Power smoothing method and system based on identification of renewable energy source dramatic fluctuation characteristics

Abstract

The application provides a power smoothing method and system based on renewable energy fluctuation feature identification, wherein the method provided by the application defines a renewable energy power fluctuation feature index, classifies renewable energy fluctuation, flexibly mobilizes and allocates flexible adjustable resources such as energy storage and adjustable load, adopts corresponding power fluctuation smoothing methods according to corresponding classes, thereby effectively smoothing renewable energy power generation, effectively realizing source-load-storage resource coordination, improving the comprehensive resource application value of the power grid, fully tapping the application potential of flexible adjustable resources in the power grid on one hand, and exploring the application effect of energy storage and load fusion adjustment on the other hand.

Description

Technical Field

[0001] This invention belongs to the field of power system dispatching technology, specifically relating to a power smoothing method and system based on the identification of severe fluctuations in renewable energy. Background Technology

[0002] The development of clean and renewable energy generation such as wind power and photovoltaics will accelerate further, and the penetration rate of wind and solar power in the power system will further increase. The volatility and randomness of renewable energy output will have a more pronounced impact on the power grid, and the "dual-high" characteristics (high proportion of renewable energy access and high proportion of power electronic device application) of the power system will become increasingly significant. Statistics show that my country needs to add no less than 75 million kilowatts of wind and solar power capacity annually over the next 10 years. Correspondingly, with the development of renewable energy, a large number of wind and solar power electronic converters will be connected to the grid, such as direct-drive wind turbine converters, photovoltaic power plants, and distributed photovoltaic inverters. At the same time, the safe and stable operation of the "dual-high" power system will become increasingly prominent, and its demand for flexible resource adjustment will become stronger. Improving or mitigating the fluctuation characteristics of renewable energy power generation connected to the grid from the "source" has become an important solution. At this time, energy storage, as a device with bidirectional power flow, precise power control, and rapid response, becomes an important means to improve or mitigate the fluctuation characteristics of renewable energy power generation connected to the grid. With the development of smart grid technology, the regulation potential of loads is being continuously explored. The detailed classification of interruptible loads, transferable loads, and adjustable loads also makes it possible for loads to be used to smooth out unbalanced power in the power grid.

[0003] Therefore, based on the fluctuation characteristics of renewable energy output, it is classified and targeted fluctuation smoothing is carried out in combination with flexible adjustment resources such as load and energy storage. On the one hand, the application potential of flexible adjustment resources in the power grid is fully explored, and on the other hand, the application effect of energy storage and load integrated regulation is also explored. Summary of the Invention

[0004] In view of this, the present invention provides a power smoothing method and system based on the identification of severe fluctuation characteristics of renewable energy, aiming to achieve effective smoothing of renewable energy power generation, effectively realize resource coordination of source-load-storage, and improve the comprehensive resource application value of the power grid. On the one hand, it fully explores the application potential of flexibly adjustable resources in the power grid, and on the other hand, it also explores the application effect of energy storage and load integration regulation.

[0005] The objective of this invention can be achieved through the following technical solutions:

[0006] In a first aspect, the present invention provides a power smoothing method based on the identification of severe fluctuations in renewable energy characteristics, comprising:

[0007] Obtain relevant data and information on renewable energy power generation that needs to be regulated;

[0008] Based on relevant data and information, the index value is calculated in conjunction with the definition of renewable energy fluctuation characteristic indicators, and the fluctuation level is determined according to the index value.

[0009] The appropriate control strategy should be determined based on the volatility level. The specific control strategies include:

[0010] When there is a slight fluctuation at level 1, strategy 1 is adopted, which means directly connecting the output of renewable energy into the grid;

[0011] During the second-level moderate fluctuation, strategy 2 is adopted, which is to use a single energy storage to smooth out the fluctuations in the output of renewable energy.

[0012] In the event of severe fluctuations at level 3, strategy 3 is adopted, namely, using a hybrid energy storage method to smooth out the fluctuations;

[0013] When there is a severe level 4 fluctuation, strategy 4 is adopted, which is to use a combination of load and energy storage to smooth the fluctuation.

[0014] The established control strategy controls the corresponding adjustable load and energy storage to smooth out the output fluctuations of renewable energy.

[0015] Furthermore, the specific definitions of the renewable energy volatility characteristic indicators are as follows:

[0016]

[0017] In the formula, K is the defined characteristic index value of renewable energy fluctuations, w is the proportional coefficient determined according to different sampling periods, and P i (t) represents the output power of the i-th type of renewable energy generator unit or cluster at time t, P rate-i The rated installed capacity of the generator set or cluster of the i-th renewable energy source.

[0018] Furthermore, the fluctuation level is determined based on the indicator value, specifically including:

[0019] When 0 ≤ K ≤ 10%, it is defined as a first-degree slight fluctuation;

[0020] When 10% < K ≤ 30%, it is defined as a second-order moderate fluctuation;

[0021] When 30% < K ≤ 70%, it is defined as a level three severe fluctuation;

[0022] When 70% < K ≤ 100%, it is defined as a level four severe fluctuation.

[0023] Furthermore, based on the determined control strategy, the corresponding adjustable load and energy storage are controlled to smooth out the output fluctuations of renewable energy, specifically including:

[0024] When Strategy 1 is adopted, the output of renewable energy is directly connected to the grid without the need for adjustable loads and energy storage to participate in regulation;

[0025] When using strategy 2, power-type energy storage is used to smooth out fluctuations in the output of renewable energy. The power-type energy storage's power command for smoothing out fluctuations is P. battery-1i (t)=P i (t)-P ave , where P i (t) represents the output power of the i-th type of renewable energy generator unit or cluster at time t, P ave The average output power of renewable energy, i.e. T is the total period, N is the total number of sampling points, and P is the total number of sampling points. battery-1i (t) represents the power fluctuation smoothing command of power-type energy storage, that is, the power value that the i-th renewable energy generator or cluster needs to be smoothed by power-type energy storage at time t.

[0026] When using strategy 3, power-type energy storage is combined with energy-type energy storage to smooth out power output fluctuations. The power-type energy storage power command for smoothing out fluctuations is P. battery-1i (t), the power command for smoothing fluctuations in energy storage is P. battery-2i (t);

[0027] When using strategy 4, adjustable load, power-type energy storage, and energy-type energy storage are used to smooth out power output fluctuations. The power command for smoothing fluctuations using power-type and energy-type energy storage is P. battery-1i (t) and P battery-2i (t), the adjustable load's power command for smoothing fluctuations is P. load-3i (t).

[0028] Furthermore, in strategies 3 and 4, the specific allocation methods for various signals are as follows:

[0029] Strategy 3 uses wavelet packet decomposition to smooth the power curve P of renewable energy generator sets or clusters that needs to be flattened. battery-i (t) is divided into two frequency bands: [0,f] and (f,∞). The power signal of the (f,∞) band is merged and reconstructed into a power-type energy storage command P. battery-1i The power signals in the [0,f] frequency band (t) are merged and reconstructed into a power command P for smoothing fluctuations in energy storage. battery-2i (t), where f is a positive integer;

[0030] Strategy 4 uses wavelet packet decomposition to smooth the power curve P of renewable energy generator sets or clusters that needs to be flattened. battery-i(t) Divide the frequency bands into three bands: [0,a], (a,b], and (b,∞). The power signal of the (b,∞) band is merged and reconstructed into a power-type energy storage power command P to smooth out fluctuations. battery-1i The power signals in the (t) and (a,b) frequency bands are merged and reconstructed into a power command P for smoothing fluctuations in energy storage. battery-2i The power signals in the (t) and [0,a] frequency bands are merged and reconstructed into a power command P for smoothing fluctuations in adjustable loads. load-3i (t), where a and b are positive integers.

[0031] Secondly, the present invention provides a power smoothing system based on the identification of severe fluctuations in renewable energy characteristics, comprising:

[0032] The data acquisition unit is used to acquire relevant data information on renewable energy power generation that needs to be regulated;

[0033] The fluctuation judgment unit is used to calculate the index value based on relevant data information and the definition of renewable energy fluctuation characteristic indicators, and to determine the fluctuation level based on the index value.

[0034] The strategy selection unit is used to determine the corresponding control strategy to be adopted based on the volatility level. The control strategies specifically include:

[0035] When there is a slight fluctuation at level 1, strategy 1 is adopted, which means directly connecting the output of renewable energy into the grid;

[0036] During the second-level moderate fluctuation, strategy 2 is adopted, which is to use a single energy storage to smooth out the fluctuations in the output of renewable energy.

[0037] In the event of severe fluctuations at level 3, strategy 3 is adopted, namely, using a hybrid energy storage method to smooth out the fluctuations;

[0038] When there is a severe level 4 fluctuation, strategy 4 is adopted, which is to use a combination of load and energy storage to smooth the fluctuation.

[0039] The fluctuation smoothing unit is used to smooth out the output fluctuations of renewable energy by controlling the corresponding adjustable load and energy storage according to the determined control strategy.

[0040] Furthermore, in the fluctuation judgment unit, the specific definition of the renewable energy fluctuation characteristic index is as follows:

[0041]

[0042] In the formula, K is the defined characteristic index value of renewable energy fluctuations, w is the proportional coefficient determined according to different sampling periods, and P i (t) represents the output power of the i-th type of renewable energy generator unit or cluster at time t, P rate-iThe rated installed capacity of the generator set or cluster of the i-th renewable energy source.

[0043] Furthermore, in the volatility judgment unit, the volatility level is determined based on the indicator value, specifically including:

[0044] When 0 ≤ K ≤ 10%, it is defined as a first-degree slight fluctuation;

[0045] When 10% < K ≤ 30%, it is defined as a second-order moderate fluctuation;

[0046] When 30% < K ≤ 70%, it is defined as a level three severe fluctuation;

[0047] When 70% < K ≤ 100%, it is defined as a level four severe fluctuation.

[0048] Furthermore, in the fluctuation mitigation unit, the corresponding adjustable load and energy storage are controlled according to a determined control strategy to mitigate the output fluctuations of renewable energy, specifically including:

[0049] When Strategy 1 is adopted, the output of renewable energy is directly connected to the grid without the need for adjustable loads and energy storage to participate in regulation;

[0050] When using strategy 2, power-type energy storage is used to smooth out fluctuations in the output of renewable energy. The power-type energy storage's power command for smoothing out fluctuations is P. battery-1i (t)=P i (t)-P ave , where P i (t) represents the output power of the i-th type of renewable energy generator unit or cluster at time t, P ave The average output power of renewable energy, i.e. T is the total period, N is the total number of sampling points, and P is the total number of sampling points. battery-1i (t) represents the power fluctuation smoothing command of power-type energy storage, that is, the power value that the renewable energy generator set or cluster needs to be smoothed by power-type energy storage at time i.

[0051] When using strategy 3, power-type energy storage is combined with energy-type energy storage to smooth out power output fluctuations. The power-type energy storage power command for smoothing out fluctuations is P. battery-1i (t), the power command for smoothing fluctuations in energy storage is P. battery-2i (t);

[0052] When using strategy 4, adjustable load, power-type energy storage, and energy-type energy storage are used to smooth out power output fluctuations. The power command for smoothing fluctuations using power-type and energy-type energy storage is P. battery-1i (t) and P battery-2i (t), the adjustable load's power command for smoothing fluctuations is P. load-3i (t).

[0053] Furthermore, within the fluctuation mitigation unit, specifically in strategies 3 and 4, the allocation methods for various signals are as follows:

[0054] The power smoothing curve P required by renewable energy generator sets or clusters is obtained by using Fourier wavelet packet analysis. battery-i (t) is divided into two frequency bands (high and low) or three frequency bands (high, medium, and low), depending on the situation, and then corresponding measures are taken to suppress power. Specifically:

[0055] Strategy 3 uses wavelet packet decomposition to smooth the power curve P of renewable energy generator sets or clusters that needs to be flattened. battery-i (t) is divided into two frequency bands: [0,f] and (f,∞). The power signal of the (f,∞) band is merged and reconstructed into a power-type energy storage power command P to smooth out fluctuations. battery-1i (t), the power signals in the [0,f] frequency band are merged and reconstructed into a power command P for smoothing fluctuations in energy storage. battery-2i (t), where f is a positive integer;

[0056] Strategy 4 uses wavelet packet decomposition to smooth the power curve P of renewable energy generator sets or clusters that needs to be flattened. battery-i (t) Divide the frequency bands into three bands: [0,a], (a,b], and (b,∞). The power signal of the (b,∞) band is merged and reconstructed into a power-type energy storage power command P to smooth out fluctuations. battery-1i The power signals in the (t) and (a,b) frequency bands are merged and reconstructed into a power command P for smoothing fluctuations in energy storage. battery-2i The power signals in the [0,a] frequency band (t) are merged and reconstructed into a power command P for smoothing fluctuations in the adjustable load. load-3i (t), where a and b are positive integers.

[0057] In summary, this invention provides a power mitigation method and system based on the identification of severe fluctuations in renewable energy. The method defines characteristic indicators of renewable energy power generation fluctuations, classifies the fluctuations of renewable energy into levels, and flexibly mobilizes and allocates resources such as energy storage and adjustable loads. Corresponding power fluctuation mitigation methods are adopted according to the corresponding levels, thereby achieving effective mitigation of renewable energy power generation, effectively coordinating resources among source, load, and storage, and improving the comprehensive resource application value of the power grid. On the one hand, it fully explores the application potential of flexibly adjustable resources in the power grid; on the other hand, it also explores the application effect of integrated regulation of energy storage and load, contributing to my country's green and low-carbon energy transformation. Attached Figure Description

[0058] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0059] Figure 1 A flowchart illustrating a power smoothing method based on the identification of severe fluctuations in renewable energy, provided in an embodiment of the present invention;

[0060] Figure 2 A schematic diagram illustrating the power allocation results of a single energy storage system in Strategy 2 provided in this embodiment of the invention, which smooths out fluctuations in the output of renewable energy.

[0061] Figure 3 This is a schematic diagram of the allocation of hybrid energy storage regulation commands provided in an embodiment of the present invention;

[0062] Figure 4 This is a schematic diagram of the distribution of adjustment commands for adjustable load and hybrid energy storage provided in an embodiment of the present invention. Detailed Implementation

[0063] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0064] With the further development and advancement of the "dual carbon" goals, clean and renewable energy power generation such as wind power and photovoltaics will accelerate, and the penetration rate of wind and solar power in the power system will further increase. The volatility and randomness of renewable energy output will have a more pronounced impact on the power grid, and the "dual high" characteristics (high proportion of renewable energy access and high proportion of power electronic device application) of the power system will become increasingly significant. Statistics show that my country needs to add no less than 75 million kilowatts of wind and solar power capacity annually over the next 10 years. Correspondingly, with the development of renewable energy, a large number of wind and solar power electronic converters will be connected to the grid, such as direct-drive wind turbine converters, photovoltaic power plants, and distributed photovoltaic inverters. At the same time, the safe and stable operation of the "dual high" power system becomes increasingly prominent, and its demand for flexible resource adjustment becomes stronger. Improving or mitigating the fluctuation characteristics of renewable energy power generation grid connection from the "source" becomes an important solution. At this time, energy storage, as a device with bidirectional power flow, precise power control, and rapid response, becomes an important means of addressing the fluctuation characteristics of renewable energy power generation grid connection. With the development of smart grid technology, the regulation potential of loads is being continuously explored. The detailed classification of interruptible loads, transferable loads, and adjustable loads also makes it possible for loads to be used to smooth out unbalanced power in the power grid.

[0065] Therefore, based on the fluctuation characteristics of renewable energy output, it is classified and targeted fluctuation smoothing is carried out in combination with flexible adjustment resources such as load and energy storage. On the one hand, the application potential of flexible adjustment resources in the power grid is fully explored, and on the other hand, the application effect of energy storage and load integration regulation is also explored, so as to help my country's green and low-carbon energy transformation.

[0066] Based on this, the present invention provides a power smoothing method and system based on the identification of severe fluctuation characteristics of renewable energy.

[0067] The following is a detailed description of an embodiment of the power smoothing method based on the identification of severe fluctuations in renewable energy according to the present invention.

[0068] Please see Figure 1 This embodiment provides a power smoothing method based on the identification of severe fluctuations in renewable energy, including the following steps:

[0069] (1) Obtain relevant information on the renewable energy generation that needs to be regulated.

[0070] Specifically, renewable energy includes fluctuating new energy sources such as wind power and solar power, and related information includes the rated installed capacity P of renewable energy generator units or clusters corresponding to solar power and wind power, respectively. rate-pv P rate-wind The daily power generation curve P pv(t), P wind (t), where the sampling frequency is T0, the total period is T, and the total number of sampling points is N = T / T0.

[0071] (2) Calculate the index value by combining the definition of renewable energy fluctuation characteristic index, and determine the fluctuation level based on the index value.

[0072] The definition of drastic power fluctuation characteristics is mainly from the perspective of time-frequency domain analysis, defining an index K. A fluctuation is defined as K > n. Specifically, the formula for calculating the value of K is as follows:

[0073]

[0074] In the formula, K is the defined characteristic index value of renewable energy fluctuation, w is the proportional coefficient determined according to different sampling periods, and its value is between (1, 10). i (t) represents the output power of the i-th type of renewable energy generator set or cluster at time t, and represents the output curve over the total period T, including the output curve P of the photovoltaic renewable energy generator set or cluster. pv (t), the output curve P of renewable energy generator sets or clusters for wind power. wind (t), P rate-i The rated installed capacity of the generator set or cluster of the i-th renewable energy source, including the rated installed capacity P of the generator set or cluster of photovoltaic renewable energy. rate-pv The rated installed capacity P of wind power renewable energy generator sets or clusters rate-wind .

[0075] Based on the magnitude of the K value, the fluctuations are divided into the following four levels according to their degree:

[0076] When 0 ≤ K ≤ 10%, it is defined as a first-degree slight fluctuation;

[0077] When 10% < K ≤ 30%, it is defined as a second-order moderate fluctuation;

[0078] When 30% < K ≤ 70%, it is defined as a level three severe fluctuation;

[0079] When 70% < K ≤ 100%, it is defined as a level four severe fluctuation.

[0080] (3) Determine the corresponding control strategy to be adopted based on the fluctuation level. The specific control strategies are as follows:

[0081] A. When there is a slight fluctuation at level one, strategy 1 is adopted, which means directly connecting the output of renewable energy into the grid.

[0082] In this strategy, since the output data of renewable energy is relatively less volatile, no additional fluctuation smoothing is required. That is, the power of this part is directly connected to the grid without the need for energy storage or load to participate in regulation.

[0083] B. During the second level of moderate fluctuations, strategy 2 is adopted, which is to use a single energy storage system to smooth out fluctuations in the output of renewable energy.

[0084] In this strategy, since the output data of renewable energy is relatively volatile, power storage is used to smooth out the fluctuations in output, so as to achieve the goal of smoothing the output curve.

[0085] The power fluctuation smoothing command for power-type energy storage involves using power-type energy storage to smooth out fluctuations in the output of renewable energy. The power fluctuation smoothing command for power-type energy storage is P. battery-1i (t)=P i (t)-P ave , where P i (t) represents the output power of the i-th type of renewable energy generator unit or cluster at time t, P ave The average output power of renewable energy, i.e. T is the total period, N is the total number of sampling points, and P is the total number of sampling points. battery-1i (t) represents the power fluctuation suppression command of power-type energy storage, that is, the power value that the renewable energy generator set or cluster needs to suppress by power-type energy storage at time i.

[0086] C. In the event of severe fluctuations at level three, strategy 3 is adopted, namely, using a hybrid energy storage method to smooth out the fluctuations.

[0087] In this strategy, due to the relatively large fluctuations in renewable energy output data, a combination of power-type and energy-type energy storage is used to smooth out these fluctuations, thereby achieving a smoother output curve. The total power smoothing signal is P. battery-i (t), selecting the power smoothing requirement for renewable energy grid connection, using Gaussian filtering to obtain the total power to be smoothed, the power fluctuation smoothing command for power-type energy storage is P. battery-1i (t)=P i (t)-P ave That is, the same as strategy 2, but the power command for smoothing fluctuations in energy storage is P. battery-2i (t), P battery-2i (t)=P battery-i (t)-P battery-1i (t).

[0088] D. When there is a severe level 4 fluctuation, strategy 4 is adopted, that is, a combination of load and energy storage is used to smooth the fluctuation.

[0089] In this strategy, due to the significant fluctuations in renewable energy output data, it is necessary to utilize adjustable loads, combined with power-type and energy-type energy storage, to smooth out these fluctuations and achieve a smoother output curve. The total power smoothing signal is P. battery-i (t), Pbattery-i (t)=P battery-1i (t)+P battery-2i (t)+P load-3i (t). Among them, the power command P for smoothing fluctuations in power-type energy storage and energy-type energy storage. battery-1i (t), P battery-2i (t) and the adjustable load's power fluctuation suppression command P load-3i (t) is obtained using the Fourier wavelet packet decomposition method. Specifically, the fluctuating power is divided into frequency bands, which are set as three frequency bands: [0,a], (a,b], and (b,∞). The power signal of the (b,∞) frequency band is reconstructed and merged into the power-type energy storage command P. battery-1i The power signals in the (t) and (a,b) frequency bands are reconstructed and merged into an energy storage command P. battery-2i The power signals in the (t) and [0,a] frequency bands are reconstructed and merged into a power command P for smoothing fluctuations in the adjustable load. load-3i (t). Where a and b are positive integers that can be adjusted according to the application scenario.

[0090] (4) Control the corresponding adjustable load and energy storage according to the determined control strategy to smooth out the output fluctuations of renewable energy.

[0091] When Strategy 3 is used for fluctuation mitigation, the signal allocation and execution for power-type energy storage and energy-type energy storage are performed as follows:

[0092] First, the power signal P is decomposed using wavelet decomposition. battery-i (t) is divided into high-frequency and low-frequency parts. The high-frequency part is smoothed by power-type energy storage, and the low-frequency signal is smoothed by energy-type energy storage.

[0093] When using Strategy 4 for fluctuation mitigation, the signal allocation and execution for adjustable loads, power-type energy storage, and energy-type energy storage are performed as follows:

[0094] First, the power signal P is decomposed using wavelet decomposition. battery-i (t) is divided into three parts: high, medium, and low frequencies. Among them, the high frequency part is smoothed by power-type energy storage, the medium frequency signal is smoothed by energy-type energy storage, and the low frequency signal is smoothed by adjustable load.

[0095] Figure 2 A schematic diagram illustrating the power allocation results for mitigating fluctuations in the output of renewable energy by a single energy storage system in Strategy 2: The upper part represents the power portion directly connected to the grid, i.e., P. ave The lower half is the power regulation command P corresponding to power-type energy storage. battery-1i (t); Figure 3This is a schematic diagram illustrating the power allocation results for power-type and energy-type energy storage to smooth out fluctuations in renewable energy output in Strategy 3: The upper part shows the regulation power command corresponding to energy-type energy storage, i.e., P. battery-2i (t), the lower part is the power regulation command P corresponding to power-type energy storage. battery-1i (t); Figure 4 This diagram illustrates the power allocation results for adjusting load, energy-type, and power-type energy storage to smooth out fluctuations in renewable energy output in Strategy 4: The upper part shows the adjustment power command P corresponding to the adjusting load. load-3i (t), where the middle part is the power regulation command corresponding to energy storage, i.e., P. battery-2i (t), the lower part is the power regulation command P corresponding to power-type energy storage. battery-1i (t).

[0096] This embodiment provides a power smoothing method based on the identification of severe fluctuations in renewable energy. By defining characteristic indicators of renewable energy power generation fluctuations, the fluctuations of renewable energy are classified into levels, and flexible and adjustable resources such as energy storage and adjustable loads are flexibly mobilized and allocated. Corresponding power fluctuation smoothing methods are adopted according to the corresponding levels, thereby achieving effective smoothing of renewable energy power generation and effectively realizing resource coordination among source, load and storage. This is of great significance for improving the utilization rate of adjustable resources in the power grid, improving the utilization rate of power grid resources, and tapping the comprehensive benefits of power grid operation.

[0097] The above is a detailed description of an embodiment of a power smoothing method based on the identification of severe fluctuations in renewable energy according to the present invention. The following will provide a detailed description of an embodiment of a power smoothing system based on the identification of severe fluctuations in renewable energy according to the present invention.

[0098] This embodiment provides a power smoothing system based on the identification of severe fluctuations in renewable energy, including: a data acquisition unit, a fluctuation judgment unit, a strategy selection unit, and a fluctuation smoothing unit.

[0099] In this embodiment, the data acquisition unit is used to acquire relevant data information of the renewable energy power generation that needs to be regulated.

[0100] In this embodiment, the fluctuation judgment unit is used to calculate the index value based on relevant data information and the definition of renewable energy fluctuation characteristic index, and to determine the fluctuation level based on the index value.

[0101] Specifically, the renewable energy volatility characteristic index is defined as follows:

[0102]

[0103] In the formula, K is the defined characteristic index value of renewable energy fluctuations, w is the proportional coefficient determined according to different sampling periods, and P i (t) represents the power generation curve of the i-th renewable energy source, P rate-i The rated installed capacity of the generator set or cluster of the i-th renewable energy source.

[0104] Based on the above definition, the following four fluctuation levels can be determined:

[0105] When 0 ≤ K ≤ 10%, it is defined as a first-degree slight fluctuation;

[0106] When 10% < K ≤ 30%, it is defined as a second-order moderate fluctuation;

[0107] When 30% < K ≤ 70%, it is defined as a level three severe fluctuation;

[0108] When 70% < K ≤ 100%, it is defined as a level four severe fluctuation.

[0109] In this embodiment, the strategy selection unit is used to determine the corresponding control strategy to be taken based on the fluctuation level. The control strategy specifically includes:

[0110] When there are slight fluctuations at level 1, strategy 1 is adopted, which means directly integrating the output of renewable energy into the grid.

[0111] When Strategy 1 is adopted, the output of renewable energy is directly connected to the grid without the need for adjustable loads and energy storage to participate in regulation.

[0112] During the second level of moderate fluctuations, strategy 2 is adopted, which involves using a single energy storage system to smooth out fluctuations in the output of renewable energy.

[0113] When using strategy 2, power-type energy storage is used to smooth out fluctuations in the output of renewable energy. The power-type energy storage's power command for smoothing out fluctuations is P. battery-1i (t)=P i (t)-P ave , where P i (t) represents the output power of the renewable energy generator set or cluster at time i, P ave The average output power of renewable energy, i.e. P battery-1i (t) represents the power value that a renewable energy generator set or cluster needs to be balanced by power storage at time i.

[0114] In the event of severe fluctuations at level three, strategy 3 is adopted, which involves using a hybrid energy storage approach to mitigate the fluctuations.

[0115] When using strategy 3, power-type energy storage is combined with energy-type energy storage to smooth out power output fluctuations. The power command for smoothing fluctuations for power-type energy storage is the same as in strategy 2, while the power command for smoothing fluctuations for energy-type energy storage is P. battery-2i (t).

[0116] When there is a severe level 4 fluctuation, strategy 4 is adopted, which is to use a combination of load and energy storage to smooth the fluctuation.

[0117] When using strategy 4, output fluctuations are mitigated using adjustable loads, power-type energy storage, and energy-type energy storage. The power command for mitigating fluctuations in power-type and energy-type energy storage is the same as in strategy 3, while the power command for mitigating fluctuations in adjustable loads is P. load-3i (t).

[0118] In this embodiment, the fluctuation smoothing unit is used to control the corresponding adjustable load and energy storage to smooth the output fluctuations of renewable energy according to the determined control strategy.

[0119] Specifically, in strategies 3 and 4, the allocation methods for various signals are as follows:

[0120] Wavelet decomposition method is used to smooth the power curve P required by renewable energy generator sets or clusters. battery-i (t) is divided into three parts: high-frequency signals are smoothed by power-type energy storage, medium-frequency signals are smoothed by energy-type energy storage, and low-frequency signals are smoothed by adjustable load.

[0121] It should be noted that the power smoothing system provided in this embodiment is used to implement the power smoothing method provided in the aforementioned embodiment. The specific settings of each unit are based on the complete implementation of the method, and will not be repeated here.

[0122] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A power smoothing method based on renewable energy source fluctuation feature recognition, characterized in that, The application relates to a renewable energy power generation fluctuation control method and device. Obtaining relevant data information of renewable energy power generation to be regulated; Based on the relevant data information, an index value is calculated according to a renewable energy fluctuation characteristic index definition, and a fluctuation level is determined according to the index value; According to the fluctuation level, a corresponding control strategy is determined, which specifically includes: In the case of a first level of slight fluctuation, strategy 1 is adopted, that is, the output of the renewable energy is directly integrated into the power grid; In the case of a second level of moderate fluctuation, strategy 2 is adopted, that is, single energy storage is used to suppress the output fluctuation of the renewable energy; In the case of a third level of serious fluctuation, strategy 3 is adopted, that is, mixed energy storage is used to suppress the output fluctuation; In the case of a fourth level of severe fluctuation, strategy 4 is adopted, that is, mixed energy storage and load are used to suppress the output fluctuation; According to the determined control strategy, the corresponding adjustable load and energy storage are controlled to suppress the output fluctuation of the renewable energy; According to the determined control strategy, the corresponding adjustable load and energy storage are controlled to suppress the output fluctuation of the renewable energy, specifically including: In the case of strategy 1, the output of the renewable energy is directly integrated into the power grid, and the adjustable load and energy storage do not participate in regulation; When the strategy 2 is adopted, the output fluctuation of the renewable energy is smoothed by using the power-type energy storage, and the smoothing fluctuation power instruction of the power-type energy storage is , wherein is the output power value of the i th renewable energy generator set or cluster at time t, is the average value of the renewable energy output power, that is, , T is the total period, and N is the total sampling point number, is the smoothing fluctuation power instruction of the power-type energy storage, that is, the power value that needs to be smoothed by the power-type energy storage of the i th renewable energy generator set or cluster at time t. When the strategy 3 is adopted, the power fluctuation is smoothed by the power-type energy storage and the energy-type energy storage, the smoothing fluctuation power instruction of the power-type energy storage is , and the smoothing fluctuation power instruction of the energy-type energy storage is . When the strategy 4 is adopted, the fluctuation of the output power is smoothed by the adjustable load, the power-type energy storage and the energy-type energy storage, the fluctuation smoothing power instruction of the power-type energy storage and the energy-type energy storage is and , and the fluctuation smoothing power instruction of the adjustable load is ; In the case of strategy 3 and strategy 4, the allocation mode of various signals is specifically as follows: The power curve that needs to be smoothed by the renewable energy generator set or cluster in strategy 3 is decomposed by a wavelet packet decomposition method According to the frequency band, it is divided into [0, f] and (f, ∞) two frequency bands, wherein the power signal of the (f, ∞] frequency band is merged and reconstructed as a smoothing fluctuation power instruction of the power type energy storage The power signal of the [0, f] frequency band is merged and reconstructed as a smoothing fluctuation power instruction of the energy type energy storage Wherein, f is a positive integer; The power curve that needs to be smoothed by the renewable energy generator or cluster in strategy 4 is decomposed by using a wavelet packet decomposition method According to the frequency band, three frequency bands of [0, a], (a, b] and (b, ∞) are set, wherein the power signals of the (b, ∞) frequency band are merged and reconstructed as a power-type energy storage smoothing fluctuating power instruction , the power signals of the (a, b] frequency band are merged and reconstructed as an energy-type energy storage smoothing fluctuating power instruction , and the power signals of the [0, a] frequency band are merged and reconstructed as an adjustable load smoothing fluctuating power instruction , wherein a and b are positive integers.

2. The power smoothing method based on renewable energy source fluctuation characteristics identification according to claim 1, characterized in that, The renewable energy fluctuation characteristic index is specifically defined as follows: In the formula, is the defined renewable energy fluctuation characteristic index value, is a proportional coefficient determined according to different sampling periods, is the output power value of the i th renewable energy generator set or cluster at time t, is the rated installed capacity of the i th renewable energy generator set or cluster.

3. The power smoothing method based on renewable energy source fluctuation characteristics identification according to claim 2, characterized in that, According to the index value, the corresponding fluctuation level is determined, specifically including: When 0<=K<=10%, the first level of slight fluctuation is defined; When 10%<K<=30%, the second level of moderate fluctuation is defined; When 30%<K<=70%, the third level of serious fluctuation is defined; When 70%<K<=100%, the fourth level of severe fluctuation is defined.

4. A power smoothing system based on renewable energy volatility signature recognition, characterized in that, The application relates to a renewable energy power generation fluctuation control method and device. A data acquisition unit is used for obtaining relevant data information of renewable energy power generation to be regulated; A fluctuation judgment unit is used for calculating an index value according to a renewable energy fluctuation characteristic index definition based on the relevant data information, and determining a corresponding fluctuation level according to the index value; A strategy selection unit is used for determining a corresponding control strategy according to the fluctuation level, which specifically includes: In the case of a first level of slight fluctuation, strategy 1 is adopted, that is, the output of the renewable energy is directly integrated into the power grid; In the case of a second level of moderate fluctuation, strategy 2 is adopted, that is, single energy storage is used to suppress the output fluctuation of the renewable energy; In the case of a third level of serious fluctuation, strategy 3 is adopted, that is, mixed energy storage is used to suppress the output fluctuation; In the case of a fourth level of severe fluctuation, strategy 4 is adopted, that is, mixed energy storage and load are used to suppress the output fluctuation; A fluctuation suppression unit is used for controlling the corresponding adjustable load and energy storage to suppress the output fluctuation of the renewable energy according to the determined control strategy; In the fluctuation suppression unit, the corresponding adjustable load and energy storage are controlled to suppress the output fluctuation of the renewable energy according to the determined control strategy, specifically including: In the case of strategy 1, the output of the renewable energy is directly integrated into the power grid, and the adjustable load and energy storage do not participate in regulation; When the strategy 2 is adopted, the output fluctuation of the renewable energy is smoothed by the power-type energy storage, and the smoothing fluctuation power instruction of the power-type energy storage is , wherein is the output power value of the i th renewable energy generator set or cluster at time t, is the average value of the renewable energy output power, that is, , T is the total period, and N is the total sampling point number, is the smoothing fluctuation power instruction of the power-type energy storage, that is, the power value that needs to be smoothed by the power-type energy storage of the i th renewable energy generator set or cluster at time t. When the strategy 3 is adopted, the power fluctuation is smoothed by the power-type energy storage and the energy-type energy storage, the smoothing fluctuation power instruction of the power-type energy storage is , and the smoothing fluctuation power instruction of the energy-type energy storage is . When the strategy 4 is adopted, the fluctuation of the output power is smoothed by the adjustable load, the power-type energy storage and the energy-type energy storage, the fluctuation smoothing power instruction of the power-type energy storage and the energy-type energy storage is and , and the fluctuation smoothing power instruction of the adjustable load is ; In the fluctuation suppression unit, in the case of strategy 3 and strategy 4, the allocation mode of various signals is specifically as follows: The power smoothing curve required by a renewable energy generator set or cluster is analyzed by using a Fourier wavelet packet analysis method The division is carried out, and the high and low frequency bands or the high, medium and low frequency bands are decomposed as appropriate, and corresponding measures are taken for power smoothing, specifically: The power curve that needs to be smoothed by the renewable energy generator set or cluster in strategy 3 is decomposed by a wavelet packet decomposition method According to the frequency band, it is divided into [0, f] and (f, ∞) two frequency bands, wherein the power signal of the (f, ∞] frequency band is merged and reconstructed as a smoothing fluctuation power instruction of the power type energy storage The power signal of the [0, f] frequency band is merged and reconstructed as a smoothing fluctuation power instruction of the energy type energy storage Wherein, f is a positive integer; The power curve that the renewable energy generator or cluster needs to smooth in strategy 4 is decomposed by using a wavelet packet decomposition method According to the frequency band, set [0, a], (a, b] and (b, ∞) three frequency bands, wherein the power signal of the (b, ∞) frequency band is merged and reconstructed as a power type energy storage smoothing fluctuating power instruction , the power signal of the (a, b] frequency band is merged and reconstructed as an energy type energy storage smoothing fluctuating power instruction , the power signal of the [0, a] frequency band is merged and reconstructed as an adjustable load smoothing fluctuating power instruction , wherein a and b are positive integers that can be adjusted according to the application scenario.

5. The power smoothing system based on renewable energy source fluctuation signature recognition of claim 4, wherein, In the fluctuation judging unit, the renewable energy fluctuation characteristic index is defined as follows: In the formula, is the defined renewable energy fluctuation characteristic index value, is the proportional coefficient determined according to different sampling periods, is the output power value of the i th renewable energy generator set or cluster at time t, is the rated installed capacity of the i th renewable energy generator set or cluster.

6. The power smoothing system based on renewable energy source fluctuation signature recognition of claim 5, wherein, In the fluctuation judging unit, the index value is used to judge the fluctuation level, specifically including: When 0≤K≤10%, it is defined as the first level of slight fluctuation; When 10%<K≤30%, it is defined as the second level of moderate fluctuation; When 30%<K≤70%, it is defined as the third level of severe fluctuation; When 70%<K≤100%, it is defined as the fourth level of severe fluctuation.

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