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CN114865888B - A power feedforward inductance parameter identification method and system for energy storage converters - Google Patents

A power feedforward inductance parameter identification method and system for energy storage converters Download PDF

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CN114865888B
CN114865888B CN202210807930.2A CN202210807930A CN114865888B CN 114865888 B CN114865888 B CN 114865888B CN 202210807930 A CN202210807930 A CN 202210807930A CN 114865888 B CN114865888 B CN 114865888B
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inductance
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storage converter
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CN114865888A (en
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张杰明
陈显超
梁妍陟
王辉
李小燕
何启洪
钟榜
汤健东
秦熙
淡言亮
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Zhaoqing Power Supply Bureau of Guangdong Power Grid Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
    • H02M1/00—Details of apparatus for conversion
    • H02M1/0003—Details of control, feedback or regulation circuits
    • H02M1/0016—Control circuits providing compensation of output voltage deviations using feedforward of disturbance parameters
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for AC mains or AC distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
    • H02M3/00—Conversion of DC power input into DC power output
    • H02M3/22—Conversion of DC power input into DC power output with intermediate conversion into AC
    • H02M3/24—Conversion of DC power input into DC power output with intermediate conversion into AC by static converters
    • H02M3/28—Conversion of DC power input into DC power output with intermediate conversion into AC by static converters using discharge tubes with control electrode or semiconductor devices with control electrode to produce the intermediate AC
    • H02M3/325—Conversion of DC power input into DC power output with intermediate conversion into AC by static converters using discharge tubes with control electrode or semiconductor devices with control electrode to produce the intermediate AC using devices of a triode or a transistor type requiring continuous application of a control signal
    • H02M3/335—Conversion of DC power input into DC power output with intermediate conversion into AC by static converters using discharge tubes with control electrode or semiconductor devices with control electrode to produce the intermediate AC using devices of a triode or a transistor type requiring continuous application of a control signal using semiconductor devices only
    • H02M3/33507—Conversion of DC power input into DC power output with intermediate conversion into AC by static converters using discharge tubes with control electrode or semiconductor devices with control electrode to produce the intermediate AC using devices of a triode or a transistor type requiring continuous application of a control signal using semiconductor devices only with automatic control of the output voltage or current, e.g. flyback converters
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
    • H02M3/00—Conversion of DC power input into DC power output
    • H02M3/22—Conversion of DC power input into DC power output with intermediate conversion into AC
    • H02M3/24—Conversion of DC power input into DC power output with intermediate conversion into AC by static converters
    • H02M3/28—Conversion of DC power input into DC power output with intermediate conversion into AC by static converters using discharge tubes with control electrode or semiconductor devices with control electrode to produce the intermediate AC
    • H02M3/325—Conversion of DC power input into DC power output with intermediate conversion into AC by static converters using discharge tubes with control electrode or semiconductor devices with control electrode to produce the intermediate AC using devices of a triode or a transistor type requiring continuous application of a control signal
    • H02M3/335—Conversion of DC power input into DC power output with intermediate conversion into AC by static converters using discharge tubes with control electrode or semiconductor devices with control electrode to produce the intermediate AC using devices of a triode or a transistor type requiring continuous application of a control signal using semiconductor devices only
    • H02M3/33507—Conversion of DC power input into DC power output with intermediate conversion into AC by static converters using discharge tubes with control electrode or semiconductor devices with control electrode to produce the intermediate AC using devices of a triode or a transistor type requiring continuous application of a control signal using semiconductor devices only with automatic control of the output voltage or current, e.g. flyback converters
    • H02M3/33523—Conversion of DC power input into DC power output with intermediate conversion into AC by static converters using discharge tubes with control electrode or semiconductor devices with control electrode to produce the intermediate AC using devices of a triode or a transistor type requiring continuous application of a control signal using semiconductor devices only with automatic control of the output voltage or current, e.g. flyback converters with galvanic isolation between input and output of both the power stage and the feedback loop
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00—Details relating to CAD techniques
    • G06F2111/04—Constraint-based CAD
    • Y—GENERAL 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
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E70/00—Other energy conversion or management systems reducing GHG emissions
    • Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin

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  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Dc-Dc Converters (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)

Abstract

本发明提供了一种用于隔离型直流储能变换器的功率前馈电感参数辨识方法和系统，其中本发明提供的方法包括基于不同调制方式下隔离型直流储能变换器的功率模型确定对应调制方式下的第一输出电流模型和稳态条件下的第二输出电流模型；然后确定实际离散采样系统中隔离型直流储能变换器满足的约束条件并定义关于控制周期的第一参数和输出电流的第二参数；将第一参数和第二参数的比例系数作为隔离型直流储能变换器的串联电感参数。本发明可以实现隔离型直流储能变换器的串联电感参数实时在线辩识以提高先进控制算法的准确性，同时该方法可以消除诸如开关死区、寄生参数、器件压降等因素导致的辩识误差，提高电感参数辩识的准确性。

Figure 202210807930

The present invention provides a power feedforward inductance parameter identification method and system for an isolated DC energy storage converter, wherein the method provided by the present invention includes determining the corresponding power based on the power models of the isolated DC energy storage converter under different modulation modes The first output current model under the modulation mode and the second output current model under the steady-state condition; then determine the constraints satisfied by the isolated DC energy storage converter in the actual discrete sampling system and define the first parameter and output about the control period The second parameter of the current; the proportional coefficient of the first parameter and the second parameter is used as the series inductance parameter of the isolated DC energy storage converter. The invention can realize the real-time online identification of the series inductance parameters of the isolated DC energy storage converter to improve the accuracy of the advanced control algorithm, and at the same time, the method can eliminate the identification caused by factors such as switch dead zone, parasitic parameters, device voltage drop, etc. error, and improve the accuracy of inductance parameter identification.

Figure 202210807930

Description

一种用于储能变换器的功率前馈电感参数辩识方法和系统A power feedforward inductance parameter identification method and system for energy storage converters

技术领域technical field

本发明属于储能变换器技术领域，具体涉及一种用于隔离型直流储能变换器的功率前馈电感参数辨识方法和系统。The invention belongs to the technical field of energy storage converters, and in particular relates to a power feedforward inductance parameter identification method and system for an isolated direct current energy storage converter.

背景技术Background technique

由于社会的不断进步，世界各国高度关注人类对于新能源的需求问题。如何有效开发、储存和利用能源，一直是人们要急需解决的难题。随着我国在能源消费和节能减排方面发展，为智能电网迅速发展注入了强大的驱动力。随着智能电网的发展，微电网作为其中一个重要成果也得到了越来越多的关注，在考虑分时电价的情景下，调节微电网系统的光储充放电直接影响到运维经济成本和电力系统的稳定性。Due to the continuous progress of society, all countries in the world are highly concerned about the demand for new energy by human beings. How to effectively develop, store and utilize energy has always been a problem that people need to solve urgently. With the development of energy consumption and energy conservation and emission reduction in China, a strong driving force has been injected into the rapid development of smart grid. With the development of smart grid, microgrid as one of the important achievements has also received more and more attention. Under the scenario of time-of-use electricity price, adjusting the charging and discharging of optical storage in the microgrid system directly affects the economic cost of operation and maintenance. Stability of the power system.

现在电池储能技术高速发展，发电厂及用户侧已配置大量电池储能系统，用于平滑出力波动或降低用电成本等。相应地，各种各样的先进控制算法被提出：如有学者提出最佳运行各类微电源策略，使微电网的年成本费用最小；有学者提出优化微电网调度，提高可再生能源利用效率；有学者提出一种面向用户的多种运行模式的 V2G（车辆到电网）方案，降低了用电高峰值等。With the rapid development of battery energy storage technology, power plants and users have been equipped with a large number of battery energy storage systems to smooth output fluctuations or reduce electricity costs. Correspondingly, various advanced control algorithms have been proposed: some scholars have proposed the optimal operation of various micro-power strategies to minimize the annual cost of the micro-grid; some scholars have proposed to optimize the scheduling of the micro-grid to improve the utilization efficiency of renewable energy. ; Some scholars have proposed a user-oriented V2G (vehicle-to-grid) scheme with multiple operating modes, which reduces the peak power consumption and so on.

尽管针对储能微电网系统，已经有各种各样的先进控制算法被相继提出。然而，在这些先进的控制方法中，隔离型直流储能变换器往往需要准确的电感参数来实现变换器的精确控制。如果电感参数出现偏移，则这些先进控制算法的准确性和控制性能将会大打折扣。因而如何实现隔离型直流储能变换器的串联电感参数的在线准确辩识是亟须解决的关键问题。Although a variety of advanced control algorithms have been proposed for energy storage microgrid systems. However, in these advanced control methods, isolated DC energy storage converters often require accurate inductance parameters to achieve precise control of the converter. The accuracy and control performance of these advanced control algorithms will be compromised if the inductance parameters are shifted. Therefore, how to realize the online accurate identification of the series inductance parameters of the isolated DC energy storage converter is a key problem that needs to be solved urgently.

发明内容SUMMARY OF THE INVENTION

有鉴于此，本发明旨在解决针对储能微电网系统的各种先进控制方法中，隔离型直流储能变换器的电感参数出现偏移可能会导致这些先进控制算法的准确性和控制性能降低的问题。In view of this, the present invention aims to solve the problem that in various advanced control methods for energy storage microgrid systems, the offset of the inductance parameters of the isolated DC energy storage converter may cause the accuracy and control performance of these advanced control algorithms to decrease. The problem.

为了解决上述技术问题，本发明提供以下技术方案：In order to solve the above-mentioned technical problems, the present invention provides the following technical solutions:

第一方面，本发明提供了一种用于储能变换器的功率前馈电感参数辩识方法，适用于隔离型直流储能变换器，包括如下步骤：In a first aspect, the present invention provides a power feedforward inductance parameter identification method for an energy storage converter, which is suitable for an isolated DC energy storage converter, including the following steps:

基于不同调制方式下隔离型直流储能变换器的功率模型确定对应调制方式下的第一输出电流模型；Determine the first output current model under the corresponding modulation mode based on the power model of the isolated DC energy storage converter under different modulation modes;

根据第一输出电流模型确定稳态条件下的第二输出电流模型；determining a second output current model under steady state conditions according to the first output current model;

基于第二输出电路模型确定实际离散采样系统中隔离型直流储能变换器满足的约束条件，约束条件用于确定控制周期、输出电流和串联电感参数之间的约束关系；Determine the constraints that the isolated DC energy storage converter in the actual discrete sampling system satisfies based on the second output circuit model, and the constraints are used to determine the constraint relationship between the control period, the output current and the series inductance parameters;

基于约束条件分别定义关于控制周期的第一参数和输出电流的第二参数，第一参数和第二参数成正比例关系；Define the first parameter about the control period and the second parameter of the output current respectively based on the constraint condition, and the first parameter and the second parameter are in a proportional relationship;

将第一参数和第二参数的比例系数作为隔离型直流储能变换器的串联电感参数。The proportional coefficient of the first parameter and the second parameter is used as the series inductance parameter of the isolated DC energy storage converter.

进一步地，若调制方式为单重相移调制时，第二输出电流模型具体为：Further, if the modulation mode is single phase shift modulation, the second output current model is specifically:

Figure 514859DEST_PATH_IMAGE001
Figure 514859DEST_PATH_IMAGE001

式中，

Figure 100561DEST_PATH_IMAGE002
表示输出电流，
Figure 327143DEST_PATH_IMAGE003
表示隔离型直流储能变换器的电池侧电压，
Figure 631085DEST_PATH_IMAGE004
表示控制周期，
Figure 171788DEST_PATH_IMAGE005
表示变换器的变比，
Figure 611997DEST_PATH_IMAGE006
表示隔离型直流储能变换器的串联电感，
Figure 275059DEST_PATH_IMAGE007
表示相移量。In the formula,
Figure 100561DEST_PATH_IMAGE002
represents the output current,
Figure 327143DEST_PATH_IMAGE003
represents the battery side voltage of the isolated DC energy storage converter,
Figure 631085DEST_PATH_IMAGE004
represents the control period,
Figure 171788DEST_PATH_IMAGE005
represents the transformation ratio of the converter,
Figure 611997DEST_PATH_IMAGE006
represents the series inductance of the isolated DC energy storage converter,
Figure 275059DEST_PATH_IMAGE007
Indicates the amount of phase shift.

进一步地，约束条件的表达式具体为：Further, the expression of the constraint condition is specifically:

Figure 800719DEST_PATH_IMAGE008
Figure 800719DEST_PATH_IMAGE008

式中，

Figure 207429DEST_PATH_IMAGE009
表示第k个采样周期下相移量的稳态值，
Figure 439827DEST_PATH_IMAGE010
和
Figure 273791DEST_PATH_IMAGE011
表示第k个采样周期下输出电流和电池电压的稳态值。In the formula,
Figure 207429DEST_PATH_IMAGE009
represents the steady-state value of the phase shift amount in the kth sampling period,
Figure 439827DEST_PATH_IMAGE010
and
Figure 273791DEST_PATH_IMAGE011
Indicates the steady-state values of output current and battery voltage at the kth sampling period.

进一步地，基于约束条件分别定义关于控制周期的第一参数和输出电流的第二参数，具体按照下式进行：Further, the first parameter about the control period and the second parameter of the output current are respectively defined based on the constraint conditions, which is specifically carried out according to the following formula:

Figure 286747DEST_PATH_IMAGE012
Figure 286747DEST_PATH_IMAGE012

式中，

Figure 169252DEST_PATH_IMAGE013
为所述第一参数，
Figure 584053DEST_PATH_IMAGE014
为所述第二参数。In the formula,
Figure 169252DEST_PATH_IMAGE013
is the first parameter,
Figure 584053DEST_PATH_IMAGE014
is the second parameter.

进一步地，还包括：Further, it also includes:

利用基于递推最小二乘算法的电感参数辩识自适应滤波算法对串联电感参数进行自适应滤波，自适应滤波按照下式进行：The series inductance parameter is adaptively filtered by using the adaptive filtering algorithm based on the recursive least squares algorithm for inductance parameter identification. The adaptive filtering is performed according to the following formula:

Figure 588918DEST_PATH_IMAGE015
Figure 588918DEST_PATH_IMAGE015

式中，

Figure 89169DEST_PATH_IMAGE016
表示第k个采样周期的误差，
Figure 775366DEST_PATH_IMAGE017
表示递推最小二乘算法的电感参数辩识自适应滤波算法下第k个采样周期的电感计算量，
Figure 44673DEST_PATH_IMAGE018
表示递推最小二乘算法的电感参数辩识自适应滤波算法下第k-1个采样周期的电感计算量，遗忘因子
Figure 220439DEST_PATH_IMAGE019
用来调整原始数据对于当前周期计算结果的影响程度，当遗忘因子
Figure 145670DEST_PATH_IMAGE019
接近于1时，表示计算结果更多的取决于之前的数据，而当遗忘因子
Figure 432295DEST_PATH_IMAGE019
接近于0时，表示计算结果更多的取决于最新的数据；
Figure 821688DEST_PATH_IMAGE020
和
Figure 902776DEST_PATH_IMAGE021
分别表示第k个采样周期的第一中间变量值和第二中间变量值，
Figure 315303DEST_PATH_IMAGE022
表示第k-1个采样周期的第一中间变量值。In the formula,
Figure 89169DEST_PATH_IMAGE016
represents the error of the kth sampling period,
Figure 775366DEST_PATH_IMAGE017
Represents the inductance calculation amount of the kth sampling period under the inductance parameter identification adaptive filtering algorithm of the recursive least squares algorithm,
Figure 44673DEST_PATH_IMAGE018
Represents the inductance calculation amount of the k-1 sampling period under the inductance parameter identification adaptive filtering algorithm of the recursive least squares algorithm, the forgetting factor
Figure 220439DEST_PATH_IMAGE019
It is used to adjust the degree of influence of the original data on the calculation results of the current cycle, when the forgetting factor
Figure 145670DEST_PATH_IMAGE019
When it is close to 1, it means that the calculation result depends more on the previous data, and when the forgetting factor
Figure 432295DEST_PATH_IMAGE019
When it is close to 0, it means that the calculation result depends more on the latest data;
Figure 821688DEST_PATH_IMAGE020
and
Figure 902776DEST_PATH_IMAGE021
respectively represent the value of the first intermediate variable and the value of the second intermediate variable in the kth sampling period,
Figure 315303DEST_PATH_IMAGE022
Represents the first intermediate variable value of the k-1th sampling period.

第二方面，本发明提供了一种用于储能变换器的功率前馈电感参数辩识系统，适用于隔离型直流储能变换器，包括：In a second aspect, the present invention provides a power feedforward inductance parameter identification system for an energy storage converter, suitable for an isolated DC energy storage converter, including:

第一输出电流模型确定单元，用于基于不同调制方式下隔离型直流储能变换器的功率模型确定对应调制方式下的第一输出电流模型；a first output current model determining unit, configured to determine a first output current model in a corresponding modulation mode based on the power models of the isolated DC energy storage converter in different modulation modes;

第二输出电流模型确定单元，用于根据第一输出电流模型确定稳态条件下的第二输出电流模型；a second output current model determining unit, configured to determine a second output current model under steady-state conditions according to the first output current model;

约束条件确定单元，用于基于第二输出电路模型确定实际离散采样系统中隔离型直流储能变换器满足的约束条件，约束条件用于确定控制周期、输出电流和串联电感参数之间的约束关系；The constraint condition determination unit is used to determine the constraint condition satisfied by the isolated DC energy storage converter in the actual discrete sampling system based on the second output circuit model, and the constraint condition is used to determine the constraint relationship between the control period, the output current and the series inductance parameter ;

参数定义单元，用于基于约束条件分别定义关于控制周期的第一参数和输出电流的第二参数，第一参数和第二参数成正比例关系；a parameter defining unit, configured to respectively define the first parameter of the control period and the second parameter of the output current based on the constraint condition, and the first parameter and the second parameter are in a proportional relationship;

电感参数辨识单元，用于将第一参数和第二参数的比例系数作为隔离型直流储能变换器的串联电感参数。The inductance parameter identification unit is configured to use the proportional coefficient of the first parameter and the second parameter as the series inductance parameter of the isolated DC energy storage converter.

进一步地，若调制方式为单重相移调制时，第二输出电流模型确定单元确定的第二输出电流模型具体为：Further, if the modulation mode is single phase shift modulation, the second output current model determined by the second output current model determining unit is specifically:

Figure 405619DEST_PATH_IMAGE001
Figure 405619DEST_PATH_IMAGE001

式中，

Figure 649518DEST_PATH_IMAGE002
表示输出电流，
Figure 104771DEST_PATH_IMAGE003
表示隔离型直流储能变换器的电池侧电压，
Figure 801331DEST_PATH_IMAGE004
表示控制周期，
Figure 429759DEST_PATH_IMAGE005
表示变换器的变比，
Figure 793744DEST_PATH_IMAGE006
表示隔离型直流储能变换器的串联电感，
Figure 419897DEST_PATH_IMAGE007
表示相移量。In the formula,
Figure 649518DEST_PATH_IMAGE002
represents the output current,
Figure 104771DEST_PATH_IMAGE003
represents the battery side voltage of the isolated DC energy storage converter,
Figure 801331DEST_PATH_IMAGE004
represents the control period,
Figure 429759DEST_PATH_IMAGE005
represents the transformation ratio of the converter,
Figure 793744DEST_PATH_IMAGE006
represents the series inductance of the isolated DC energy storage converter,
Figure 419897DEST_PATH_IMAGE007
Indicates the amount of phase shift.

进一步地，约束条件确定单元确定的约束条件的表达式具体为：Further, the expression of the constraint condition determined by the constraint condition determination unit is specifically:

Figure 603754DEST_PATH_IMAGE008
Figure 603754DEST_PATH_IMAGE008

式中，

Figure 35872DEST_PATH_IMAGE009
表示第k个采样周期下相移量的稳态值，
Figure 192047DEST_PATH_IMAGE010
和
Figure 51419DEST_PATH_IMAGE011
表示第k个采样周期下输出电流和电池电压的稳态值。In the formula,
Figure 35872DEST_PATH_IMAGE009
represents the steady-state value of the phase shift amount in the kth sampling period,
Figure 192047DEST_PATH_IMAGE010
and
Figure 51419DEST_PATH_IMAGE011
Indicates the steady-state values of output current and battery voltage at the kth sampling period.

进一步地，参数定义单元定义第一参数和第二参数，具体按照下式进行：Further, the parameter definition unit defines the first parameter and the second parameter, and is specifically carried out according to the following formula:

Figure 722571DEST_PATH_IMAGE012
Figure 722571DEST_PATH_IMAGE012

式中，

Figure 630485DEST_PATH_IMAGE013
为第一参数，
Figure 703483DEST_PATH_IMAGE014
为第二参数。In the formula,
Figure 630485DEST_PATH_IMAGE013
is the first parameter,
Figure 703483DEST_PATH_IMAGE014
is the second parameter.

进一步地，还包括：Further, it also includes:

自适应滤波单元，用于利用基于递推最小二乘算法的电感参数辩识自适应滤波算法对串联电感参数进行自适应滤波，自适应滤波按照下式进行：The adaptive filtering unit is used to adaptively filter the series inductance parameters using the inductance parameter identification adaptive filtering algorithm based on the recursive least squares algorithm, and the adaptive filtering is performed according to the following formula:

Figure 733756DEST_PATH_IMAGE015
Figure 733756DEST_PATH_IMAGE015

式中，

Figure 829888DEST_PATH_IMAGE016
表示第k个采样周期的误差，
Figure 603809DEST_PATH_IMAGE017
表示递推最小二乘算法的电感参数辩识自适应滤波算法下第k个采样周期的电感计算量，
Figure 531313DEST_PATH_IMAGE018
表示递推最小二乘算法的电感参数辩识自适应滤波算法下第k-1个采样周期的电感计算量，遗忘因子
Figure 732488DEST_PATH_IMAGE019
用来调整原始数据对于当前周期计算结果的影响程度，当遗忘因子
Figure 315916DEST_PATH_IMAGE019
接近于1时，表示计算结果更多的取决于之前的数据，而当遗忘因子
Figure 893528DEST_PATH_IMAGE019
接近于0时，表示计算结果更多的取决于最新的数据；
Figure 675539DEST_PATH_IMAGE020
和
Figure 47614DEST_PATH_IMAGE021
分别表示第k个采样周期的第一中间变量值和第二中间变量值，
Figure 118338DEST_PATH_IMAGE022
表示第k-1个采样周期的第一中间变量值。In the formula,
Figure 829888DEST_PATH_IMAGE016
represents the error of the kth sampling period,
Figure 603809DEST_PATH_IMAGE017
Represents the inductance calculation amount of the kth sampling period under the inductance parameter identification adaptive filtering algorithm of the recursive least squares algorithm,
Figure 531313DEST_PATH_IMAGE018
Represents the inductance calculation amount of the k-1 sampling period under the inductance parameter identification adaptive filtering algorithm of the recursive least squares algorithm, the forgetting factor
Figure 732488DEST_PATH_IMAGE019
It is used to adjust the degree of influence of the original data on the calculation results of the current cycle, when the forgetting factor
Figure 315916DEST_PATH_IMAGE019
When it is close to 1, it means that the calculation result depends more on the previous data, and when the forgetting factor
Figure 893528DEST_PATH_IMAGE019
When it is close to 0, it means that the calculation result depends more on the latest data;
Figure 675539DEST_PATH_IMAGE020
and
Figure 47614DEST_PATH_IMAGE021
respectively represent the value of the first intermediate variable and the value of the second intermediate variable in the kth sampling period,
Figure 118338DEST_PATH_IMAGE022
Represents the first intermediate variable value of the k-1th sampling period.

综上，本发明提供了一种用于隔离型直流储能变换器的功率前馈电感参数辨识方法和系统，其中本发明提供的方法包括基于不同调制方式下隔离型直流储能变换器的功率模型确定对应调制方式下的第一输出电流模型；根据第一输出电流模型确定稳态条件下的第二输出电流模型；基于第二输出电路模型确定实际离散采样系统中隔离型直流储能变换器满足的约束条件；基于约束条件分别定义关于控制周期的第一参数和输出电流的第二参数，第一参数和第二参数成正比例关系；将第一参数和第二参数的比例系数作为隔离型直流储能变换器的串联电感参数。本发明通过以隔离型直流储能变换器在传统调制方式下的功率模型为基础，推导了串联电感的辨识模型，该方法可以实现隔离型直流储能变换器的串联电感参数实时在线辩识以提高先进控制算法的准确性，同时该方法可以消除诸如开关死区、寄生参数、器件压降等因素导致的辩识误差，提高电感参数辩识的准确性。In summary, the present invention provides a power feedforward inductance parameter identification method and system for an isolated DC energy storage converter, wherein the method provided by the present invention includes the power of the isolated DC energy storage converter based on different modulation modes The model determines the first output current model under the corresponding modulation mode; determines the second output current model under steady-state conditions according to the first output current model; determines the isolated DC energy storage converter in the actual discrete sampling system based on the second output circuit model Satisfied constraints; define the first parameter of the control period and the second parameter of the output current respectively based on the constraints, the first parameter and the second parameter are in a proportional relationship; take the proportionality coefficient of the first parameter and the second parameter as the isolation type Series inductance parameters of DC energy storage converters. The invention derives the identification model of the series inductance based on the power model of the isolated direct current energy storage converter in the traditional modulation mode, and the method can realize the real-time online identification of the series inductance parameters of the isolated direct current energy storage converter, so as to obtain Improve the accuracy of advanced control algorithms, and at the same time, this method can eliminate identification errors caused by factors such as switch dead zone, parasitic parameters, device voltage drop, etc., and improve the accuracy of inductance parameter identification.

附图说明Description of drawings

为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其它的附图。In order to explain the embodiments of the present invention or the technical solutions in the prior art more clearly, the following briefly introduces the accompanying drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only These are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without any creative effort.

图1为本发明实施例提供的一种用于隔离型直流储能变换器的功率前馈电感参数辨识方法的流程示意图；1 is a schematic flowchart of a method for identifying power feedforward inductance parameters of an isolated DC energy storage converter according to an embodiment of the present invention;

图2为本发明实施例提供的隔离型直流储能变换器的电路结构图；2 is a circuit structure diagram of an isolated DC energy storage converter provided by an embodiment of the present invention;

图3为本发明实施例提供的功率前馈电感参数辨识方法的控制框图。FIG. 3 is a control block diagram of a power feedforward inductance parameter identification method according to an embodiment of the present invention.

具体实施方式Detailed ways

为使得本发明的目的、特征、优点能够更加的明显和易懂，下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，下面所描述的实施例仅仅是本发明一部分实施例，而非全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其它实施例，都属于本发明保护的范围。In order to make the purposes, features and advantages of the present invention more obvious and understandable, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the following description The embodiments described above are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

由于社会的不断进步，世界各国高度关注人类对于新能源的需求问题。如何有效开发、储存和利用能源，一直是人们要急需解决的难题。随着我国在能源消费和节能减排方面发展，为智能电网迅速发展注入了强大的驱动力。随着智能电网的发展，微电网作为其中一个重要成果也得到了越来越多的关注，在考虑分时电价的情景下，调节微电网系统的光储充放电直接影响到运维经济成本和电力系统的稳定性。Due to the continuous progress of society, all countries in the world are highly concerned about the demand for new energy by human beings. How to effectively develop, store and utilize energy has always been a problem that people need to solve urgently. With the development of energy consumption and energy conservation and emission reduction in China, a strong driving force has been injected into the rapid development of smart grid. With the development of smart grid, microgrid as one of the important achievements has also received more and more attention. Under the scenario of time-of-use electricity price, adjusting the charging and discharging of optical storage in the microgrid system directly affects the economic cost of operation and maintenance. Stability of the power system.

现在电池储能技术高速发展，发电厂及用户侧已配置大量电池储能系统，用于平滑出力波动或降低用电成本等。相应地，各种各样的先进控制算法被提出：针对微电网能量优化调度方法考虑了灵活性与经济性相协同的问题，有学者提出最佳运行各类微电源策略，使微电网的年成本费用最小。同时，考虑了需求侧的负荷响应，改进了对内部搜索算法，对微电网优化。此外，有学者提出优化微电网调度是提高可再生能源利用效率的重要途径之一，提出基于粒子群优化算法，对一个包括光电、风力、柴油机和电池在内的微电网系统进行了优化。同时面对用电需求的程度越来越大，为了降低用电高峰值，有学者提出一种面向用户的多种运行模式的 V2G（车辆到电网）方案，使更多的 EV 参与 V2G 运行进行协调充电，削峰填谷降低电网峰值。此外，考虑了风力发电，面对多变的功率变化，以储能 SOC（荷电状态）运行状态最优为目标，选用了 PSO（粒子群算法）对储能系统容量优化，进行求解计算。进一步地，面对电网的经济调度问题，改进 PSO 优化算法求解。考虑自平衡约束，优化粒子群算法来优化容量配置。针对分时电价利用灰狼算法进行优化求解，实现经济最优。With the rapid development of battery energy storage technology, power plants and users have been equipped with a large number of battery energy storage systems to smooth output fluctuations or reduce electricity costs. Correspondingly, a variety of advanced control algorithms have been proposed: for the optimal scheduling method of microgrid energy, considering the coordination of flexibility and economy, some scholars have proposed the optimal operation of various micropower strategies, so as to make the microgrid’s annual energy efficient. Cost is minimal. At the same time, considering the load response of the demand side, the internal search algorithm is improved, and the microgrid is optimized. In addition, some scholars proposed that optimizing microgrid scheduling is one of the important ways to improve the utilization efficiency of renewable energy, and proposed a particle swarm optimization algorithm to optimize a microgrid system including photovoltaics, wind power, diesel engines and batteries. At the same time, in the face of increasing power demand, in order to reduce the peak power consumption, some scholars have proposed a user-oriented V2G (vehicle-to-grid) scheme with multiple operating modes, so that more EVs can participate in V2G operation. Coordinate charging, cut peaks and fill valleys to reduce grid peaks. In addition, considering wind power generation, in the face of variable power changes, with the goal of optimizing the SOC (state of charge) operating state of the energy storage, the PSO (particle swarm algorithm) is selected to optimize the capacity of the energy storage system to solve the calculation. Further, in the face of the economic dispatch problem of the power grid, the PSO optimization algorithm is improved to solve it. Considering the self-balancing constraints, the particle swarm algorithm is optimized to optimize the capacity allocation. The gray wolf algorithm is used to optimize the time-of-use electricity price to achieve economic optimization.

尽管针对储能微电网系统，已经有各种各样的先进控制算法被相继提出。然而，在这些先进的控制方法中，隔离型直流储能变换器往往需要准确的电感参数来实现变换器的精确控制。如果电感参数出现偏移，则这些先进控制算法的准确性和控制性能将会大打折扣。因而如何实现隔离型直流储能变换器的串联电感参数的在线准确辩识是亟须解决的关键问题。Although a variety of advanced control algorithms have been proposed for energy storage microgrid systems. However, in these advanced control methods, isolated DC energy storage converters often require accurate inductance parameters to achieve precise control of the converter. The accuracy and control performance of these advanced control algorithms will be compromised if the inductance parameters are shifted. Therefore, how to realize the online accurate identification of the series inductance parameters of the isolated DC energy storage converter is a key problem that needs to be solved urgently.

基于此，本发明提供了一种用于隔离型直流储能变换器的功率前馈电感参数辨识方法和系统。Based on this, the present invention provides a power feedforward inductance parameter identification method and system for an isolated DC energy storage converter.

首先对隔离型直流储能变换器的电路结构进行简单说明。如图2所示，隔离型直流储能变换器的电路结构中，

Figure 234062DEST_PATH_IMAGE023
表示隔离型直流储能变换器的输出功率，
Figure 136159DEST_PATH_IMAGE003
和
Figure 616819DEST_PATH_IMAGE024
分别表示隔离型直流储能变换器的电池侧电压和输出电压，
Figure 237156DEST_PATH_IMAGE004
表示控制周期，
Figure 890991DEST_PATH_IMAGE005
表示变压器的变比，
Figure 585278DEST_PATH_IMAGE006
表示隔离型直流储能变换器的串联电感，
Figure 564735DEST_PATH_IMAGE025
表示单重相移调制下的相移量。Firstly, the circuit structure of the isolated DC energy storage converter is briefly described. As shown in Figure 2, in the circuit structure of the isolated DC energy storage converter,
Figure 234062DEST_PATH_IMAGE023
represents the output power of the isolated DC energy storage converter,
Figure 136159DEST_PATH_IMAGE003
and
Figure 616819DEST_PATH_IMAGE024
represent the battery side voltage and output voltage of the isolated DC energy storage converter, respectively,
Figure 237156DEST_PATH_IMAGE004
represents the control period,
Figure 890991DEST_PATH_IMAGE005
represents the transformation ratio of the transformer,
Figure 585278DEST_PATH_IMAGE006
represents the series inductance of the isolated DC energy storage converter,
Figure 564735DEST_PATH_IMAGE025
Indicates the amount of phase shift under single phase shift modulation.

以下对本发明的一种用于隔离型直流储能变换器的功率前馈电感参数辨识方法的实施例进行详细的介绍。The following describes in detail an embodiment of a power feedforward inductance parameter identification method for an isolated DC energy storage converter of the present invention.

请参阅图1，本实施例提供了一种用于隔离型直流储能变换器的功率前馈电感参数辨识方法，包括如下步骤：Referring to FIG. 1, this embodiment provides a power feedforward inductance parameter identification method for an isolated DC energy storage converter, including the following steps:

S100：基于不同调制方式下隔离型直流储能变换器的功率模型确定对应调制方式下的第一输出电流模型。S100: Determine a first output current model in a corresponding modulation mode based on power models of the isolated DC energy storage converter in different modulation modes.

针对隔离型直流储能变换器，其调制方式包括单重相移调制、双重相移调制以及三重相移调制。在不同的调制方式下，变换器具有不同数量的可控自由度。在稳态工作条件下，隔离型直流储能变换器通过控制储能电池的充放电电流来实现储能电池模块的充电和放电。以单重相移调制为例，隔离型直流储能变换器的功率模型可以表示为，For the isolated DC energy storage converter, the modulation methods include single phase shift modulation, double phase shift modulation and triple phase shift modulation. Under different modulation modes, the converter has different numbers of controllable degrees of freedom. Under steady-state working conditions, the isolated DC energy storage converter realizes the charging and discharging of the energy storage battery module by controlling the charging and discharging current of the energy storage battery. Taking the single phase shift modulation as an example, the power model of the isolated DC energy storage converter can be expressed as,

Figure 406789DEST_PATH_IMAGE026
（1）
Figure 406789DEST_PATH_IMAGE026
(1)

其中，

Figure 864315DEST_PATH_IMAGE023
表示隔离型直流储能变换器的输出功率，
Figure 678688DEST_PATH_IMAGE003
和
Figure 563467DEST_PATH_IMAGE024
分别表示隔离型直流储能变换器的电池侧电压和输出电压，
Figure 916255DEST_PATH_IMAGE004
表示控制周期，
Figure 177472DEST_PATH_IMAGE005
表示变压器的变比，
Figure 846350DEST_PATH_IMAGE006
表示隔离型直流储能变换器的串联电感，
Figure 902031DEST_PATH_IMAGE025
表示单重相移调制下的相移量。in,
Figure 864315DEST_PATH_IMAGE023
represents the output power of the isolated DC energy storage converter,
Figure 678688DEST_PATH_IMAGE003
and
Figure 563467DEST_PATH_IMAGE024
represent the battery side voltage and output voltage of the isolated DC energy storage converter, respectively,
Figure 916255DEST_PATH_IMAGE004
represents the control period,
Figure 177472DEST_PATH_IMAGE005
represents the transformation ratio of the transformer,
Figure 846350DEST_PATH_IMAGE006
represents the series inductance of the isolated DC energy storage converter,
Figure 902031DEST_PATH_IMAGE025
Indicates the amount of phase shift under single phase shift modulation.

在此基础上，隔离型直流储能变换器在单重相移调制下的输出电流模型可以表示为，On this basis, the output current model of the isolated DC energy storage converter under single phase shift modulation can be expressed as,

Figure 718677DEST_PATH_IMAGE027
（2）
Figure 718677DEST_PATH_IMAGE027
(2)

其中，

Figure 455689DEST_PATH_IMAGE028
表示隔离型直流储能变换器在单重相移调制下的输出电流。in,
Figure 455689DEST_PATH_IMAGE028
Represents the output current of the isolated DC energy storage converter under single phase shift modulation.

由上式可知，稳态运行条件下，隔离型储能直流变换器的负载电流独立于输出电压，即可以根据变换器的负载电流来进一步推导变换器的优化相移量。在传统的输出电压闭环控制方法中，变换器的动态响应速度是比较缓慢的，这是因为变换器的相移量1主要根据输出电压的误差来进行调节。当负载发生突变时，输出电压的变化是比较小的，所以变换器的相移量无法快速调节。然而当变换器的负载发生突变时，变换器的输出电流却可以瞬间突变。因而，变换器的优化相移量可以根据输出电流来进行推导，即，It can be seen from the above formula that under steady-state operating conditions, the load current of the isolated energy storage DC converter is independent of the output voltage, that is, the optimal phase shift amount of the converter can be further deduced according to the load current of the converter. In the traditional output voltage closed-loop control method, the dynamic response speed of the converter is relatively slow, because the phase shift amount 1 of the converter is mainly adjusted according to the error of the output voltage. When the load changes suddenly, the change of the output voltage is relatively small, so the phase shift of the converter cannot be adjusted quickly. However, when the load of the converter changes abruptly, the output current of the converter can suddenly change suddenly. Thus, the optimal phase shift amount of the converter can be derived from the output current, ie,

Figure 41391DEST_PATH_IMAGE029
（3）
Figure 41391DEST_PATH_IMAGE029
(3)

其中，

Figure 533553DEST_PATH_IMAGE030
表示隔离型直流储能变换器在单重相移调制下的输出电流基准，满足，in,
Figure 533553DEST_PATH_IMAGE030
Represents the output current reference of the isolated DC energy storage converter under the single phase shift modulation, which satisfies,

Figure 837495DEST_PATH_IMAGE031
（4）
Figure 837495DEST_PATH_IMAGE031
(4)

S200：根据第一输出电流模型确定稳态条件下的第二输出电流模型。S200: Determine a second output current model under steady-state conditions according to the first output current model.

根据隔离型直流储能变换器在单重相移调制下的输出电流模型，在稳态条件下，输出电流模型可以进一步表示为，According to the output current model of the isolated DC energy storage converter under single phase shift modulation, under steady-state conditions, the output current model can be further expressed as,

Figure 112618DEST_PATH_IMAGE032
（5）
Figure 112618DEST_PATH_IMAGE032
(5)

S300：基于第二输出电路模型确定实际离散采样系统中隔离型直流储能变换器满足的约束条件，约束条件用于确定控制周期、输出电流和串联电感参数之间的约束关系。S300 : Determine the constraint conditions satisfied by the isolated DC energy storage converter in the actual discrete sampling system based on the second output circuit model, where the constraint conditions are used to determine the constraint relationship among the control period, the output current and the series inductance parameter.

基于步骤S200的第二输出电路模型，进一步地，输出电流模型可以表示为，Based on the second output circuit model in step S200, further, the output current model can be expressed as,

Figure 818406DEST_PATH_IMAGE033
（6）
Figure 818406DEST_PATH_IMAGE033
(6)

考虑到在实际的离散采样系统中，隔离型储能直流变压器的输出电流、电池侧电压以及相移量应该满足一下约束条件，即，Considering that in the actual discrete sampling system, the output current, battery side voltage and phase shift of the isolated energy storage DC transformer should meet the following constraints, namely,

Figure 215890DEST_PATH_IMAGE034
（7）
Figure 215890DEST_PATH_IMAGE034
(7)

其中，

Figure 944811DEST_PATH_IMAGE009
表示第k个采样周期下相移量的稳态值，
Figure 85943DEST_PATH_IMAGE010
和
Figure 646237DEST_PATH_IMAGE011
表示第k个采样周期下输出电流和电池电压的稳态值。in,
Figure 944811DEST_PATH_IMAGE009
represents the steady-state value of the phase shift amount in the kth sampling period,
Figure 85943DEST_PATH_IMAGE010
and
Figure 646237DEST_PATH_IMAGE011
Indicates the steady-state values of output current and battery voltage at the kth sampling period.

S400：基于约束条件分别定义关于控制周期的第一参数和输出电流的第二参数，第一参数和第二参数成正比例关系。S400: Define the first parameter of the control period and the second parameter of the output current respectively based on the constraint condition, and the first parameter and the second parameter are in a proportional relationship.

为了便于实现串联电感的在线参数辩识，分别定义

Figure 417884DEST_PATH_IMAGE013
和
Figure 430839DEST_PATH_IMAGE014
，满足
Figure 375661DEST_PATH_IMAGE013
和
Figure 790462DEST_PATH_IMAGE014
成正比例关系，同时比例系数即为串联电感系数，In order to facilitate the online parameter identification of series inductance, respectively define
Figure 417884DEST_PATH_IMAGE013
and
Figure 430839DEST_PATH_IMAGE014
,Satisfy
Figure 375661DEST_PATH_IMAGE013
and
Figure 790462DEST_PATH_IMAGE014
proportional relationship, and the proportional coefficient is the series inductance coefficient,

Figure 795327DEST_PATH_IMAGE035
（8）
Figure 795327DEST_PATH_IMAGE035
(8)

S500：将第一参数和第二参数的比例系数作为隔离型直流储能变换器的串联电感参数。S500: Use the proportional coefficient of the first parameter and the second parameter as the series inductance parameter of the isolated DC energy storage converter.

除此之外，在电感参数辩识算法的实际实施中总会存在采样噪声，因而电感参数的计算也会存在采样噪声。因而，为了实现电感参数在线辩识的动态响应和控制环路的动态响应相互解耦，提出了基于递推最小二乘算法的电感参数辩识自适应滤波算法，以实现串联电感参数的实时辩识。具体地，实现递推最小二乘算法的电感参数辩识自适应滤波算法的步骤为，In addition, sampling noise will always exist in the actual implementation of the inductance parameter identification algorithm, so the calculation of the inductance parameter will also have sampling noise. Therefore, in order to realize the mutual decoupling of the dynamic response of the online identification of the inductance parameters and the dynamic response of the control loop, an adaptive filtering algorithm for the identification of the inductance parameters based on the recursive least squares algorithm is proposed to realize the real-time identification of the series inductance parameters. knowledge. Specifically, the steps of realizing the inductance parameter identification adaptive filtering algorithm of the recursive least squares algorithm are:

Figure 233262DEST_PATH_IMAGE036
（9）
Figure 233262DEST_PATH_IMAGE036
(9)

式中，

Figure 716196DEST_PATH_IMAGE016
表示第k个采样周期的误差，
Figure 251082DEST_PATH_IMAGE017
表示递推最小二乘算法的电感参数辩识自适应滤波算法下第k个采样周期的电感计算量，
Figure 364532DEST_PATH_IMAGE018
表示递推最小二乘算法的电感参数辩识自适应滤波算法下第k-1个采样周期的电感计算量，遗忘因子
Figure 352079DEST_PATH_IMAGE019
用来调整原始数据对于当前周期计算结果的影响程度，当遗忘因子
Figure 638704DEST_PATH_IMAGE019
接近于1时，表示计算结果更多的取决于之前的数据，而当遗忘因子
Figure 762518DEST_PATH_IMAGE019
接近于0时，表示计算结果更多的取决于最新的数据；
Figure 46869DEST_PATH_IMAGE020
和
Figure 521713DEST_PATH_IMAGE021
分别表示第k个采样周期的第一中间变量值和第二中间变量值，
Figure 612028DEST_PATH_IMAGE022
表示第k-1个采样周期的第一中间变量值。In the formula,
Figure 716196DEST_PATH_IMAGE016
represents the error of the kth sampling period,
Figure 251082DEST_PATH_IMAGE017
Represents the inductance calculation amount of the kth sampling period under the inductance parameter identification adaptive filtering algorithm of the recursive least squares algorithm,
Figure 364532DEST_PATH_IMAGE018
Represents the inductance calculation amount of the k-1 sampling period under the inductance parameter identification adaptive filtering algorithm of the recursive least squares algorithm, the forgetting factor
Figure 352079DEST_PATH_IMAGE019
It is used to adjust the degree of influence of the original data on the calculation results of the current cycle, when the forgetting factor
Figure 638704DEST_PATH_IMAGE019
When it is close to 1, it means that the calculation result depends more on the previous data, and when the forgetting factor
Figure 762518DEST_PATH_IMAGE019
When it is close to 0, it means that the calculation result depends more on the latest data;
Figure 46869DEST_PATH_IMAGE020
and
Figure 521713DEST_PATH_IMAGE021
respectively represent the value of the first intermediate variable and the value of the second intermediate variable in the kth sampling period,
Figure 612028DEST_PATH_IMAGE022
Represents the first intermediate variable value of the k-1th sampling period.

基于上述步骤，对于隔离型直流储能变换器的控制方法为，首先检测隔离型储能直流变压器的输入电压、输出电压和输出电流；然后采用输出电压闭环的比例积分控制器来实现实时控制；同时，结合采样得到的输出电压、输入电压和输出电流，采用基于递推最小二乘算法的电感参数辩识自适应滤波算法对变换器的电感参数进行实时辩识；最后，基于所得到的辩识电感参数，结合所推导的隔离型储能直流变压器的电流模型完成变换器的功率前馈控制以提高储能直流变换器的动态响应速度。Based on the above steps, the control method for the isolated DC energy storage converter is as follows: firstly detect the input voltage, output voltage and output current of the isolated DC energy storage transformer; At the same time, combined with the sampled output voltage, input voltage and output current, the inductance parameter identification adaptive filtering algorithm based on the recursive least squares algorithm is used to identify the inductance parameters of the converter in real time; finally, based on the obtained identification By identifying the inductance parameters, combined with the derived current model of the isolated energy storage DC transformer, the power feedforward control of the converter is completed to improve the dynamic response speed of the energy storage DC converter.

图3为所提出的电感参数辨识方法的控制框图，在该图中通过将变换器的输出电压vo与参考电压vref进行比较，然后将电压误差送到比例积分控制器Gc(s)中，计算出用于实现变换器电压控制的相移量Δф，然后采样变换器的输出电流经过式（3）所述的电流前馈控制器输出前馈相移量фm进行叠加，所得到的最终相移量ф经过变换器的相移量-输出电压传递函数即可得到变换器的实际输出电流，然后经过变换的等效输出阻抗模型Zout(s)即可获得实际输出电压。Fig. 3 is the control block diagram of the proposed inductance parameter identification method. In this figure, the output voltage v o of the converter is compared with the reference voltage v ref , and then the voltage error is sent to the proportional integral controller Gc(s) , calculate the phase shift amount Δф used to realize the voltage control of the converter, and then the output current of the sampling converter is superimposed by the output feed forward phase shift amount ф m of the current feedforward controller described in equation (3), and the obtained The final phase shift ф can obtain the actual output current of the converter through the phase shift-output voltage transfer function of the converter, and then the actual output voltage can be obtained through the transformed equivalent output impedance model Z out (s).

本实施例提供了一种用于隔离型直流储能变换器的功率前馈电感参数辨识方法，以功率前馈控制算法为例，首先分析了隔离型直流储能变换器在传统的单相移调制下的功率模型，并进一步推导了对应的电流模型。在此基础上，推导了变换器在功率前馈控制算法下的前馈相移量计算方法；同时，以直流储能变换器的电流模型为基础，推导了串联电感的辨识模型；为了提高辩识准确性并抑制采样噪声，提出了基于递推最小二乘算法的电感参数辩识自适应滤波算法，以实现串联电感参数的实时辩识。This embodiment provides a power feedforward inductance parameter identification method for an isolated DC energy storage converter. Taking the power feedforward control algorithm as an example, firstly analyzes the performance of the isolated DC energy storage converter in the traditional single-phase shift The power model under modulation, and the corresponding current model is further derived. On this basis, the calculation method of the feedforward phase shift of the converter under the power feedforward control algorithm is deduced; at the same time, based on the current model of the DC energy storage converter, the identification model of the series inductance is deduced; In order to identify the accuracy and suppress sampling noise, an adaptive filtering algorithm based on recursive least squares algorithm for inductance parameter identification is proposed to realize real-time identification of series inductance parameters.

本实施例所提出的隔离型直流储能变换器的功率前馈电感参数辩识方法，可以实现隔离型直流储能变换器的串联电感参数实时在线辩识以提高先进控制算法的准确性，同时该方法可以消除诸如开关死区、寄生参数、器件压降等因素导致的辩识误差，提高电感参数辩识的准确性。The method for identifying the power feedforward inductance parameters of the isolated DC energy storage converter proposed in this embodiment can realize the real-time online identification of the series inductance parameters of the isolated DC energy storage converter to improve the accuracy of the advanced control algorithm. The method can eliminate identification errors caused by factors such as switch dead zone, parasitic parameters, device voltage drop, etc., and improve the accuracy of inductance parameter identification.

以上是对本发明的一种用于隔离型直流储能变换器的功率前馈电感参数辨识方法的实施例进行的详细介绍，以下将对本发明的一种用于隔离型直流储能变换器的功率前馈电感参数辨识系统的实施例进行详细的介绍。The above is a detailed introduction to an embodiment of a power feedforward inductance parameter identification method for an isolated DC energy storage converter of the present invention. The embodiment of the feedforward inductance parameter identification system is introduced in detail.

本实施例提供了一种用于储能变换器的功率前馈电感参数辩识系统，适用于隔离型直流储能变换器，包括：This embodiment provides a power feedforward inductance parameter identification system for an energy storage converter, which is suitable for an isolated DC energy storage converter, including:

第一输出电流模型确定单元，用于基于不同调制方式下隔离型直流储能变换器的功率模型确定对应调制方式下的第一输出电流模型。The first output current model determining unit is configured to determine the first output current model in the corresponding modulation mode based on the power models of the isolated DC energy storage converter in different modulation modes.

第二输出电流模型确定单元，用于根据第一输出电流模型确定稳态条件下的第二输出电流模型。The second output current model determining unit is configured to determine a second output current model under steady-state conditions according to the first output current model.

需要说明的是，若调制方式为单重相移调制时，第二输出电流模型确定单元确定的第二输出电流模型具体为：It should be noted that, if the modulation mode is single phase shift modulation, the second output current model determined by the second output current model determining unit is specifically:

Figure 793611DEST_PATH_IMAGE001
Figure 793611DEST_PATH_IMAGE001

式中，

Figure 45601DEST_PATH_IMAGE002
表示输出电流，
Figure 7741DEST_PATH_IMAGE003
表示隔离型直流储能变换器的电池侧电压，
Figure 636168DEST_PATH_IMAGE004
表示控制周期，
Figure 937836DEST_PATH_IMAGE005
表示变换器的变比，
Figure 360727DEST_PATH_IMAGE006
表示隔离型直流储能变换器的串联电感，
Figure 810163DEST_PATH_IMAGE007
表示相移量。In the formula,
Figure 45601DEST_PATH_IMAGE002
represents the output current,
Figure 7741DEST_PATH_IMAGE003
represents the battery side voltage of the isolated DC energy storage converter,
Figure 636168DEST_PATH_IMAGE004
represents the control period,
Figure 937836DEST_PATH_IMAGE005
represents the transformation ratio of the converter,
Figure 360727DEST_PATH_IMAGE006
represents the series inductance of the isolated DC energy storage converter,
Figure 810163DEST_PATH_IMAGE007
Indicates the amount of phase shift.

约束条件确定单元，用于基于第二输出电路模型确定实际离散采样系统中隔离型直流储能变换器满足的约束条件，约束条件用于确定控制周期、输出电流和串联电感参数之间的约束关系。The constraint condition determination unit is used to determine the constraint condition satisfied by the isolated DC energy storage converter in the actual discrete sampling system based on the second output circuit model, and the constraint condition is used to determine the constraint relationship between the control period, the output current and the series inductance parameter .

需要说明的是，约束条件确定单元确定的约束条件的表达式具体为：It should be noted that the expression of the constraint condition determined by the constraint condition determination unit is specifically:

Figure 242282DEST_PATH_IMAGE008
Figure 242282DEST_PATH_IMAGE008

式中，

Figure 132877DEST_PATH_IMAGE009
表示第k个采样周期下相移量的稳态值，
Figure 992249DEST_PATH_IMAGE010
和
Figure 663402DEST_PATH_IMAGE011
表示第k个采样周期下输出电流和电池电压的稳态值。In the formula,
Figure 132877DEST_PATH_IMAGE009
represents the steady-state value of the phase shift amount in the kth sampling period,
Figure 992249DEST_PATH_IMAGE010
and
Figure 663402DEST_PATH_IMAGE011
Indicates the steady-state values of output current and battery voltage at the kth sampling period.

参数定义单元，用于基于约束条件分别定义关于控制周期的第一参数和输出电流的第二参数，第一参数和第二参数成正比例关系。The parameter defining unit is used for respectively defining the first parameter of the control period and the second parameter of the output current based on the constraint condition, and the first parameter and the second parameter are in a proportional relationship.

需要说明的是，参数定义单元定义第一参数和第二参数，具体按照下式进行：It should be noted that the parameter definition unit defines the first parameter and the second parameter, which is specifically carried out according to the following formula:

Figure 899211DEST_PATH_IMAGE012
Figure 899211DEST_PATH_IMAGE012

式中，

Figure 909892DEST_PATH_IMAGE013
为第一参数，
Figure 940165DEST_PATH_IMAGE014
为第二参数。In the formula,
Figure 909892DEST_PATH_IMAGE013
is the first parameter,
Figure 940165DEST_PATH_IMAGE014
is the second parameter.

电感参数辨识单元，用于将第一参数和第二参数的比例系数作为隔离型直流储能变换器的串联电感参数。The inductance parameter identification unit is configured to use the proportional coefficient of the first parameter and the second parameter as the series inductance parameter of the isolated DC energy storage converter.

除此之外，本实施例提供的系统还包括自适应滤波单元，用于利用基于递推最小二乘算法的电感参数辩识自适应滤波算法对串联电感参数进行自适应滤波，自适应滤波按照下式进行：In addition, the system provided by this embodiment further includes an adaptive filtering unit, which is used to adaptively filter the series inductance parameters by using the inductance parameter identification adaptive filtering algorithm based on the recursive least squares algorithm. Proceed as follows:

Figure 98614DEST_PATH_IMAGE015
Figure 98614DEST_PATH_IMAGE015

式中，

Figure 872535DEST_PATH_IMAGE016
表示第k个采样周期的误差，
Figure 737723DEST_PATH_IMAGE017
表示递推最小二乘算法的电感参数辩识自适应滤波算法下第k个采样周期的电感计算量，
Figure 938897DEST_PATH_IMAGE018
表示递推最小二乘算法的电感参数辩识自适应滤波算法下第k-1个采样周期的电感计算量，遗忘因子
Figure 584642DEST_PATH_IMAGE019
用来调整原始数据对于当前周期计算结果的影响程度，当遗忘因子
Figure 834358DEST_PATH_IMAGE019
接近于1时，表示计算结果更多的取决于之前的数据，而当遗忘因子
Figure 881948DEST_PATH_IMAGE019
接近于0时，表示计算结果更多的取决于最新的数据；
Figure 254024DEST_PATH_IMAGE020
和
Figure 387065DEST_PATH_IMAGE021
分别表示第k个采样周期的第一中间变量值和第二中间变量值，
Figure 440471DEST_PATH_IMAGE022
表示第k-1个采样周期的第一中间变量值。In the formula,
Figure 872535DEST_PATH_IMAGE016
represents the error of the kth sampling period,
Figure 737723DEST_PATH_IMAGE017
Represents the inductance calculation amount of the kth sampling period under the inductance parameter identification adaptive filtering algorithm of the recursive least squares algorithm,
Figure 938897DEST_PATH_IMAGE018
Represents the inductance calculation amount of the k-1 sampling period under the inductance parameter identification adaptive filtering algorithm of the recursive least squares algorithm, the forgetting factor
Figure 584642DEST_PATH_IMAGE019
It is used to adjust the degree of influence of the original data on the calculation results of the current cycle, when the forgetting factor
Figure 834358DEST_PATH_IMAGE019
When it is close to 1, it means that the calculation result depends more on the previous data, and when the forgetting factor
Figure 881948DEST_PATH_IMAGE019
When it is close to 0, it means that the calculation result depends more on the latest data;
Figure 254024DEST_PATH_IMAGE020
and
Figure 387065DEST_PATH_IMAGE021
respectively represent the value of the first intermediate variable and the value of the second intermediate variable in the kth sampling period,
Figure 440471DEST_PATH_IMAGE022
Represents the first intermediate variable value of the k-1th sampling period.

需要说明的是，本实施例通过的电感参数辨识系统用于实现前述实施例提供的电感参数辨识方法，各单元的具体设置均已完整实现该方法为准，在此不再赘述。It should be noted that the inductance parameter identification system adopted in this embodiment is used to implement the inductance parameter identification method provided in the foregoing embodiment, and the specific settings of each unit have been fully realized by the method, which will not be repeated here.

以上实施例仅用以说明本发明的技术方案，而非对其限制；尽管参照前述实施例对本发明进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本发明各实施例技术方案的精神和范围。The above embodiments are only used to illustrate the technical solutions of the present invention, but not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: The recorded technical solutions are modified, or some technical features thereof are equivalently replaced; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (10)

1. A method for identifying power feedforward inductance parameters of an energy storage converter is suitable for an isolated direct current energy storage converter and is characterized by comprising the following steps:
determining a first output current model under a corresponding modulation mode based on power models of the isolated DC energy storage converter under different modulation modes;
determining a second output current model under a steady-state condition according to the first output current model;
determining constraint conditions met by the isolated DC energy storage converter in the actual discrete sampling system based on the second output current model, wherein the constraint conditions are used for determining constraint relations among a control period, output current and series inductance parameters;
defining a first parameter and a second parameter of the output current respectively with respect to the control period based on the constraint condition, the first parameter and the second parameter being in a direct proportional relationship;
and taking the proportionality coefficient of the first parameter and the second parameter as the series inductance parameter of the isolated direct current energy storage converter.
2. A method as claimed in claim 1, wherein if the modulation scheme is single phase shift modulation, the second output current model is specifically:
Figure 534425DEST_PATH_IMAGE001
in the formula,
Figure 79675DEST_PATH_IMAGE002
which is representative of the output current of the power supply,
Figure 178344DEST_PATH_IMAGE003
the battery side voltage of the isolated DC energy storage converter is shown,
Figure 291793DEST_PATH_IMAGE004
it is indicated that the control period is,
Figure 341658DEST_PATH_IMAGE005
which represents the ratio of the transformation of the converter,
Figure 565966DEST_PATH_IMAGE006
the series inductance of the isolated DC energy storage converter is shown,
Figure 253561DEST_PATH_IMAGE007
the amount of phase shift is indicated.
3. A method for identifying parameters of a power feed forward inductance for an energy storage converter as claimed in claim 2, wherein the constraint is expressed by the following expression:
Figure 662546DEST_PATH_IMAGE008
in the formula,
Figure 75073DEST_PATH_IMAGE009
a steady state value representing the amount of phase shift during the kth sampling period,
Figure 729170DEST_PATH_IMAGE010
and
Figure 910753DEST_PATH_IMAGE011
representing the steady state values of the output current and the battery voltage at the kth sampling period.
4. A power feed forward inductance parameter identification method for an energy storage converter according to claim 3, characterized in that the first parameter related to the control period and the second parameter related to the output current are respectively defined based on the constraint conditions, and specifically according to the following formula:
Figure 225059DEST_PATH_IMAGE012
in the formula,
Figure 750981DEST_PATH_IMAGE013
in order to be able to determine the first parameter,
Figure 317091DEST_PATH_IMAGE014
is the second parameter.
5. A power feed forward inductance parameter identification method for a power storage converter as claimed in claim 4, further comprising:
and carrying out adaptive filtering on the series inductance parameters by using an inductance parameter identification adaptive filtering algorithm based on a recursive least square algorithm, wherein the adaptive filtering is carried out according to the following formula:
Figure 743394DEST_PATH_IMAGE015
in the formula,
Figure 103968DEST_PATH_IMAGE016
indicating the error for the k-th sampling period,
Figure 117185DEST_PATH_IMAGE017
the inductance parameter of the recursive least square algorithm represents the inductance calculated quantity of the kth sampling period under the inductance parameter identification adaptive filtering algorithm,
Figure 611621DEST_PATH_IMAGE018
inductance calculation amount and forgetting factor of k-1 sampling period under inductance parameter identification adaptive filtering algorithm representing recursive least square algorithm
Figure 502216DEST_PATH_IMAGE019
Used for adjusting the influence degree of the original data on the calculation result of the current period, as a forgetting factor
Figure 925370DEST_PATH_IMAGE019
When approaching 1, the representation calculation result depends more on the previous data, and when the forgetting factor is
Figure 534205DEST_PATH_IMAGE019
When the value is close to 0, the calculation result is more dependent on the latest data;
Figure 832332DEST_PATH_IMAGE020
and
Figure 469112DEST_PATH_IMAGE021
respectively representing a first intermediate variable value and a second intermediate variable value for the kth sampling period,
Figure 437068DEST_PATH_IMAGE022
representing the first intermediate variable value for the (k-1) th sampling period.
6. A power feedforward inductance parameter identification system for an energy storage converter, suitable for an isolated DC energy storage converter, comprising:
the first output current model determining unit is used for determining a first output current model in a corresponding modulation mode based on power models of the isolated direct-current energy storage converter in different modulation modes;
a second output current model determination unit for determining a second output current model under a steady-state condition according to the first output current model;
the constraint condition determining unit is used for determining a constraint condition which is met by the isolated direct-current energy storage converter in the actual discrete sampling system based on the second output current model, and the constraint condition is used for determining a constraint relation among a control period, output current and series inductance parameters;
a parameter defining unit for defining a first parameter regarding a control period and a second parameter regarding an output current, respectively, based on the constraint condition, the first parameter and the second parameter being in a direct proportional relationship;
and the inductance parameter identification unit is used for taking the proportionality coefficient of the first parameter and the second parameter as the series inductance parameter of the isolated DC energy storage converter.
7. A power feedforward inductance parameter identification system for an energy storage converter according to claim 6, wherein if the modulation mode is single phase shift modulation, the second output current model determined by the second output current model determining unit is specifically:
Figure 657833DEST_PATH_IMAGE001
in the formula,
Figure 369437DEST_PATH_IMAGE002
which is indicative of the output current of the power converter,
Figure 860724DEST_PATH_IMAGE003
the battery side voltage of the isolated DC energy storage converter is shown,
Figure 999581DEST_PATH_IMAGE004
it is indicated that the control period is,
Figure 707643DEST_PATH_IMAGE005
which represents the ratio of the transformation of the converter,
Figure 957359DEST_PATH_IMAGE006
the series inductance of the isolated DC energy storage converter is shown,
Figure 545294DEST_PATH_IMAGE007
the amount of phase shift is indicated.
8. A power feedforward inductance parameter identification system for an energy storage converter according to claim 7, wherein the constraint condition determined by the constraint condition determining unit is specifically expressed as:
Figure 855052DEST_PATH_IMAGE008
in the formula,
Figure 50410DEST_PATH_IMAGE009
a steady state value representing the amount of phase shift during the kth sampling period,
Figure 729915DEST_PATH_IMAGE010
and
Figure 694329DEST_PATH_IMAGE011
representing the steady state values of the output current and the battery voltage at the kth sampling period.
9. A power feed forward inductance parameter identification system for a power storage converter as claimed in claim 8 wherein said parameter definition unit defines a first parameter and a second parameter in accordance with the following equation:
Figure 174989DEST_PATH_IMAGE012
in the formula,
Figure 93529DEST_PATH_IMAGE013
is a function of the first parameter and is,
Figure 950626DEST_PATH_IMAGE014
is the second parameter.
10. A power feed forward inductance parameter identification system for a power storage converter as claimed in claim 9 further comprising:
the adaptive filtering unit is used for carrying out adaptive filtering on the series inductance parameters by utilizing an inductance parameter identification adaptive filtering algorithm based on a recursive least square algorithm, and the adaptive filtering is carried out according to the following formula:
Figure 769547DEST_PATH_IMAGE015
in the formula,
Figure 421108DEST_PATH_IMAGE016
represents the kth sampleThe error in the period of time of the cycle,
Figure 92523DEST_PATH_IMAGE017
inductance parameters representing the recursive least square algorithm identify the inductance calculation amount of the kth sampling period under the adaptive filtering algorithm,
Figure 487732DEST_PATH_IMAGE018
inductance calculation amount and forgetting factor of k-1 sampling period under inductance parameter identification adaptive filtering algorithm representing recursive least square algorithm
Figure 161159DEST_PATH_IMAGE019
Used for adjusting the influence degree of the original data on the calculation result of the current period, as a forgetting factor
Figure 875299DEST_PATH_IMAGE019
When approaching 1, the representation calculation result depends more on the previous data, and when forgetting the factor
Figure 142333DEST_PATH_IMAGE019
When the value is close to 0, the calculation result is more dependent on the latest data;
Figure 465867DEST_PATH_IMAGE020
and
Figure 869166DEST_PATH_IMAGE021
respectively representing a first intermediate variable value and a second intermediate variable value for the kth sampling period,
Figure 754208DEST_PATH_IMAGE022
representing the first intermediate variable value for the (k-1) th sampling period.
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