤四、应用Schur模型对步骤三经过Taylor级数分离后的时滞电力系统数学模型进行简化,状态变量的数目由n个减少到r个,最终得到简化后的时滞电力系统数学模型;
步骤五、在电力系统时滞稳定性判据下,利用步骤四得到的简化后的时滞电力系统数学模型求出含有m个时滞环节的时滞电力系统的时滞稳定裕度,完成电力系统时滞稳定裕度的快速求解,从而得到保证电力系统稳定运行所允许的最大时滞。
与现有技术相比,本发明的有益效果是:
该发明方法针对含有多时滞的广域电力系统提出了一种电力系统时滞稳定裕度快速求解(简称为JTS快速求解)方法,利用Jordan标准变换、Taylor级数分离、Schur模型降阶实现对时滞电力系统的模型简化,简化后的模型能够适用于各种时滞稳定性判据,能够大幅提高计算效率、改观计算性能。
附图说明
图1是三种判据直接求解的WSCC-3机9节点电力系统时滞稳定域边界图;
图2是三种判据利用本发明JTS快速求解方法求解的WSCC-3机9节点电力系统时滞稳定域边界图。
具体实施方式
下面结合附图和具体实施例对本发明技术方案作进一步详细描述,所描述的具体实施例仅对本发明进行解释说明,并不用以限制本发明。
本发明提出的一种电力系统时滞稳定裕度快速求解方法,对于含有m个时滞环节的时滞电力系统,构建时滞电力系统数学模型,应用Jordan标准变换、Taylor级数分离、Schur模型降阶对所述时滞电力系统数学模型进行简化,得到简化后的时滞电力系统数学模型,进而快速求出时滞电力系统的时滞稳定裕度,根据该时滞稳定裕度判断当前运行的电力系统是否稳定,具体步骤如下:
步骤一、构建时滞电力系统数学模型:具体步骤如下:
步骤1-1:将WSCC-3机9节点系统中的2、3号发电机视为含有广域控制回路的局部电网等值机组,设在2号母线上测量的机端电压在反馈给励磁调节器的过程中存在延时τ1,在3号母线上测量的机端电压存在反馈延时τ2,构建含有时滞环节的电力系统微分代数方程组:
Figure PCTCN2016097114-appb-000006
式(2)中:s∈Rn,为系统的原始状态变量;y∈Rr,为系统的原始代数变量;si=s(t-τi),i=1,2,为系统的原始时滞状态变量;yi=y(t-τi),i=1,2,为系统的原始时滞代数变量;τi∈R,i=1,2,,为系统的时滞常数;
步骤1-2:将式(2)在平衡点处(xe,ye)线性化,得到:
Figure PCTCN2016097114-appb-000007
式(3)中:
Figure PCTCN2016097114-appb-000008
i=1,2;
步骤1-3:在不考虑奇异的前提下,式(2)中的Gy,Gyi可逆,上述式(2)表示为:
Figure PCTCN2016097114-appb-000009
式(4)中:
Figure PCTCN2016097114-appb-000010
步骤1-4:采用x(t)=Δz表示状态变量的增量,式(3)改写成:
Figure PCTCN2016097114-appb-000011
步骤1-5:时滞电力系统数学模型表示如下:
Figure PCTCN2016097114-appb-000012
式(5)中:t表示时间变量;x(t)为状态变量;
Figure PCTCN2016097114-appb-000013
为状态变量对时间的导数;x(t-τi),i=1,2,为时滞状态变量;h(t,ξ),为状态变量x(t)的历史轨迹;ξ∈[-max(τi),0)表示变量ξ在τi最大值的相反数和0之间变化;上述代数变量均属于实数域R,上述向量变量均属于10维实数向量R10,非时滞系数矩阵A0,时滞系数矩阵A1、A2的具体数值如下:
Figure PCTCN2016097114-appb-000014
Figure PCTCN2016097114-appb-000015
Figure PCTCN2016097114-appb-000016
Figure PCTCN2016097114-appb-000017
Figure PCTCN2016097114-appb-000018
Figure PCTCN2016097114-appb-000019
Figure PCTCN2016097114-appb-000020
Figure PCTCN2016097114-appb-000021
Figure PCTCN2016097114-appb-000022
Figure PCTCN2016097114-appb-000023
步骤二、利用时滞系数矩阵A1、A2的稀疏性,对步骤一构建的时滞电力系统数学模型中的时滞系数矩阵Ai,i=1,2之和进行Jordan标准变换,并根据稀疏性进行行列变换;具体步骤如下:
步骤2-1:对时滞系数矩阵Ai,i=1,2求和,得到
Figure PCTCN2016097114-appb-000024
步骤2-2:对步骤2-1的
Figure PCTCN2016097114-appb-000025
求和结果进行Jordan标准变换,即对时滞系数矩阵Ai,i=1,2之和进行行列变换:
Figure PCTCN2016097114-appb-000026
式(9)中:T为行列变换矩阵;
步骤2-3:对步骤一建立的含时滞环节的电力系统数学模型的第一个式子:
Figure PCTCN2016097114-appb-000027
进行行变换得到:
Figure PCTCN2016097114-appb-000028
步骤2-4:对状态变量x(t)进行变量替换,令Tx(t)=z(t),则x(t)=T-1z(t)、x(t-τi)=T-1z(t-τi),代入式(10)得到:
Figure PCTCN2016097114-appb-000029
步骤2-5:根据式(11)中的时滞系数矩阵AiJ的稀疏性对该时滞系数矩阵AiJ进行行列变换,变换原则是:对于某个变量zk,1≤k≤10,如果AiJ中的元素AiJ(i,j)或AiJ(j,i),1≤i≤2,1≤j≤10,AiJ(i,j)和AiJ(j,i)的值均为零,则将该变量zk依次后移至状态变量排序最末,得到顺序重新整理排列后的状态变量:
Figure PCTCN2016097114-appb-000030
其中,
Figure PCTCN2016097114-appb-000031
根据上述变换原则得到:
Figure PCTCN2016097114-appb-000032
式(12)中:
Figure PCTCN2016097114-appb-000033
经过Jordan标准变换和稀疏性行列变换后的时滞电力系统数学模型表示如下:
Figure PCTCN2016097114-appb-000034
步骤三、利用Taylor级数展开时滞状态变量
Figure PCTCN2016097114-appb-000035
分离经过Jordan标准变换和稀疏性行列变换后的时滞电力系统数学模型中的非时滞项
Figure PCTCN2016097114-appb-000036
和时滞项
Figure PCTCN2016097114-appb-000037
之间的相互关联;具体步骤如下:
步骤3-1:利用Taylor级数展开式(13)中的时滞状态变量
Figure PCTCN2016097114-appb-000038
Figure PCTCN2016097114-appb-000039
步骤3-2:将式(14)代入式(13)中的第一个式子
Figure PCTCN2016097114-appb-000040
得到:
Figure PCTCN2016097114-appb-000041
步骤3-3:对式(15)进行同类项合并:
Figure PCTCN2016097114-appb-000042
Figure PCTCN2016097114-appb-000043
是可逆的,式(16)的两边乘以
Figure PCTCN2016097114-appb-000044
的逆矩阵得到经过Taylor级数分离后的时滞电力系统数学模型:
Figure PCTCN2016097114-appb-000045
步骤四、应用Schur模型降阶对步骤三经过Taylor级数分离后的时滞电力系统数学模型进行简化,状态变量的数目由10个减少到4个,最终得到简化后的时滞电力系统数学模型;具体步骤如下:
步骤4-1:对经过Taylor级数分离后的时滞电力系统数学模型进行输入-输出化整理得到:
Figure PCTCN2016097114-appb-000046
式(18)中:
Figure PCTCN2016097114-appb-000047
Figure PCTCN2016097114-appb-000048
Figure PCTCN2016097114-appb-000049
Figure PCTCN2016097114-appb-000050
步骤4-2:应用Schur模型降阶方法将式(18)中的10个状态变量减少到4个:
Figure PCTCN2016097114-appb-000051
式(19)中:zred(t)∈R4,y(t)∈R4,Ared∈R4×4,Bred,i∈R4×4,Cred∈R4×4,Bred=[Bred,1 Bred,2];
步骤4-3:根据式(18),将
Figure PCTCN2016097114-appb-000052
代入式(19):
Figure PCTCN2016097114-appb-000053
步骤4-4:将式(20)中第二式
Figure PCTCN2016097114-appb-000054
代入第一式
Figure PCTCN2016097114-appb-000055
中得到:
Figure PCTCN2016097114-appb-000056
步骤4-5:根据Taylor级数,展开式(18)中输入u(t)的每个输入分量ui(t):
Figure PCTCN2016097114-appb-000057
Figure PCTCN2016097114-appb-000058
Figure PCTCN2016097114-appb-000059
步骤4-6:将所有输入分量代入式(21),最终得到简化后的时滞电力系统数学模型:
Figure PCTCN2016097114-appb-000060
式(23)中:
Figure PCTCN2016097114-appb-000061
Figure PCTCN2016097114-appb-000062
步骤五、在电力系统时滞稳定性判据下,利用步骤四得到的简化后的时滞电力系统数学模型求出含有2个时滞环节的时滞电力系统的时滞稳定裕度,从而得到保证电力系统稳定运行所允许的最大时滞。其中,所述电力系统时滞稳定性判据包括以下两种情形之一:
(1)Layapunov稳定性判据;
(2)特征值分析稳定性判据。
下面以三种具体的Layapunov稳定性判据为例对本方法的效果进行说明:
利用步骤四得到的简化后的时滞电力系统数学模型求出双时滞WSCC-3机9节点电力系统的时滞稳定裕度,将本发明JTS快速求解方法和直接用判据方法求解的结果进行比较,Layapunov稳定性判据的三个典型判据具体内容如下:
判据1给出一种含自由权矩阵的电力系统多时滞稳定性判据。
判据1对于含有m个时滞环节的系统,如果存在正定矩阵P∈Rn×n,Qi∈Rn×n,i=1,2,…,m,半正定矩阵Wi,j∈Rn×n,对称矩阵Xi,j∈R(m+1)n×(m+1)n,0≤i<j<m和矩阵
Figure PCTCN2016097114-appb-000063
0≤i<j<m,i=1,2,…,m,m+1,使得下列矩阵不等式成立:
Figure PCTCN2016097114-appb-000064
Mi,j≥O,0≤i<j<m                    (29)
式中:
Figure PCTCN2016097114-appb-000065
Figure PCTCN2016097114-appb-000066
Figure PCTCN2016097114-appb-000067
Figure PCTCN2016097114-appb-000068
Figure PCTCN2016097114-appb-000069
Figure PCTCN2016097114-appb-000070
Figure PCTCN2016097114-appb-000071
Figure PCTCN2016097114-appb-000072
Figure PCTCN2016097114-appb-000073
Figure PCTCN2016097114-appb-000074
判据2给出一种不含自由权矩阵的电力系统多时滞稳定性判据。
判据2对于含有m个时滞环节的系统,如果存在正定矩阵P∈Rn×n,Qi∈Rn×n,i=1,2,…,m和半正定矩阵Wi,j∈Rn×n,i=1,2,…,m,使得下列矩阵不等式成立:
Figure PCTCN2016097114-appb-000075
式中:
Figure PCTCN2016097114-appb-000076
Figure PCTCN2016097114-appb-000077
Figure PCTCN2016097114-appb-000078
Figure PCTCN2016097114-appb-000079
Figure PCTCN2016097114-appb-000080
Figure PCTCN2016097114-appb-000081
Figure PCTCN2016097114-appb-000082
判据3引入积分二次型,给出一种含积分二次型的电力系统多时滞稳定性判据。
判据3如果存在正定矩阵P∈R(2m+1)n×(2m+1)n,Ui∈Rn×n,Yi∈R2n×2n和半正定矩阵Qi∈R2n×2n,Zi∈R2n×2n,i=1,2,…,m使得下列矩阵负定:
Figure PCTCN2016097114-appb-000083
则含m个时滞环节的系统是渐进稳定,其中:
Ac=[A0 A1 A2 … Am-1 Am O … O],
C1=[e1 e2 e3 … em em+1 em+2 e2m+2 e2m+3 … e3m e3m+1],
Figure PCTCN2016097114-appb-000084
图1为直接求解得到的时滞稳定域边界、图2为应用JTS快速求解方法后得到的时滞稳定域边界。
对比图1和图2可以明显看出,经过JTS快速求解方法得到的WSCC-3机9节点电力系统时滞稳定域边界除个别点外,几乎同判据直接求解得到的曲线完全一致。
为对比判据的耗时情况,定义参数θ和计算效能提高率(Calculation Efficiency Increasing Rate,CEIR)如下:
Figure PCTCN2016097114-appb-000085
Figure PCTCN2016097114-appb-000086
根据θ从0°增加至90°,表1给出了相应的计算时间和CEIR值:
表1 WSCC-3机9节点电力系统计算时间比较
Figure PCTCN2016097114-appb-000087
Figure PCTCN2016097114-appb-000088
从表1可以看出,先利用本发明JTS快速求解方法化简WSCC-3机9节点多时滞电力系统,再通过稳定性判据计算时滞稳定裕度,可以大幅减少求解时间。当θ在0°至90°之间变化时,判据1的CEIR值最高可达到40131.13%,判据2的CEIR值最高可达到3266.67%,判据3的CEIR值最高可达到4613.11%,结果表明JTS方法具有明显快速的效果。
以判据1计算WSCC-3机9节点电力系统时滞稳定裕度为例对JTS方法的快速求解原理进行说明,在使用JTS方法后,判据1的待求变量矩阵P,Q1,Q2,W1,W2,W3,X11,X22,X33,Y11,Y22,Y33和Z11,Z22,Z33均为4×4方阵,N1,N2,N3,S1,S2,S3,T1,T2,T3,X12,X13,X23,Y12,Y13,Y23和Z12,Z13,Z23都是适当的4×4矩阵,待求变量总数N1为:
Figure PCTCN2016097114-appb-000089
而对于直接利用判据求解而言,待求变量矩阵中有15个10×10的对称矩阵和18个10×10的适当矩阵,待求变量总数N2为:
Figure PCTCN2016097114-appb-000090
使用JTS方法后的待求变量总数约为不使用情况的1/6,较直接计算大幅减少,因此具有更高的计算效率。其它两种判据的分析情况与之类似,判据1至判据3的待求变量减少率分别为83.31%、81.82%和83.16%,可以明显看出通过JTS快速求解方法能够极大地降低待求变量数目,提高求解效率。
尽管上面结合附图对本发明进行了描述,但是本发明并不局限于上述的具体实施方式,上述的具体实施方式仅仅是示意性的,而不是限制性的,本领域的普通技术人员在本发明的启示下,在不脱离本发明宗旨的情况下,还可以做出很多变形,这些均属于本发明的保护之内。

Claims (6)

  1. 一种电力系统时滞稳定裕度快速求解方法,其特征在于,对于含有m个时滞环节的时滞电力系统,构建时滞电力系统数学模型,应用Jordan标准变换、Taylor级数分离、Schur模型降阶对所述时滞电力系统数学模型进行简化,得到简化后的时滞电力系统数学模型,进而快速求出时滞电力系统的时滞稳定裕度,从而得到保证电力系统稳定运行所允许的最大时滞,具体步骤如下:
    步骤一、构建时滞电力系统数学模型:
    Figure PCTCN2016097114-appb-100001
    式中:t表示时间变量;x(t)为状态变量;
    Figure PCTCN2016097114-appb-100002
    为状态变量对时间的导数;A0为非时滞系数矩阵;Ai,i=1,2,…,m,为时滞系数矩阵,m表示时滞环节数目;τi,i=1,2,…,m,为系统的时滞常数;τi>0表示时滞均大于0;x(t-τi),i=1,2,…,m,为时滞状态变量;h(t,ξ),为状态变量x(t)的历史轨迹;ξ∈[-max(τi),0)表示变量ξ在τi最大值的相反数和0之间变化;上述代数变量均属于实数域R,上述向量变量均属于n维实数向量Rn
    步骤二、利用时滞系数矩阵Ai的稀疏性,对步骤一构建的时滞电力系统数学模型中的时滞系数矩阵Ai,i=1,2,…,m之和进行Jordan标准变换,并根据稀疏性对时滞电力系统数学模型进行行列变换;
    步骤三、利用Taylor级数展开步骤二中行列变换后的时滞状态变量
    Figure PCTCN2016097114-appb-100003
    分离经过Jordan标准变换和稀疏性行列变换后的时滞电力系统数学模型中的非时滞项
    Figure PCTCN2016097114-appb-100004
    和时滞项
    Figure PCTCN2016097114-appb-100005
    之间的相互关联;
    步骤四、应用Schur模型对步骤三经过Taylor级数分离后的时滞电力系统数学模型进行简化,状态变量的数目由n个减少到r个,最终得到简化后的时滞电力系统数学模型;
    步骤五、在电力系统时滞稳定性判据下,利用步骤四得到的简化后的时滞电力系统数学模型求出含有m个时滞环节的时滞电力系统的时滞稳定裕度,完成电力系统时滞稳定裕度的快速求解,从而得到保证电力系统稳定运行所允许的最大时滞。
  2. 根据权利要求1所述电力系统时滞稳定裕度快速求解方法,其特征在于:步骤一包括以下步骤:
    步骤1-1:构建含有时滞环节的电力系统微分代数方程组:
    Figure PCTCN2016097114-appb-100006
    式(2)中:s∈Rn,为系统的原始状态变量;y∈Rr,为系统的原始代数变量; si=s(t-τi),i=1,2,…,m,为系统的原始时滞状态变量;yi=y(t-τi),i=1,2,…,m,为系统的原始时滞代数变量;τi∈R,i=1,2,…,m,为系统的时滞常数;
    步骤1-2:将式(2)在平衡点处(xe,ye)线性化,得到:
    Figure PCTCN2016097114-appb-100007
    式(3)中:
    Figure PCTCN2016097114-appb-100008
    Figure PCTCN2016097114-appb-100009
    Δs,Δy,Δsi,Δyi为在平衡点附近的增量;
    步骤1-3:在不考虑奇异的前提下,式(3)中的Gy,Gyi可逆,上述式(3)表示为:
    Figure PCTCN2016097114-appb-100010
    式(4)中:
    Figure PCTCN2016097114-appb-100011
    步骤1-4:采用x(t)=Δz表示状态变量的增量,式(4)改写成:
    Figure PCTCN2016097114-appb-100012
    步骤1-5:时滞电力系统数学模型表示如下:
    Figure PCTCN2016097114-appb-100013
    式(6)中:t表示时间变量;x(t)为状态变量;
    Figure PCTCN2016097114-appb-100014
    为状态变量对时间的导数;A0为非时滞系数矩阵;Ai,i=1,2,…,m,为时滞系数矩阵,m表示时滞环节数目;τi,i=1,2,…,m,为系统的时滞常数;τi>0表示时滞均大于0;x(t-τi),i=1,2,…,m,为时滞状态变量;h(t,ξ),为状态变量x(t)的历史轨迹;ξ∈[-max(τi),0)表示变量ξ在τi最大值的相反数和0之间变化;上述代数变量均属于实数域R,上述向量变量均属于n维实数向量Rn
  3. 根据权利要求1所述电力系统时滞稳定裕度快速求解方法,其特征在于:步骤二包括以下步骤:
    步骤2-1:对时滞系数矩阵Ai,i=1,2,…,m求和,得到
    Figure PCTCN2016097114-appb-100015
    步骤2-2:对步骤2-1的
    Figure PCTCN2016097114-appb-100016
    求和结果进行Jordan标准变换,即对时滞系数矩阵Ai,i=1,2,…,m之和进行行列变换:
    Figure PCTCN2016097114-appb-100017
    式(7)中:T为行列变换矩阵;
    步骤2-3:对步骤一建立的含时滞环节的电力系统数学模型的第一个式子:
    Figure PCTCN2016097114-appb-100018
    进行行变换得到:
    Figure PCTCN2016097114-appb-100019
    步骤2-4:对状态变量x(t)进行变量替换,令Tx(t)=z(t),则x(t)=T-1z(t)、x(t-τi)=T-1z(t-τi),代入式(8)得到:
    Figure PCTCN2016097114-appb-100020
    式(9)中:A0J=TA0T-1
    Figure PCTCN2016097114-appb-100021
    步骤2-5:根据式(9)中的时滞系数矩阵AiJ的稀疏性对该时滞系数矩阵AiJ进行行列变换,变换原则是:对于某个变量zk,1≤k≤n,如果AiJ中的元素AiJ(i,j)或AiJ(j,i),1≤i≤m,1≤j≤n,AiJ(i,j)和AiJ(j,i)的值均为零,则将该变量zk依次后移至状态变量排序最末,得到顺序重新整理排列后的状态变量:
    Figure PCTCN2016097114-appb-100022
    其中,
    Figure PCTCN2016097114-appb-100023
    Figure PCTCN2016097114-appb-100024
    根据上述变换原则得到:
    Figure PCTCN2016097114-appb-100025
    式(10)中:
    Figure PCTCN2016097114-appb-100026
    经过Jordan标准变换和稀疏性行列变换后的时滞电力系统数学模型表示如下:
    Figure PCTCN2016097114-appb-100027
  4. 根据权利要求1所述电力系统时滞稳定裕度快速求解方法,其特征在于:步骤三包括以下步骤:
    步骤3-1:利用Taylor级数展开式(11)中的时滞状态变量
    Figure PCTCN2016097114-appb-100028
    Figure PCTCN2016097114-appb-100029
    步骤3-2:将式(12)代入式(11)中的第一个式子
    Figure PCTCN2016097114-appb-100030
    得到:
    Figure PCTCN2016097114-appb-100031
    步骤3-3:对式(13)进行同类项合并:
    Figure PCTCN2016097114-appb-100032
    Figure PCTCN2016097114-appb-100033
    是可逆的,将式(14)的两边同时乘以
    Figure PCTCN2016097114-appb-100034
    的逆矩阵,得到经过Taylor级数分离后的时滞电力系统数学模型:
    Figure PCTCN2016097114-appb-100035
  5. 根据权利要求1所述电力系统时滞稳定裕度快速求解方法,其特征在于:步骤四包 括以下步骤:
    步骤4-1:对经过Taylor级数分离后的时滞电力系统数学模型进行输入-输出化整理得到:
    Figure PCTCN2016097114-appb-100036
    式(16)中:
    Figure PCTCN2016097114-appb-100037
    Figure PCTCN2016097114-appb-100038
    Figure PCTCN2016097114-appb-100039
    Figure PCTCN2016097114-appb-100040
    Figure PCTCN2016097114-appb-100041
    步骤4-2:应用Schur模型降阶方法将式(16)中的n个状态变量减少到r个:
    Figure PCTCN2016097114-appb-100042
    式(17)中:zred(t)∈Rr,y(t)∈Rr,Ared∈Rr×r,Bred,i∈Rr×r,Cred∈Rr×r
    Bred=[Bred,1 Bred,2 … Bred,i … Bred,m-1 Bred,m];
    步骤4-3:根据式(16),将
    Figure PCTCN2016097114-appb-100043
    代入式(17):
    Figure PCTCN2016097114-appb-100044
    步骤4-4:将式(18)中的第二式
    Figure PCTCN2016097114-appb-100045
    代入第一式
    Figure PCTCN2016097114-appb-100046
    中得到:
    Figure PCTCN2016097114-appb-100047
    步骤4-5:根据Taylor级数,展开式(16)中输入u(t)的每个输入分量ui(t):
    Figure PCTCN2016097114-appb-100048
    Figure PCTCN2016097114-appb-100049
    Figure PCTCN2016097114-appb-100050
    步骤4-6:将所有输入分量代入式(18),最终得到简化后的时滞电力系统数学模型:
    Figure PCTCN2016097114-appb-100051
    式(21)中:
    Figure PCTCN2016097114-appb-100052
    Figure PCTCN2016097114-appb-100053
  6. 根据权利要求1所述电力系统时滞稳定裕度快速求解方法,其特征在于:步骤五中,所述电力系统时滞稳定性判据包括以下两种情形之一:
    (1)Layapunov稳定性判据;
    (2)特征值分析稳定性判据。
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