CN-122000903-A - Wind power fluctuation stabilizing method for improving rain flow counting method

Abstract

The invention relates to a wind power fluctuation stabilizing method for improving a rain flow counting method, and belongs to the technical field of wind power. The method comprises the following steps of (1) designing an improved raccoon optimization algorithm, (2) optimizing a global optimal stress threshold of a rain flow counting method by utilizing the improved raccoon optimization algorithm, (3) extracting wind power characteristic data points representing wind power output based on the global optimal stress threshold, (4) carrying out Lagrange interpolation processing on the data points to obtain wind power characteristic trend, (5) distributing deviation between wind power and the characteristic trend to BESS, and distributing the deviation to internal battery units by the BESS and enabling the battery units to respond. The invention effectively stabilizes wind power fluctuation, reduces the switching times of the charge and discharge states of the battery units, thereby reducing the service life loss of the BESS, ensuring the charge state balance of the battery units, and improving the sustainable regulation and control capability of the BESS.

Inventors

• QUAN LI
• WANG XIN
• WANG JIE
• LIU XINYUE
• LIU ZIMO
• Wu Haodai
• MENG DEFANG
• ZHANG CHENG
• GAO LISHUAI
• SUN JIAHUI
• LI ZHUANG
• GAO PENG
• LIU LIJIE
• YANG MANMAN
• ZHANG WANMING
• ZHANG XINLIANG
• Xi Haikuo
• MIAO HONGYING
• CHEN SIQI
• HE YUXIN
• ZHOU YONGJUN
• QI DAWEI
• DU WEIWEI
• GUO JIANFENG
• CHEN DONGYANG
• YU WENHAO
• YU DE
• ZHU JIALI

Assignees

• 国网冀北电力有限公司承德供电公司

Dates

Publication Date

20260508

Application Date

20260119

Claims (6)

1. 1. A wind power fluctuation stabilizing method for improving a rain flow counting method is characterized by comprising the following steps of: (1) Designing an improved raccoon optimization algorithm, designing a position update formula of a local development stage based on an exponential function, and improving optimizing precision; (2) Obtaining wind power P w , and optimizing a global optimal stress threshold E of a rain flow counting method by using an improved raccoon optimization algorithm; (3) Based on the global optimal stress threshold E, processing the P w by using a rain flow counting method again, so as to extract the characteristic moment representing the wind power and the corresponding power data point; (4) Performing interpolation processing on the wind power characteristic data points by adopting a Lagrangian interpolation method to obtain a wind power characteristic trend P f ; (5) The power offset P d between P w and P f is calculated and P d is assigned to the battery energy storage system, which assigns the offset to the internal battery cell and allows the battery cell to respond.
2. 2. The method for stabilizing wind power fluctuation by improving a rain flow counting method according to claim 1, wherein the partial development stage in the step (1) has a position update formula as follows: ; in the formula, And Respectively representing the position of the ith optimizing individual in the jth dimensional space in the nth+1th iteration and the nth iteration, wherein r is a random number between [0,1], And The upper and lower limits of the optimizing individual position are respectively set, e is a natural constant, and the size of e is 2.718.
3. 3. The method for stabilizing wind power fluctuations based on improved rain flow counting according to claim 1, wherein said step (2) utilizes an improved raccoon optimization algorithm to optimize a global optimal stress threshold E in the rain flow counting, wherein the cost function is as follows: ; Wherein: And Standard deviation and compression ratio respectively representing characteristic trend of wind power, And Respectively the maximum value and the minimum value of the standard deviation of the characteristic trend of the wind power, And Respectively the maximum and minimum of the compression ratio, The number of samples to be taken as a total, In order to be a sample data value, To interpolate the feature data points to obtain feature trend values, To the number of feature data points extracted.
4. 4. The method for stabilizing wind power fluctuation by improving a rain flow counting method according to claim 1, wherein in the step (3), the wind power P w is processed again by using the rain flow counting method in combination with the global optimal stress threshold E obtained by optimization in the step (2), so that characteristic moments and corresponding power data points which can represent wind power are extracted.
5. 5. The method for stabilizing wind power fluctuation by improving a rain flow counting method according to claim 1, wherein in the step (4), based on the characteristic time of wind power obtained in the step (3) and corresponding power data points, interpolation processing is performed on the wind power characteristic data points by using a Lagrange interpolation method, so as to obtain a wind power characteristic trend P f capable of representing wind power output.
6. 6. The method for stabilizing wind power fluctuation by improving a rain flow counting method according to claim 1, wherein in the step (5), based on the wind power characteristic trend P f obtained in the step (4), a power deviation P d between the wind power P w and the characteristic trend P f is calculated, and P d is allocated to a battery energy storage system, and the battery energy storage system further allocates the deviation P d to an internal battery unit according to the SOC uniformity power allocation method and allows the battery unit to respond.

Description

Wind power fluctuation stabilizing method for improving rain flow counting method Technical Field The invention relates to a wind power fluctuation stabilizing method for improving a rain flow counting method, and belongs to the technical field of wind power. Background Wind energy has received high-speed attention as a clean renewable energy source. With the proposal of the 'double carbon' target, wind power is connected into a power grid in a larger scale. However, due to the influence of natural factors such as wind speed, the output power of the wind power plant has randomness and intermittence, so that the grid-connected power fluctuation of the wind power plant is large, and the safe and stable operation of the power grid is seriously adversely affected. Therefore, how to effectively balance the fluctuation of the output power of the wind power plant so as to reduce the influence of the output power on a power system is a problem to be solved. The battery energy storage system (battery energy storage system, BESS) is called BESS for short, has rapid charge and discharge characteristics, can realize energy transfer in time and space, and is an important means for assisting wind power grid connection at present. However, if the BESS does not adopt a reasonable control strategy, the battery unit can be caused to perform irregular action, so that a stabilizing effect is not achieved, fluctuation of grid-connected power is aggravated, and the operation performance of the system is deteriorated. In addition, the irregular action of the BESS also causes the increase of the switching times of the charge and discharge states of the battery units in the BESS and the poor equalization of the charge States (SOC), thereby increasing the service life loss of the BESS and reducing the sustainable regulation and control capability of the BESS. Therefore, a control strategy for stabilizing wind power fluctuation of a battery energy storage system with reasonable design is needed, the running life loss of the BESS is reduced while the wind power grid-connected power fluctuation is effectively reduced, and the sustainable regulation and control capability of the BESS is improved. Disclosure of Invention The invention provides a wind power fluctuation stabilizing method for improving a rain flow counting method, which reduces the fluctuation of grid-connected power of a wind power plant, enables the wind power to be safely and stably integrated into a power grid, ensures that the SOC of battery units tends to be consistent in the running process of BESS, improves the sustainable regulation capability of the BESS, designs an improved raccoon optimization algorithm based on the improved raccoon optimization algorithm, and combines a Lagrange interpolation method to extract the characteristic trend of the wind power representing wind power output. The technical scheme of the invention is as follows: a wind power fluctuation stabilizing method for improving a rain flow counting method comprises the following steps: (1) Designing an improved raccoon optimization algorithm, designing a position update formula of a local development stage based on an exponential function, and improving optimizing precision; (2) Obtaining wind power P w, and optimizing a global optimal stress threshold E of a rain flow counting method by using an improved raccoon optimization algorithm; (3) Based on the global optimal stress threshold E, processing the P w by using a rain flow counting method again, so as to extract the characteristic moment representing the wind power and the corresponding power data point; (4) Performing interpolation processing on the wind power characteristic data points by adopting a Lagrangian interpolation method to obtain a wind power characteristic trend P f; (5) The power offset P d between P w and P f is calculated and P d is assigned to the battery energy storage system, which assigns the offset to the internal battery cell and allows the battery cell to respond. The location update formula of the local development stage in the step (1) is as follows: in the formula, AndRespectively representing the position of the ith optimizing individual in the jth dimensional space in the nth+1th iteration and the nth iteration, wherein r is a random number between [0,1],AndThe upper and lower limits of the optimizing individual position are respectively set, e is a natural constant, and the size of e is 2.718. The use of step (2) of the modified raccoon optimization algorithm optimizes the global optimal stress threshold E in the rain flow count method, wherein the cost function is as follows: Wherein: And Standard deviation and compression ratio respectively representing characteristic trend of wind power,AndRespectively the maximum value and the minimum value of the standard deviation of the characteristic trend of the wind power,AndRespectively the maximum and minimum of the compression ratio,The number of samples to be take