A dual energy storage battery energy management method for wind power grid connection plan deviation compensation

Abstract

The present invention relates to the field of wind power generation system control technology, and in particular to a dual energy storage battery energy management method for wind power grid-connected plan deviation compensation, comprising: first, the energy storage is put into operation for the first time, and the SOC initial value is identified using production experimental data and an extended Kalman parameter identification algorithm. Secondly, when the energy storage participates in the wind power grid-connected plan deviation compensation process, the energy storage charge state is managed using the power-time integration method. When the cumulative charging and discharging both meet half of the available total capacity, it is counted as a half-cycle of the energy storage operation, and the total number of current operation cycles of the battery is counted; thirdly, the OCV-SOC curve parameters of the replaced energy storage are identified using an image recognition method to determine the current charge state of the replaced battery. At the same time, the battery is cut out and replaced by another energy storage battery. The present invention can not only ensure the accuracy of the grid-connected wind power plan report, but also avoid major safety accidents caused by overheating of the energy storage battery due to continuous long-term battery life, and has practical engineering application value.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power generation system control, and in particular to a dual energy storage battery energy management method for wind power grid connection plan deviation compensation. Background Art

[0002] As a natural resource, wind energy is clean, abundant and does not produce greenhouse gases, which has led to the accelerated development and utilization of wind energy around the world. As one of the countries with the richest wind energy resources in the world, China attaches great importance to the development and utilization of wind energy and has formed a comprehensive plan from strategic goals to technical routes, development priorities and policy measures.

[0003] In the wind power grid connection plan, the volatility and uncertainty of wind power generation may lead to an imbalance in power supply and demand in the power grid, which in turn causes problems such as grid frequency fluctuations or voltage instability. In order to solve these problems, dual energy storage battery dynamic energy management technology has been proposed and applied to wind power grid connection systems.

[0004] As a flexible energy storage device, energy storage batteries can absorb or release electrical energy when needed to adjust the supply and demand balance of the power grid. By rationally configuring and controlling the energy storage battery system, the impact of wind power volatility can be effectively mitigated. Dynamic energy management technology refers to a method of flexibly dispatching and managing energy storage battery systems based on changes in the real-time status of the power grid and wind farm. By real-time monitoring of wind farm output power, power grid load conditions and other information, the charging and discharging strategies of energy storage batteries are dynamically adjusted to achieve grid frequency and voltage stability.

[0005] In view of the wind power forecast error or the deviation between the actual output of the wind farm and the planned output, it is necessary to design a corresponding compensation strategy. Energy storage batteries can compensate for the volatility of wind power by adjusting their charge and discharge states, so that the actual wind power output can be close to the expected value, thereby ensuring the stability of the power grid.

[0006] Since the SOC of a battery cannot be measured directly, it needs to be obtained indirectly through other parameters and methods. Domestic and foreign researchers have proposed a variety of methods for indirectly obtaining SOC, which are mainly based on the physical properties of the battery, the chemical reaction process, and the data processing capabilities of the battery management system (BMS).

[0007] The discharge experiment method measures the SOC of the battery through the actual discharge process. This method is intuitive but time-consuming and not suitable for frequent monitoring. The open circuit voltage method uses the voltage of the battery in the open circuit state to estimate the SOC. The operation is simple but is greatly affected by temperature. The internal resistance method estimates the SOC by measuring the change in the internal resistance of the battery. This method is relatively complex and requires special instruments. The ampere-hour integration method estimates based on the relationship between the power consumed during the battery discharge process and the SOC. It is suitable for batteries with fewer cycles. Both the linear model method and the neural network algorithm predict the SOC by establishing a mathematical model based on the battery discharge data. Among them, the neural network algorithm is widely used due to its powerful nonlinear fitting ability. The Kalman filter method is a state estimation method based on a dynamic system. It can effectively handle noise interference and is suitable for continuous monitoring systems.

[0008] Due to the volatility and uncertainty of wind farm output power, the battery SOC acquisition method needs to have a fast response capability and be able to obtain the battery SOC information in real time. Accurate SOC estimation is essential to ensure the stability and reliability of energy management. Therefore, the selected method needs to be able to provide high accuracy under different operating conditions. Considering the complexity and variability of the wind farm operating environment, the battery SOC acquisition method needs to have a certain degree of adaptability and be applicable to different types of wind farms and energy storage systems. In the wind power grid-connected system, based on the current integration method, combined with wind farm prediction data and real-time monitoring data, an improved integration algorithm is used to estimate the battery SOC. By considering the prediction error of the wind farm output power, the integration parameters are adjusted in real time to improve the accuracy of SOC estimation. Summary of the invention

[0009] The purpose of the present invention is to solve the shortcomings existing in the prior art, and proposes a dual energy storage battery energy management method for wind power grid connection plan deviation compensation, which realizes an offline SOC estimation method by establishing a standard for the working rotation of dual energy storage batteries, solves the problem that dynamic open circuit voltage measurement is difficult to measure online, realizes dynamic management of battery energy, effectively prolongs battery life, and meets the requirements of accurate wind farm forecasting.

[0010] In order to achieve the above object, the present invention adopts the following technical solutions:

[0011] A dual energy storage battery energy management method for wind power grid connection plan deviation compensation, the specific steps are as follows:

[0012] Step 1: Dual battery energy management adopts a combination of online statistics and offline parameter identification. First, the complete cycle open circuit voltage OCV-state of charge SOC curve cluster is obtained by combining the complete life cycle experimental parameters provided by the energy storage battery when it leaves the factory. The curve cluster is used to identify different cycle operation curves using image recognition software; each curve in the curve cluster corresponds to the relationship between the battery open circuit voltage OCV and the state of charge SOC during a complete charge and discharge cycle process, which is used for subsequent parameter estimation;

[0013] Step 2: Test the open circuit voltage (OCV) of the energy storage to be put into use, determine the initial state of charge (SOC) of the battery by the extended Kalman filter parameter identification method, and then dynamically manage the battery state of charge (SOC) based on the deviation data between the actual wind power sampled each time and the plan. When the cumulative charge and discharge capacity reaches half of the total available capacity, it is counted as half a cycle, and the total number of operating cycles is counted. At the same time, the battery group is cut out and another battery group is rotated to serve;

[0014] Step 3: For the replaced battery, combined with the current service cycle number m, find the numerical matrix corresponding to the SOC-OCV of the mth cycle, test the open circuit voltage OCV after half an hour of rest, and obtain the state of charge SOC value corresponding to the open circuit voltage OCV through this cycle curve parameter matrix, and then adjust the energy storage battery state of charge SOC to 50% of the available power in this cycle, and then wait for the next access to the system to work.

[0015] Preferably, in step 2, the following steps are included:

[0016] Step 2-1: When the wind power plan deviation is greater than 0, the energy storage system discharges; when the wind power plan deviation is less than 0, the energy storage system charges; the total amount of charging and discharging power is the product of the deviation power and the sampling period, and the charging and discharging power is counted separately;

[0017] Step 2-2: Given that there is a slight difference in the actual wind power before and after each sampling period, the average power of the period is used as the statistical data source to calculate the energy storage charge and discharge capacity;

[0018] Step 2-3: Consider the operating temperature effect of the energy storage system and combine it with temperature monitoring. When the temperature is too high, consider a flexible cut-out mechanism. If it is less than 0.5 cycles, it can be cut out at any cycle.

[0019] Preferably, in step 3, the following steps are included:

[0020] Step 3-1: Considering that the battery shows a decline trend with the number of cycles, the current energy storage state of charge SOC is obtained offline, and then connected to the grid to adjust the current state of charge SOC to 0.5, which is half of the available capacity of the current cycle. The state of charge SOC measurement method is the ampere-hour integration method;

[0021] Step 3-2: The dual battery rotation mechanism ensures that the usage cycles are basically the same and they can be reconnected in parallel if necessary.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] 1. The present invention can avoid major accidents caused by overheating and protect battery health by using dual energy storage to effectively manage wind power plan deviations.

[0024] 2. The present invention combines online statistics of the dual energy storage system with offline parameter identification, making energy management data more accurate and preventing the wind power grid connection plan from being effectively compensated and suffering electricity price penalties due to unreliable energy storage capacity.

[0025] 3. The present invention utilizes the battery SOC-OCV curves of different cycle periods to find the SOC under a specific OCV, thereby providing a basis for offline battery energy adjustment. Batteries 1 and 2 are replaced at the end of each working cycle, which is conducive to parameter comparison and early maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a schematic diagram of the process of the present invention;

[0027] Figure 2 Embedding real-time correction hardware connection diagram for wind power energy storage in the present invention;

[0028] Figure 3 The SOC-OCV curve corresponding to the m-cycle period retrieved by image recognition in the present invention;

[0029] Figure 4 It is a curve diagram obtained by fitting the SOC-OCV curve of m cycles retrieved in the present invention. DETAILED DESCRIPTION

[0030] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings, so that those skilled in the art can better understand the advantages and features of the present invention, thereby making a clearer definition of the protection scope of the present invention. The embodiments described in the present invention are only a part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present invention.

[0031] like Figure 1 As shown, a dual energy storage battery energy management method for wind power grid connection plan deviation compensation, the specific steps are as follows:

[0032] Step 1: Dual battery energy management adopts a combination of online statistics and offline parameter identification. First, the complete cycle open circuit voltage OCV-state of charge SOC curve cluster is obtained by combining the complete life cycle experimental parameters provided by the energy storage battery when it leaves the factory. The curve cluster is used to identify different cycle operation curves using image recognition software; each curve in the curve cluster corresponds to the relationship between the battery open circuit voltage OCV and the state of charge SOC during a complete charge and discharge cycle process, which is used for subsequent parameter estimation;

[0033] Step 2: Test the open circuit voltage (OCV) of the energy storage to be put into use, determine the initial state of charge (SOC) of the battery by the extended Kalman filter parameter identification method, and then dynamically manage the battery state of charge (SOC) based on the deviation data between the actual wind power sampled each time and the plan. When the cumulative charge and discharge capacity reaches half of the total available capacity, it is counted as half a cycle, and the total number of operating cycles is counted. At the same time, the battery group is cut out and another battery group is rotated to serve;

[0034] Step 3: For the replaced battery, combined with the current service cycle number m, find the numerical matrix corresponding to the SOC-OCV of the mth cycle, test the open circuit voltage OCV after half an hour of rest, and obtain the state of charge SOC value corresponding to the open circuit voltage OCV through this cycle curve parameter matrix, and then adjust the energy storage battery state of charge SOC to 50% of the available power in this cycle, and then wait for the next access to the system to work.

[0035] Specifically, in step 2, the following steps are included:

[0036] Step 2-1: When the wind power plan deviation is greater than 0, the energy storage system discharges; when the wind power plan deviation is less than 0, the energy storage system charges; the total amount of charging and discharging power is the product of the deviation power and the sampling period, and the charging and discharging power is counted separately;

[0037] Step 2-2: Given that there is a slight difference in the actual wind power before and after each sampling period, the average power of the period is used as the statistical data source to calculate the energy storage charge and discharge capacity;

[0038] Step 2-3: Consider the operating temperature effect of the energy storage system and combine it with temperature monitoring. When the temperature is too high, consider a flexible cut-out mechanism. If it is less than 0.5 cycles, it can be cut out at any cycle.

[0039] Specifically, in step 3, the following steps are included:

[0040] Step 3-1: Considering that the battery shows a decline trend with the number of cycles, the current energy storage state of charge SOC is obtained offline, and then connected to the grid to adjust the current state of charge SOC to 0.5, which is half of the available capacity of the current cycle. The state of charge SOC measurement method is the ampere-hour integration method;

[0041] Step 3-2: The dual battery rotation mechanism ensures that the usage cycles are basically the same and they can be reconnected in parallel if necessary.

[0042] Example:

[0043] like Figure 2 As shown in the simulation physical wiring diagram of the wind power grid-connected system, the energy storage battery is already in working condition and performs deviation compensation: when the wind power plan deviation is greater than 0, the energy storage system discharges; when the wind power plan deviation is less than 0, the energy storage system charges.

[0044] like Figure 3 As shown, firstly, the complete cycle open circuit voltage OCV-state of charge SOC curve cluster is obtained by combining the complete life cycle experimental parameters provided by the energy storage battery at the factory. The curve cluster is used to identify different cycle operation curves using image recognition software. Each curve in the curve cluster corresponds to the relationship between the battery open circuit voltage OCV and the state of charge SOC during a complete charge and discharge cycle. The order of curve fitting is 3, and the fitting function is y=-0.0001x 3 +0.04x 2 -5.1118x, used for subsequent parameter estimation.

[0045] like Figure 4 As shown, after standing for 0.5h, the voltage and current of the replaced battery are tested for a period of time, and the SOC-OCV curve is obtained by the ampere-hour integration method, and the function curve is fitted. Figure 3 Identify the curve and Figure 4 Curve, the SOC corresponding to the same open circuit voltage OCV is different. By adjusting the battery capacity so that the battery meets the initial capacity of 0.5, it enters the standby state and prepares for the next replacement work.

[0046] In this embodiment, the error between the wind power forecast and the actual sampled power in 15 minutes is used to estimate the electric energy that the battery needs to store or release in the cycle, and the change in the battery's state of charge is estimated. When the cycle is completed, the battery is switched out of the working state to protect the battery health.

[0047] When the battery dynamically corrects the predicted power error, the charging and discharging energy are dynamically counted in real time, and the number of battery charge and discharge cycles is counted;

[0048] By using the different SOC-OCV curves corresponding to batteries in different cycle periods, we can find the ideal SOC corresponding to the OCV, so as to adjust the battery energy offline. Replacing batteries 1 and 2 in each working cycle is conducive to timely and early maintenance and reduce the adverse effects of forecast correction work.

[0049] In summary, the present invention can ensure the accuracy of the reported grid-connected wind power plan, and at the same time avoid major safety accidents caused by overheating of the energy storage battery due to continuous long-term operation, and has practical engineering application value.

[0050] The description and practice disclosed in the present invention are easy to think and understand for ordinary technicians in the technical field, and several improvements and modifications can be made without departing from the principles of the present invention. Therefore, modifications or improvements made without departing from the spirit of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A dual energy storage battery energy management method for wind power grid connection plan deviation compensation, characterized in that: The specific steps are as follows: Step 1: Dual battery energy management adopts a combination of online statistics and offline parameter identification. First, the complete life cycle experimental parameters provided by the energy storage battery at the factory are combined to obtain the complete cycle open circuit voltage OCV-state of charge SOC curve cluster. The curve cluster is identified by image recognition software for different cycle operation curves. Each curve in the curve cluster corresponds to the relationship between the battery open circuit voltage OCV and the state of charge SOC during a complete charge and discharge cycle, which is used for subsequent parameter estimation; Step 2: Test the open circuit voltage (OCV) of the energy storage to be put into use, determine the initial state of charge (SOC) of the battery by the extended Kalman filter parameter identification method, and then dynamically manage the battery state of charge (SOC) based on the deviation data between the actual wind power sampled each time and the plan. When the cumulative charge and discharge capacity reaches half of the total available capacity, it is counted as half a cycle, and the total number of operating cycles is counted. At the same time, the battery group is cut out and another battery group is rotated to serve; Step 3: For the replaced battery, combined with the current service cycle number m, find the numerical matrix corresponding to the SOC-OCV of the mth cycle, test the open circuit voltage OCV after half an hour of rest, and obtain the state of charge SOC value corresponding to the open circuit voltage OCV through this cycle curve parameter matrix, then connect to the grid and adjust the energy storage battery state of charge SOC to 50% of the available power in this cycle, and then wait for the next access to the system to work.

2. A dual energy storage battery energy management method for wind power grid connection plan deviation compensation according to claim 1, characterized in that: In step 2, the following steps are included: Step 2-1: When the wind power plan deviation is greater than 0, the energy storage system discharges; when the wind power plan deviation is less than 0, the energy storage system charges; the total amount of charging and discharging power is the product of the deviation power and the sampling period, and the charging and discharging power is counted separately; Step 2-2: Given that there is a slight difference in the actual wind power before and after each sampling period, the average power in the time period is used as the statistical data source to calculate the energy storage charge and discharge capacity; Step 2-3: Consider the operating temperature effect of the energy storage system and combine it with temperature monitoring. When the temperature is too high, consider a flexible cut-out mechanism. If it is less than 0.5 cycles, cut out at any cycle.

3. A dual energy storage battery energy management method for wind power grid connection plan deviation compensation according to claim 1, characterized in that: In step 3, the following steps are included: Step 3-1: Considering that the battery shows a decline trend with the number of cycles, the current energy storage state of charge SOC is obtained offline, and then connected to the grid to adjust the current state of charge SOC to 0.5, which is half of the available capacity of the current cycle. The state of charge SOC measurement method is the ampere-hour integration method; Step 3-2: The dual battery rotation mechanism ensures that the usage cycles are basically the same, and they can be reconnected in parallel for use when necessary.

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