阅读说明：本技术 基于间接模型预测的光储系统用动态优化方法 (Dynamic optimization method for light storage system based on indirect model prediction ) 是由 洪晓燕 高梅鹃 卢奇 赵冬义 刘达 金亮亮 张蕾琼 庄建斌 姚天明 李云瑞 周宗 于 2020-06-06 设计创作，主要内容包括：本发明公开了一种基于间接模型预测的光储系统用动态优化方法,包括以下步骤：步骤S1：在初始判断周期或者在前序判断周期判断结束后的下一判断周期,判断参考电流是否发生突变,如果判断成功则执行步骤S4,同时置持续周期Prd＝1,否则执行步骤S2；步骤S2：判断光储系统的交流侧电流误差是否小于光储系统的预置的交流侧电流误差阈值,如果判断成功则执行步骤S9,否则执行步骤S3。本发明公开的基于间接模型预测的光储系统用动态优化方法,控制器的参数整定不再依赖试凑等具有随机性、不确定性的约束行为,同时有助于优化计算量。(The invention discloses a dynamic optimization method for an optical storage system based on indirect model prediction, which comprises the following steps: step S1: judging whether the reference current has sudden change in the initial judgment period or in the next judgment period after the judgment of the previous judgment period is finished, if so, executing the step S4, and setting the continuous period Prd to 1, otherwise, executing the step S2; step S2: and judging whether the alternating current side current error of the light storage system is smaller than a preset alternating current side current error threshold value of the light storage system, if so, executing the step S9, otherwise, executing the step S3. According to the dynamic optimization method for the light storage system based on indirect model prediction, parameter setting of the controller does not depend on constraint behaviors such as trial and error and the like, has randomness and uncertainty, and is beneficial to optimization of calculated amount.)

1. A dynamic optimization method for a light storage system based on indirect model prediction is characterized by comprising the following steps:

step S1: judging whether the reference current has sudden change in the initial judgment period or in the next judgment period after the judgment of the previous judgment period is finished, if so, executing the step S4, and setting the continuous period Prd to 1, otherwise, executing the step S2;

step S2: judging whether the alternating current side current error of the optical storage system is smaller than a preset alternating current side current error threshold value of the optical storage system, if so, executing a step S9, otherwise, executing a step S3;

step S3: judging whether the duration period Prd is 1, if so, executing step S4, otherwise, setting the duration period Prd to Prd-1 and executing step S9;

step S4: setting n as 1;

step S5: performing reference current prediction according to the value of n;

step S6: calculating MPC algorithm input value level_new；

Step S7: setting a duration period Prd as n;

step S8: judging MPC algorithm input value level_newWhether the MPC algorithm is in an open interval (-X, X) or not, and if the MPC algorithm is successfully judged, outputting an input value level of the MPC algorithm_newAnd performing step S8, otherwise setting n to n +1 and performing step S5;

step S9: the MPC algorithm is executed.

2. The indirect model prediction-based dynamic optimization method for the light storage system according to claim 1, wherein in step S8, when the level is N +1, the value of X is N/2, and N is the number of bridge arm submodules.

3. The indirect model prediction-based dynamic optimization method for the light storage system according to claim 1, wherein in step S8, when the level is 2N +1, X is N, and N is the number of bridge arm submodules.

4. The method for dynamically optimizing a light storage system based on indirect model prediction according to any one of claims 1 to 3, wherein the step S5 is calculated by using formula (1):

wherein i_d(k) Represents the internal unbalance current at time k; θ represents an angle; i denotes the magnitude of the ac side current vector of the optical storage system.

5. The method for dynamically optimizing a light storage system based on indirect model prediction according to any one of claims 1 to 3, wherein the step S6 is calculated by using formula (2):

wherein i_sjRepresents the ac side current of the optical storage system; u shape_sjRepresenting the ac side voltage of the optical storage system; u shape_dcRepresenting the dc side voltage of the optical storage system.

Technical Field

The invention belongs to the technical field of power electronics, and particularly relates to a dynamic optimization method for an optical storage system based on indirect model prediction.

Background

In the field of power electronics, when MPC is applied, the existing conventional model prediction algorithm is noteworthy that no general rule for linear controller parameter design can be followed. In other words, the tuning of the controller parameters still relies on trial and error in most cases.

Since the optical storage system based on the MMC has more control targets, a control strategy of model prediction can be adopted, and aspects such as design, calculation amount and dynamic performance of a model prediction control cost function need to be considered.

Document 1 (guosheng, pengpo, public shining.) a model-optimized model predictive control of a modular multilevel converter based on module unified pulse width modulation [ J ]. the journal of electrical engineering in china, 2017,37(05): 1478-.

Document 2 (shining, five Xiaojie, Peng. fast voltage model prediction control strategy of modular multilevel converter [ J ] power system automation, 2017,41(01): 122-.

Document 3(j.moon, j.gwon, j.park, d.kang and j.kim, "Model Predictive control with a Reduced Number of associated States in a Modular Multilevel converter HVDC System," in IEEE Transactions on Power Delivery, vol.30, No.2, pp.608-617, April 2015) proposes three different cost functions to reduce the state of the switches to be Considered.

However, for the MMC based optical storage system, due to the increase of the content of the part of the stored energy, further improvement is needed to optimize the control effect.

Disclosure of Invention

Aiming at the conditions of the prior art, the invention overcomes the defects and provides a dynamic optimization method for the light storage system based on indirect model prediction.

The invention discloses a dynamic optimization method for an optical storage system based on indirect model prediction, which mainly aims to ensure that parameter setting of a controller does not depend on random and uncertain constraint behaviors such as trial and error.

The invention discloses a dynamic optimization method for a light storage system based on indirect model prediction, which aims to help to optimize the calculated amount.

The invention discloses a dynamic optimization method for an optical storage system based on indirect model prediction, and the method is further used for remarkably reducing the calculated amount aiming at specific application occasions with more sub-modules and the like, so that the overall expense of the system is reduced.

The invention adopts the following technical scheme that the dynamic optimization method for the light storage system based on indirect model prediction comprises the following steps:

step S1: judging whether the reference current has sudden change in the initial judgment period or in the next judgment period after the judgment of the previous judgment period is finished, if so, executing the step S4, and setting the continuous period Prd to 1, otherwise, executing the step S2;

step S2: judging whether the alternating current side current error of the optical storage system is smaller than a preset alternating current side current error threshold value of the optical storage system, if so, executing a step S9, otherwise, executing a step S3;

step S3: judging whether the duration period Prd is 1, if so, executing step S4, otherwise, setting the duration period Prd to Prd-1 and executing step S9;

step S4: setting n as 1;

step S5: performing reference current prediction according to the value of n;

step S6: calculating MPC algorithm input value level_new；

Step S7: setting a duration period Prd as n;

step S8: judging MPC algorithm input value level_newWhether the MPC algorithm is in an open interval (-X, X) or not, and if the MPC algorithm is successfully judged, outputting an input value level of the MPC algorithm_newAnd performing step S8, otherwise setting n to n +1 and performing step S5;

step S9: the MPC algorithm is executed.

According to the above technical solution, as a further preferable technical solution of the above technical solution, in step S8, when the N +1 level is implemented, the value of X is N/2, and N is the number of bridge arm sub-modules.

According to the above technical solution, as a further preferable technical solution of the above technical solution, in step S8, when the level is implemented as 2N +1 level, the value of X is N, and N is the number of bridge arm sub-modules.

According to the above technical solution, as a further preferable technical solution of the above technical solution, step S5 is calculated by using formula (1):

wherein i_d(k) Represents the internal unbalance current at time k; θ represents an angle; i denotes the magnitude of the ac side current vector of the optical storage system.

According to the above technical solution, as a further preferable technical solution of the above technical solution, step S6 is calculated by using formula (2):

wherein i_sjRepresents the ac side current of the optical storage system; u shape_sjRepresenting the ac side voltage of the optical storage system; u shape_dcRepresenting the dc side voltage of the optical storage system.

The dynamic optimization method for the optical storage system based on indirect model prediction has the advantages that parameter setting of the controller does not depend on trial and error and other constraint behaviors with randomness and uncertainty, and meanwhile, the optimization of calculated amount is facilitated.

Drawings

FIG. 1 is a schematic flow diagram of the present invention.

Detailed Description

The invention discloses a dynamic optimization method for an optical storage system based on indirect model prediction, and the specific implementation mode of the invention is further described in combination with the preferred embodiment.

It should be noted that the mmc (modular Multilevel converter) disclosed in the embodiments of the present invention is defined as a modular Multilevel technology (converter/converter).

It is worth mentioning that the soc (state of charge) disclosed in the embodiments of the present invention is defined as a state of charge/state of charge.

It should be noted that mpc (model Predictive control) disclosed in the embodiments of the present invention is defined as model Predictive control.

It should be noted that the converters, etc. that may be involved in the embodiments of the present invention are all the same concept and are not distinguished.

Preferred embodiments.

Referring to fig. 1 of the drawings, fig. 1 shows a related flow of the dynamic optimization method for the light storage system based on indirect model prediction.

Preferably, the dynamic optimization method for the light storage system based on indirect model prediction includes the following steps:

step S1: judging whether the reference current has sudden change in the initial judgment period or in the next judgment period after the judgment of the previous judgment period is finished, if the judgment is successful (sudden change occurs), executing step S4, and setting the continuous period Prd to 1, otherwise executing step S2;

step S2: judging the AC side current error (i) of the light storage system_{sj err}) Whether or not it is less than the preset AC side current error threshold (i) of the light storage system_{sj T}) If the judgment is successful (the alternating current side current error of the optical storage system is smaller than the preset alternating current side current error threshold value of the optical storage system), executing the step S9, otherwise, executing the step S3;

step S3: determining whether the duration period Prd is 1, if the determination is successful (Prd ═ 1), performing step S4, otherwise setting the duration period Prd ═ Prd-1 and performing step S9;

step S4: setting n as 1;

step S5: performing reference current prediction according to the value of n;

step S6: calculating MPC algorithm input value level_new；

Step S7: setting a duration period Prd as n;

step S8: judging MPC algorithm input value level_newWhether the current is in an open interval (-X, X), if the judgment is successful (MPC algorithm input value level)_newIn open interval) then outputs the input value level of the MPC algorithm_newAnd performing step S8, otherwise setting n to n +1 and performing step S5;

step S9: the (pre-set) MPC algorithm is executed.

It should be noted that in step S8, when the level is N +1, X is N/2, and N is the number of bridge arm submodules.

It should be noted that in step S8, when the level is 2N +1, X is N, and N is the number of bridge arm submodules.

Further, step S5 is calculated by using formula (1):

wherein i_d(k) Represents the internal unbalance current at time k; θ represents an angle; i denotes the magnitude of the ac side current vector of the optical storage system.

Further, step S6 is calculated by using formula (2):

wherein i_sjRepresents the ac side current of the optical storage system; u shape_sjRepresenting the ac side voltage of the optical storage system; u shape_dcRepresenting the dc side voltage of the optical storage system.

It should be noted that the technical features such as the MPC algorithm in step S9 related to the present patent application should be regarded as the prior art, and the specific structure, the operation principle, the control mode and the spatial arrangement mode of the technical features may be selected conventionally in the field, and should not be regarded as the invention point of the present patent, and the present patent is not further specifically described in detail.

It will be apparent to those skilled in the art that modifications and equivalents may be made in the embodiments and/or portions thereof without departing from the spirit and scope of the present invention.