Output power allocation method of hybrid energy storage system based on edge charge control coefficient

Abstract

The present invention discloses a hybrid energy storage system output power distribution method based on a marginal charge control coefficient. Based on the marginal charge control coefficient of the energy-type energy storage system, the output distribution of the hybrid energy storage system is adjusted according to whether it exceeds a threshold, and the filter coefficient is adjusted according to the new state of charge. This method utilizes the fact that the operating life of energy-type energy storage is closely related to its state of charge. By limiting the state of charge of the hybrid energy storage during energy distribution, power output adjustment is achieved. This method does not require additional control variables and can ensure safe and stable operation of the system under balanced state of charge conditions.

Description

Technical Field

[0001] The present invention relates to energy storage technology in the field of renewable energy, and in particular to a method for real-time output power distribution of a hybrid energy storage system based on an edge charge control coefficient for an offshore wind farm. Background Art

[0002] As a key source of renewable energy, the stability and efficiency of offshore wind farms are crucial to the reliable operation of the power grid. However, the intermittent and unpredictable nature of wind energy presents numerous challenges for offshore wind farm energy management. The volatility of wind power output makes it difficult for the power grid to maintain a stable power supply even when wind speeds vary widely. Therefore, effectively managing wind power output and smoothing fluctuations are key to improving the operational efficiency of offshore wind farms.

[0003] To address this challenge, energy storage systems are widely used as a key supporting technology for wind power systems. They can store excess wind energy when the wind is strong, preventing energy waste, and release the stored energy when the wind is weak, thereby balancing the supply and demand of the power grid.

[0004] Existing energy storage technologies can be roughly divided into two categories: energy storage and power storage. Energy storage systems are mainly used for long-term energy storage to provide continuous energy output, while power storage systems are used for short-term high-power output to cope with instantaneous changes in grid load. Although these two types of energy storage systems each have certain advantages, they lack flexibility in dealing with wind power fluctuations, cannot meet the needs of different time scales at the same time, and are difficult to optimize the overall efficiency of the energy storage system when smoothing wind power fluctuations. In hybrid energy storage systems, existing energy storage system energy distribution schemes are often based on predetermined rules or experience, and lack sufficient consideration of the real-time dynamic characteristics of the system. In hybrid energy storage systems, the coordinated work and power distribution of different types of energy storage units usually rely on simple rules or timetables, which makes it difficult to provide efficient and real-time energy scheduling when wind speed changes greatly and load demand fluctuates.

[0005] Therefore, how to achieve dynamic and automatic adjustment and scheduling between different types of energy storage units and ensure system stability and improve efficiency is a key issue in the optimization of hybrid energy storage systems. Summary of the Invention

[0006] The purpose of the present invention is to provide a hybrid energy storage system output power distribution method based on the edge charge control coefficient, aiming to solve the defects in the existing technology, and can distribute the output power of the hybrid energy storage system in real time, cope with the complex, nonlinear and dynamically changing wind power output, reasonably distribute the output power of energy-type and power-type energy storage, smooth out wind power fluctuations, effectively extend the service life of energy storage equipment, and ensure that the charge states of different energy storage devices work together under safe and balanced conditions to achieve efficient operation of offshore wind power systems.

[0007] In order to achieve the above-mentioned object of the invention, the present invention adopts the following technical solutions:

[0008] The output power distribution method of the hybrid energy storage system based on the edge charge control coefficient, the hybrid energy storage system includes an energy type energy storage system and a power type energy storage system, characterized in that: the output power distribution method is based on the hybrid energy storage system power at the sampling time , filter coefficient c(t) and edge charge control coefficient k(t) of the energy-type energy storage system, and determine the output power distribution of the energy-type energy storage system and the power-type energy storage system in real time, where t is the sampling time;

[0009] , and They represent the upper and lower limits of the state of charge of the energy storage system respectively; Represents the state of charge of the energy storage system at the sampling moment;

[0010] And according to the determined output power distribution, the charge state of the energy-type energy storage system and the power-type energy storage system is recalculated. If the charge state is within the set upper and lower limits, the current output power distribution is kept unchanged and the distribution result is output. Otherwise, the charge state of the energy-type energy storage system is recalculated, and the edge charge control coefficient is recalculated. The edge charge control coefficient k(t) of the energy-type energy storage system is iterated using the recalculated edge charge control coefficient, and the filter coefficient is recalculated. The filter coefficient c(t) is iterated using the recalculated filter coefficient to redetermine the output power distribution of the energy-type energy storage system and the power-type energy storage system until the charge state of the energy-type energy storage system and the power-type energy storage system are both within the set upper and lower limits.

[0011] On the basis of adopting the above technical solutions, the present invention may also adopt the following further technical solutions, or use these further technical solutions in combination:

[0012] The hybrid energy storage system output power distribution method comprises the following steps:

[0013] (1) Calculate the edge charge control coefficient k(t) and compare it with the edge charge control coefficient threshold k*. When the k(t) value is less than or equal to k*, the energy storage system triggers the attenuation mechanism and the attenuation coefficient ; When the value of k(t) is greater than k*, the attenuation coefficient b(t) =1, full power output of energy storage system;

[0014] The output power allocated to the energy storage system at the sampling time Calculate the sampling time value of the filter coefficient used in the first-order filter algorithm, and calculate the power of the hybrid energy storage system With the output power Obtain the output power allocated to the power type energy storage system at the sampling time ,in, ;

[0015] (2) After determining the output power distribution of the energy storage system and the power storage system, the state of charge of the energy storage system and the power storage system are calculated in real time. If the state of charge is within the set upper and lower limits, the current output power distribution ratio is kept unchanged and the distribution result is output; if the state of charge of the energy storage system and / or the state of charge of the power storage system exceeds its upper and lower limits, the marginal charge control coefficient is recalculated using the recalculated state of charge of the energy storage system, and the filter coefficient is recalculated based on the recalculated marginal charge control coefficient. The filter coefficient value c(t) obtained by recalculation is iterated using the recalculated filter coefficient to recalculate the output power allocated to the energy storage system, and the output power allocated to the energy storage system at the sampling moment in step (1) is replaced by the recalculated output power. , return to step (1).

[0016] Recalculate the filter coefficient using the following formula: , c'(t) is the filtering coefficient at the iterated sampling moment.

[0017] The following formula is used to calculate the output power allocated to the energy storage system: , t-1 is the previous sampling time of sampling time t.

[0018] The k*=0.5.

[0019] Before output power distribution is performed, the filter coefficients in the first-order filter algorithm in the output power distribution of the hybrid energy storage system are initialized.

[0020] Before distributing the output power of the hybrid energy storage system, obtain the value.

[0021] Due to the adoption of the technical solution of the present invention, the beneficial effects of the present invention are:

[0022] Traditional scheduling strategies don't specifically monitor the state of charge (SOC) of energy storage units, failing to ensure safe and stable operation of the hybrid energy storage system's output. This invention leverages the close relationship between the operation of energy storage units and their SOC. By limiting the SOC during energy distribution within the hybrid energy storage system, power output can be adjusted. This eliminates the need for additional control variables and ensures safe and stable system operation under balanced SOC conditions.

[0023] In order to make the above and other objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 is a flow chart of the present invention;

[0025] Figure 2 It is the power that the offshore wind farm in the example of the present invention needs to bear after low-pass filtering within 30 minutes by the hybrid energy storage;

[0026] Figure 3 The real-time power distribution of the energy storage system in the hybrid energy storage system within 30 minutes after the method of the present invention is adopted;

[0027] Figure 4 This is the real-time power distribution of the power-type energy storage system in the hybrid energy storage system within 30 minutes after adopting the method of the present invention.

[0028] Figure 5 This is the SOC change of the energy-type energy storage system in the hybrid energy storage system within 30 minutes after adopting the method of the present invention.

[0029] Figure 6 This is the SOC change of the power type energy storage system in the hybrid energy storage system within 30 minutes after adopting the method of the present invention. DETAILED DESCRIPTION

[0030] In one embodiment of the present invention, for an offshore wind power-hybrid energy storage system consisting of a power-type energy storage system and an energy-type energy storage system, the following steps are performed to optimize the hybrid energy storage system, wherein in this example, the power-type energy storage adopts supercapacitors and the energy-type energy storage adopts battery energy storage;

[0031] Reference Figure 1 The output power distribution method of the hybrid energy storage system based on the edge charge control coefficient provided by the present invention includes the following steps:

[0032] (1) Calculate the edge charge control coefficient k(t) and compare it with the edge charge control coefficient threshold k*. The optimal value of k* is 0.5. When the k(t) value is less than or equal to k*, the energy storage system triggers the attenuation mechanism, and the attenuation coefficient ; When the value of k(t) is greater than k*, the attenuation coefficient b(t) =1, the energy storage system is at full power output; k(t) is calculated using the following method:

[0033] , t is the sampling time; and They represent the upper and lower limits of the state of charge of the energy storage system respectively; The state of charge of the energy storage system at the sampling time is calculated using the following formula:

[0034] , is the initial charge number in the energy storage system, 、 Represent the charging and discharging efficiency of the energy storage system respectively, 、 are the charging and discharging power of the energy storage system, is the rated charge of the energy storage system. This formula is also applicable to the calculation of the state of charge of the power storage system.

[0035] For power-type energy storage systems and energy-type energy storage systems, the state of charge calculation and constraints are:

[0036]

[0037] The subscript B indicates an energy-type energy storage system, the subscript SC indicates a power-type energy storage system, the subscripts ch and dis indicate the charging process and the discharging process respectively; the superscripts min and max indicate the lower and upper limits respectively; SOC indicates the state of charge, t indicates the sampling time, and P indicates the power. 、 Represents the rated charge of energy-type energy storage system and power-type energy storage system respectively. This calculation process fully considers the power output fluctuation of the wind farm and the dynamic characteristics of the energy storage system, such as the charging and discharging efficiency of the battery and the rated energy and power;

[0038] The output power allocated to the energy storage system at the sampling time Calculate the sampling time value of the filter coefficient used in the first-order filter algorithm, and calculate the power of the hybrid energy storage system With the output power Obtain the output power allocated to the power type energy storage system at the sampling time ,in, .

[0039] in, Obtained based on the hybrid energy storage system's ability to smooth fluctuations. For any sampling time t, the total output power is arranged as a fixed value through the scheduling plan , which consists of: The real-time total output power of the offshore wind power system can be obtained by filtering the offshore wind power system using the first-order filtering method. Real-time output power of offshore wind power The relationship is , where c1 is the filter coefficient for smoothing wind farm fluctuations at the sampling moment, and t-1 is the previous sampling moment. Therefore, for any sampling moment t, the real-time power of the hybrid energy storage can be obtained by At the same time, the low-pass filtering algorithm is used, that is, , calculate the output power allocated to the energy storage system at sampling time t, where t-1 is the sampling time before sampling time t. When calculating the output power allocated to the energy storage system for the first time at each sampling time, b(t) can be set to an initial value based on experience, such as 0.5.

[0040] The filter coefficient of the hybrid energy storage system needs to be initialized. The initial value is any value between 0 and 1. The power required by the energy storage system after initialization is obtained. , subsequently, the initial value of the filter coefficient at each sampling moment first adopts the filter coefficient value at the previous sampling moment or the filter coefficient value after iteration.

[0041] (2) After determining the output power distribution of the energy storage system and the power storage system, the state of charge of the energy storage system and the power storage system are calculated in real time. If the state of charge is within the set upper and lower limits, the current output power distribution ratio is kept unchanged and the distribution result is output; if the state of charge of the energy storage system and / or the state of charge of the power storage system exceeds its upper and lower limits, the marginal charge control coefficient is recalculated using the recalculated state of charge of the energy storage system, and the filter coefficient is recalculated based on the recalculated marginal charge control coefficient. The filter coefficient value c(t) is iterated using the recalculated filter coefficient, and the filter coefficient value c(t) is recalculated based on the formula Calculate the output power allocated to the energy storage system, and replace the output power allocated to the energy storage system at the sampling time in step (1) with the recalculated output power , return to step (1).

[0042] Recalculate the filter coefficient using the following formula: , c'(t) is the filtering coefficient at the iterated sampling moment.

[0043] The following combination Figure 2-Figure 6 The present invention is further described with reference to the accompanying drawings and examples.

[0044] Figure 2 This figure shows the power distribution required of the hybrid energy storage system for a 12MW offshore wind farm over a 30-minute period, after low-pass filtering. The low-pass filter removes high-frequency fluctuations in wind power output and smoothes the wind power curve. This figure demonstrates that during periods of significant wind power fluctuations, the energy storage system must respond quickly to maintain grid stability. This smoothing process reduces the impact of wind power fluctuations on the grid and ensures optimal power dispatch for the energy storage system.

[0045] Figure 3 This demonstration demonstrates the power distribution of the energy storage system (battery) within a hybrid energy storage system over a 30-minute period using the method of this invention. The battery maintains relative stability throughout this process, with minimal frequent starts and stops. The long duration of each power cycle indicates that the battery primarily handles medium- to long-term power regulation, ensuring sufficient energy supply during peak demand. By gradually discharging and recharging, the battery balances the wind farm's output fluctuations while avoiding frequent charging and discharging operations, thereby extending the battery's lifespan.

[0046] Figure 4 This demonstrates the real-time power distribution of the power-type energy storage system (supercapacitor) within a hybrid energy storage system over a 30-minute period after adopting the method of the present invention. Unlike batteries, supercapacitors are primarily designed to quickly respond to high-frequency fluctuations in wind farm power, and therefore exhibit significant frequent starts and stops. Through this high-frequency on-off operation, supercapacitors can quickly suppress the high-frequency components of wind power output, thereby achieving grid stability. However, excessive starts and stops can increase wear and tear on equipment, so the supercapacitor's charge and discharge strategy needs to be properly controlled during design to ensure system stability and equipment life.

[0047] Figure 5 and Figure 6 The graphs show the state of charge (SOC) changes for an energy-based energy storage system (battery) and a power-based energy storage system (supercapacitor) using the method of the present invention. The upper and lower lines in the graph represent the minimum and maximum SOC values, respectively, demonstrating that each storage system maintains its SOC limit. The waveforms also reveal that the fluctuations in battery energy storage (energy-based energy storage system) are much lower than those in supercapacitor energy storage (power-based energy storage system), meeting the requirements for high- and low-frequency power distribution.

[0048] In summary, the technical solution of the present invention utilizes the different state of charge characteristics of energy-type energy storage and power-type energy storage to achieve real-time allocation of a hybrid energy storage system based on edge control of the energy-type energy storage state of charge. At the same time, no additional control quantity is required, and the system can be ensured to operate safely and stably under SOC equilibrium conditions.

[0049] Note that the above are only preferred embodiments of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments, and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments and may include many other equivalent embodiments without departing from the concept of the present invention. The scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for distributing output power of a hybrid energy storage system based on an edge charge control coefficient, wherein the hybrid energy storage system includes an energy-type energy storage system and a power-type energy storage system, and is characterized in that: The output power distribution method is based on the hybrid energy storage system power P at the sampling time. HESS (t), the filter coefficient c(t) and the edge charge control coefficient k(t) of the energy-type energy storage system are used to determine the output power distribution of the energy-type energy storage system and the power-type energy storage system in real time, where t is the sampling time; and Respectively represent the upper and lower limits of the state of charge of the energy storage system; SOC B (t) represents the state of charge of the energy storage system at the sampling moment; And according to the determined output power distribution, the charge state of the energy type energy storage system and the power type energy storage system is recalculated. If the charge state is within the set upper and lower limits, the current output power distribution is kept unchanged and the distribution result is output. Otherwise, the charge state of the energy type energy storage system is recalculated, and the edge charge control coefficient is recalculated. The edge charge control coefficient k(t) of the energy type energy storage system is iterated using the recalculated edge charge control coefficient, and the filter coefficient is recalculated. The filter coefficient c(t) is iterated using the recalculated filter coefficient to re-determine the output power distribution of the energy type energy storage system and the power type energy storage system until the charge state of the energy type energy storage system and the power type energy storage system are both within the set upper and lower limits. The hybrid energy storage system output power distribution method comprises the following steps: (1) Calculate the edge charge control coefficient k(t) and compare it with the edge charge control coefficient threshold k*. When the value of k(t) is less than or equal to k*, the energy storage system triggers the attenuation mechanism, and the attenuation coefficient b(t) = k(t)(1-k(t)); when the value of k(t) is greater than k*, the attenuation coefficient b(t) = 1, and the energy storage system outputs full power. The output power P allocated to the energy storage system at the sampling time B (t) is calculated based on the sampling time value of the filter coefficient used in the first-order filter algorithm, and the power P of the hybrid energy storage system is calculated based on the sampling time value of the filter coefficient used in the first-order filter algorithm. HESS (t) and the output power P B (t) Obtain the output power P allocated to the power type energy storage system at the sampling time SC (t), where P SC (t) = P HESS (t)-P B (t); (2) After determining the output power distribution of the energy storage system and the power storage system, the state of charge of the energy storage system and the power storage system are calculated in real time. If the state of charge is within the set upper and lower limits, the current output power distribution ratio is kept unchanged and the distribution result is output; if the state of charge of the energy storage system and / or the state of charge of the power storage system exceeds its upper and lower limits, the marginal charge control coefficient is recalculated using the recalculated state of charge of the energy storage system, and the filter coefficient is recalculated based on the recalculated marginal charge control coefficient. The filter coefficient value c(t) obtained by recalculation is iterated using the recalculated filter coefficient to recalculate the output power allocated to the energy storage system, and the output power P allocated to the energy storage system at the sampling moment in step (1) is replaced by the recalculated output power. B (t), return to step (1); The filter coefficient is recalculated using the following formula: c(t) = (1-k(t) 2 )c'(t), c'(t) is the filtering coefficient at the sampling moment being iterated; the output power allocated to the energy storage system is calculated using the following formula: P B (t) = b(t)·(1-c(t))·P B (t-1)+b(t)·c(t)·P HESS (t), t-1 is the previous sampling time of sampling time t; k*=0.

5.

2. The hybrid energy storage system output power distribution method according to claim 1, characterized in that: Before output power distribution is performed, the filter coefficients in the first-order filter algorithm in the output power distribution of the hybrid energy storage system are initialized.

3. The hybrid energy storage system output power distribution method according to claim 1, characterized in that: Before distributing the output power of the hybrid energy storage system, obtain P according to the hybrid energy storage system's fluctuation smoothing function. HESS (t) value.

Images