Sustainable and stable output control method for grid-connected output power of photovoltaic power generation system

Abstract

The invention relates to a sustainable and stable output control method for grid-connected output power of a photovoltaic power generation system, and belongs to the technical field of photovoltaic power generation. According to the method, based on an existing photovoltaic power prediction model, a constant output power reference value of each time period is formulated, visual advance of the photovoltaic power generation power and adjustability of the photovoltaic power generation output power by a power grid are realized, and the problems of randomness, intermittency and uncontrollability of a photovoltaic power generation system under the influence of environmental meteorological factors are solved. Through the time-phased method, the power fluctuation needing to be adjusted of the energy storage system is remarkably reduced, so that the configuration capacity required by energy storage is effectively reduced, the cost is reduced, and the economical efficiency and the operation efficiency of the system are improved. Through the coordinated operation strategy of the photovoltaic-storage combined system, the stability and controllability of the photovoltaic system are enhanced, and stable grid connection of the photovoltaic system is ensured. According to the invention, large-scale grid connection of photovoltaic power generation is promoted, and the economic benefit of the photovoltaic-energy storage combined system and the operation reliability of the power grid are further improved.

Description

Technical Field

[0001] The invention belongs to the technical field of photovoltaic power generation, and relates to a method for controlling the sustainable and stable output of grid-connected output power of a photovoltaic power generation system. Background Art

[0002] Photovoltaic power generation technology uses the photoelectric effect of semiconductor materials to convert solar radiation into electrical energy. The most common photovoltaic cells use polycrystalline silicon. When sunlight shines on the surface of the semiconductor, it excites electrons to form an electric current. Photovoltaic power generation is environmentally friendly, renewable, and can be distributed and connected to the grid. It is an integral part of the new power system. However, the main problem facing photovoltaic power generation is that its power generation is susceptible to a variety of meteorological factors, showing significant intermittent and highly random, unreliable. With the increase in the proportion of photovoltaic power generation, its connection to the power grid has become increasingly prominent, thus affecting the stability of the power system. It poses a severe challenge to the dispatching and safe and stable operation of the power grid, and has become a key issue to be solved. The adverse factors brought about by the connection of photovoltaic power generation to the grid are mainly manifested in: the impact on system stability; the impact on power quality; the impact on the power generation plan and economic dispatch of the power grid.

[0003] In order to solve the problem of intermittent random fluctuations in the output power of photovoltaic power generation systems due to environmental changes, configuring a certain capacity of energy storage devices in photovoltaic power generation systems and using advanced control methods to adjust the charging and discharging of energy storage devices is an effective way to solve this problem. In recent years, the rapid development of energy storage technology has given it significant advantages in improving photovoltaic grid-connected characteristics, smoothing fluctuations, and participating in grid frequency regulation. By coordinating the operation of efficient, reliable, energy-saving and environmentally friendly energy storage devices with photovoltaic systems, and combining advanced control methods to accurately adjust the charging and discharging of energy storage, photovoltaic power fluctuations can be effectively smoothed, grid-connected stability can be improved, and the grid's ability to absorb large-scale photovoltaics can be enhanced. Therefore, the combination of energy storage and advanced control methods has broad development prospects in photovoltaic power generation systems, and is of great significance to improving photovoltaic grid-connected compatibility and smart grid construction.

[0004] At present, the output power of photovoltaic power generation systems is greatly affected by environmental meteorological factors such as light intensity, temperature, and weather changes, which leads to significant randomness, intermittency, weak controllability, and uncontrollability, which in turn exacerbates the frequency and voltage fluctuations of the power grid. Some studies have proposed some effective control and optimization methods. Some studies have coordinated and optimized the photovoltaic and energy storage combined system through a hierarchical control strategy, and adopted methods such as discharge droop control and charging fuzzy control to solve the problems of voltage fluctuations and uneven power output caused by photovoltaic power generation fluctuations. Secondly, other studies have proposed a photovoltaic load power balance control method in distribution stations based on energy storage regulation. By optimizing the energy storage charging and discharging path and reasonably adjusting the energy storage start and stop time, it can effectively alleviate the problems of uneven power flow distribution and excessive voltage deviation caused by photovoltaic penetration in distribution stations. There are also studies that use particle swarm algorithms, combined with optimization measures such as energy storage batteries and reactive power compensation devices, to achieve 24-hour dynamic optimization of the distribution network system, focusing on improving voltage stability, reducing network losses, and preventing voltage over-limit.

[0005] Although the current methods have alleviated the volatility of photovoltaic output to a certain extent, they require a large amount of computing resources and more complex control algorithms, which increases the operating cost and complexity of the system. In addition, these solutions assume that the energy storage system needs to undertake a larger proportion of power regulation tasks, resulting in the need for the energy storage system to be configured with a higher capacity. In the face of drastic or unpredictable photovoltaic fluctuations, these solutions have poor response speed and flexibility, making it difficult to achieve stable power output. Summary of the invention

[0006] In view of this, the problem to be solved by the present invention is: intermittent random fluctuations in the grid-connected output power of photovoltaic power generation systems under the disturbance of environmental meteorological factors; improving the grid-connected characteristics of photovoltaic power generation systems and maintaining sustainable and stable power output, and improving the impact of intermittent random fluctuations in the output power of photovoltaic power generation under environmental meteorological disturbances on the safety of grid operation and power quality. The purpose of the present invention is to provide a method for controlling the sustainable and stable output of the grid-connected output power of photovoltaic power generation systems.

[0007] In order to achieve the above object, the present invention provides the following technical solutions:

[0008] A method for controlling the sustainable and stable output power of a photovoltaic power generation system connected to the grid, comprising the following steps:

[0009] S1. Formulate a constant output power reference value based on the photovoltaic power generation power prediction curve: optimize the photovoltaic power generation power prediction curve for each period, and calculate the average power value of each period as a reference value for sustainable and stable power output to the power grid in each period;

[0010] S2. Adaptive variational modal decomposition hybrid energy storage configuration based on existing energy storage priority: Optimal configuration of hybrid energy storage resources based on adaptive variational modal decomposition;

[0011] S3. Combined coordinated control of charging and discharging of photovoltaic and storage based on rolling optimization: A method for controlling the sustainable and stable power output of photovoltaic and storage integrated joint coordination in different time periods based on the rolling optimization of power reference values ​​to execute the charging and discharging operation control of energy storage resources.

[0012] Furthermore, S1 is: during the effective power generation period, the average value of the predicted power of photovoltaic power generation is used as the constant output power reference value P of the photovoltaic-storage combined system to transmit power to the power grid set ; When the output of the photovoltaic power generation system is higher than P set When the output of the photovoltaic power station is lower than P set When the energy storage system releases the corresponding power, the grid-connected power of the solar-storage combined system is close to the expected value.

[0013] Further, the S1 specifically includes the following steps:

[0014] Assume that the grid-connected power P N With constant output power reference value P set Same, photovoltaic system output power P W And the energy storage system charging and discharging power P Hess The relationship is expressed as the following formula:

[0015] P N (t) = P W (t)+P Hess (t) (1)

[0016] In the formula, t represents a certain moment of system operation;

[0017] When P N (t)>P W (t), P Hess >0 energy storage system discharge;

[0018] When P N (t)<P W (t), P Hess <0 Energy storage system charging;

[0019] The average value of the predicted power in each period during the effective power generation period is used as the constant output power reference value of the current period to reduce the power regulation of the power grid.

[0020] Furthermore, the S1 further comprises the following steps:

[0021] If the photovoltaic power generation power forecast value shows a continuous upward or downward trend in a certain period of time, the constant output power reference value in the effective power generation period is adjusted to a linear output power reference value that fits the change of the forecast value, so as to match the large fluctuation characteristics of the photovoltaic power generation system;

[0022] If a large-capacity energy storage system is available locally, the average value of all predicted powers during the effective power generation period will be used as a constant output power reference value to smooth out the fluctuating characteristics of the photovoltaic power generation system.

[0023] Further, the S2 is:

[0024] S21, adaptive variational mode: using an adaptive variational mode decomposition algorithm based on the photovoltaic grid-connected power fluctuation standard to adaptively determine the decomposition mode number k and the grid-connected mode number k1;

[0025] S22. Hybrid energy storage system power allocation: Use the available energy storage methods in the area where the photovoltaic power generation system is installed, and configure energy storage equipment according to local resource conditions; if the capacity of the energy storage method at the installation point can meet the requirements of photovoltaic fluctuations for power stability, no additional energy storage equipment will be configured; if it meets the requirements, a hybrid energy storage system of lead-carbon batteries and supercapacitors will be established according to the configuration requirements;

[0026] The marginal spectrum of each modal component is obtained by using a signal processing method that combines variational mode decomposition with Hilbert transform adaptively and by time integration.

[0027] According to the physical characteristics of lead-carbon batteries and supercapacitors, find the high and low frequency dividing point ω f , so that the crossover frequency ω f Adjacent modal components IMF i and IMF i+1 Minimum aliasing; for a non-periodic signal, the instantaneous energy E at a certain frequency k The formula is as follows:

[0028] E k =α k 2 *ω k 2 (4)

[0029] In the formula, α k is the instantaneous amplitude; ω k is the instantaneous power;

[0030] If two modal components have different amplitudes but the same frequency, the aliasing energy E mixing The formula is as follows:

[0031] E mixing =α i2 *ω 2 mixing +α 2 i+1 *ω 2 mixing (5)

[0032] Where i is the index of IMF; α i and α i+1 They are modal components IMF i and IMF i+1 The instantaneous amplitude of mixing is the frequency when two modal components are aliased;

[0033] Assume that the frequency corresponding to the minimum modal aliasing energy is the dividing frequency ω between high frequency and low frequency. f ; Reconstruction below ω f The intrinsic mode functions of the lead-carbon battery are reconstructed to be higher than ω f The intrinsic mode function of and assigned to the supercapacitor is expressed as follows:

[0034]

[0035] Where P b is the lead-carbon battery power; P c is the supercapacitor power; k is the grid-connected mode number; f is the boundary frequency point between high frequency and low frequency;

[0036] S23. Hybrid energy storage system capacity configuration

[0037] The value range of the state of charge (SOC) of the energy storage battery is 0 to 1. When SOC = 0, it means that the capacity of the energy storage element is insufficient, and when SOC = 1, it means that the capacity of the energy storage element is sufficient. The calculation formula and constraints of SOC are as follows:

[0038]

[0039] SOC min ≤SOC≤SOC max (9)

[0040] In the formula, E rate is the rated capacity of the energy storage system; E d is the discharge capacity of the energy storage system; SOC max and SOC min is the maximum and minimum value of the state of charge of the energy storage system;

[0041] According to formulas (6) and (7), the power P of the lead-carbon battery and supercapacitor is obtained: b and P c, SOC at time s s The formula is as follows:

[0042]

[0043] Where SOC0 is the initial value of the energy storage system SOC; P t is the power change from 0 to sΔT;

[0044] The calculation results in the following formula:

[0045]

[0046] Determine the rated capacity of the energy storage system, the maximum value E rate The formula is as follows:

[0047]

[0048] Further, the hybrid energy storage system of lead-carbon battery-supercapacitor established in S22 is specifically as follows:

[0049] Introducing equivalent time T ET It is expressed as the following formula:

[0050]

[0051] In the formula, E s is the rated capacity of the energy storage element; P r is the rated power of the energy storage element; the equivalent time T ET is the rated power charging and discharging time of the energy storage element, and the response time T T It is the time required for a complete charge / discharge cycle of the energy storage element, which is twice the equivalent time, that is, T T =2T ET ;

[0052] The response frequency of the energy storage element ω T It is expressed as the following formula:

[0053]

[0054] Lead-carbon batteries are used to smooth out low-frequency fluctuations, and supercapacitors are used to smooth out high-frequency fluctuations. When the capacity of the lead-carbon battery-supercapacitor energy storage system is insufficient to meet the photovoltaic fluctuation compensation needs, low-frequency fluctuations are smoothed by the pumped energy storage system; high-frequency fluctuations are regulated by the flywheel energy storage system.

[0055] Furthermore, the S23 further comprises the following steps:

[0056] When the capacity of the local energy storage system cannot fully meet the fluctuation demand of the photovoltaic power generation system, the photovoltaic power generation signal is analyzed into low-frequency and high-frequency fluctuation components through adaptive variational mode decomposition technology, and the hybrid energy storage system composed of supercapacitors and lead-carbon batteries is combined to adjust the above fluctuations in a targeted manner.

[0057] Further, the S3 specifically includes the following steps:

[0058] S31. Preliminary optimization:

[0059] Based on the photovoltaic output value predicted by the existing day-ahead photovoltaic power prediction model, a constant output power reference value is formulated to preliminarily optimize the charging and discharging power of the energy storage battery in the first control cycle;

[0060] S32, SOC update and re-optimization:

[0061] According to the charging and discharging power of the energy storage battery in the last five periods of the first control cycle, the SOC is determined, and the photovoltaic power fluctuation at each moment in the second control cycle is updated;

[0062] The actual power data of the above five periods provide real-time feedback to evaluate the performance of the energy storage system and optimize the subsequent control strategy;

[0063] Combined with the existing intraday ultra-short-term photovoltaic prediction perception model, the constant output power reference value is fine-tuned;

[0064] Based on the new constant output power reference value, the advanced control strategy is used to optimize the charging and discharging power of the energy storage battery in the second control cycle;

[0065] Update the power of the five time periods that coincide with the first control cycle to reflect the latest fluctuations in photovoltaic power generation and enable a smooth transition of the energy storage charging and discharging strategy;

[0066] S33, rolling calculation:

[0067] The calculation is rolled forward sequentially until the optimization cycle is completed.

[0068] Furthermore, the energy storage resources described in S2 include electrochemical energy storage, mechanical energy storage, wind-solar complementarity, and photovoltaic complementarity.

[0069] The beneficial effects of the present invention are:

[0070] Based on the existing photovoltaic power prediction model, a constant output power reference value is formulated for each time period, which realizes the visual prediction of the photovoltaic power generation power by the power grid, and then realizes the controllable and adjustable output power of the photovoltaic power generation by the power grid, effectively solving the randomness, intermittency and uncontrollability of the photovoltaic power generation system under the influence of environmental meteorological factors. Through the time division method, the average output power of the photovoltaic power generation system in each time period is used as the constant output power reference value, which significantly reduces the power fluctuation that the energy storage system needs to adjust, thereby effectively reducing the configuration capacity required for energy storage, reducing costs, and improving the economy and operation efficiency of the system. Through the coordinated operation strategy of the light-storage joint system, the stability and controllability of the photovoltaic system are enhanced, ensuring its smooth grid connection. The present invention not only promotes the large-scale grid connection of photovoltaic power generation and improves the power grid's acceptance capacity for renewable energy, but also further improves the economic benefits of the light-storage joint system and the operation reliability of the power grid by optimizing the energy storage charging and discharging process, so that the photovoltaic power generation system has basic functions.

[0071] Other advantages, objectives and features of the present invention will be described in the following description to some extent, and to some extent, will be obvious to those skilled in the art based on the following examination and study, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below in conjunction with the accompanying drawings, wherein:

[0073] Figure 1 This is a photovoltaic grid-connected system architecture diagram according to an embodiment of the present invention;

[0074] Figure 2 The present invention is a flowchart of a method for controlling the sustainable and stable output power of a photovoltaic power generation system connected to the grid according to an embodiment of the present invention.

[0075] Figure 3 It is a time-division average power output diagram of an embodiment of the present invention;

[0076] Figure 4 It is a time-division integrated power output diagram of an embodiment of the present invention;

[0077] Figure 5 A single period average power output diagram of an embodiment of the present invention;

[0078] Figure 6 This is a schematic diagram of a rolling optimization method according to an embodiment of the present invention;

[0079] Figure 7This is a flow chart of a control strategy for a photovoltaic-storage combined system based on rolling optimization according to an embodiment of the present invention; DETAILED DESCRIPTION

[0080] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner, and the following embodiments and features in the embodiments can be combined with each other without conflict.

[0081] Among them, the drawings are only used for illustrative explanations, and they only represent schematic diagrams rather than actual pictures, and should not be understood as limitations on the present invention. In order to better illustrate the embodiments of the present invention, some parts of the drawings may be omitted, enlarged or reduced, and do not represent the size of actual products. For those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted.

[0082] The same or similar numbers in the drawings of the embodiments of the present invention correspond to the same or similar parts; in the description of the present invention, it should be understood that if the terms "upper", "lower", "left", "right", "front", "rear", etc. indicate the orientation or position relationship, they are based on the orientation or position relationship shown in the drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, the terms describing the position relationship in the drawings are only used for illustrative purposes and cannot be understood as limiting the present invention. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0083] See also Figure 1 , which is a photovoltaic grid-connected system architecture diagram of an embodiment of the present invention; a constant output power reference value is formulated through photovoltaic power prediction, and the control system compares the deviation between the actual photovoltaic output power and the constant output power reference value in real time to generate a power adjustment instruction, and controls the energy storage system to charge and discharge, and finally realizes the photovoltaic-storage combined system to be grid-connected at a constant power.

[0084] See also Figure 2 , is a flow chart of a method for controlling the sustainable and stable output of the grid-connected output power of a photovoltaic power generation system according to an embodiment of the present invention. The method for controlling the sustainable and stable output of the grid-connected output power of a photovoltaic power generation system provided by the present invention comprises the following steps:

[0085] 1. Formulate a constant output power reference value based on the photovoltaic power generation power prediction curve: optimize the photovoltaic power generation power prediction curve for each period, and calculate the average power value of each period as the reference value for sustainable and stable power output to the power grid in each period;

[0086] 2. Adaptive variational modal decomposition hybrid energy storage configuration based on existing energy storage priority: Optimal configuration of hybrid energy storage (including but not limited to electrochemical energy storage, mechanical energy storage, wind-solar hybrid, photovoltaic-photovoltaic hybrid, etc.) resources based on adaptive variational modal decomposition;

[0087] 3. Combined coordinated control of charging and discharging of photovoltaic and storage based on rolling optimization: The combined coordinated sustainable and stable power output control method of photovoltaic and storage based on rolling optimization of power reference value in different time periods executes the charging and discharging operation control strategy of energy storage resources.

[0088] 1. Establishment of constant output power reference value based on photovoltaic power generation power prediction curve

[0089] The existing day-ahead photovoltaic power prediction model is used to predict the expected output power of the photovoltaic power generation system in the next day, and the day is divided into several time periods. Since the power generation of the photovoltaic system is affected by solar radiation, the system will not generate electricity when the sun does not rise or the sun has set, so it is necessary to eliminate these periods when there is no power generation at all. After elimination, the effective power generation period in a day is obtained, and these periods are used for subsequent power dispatch and management.

[0090] Since the output power of photovoltaic power generation systems is affected by environmental meteorological factors, the changes in their output power are random, intermittent, weakly controllable and uncontrollable to the power grid, which increases the difficulty of power grid dispatching and may cause problems such as power grid fluctuations, power fluctuations and voltage over-limit, thus affecting the reliability and economic operation of the power grid. Therefore, accurate power forecasting must be used to take the average predicted power of photovoltaic power generation during the effective power generation period as the constant output power reference value P for the power that the photovoltaic-storage combined system plans to deliver to the power grid. set The photovoltaic-storage combined system uses the output value of the reference value as a benchmark to ensure that the two cooperate in output, thereby ensuring that the output power of the photovoltaic-storage combined system is known and controllable to the power grid at each time period of the day. Specifically, when the output of the photovoltaic power generation system is higher than the constant output power reference value, the energy storage absorbs this part of the power; conversely, when the output of the photovoltaic power station is lower than the constant output power reference value, the energy storage system releases the corresponding power to make the grid-connected power of the photovoltaic-storage combined system as close to the expected value as possible.

[0091] S1 specifically includes the following steps:

[0092] Assume that the grid-connected power P N With constant output power reference value P setSame, photovoltaic system output power P W And the energy storage system charging and discharging power P Hess The relationship is as follows:

[0093] P N (t) = P W (t)+P Hess (t) (1)

[0094] Where: t represents a certain moment when the system is running.

[0095] When P N (t)>P W (t), P Hess >0 energy storage system discharge;

[0096] When P N (t)<P W (t), P Hess <0Energy storage system charging.

[0097] See also Figure 3 , which is a time-divided average power output diagram of an embodiment of the present invention; by taking the average value of the predicted power in each time period within the effective power generation period as the constant output power reference value of the current time period, the grid can visually predict the photovoltaic power generation power, thereby realizing the grid's controllable and adjustable photovoltaic power generation output power. Through the time-divided method, the power fluctuations that need to be adjusted by the energy storage system are significantly reduced, thereby effectively reducing the configuration capacity required for energy storage. According to the local lighting conditions and the needs of the power grid, the number of time periods and the length of each time period can be flexibly determined, and more detailed divisions can be made during the periods of drastic fluctuations in photovoltaic power generation to achieve optimal energy storage configuration and power regulation, ensuring that the system can adapt to the needs under different conditions.

[0098] See also Figure 4 , which is a time-divided comprehensive power output diagram of an embodiment of the present invention; if the predicted value of photovoltaic power generation in a certain period roughly shows a continuous upward or downward trend, the constant output power reference value of the period can be adjusted to a linear output power reference value (slanted line) that fits the change of the predicted value. The linear output power reference value can more accurately match the changing characteristics of photovoltaic power generation with large fluctuations, reducing the regulation pressure of the energy storage system.

[0099] See also Figure 5, which is a single-time period average power output diagram of an embodiment of the present invention; taking the average value of all predicted powers within the effective power generation period as the constant output power reference value can effectively smooth the volatility of the photovoltaic power generation system, achieve continuous stability in the output power of the photovoltaic-storage combined system, and reduce the frequent demand for power regulation by the power grid, thereby improving the stability and operating efficiency of the power grid. This method simplifies the power regulation strategy, improves the synergy between the photovoltaic power generation system and the power grid, and enables the photovoltaic power generation system to have the capacity of a base load power plant to a certain extent. However, due to the power fluctuation characteristics of photovoltaic power generation, power gaps or surpluses may occur in some periods, thereby increasing the capacity demand of the energy storage system. If a large-capacity pumped storage system is available locally, the single-time period method is feasible under certain conditions.

[0100] 2. Adaptive variational mode decomposition hybrid energy storage configuration method based on existing energy storage priority

[0101] Since the output fluctuation of photovoltaic power generation is seasonal, daily cyclical and climate-related, the capacity demand adjustment strategy required for energy storage configuration can be extracted through the analysis of historical data, especially the analysis of photovoltaic power generation data on typical days, and provide reference for other similar dates. By combining adaptive variational mode decomposition technology, the configuration requirements of the energy storage system can be extracted, and appropriate energy storage equipment can be selected for different fluctuation frequency bands. In this way, photovoltaic power fluctuations can be effectively smoothed and the photovoltaic grid-connected power fluctuation standards can be met.

[0102] 2.1 Adaptive variational modes

[0103] Variational mode decomposition uses the alternating direction multiplier method, which has good local optimization effects in noise resistance and processing of non-steady-state burst signals, and is suitable for smoothing the fluctuation of photovoltaic power. However, the decomposition mode number k of the traditional variational mode decomposition algorithm is artificially determined and has great subjectivity. An unreasonable decomposition mode number k will cause under-decomposition or over-decomposition of photovoltaic power generation, affecting the grid-connected effect. In addition, the traditional variational mode decomposition algorithm only uses the first modal component obtained by decomposition, that is, k1, without considering the influence of the remaining components on the results. When smoothing the fluctuation of photovoltaic power, it may cause low grid-connected power and increase the power of the hybrid energy storage system. After optimizing the grid-connected mode number k1, if the grid-connected mode number k1 is too small, the capacity of the hybrid energy storage system will increase; if the grid-connected mode number k1 is too large, it will lead to unsatisfactory smoothing of photovoltaic power and will not meet the standard of photovoltaic grid-connected power fluctuation.

[0104] Therefore, the present invention adopts an adaptive variational modal decomposition algorithm based on the photovoltaic grid-connected power fluctuation standard, which can adaptively determine the decomposition mode number k and the grid-connected mode number k1, thereby ensuring the grid-connected power while obtaining good decomposition results.

[0105] 2.2 Power distribution of hybrid energy storage system

[0106] The present invention gives priority to using available energy storage methods in the area where the photovoltaic power generation system is installed, and configures appropriate energy storage equipment according to local resource conditions. Priority is given to locally deployed energy storage methods, such as pumped storage, flywheel storage, or other local unique energy storage methods, and observes whether their capacity meets the fluctuation requirements of the photovoltaic system. If the capacity of the local energy storage method can meet the requirements of photovoltaic fluctuations for power stability, no additional energy storage equipment is configured. On the contrary, according to the configuration requirements, a hybrid energy storage system of lead-carbon batteries and supercapacitors is established.

[0107] Lead-carbon batteries and supercapacitors have different working characteristics. In order to quantify the characteristics of energy storage components and form a unified index, the equivalent time T is introduced. ET It is expressed as the following formula:

[0108]

[0109] In the formula, E s is the rated capacity of the energy storage element; P r is the rated power of the energy storage element.

[0110] T ET It is the rated power charging and discharging time of the energy storage element. Response time T T It is the time required for a complete charge / discharge cycle of the energy storage element, which is twice the equivalent time, that is, T T =2T ET .

[0111] The response frequency of the energy storage element ω T It is expressed as the following formula:

[0112]

[0113] The response frequency and response time of the energy storage element are inversely proportional, and the response time is equal to twice the equivalent time. Therefore, low-frequency fluctuations are smoothed by energy storage elements with long response times, and high-frequency fluctuations are smoothed by energy storage elements with short response times. According to the characteristics of the two energy storage elements, lead-carbon batteries are used to smooth low-frequency fluctuations, and supercapacitors are used to smooth high-frequency fluctuations. When the capacity of the lead-carbon battery-supercapacitor energy storage system is insufficient to meet the demand for photovoltaic fluctuation compensation, low-frequency fluctuations are smoothed by pumped energy storage and the like. High-frequency fluctuations are regulated by flywheel energy storage and other systems.

[0114] VHT (VMD-Hilbert) is a signal processing method that adaptively combines variational mode decomposition (VMD) with Hilbert transform. Through time integration, the marginal spectrum of each modal component can be obtained.

[0115] According to the physical characteristics of lead-carbon batteries and supercapacitors, find a suitable high and low frequency dividing point ω f , so that the crossover frequency ω f Adjacent modal components IMF i and IMF i+1 The aliasing (the phenomenon that high-frequency components in the signal are mistakenly interpreted as low-frequency components during the sampling process) is minimized. The concept of signal energy is introduced. The signal energy method is a method that uses frequency to extract energy-based features from a signal. For a non-periodic signal, the instantaneous energy E at a certain frequency is k The formula is as follows:

[0116] E k =α k 2 *ω k 2 (4)

[0117] Where: α k is the instantaneous amplitude; ω k is the instantaneous power.

[0118] If two modal components have different amplitudes but the same frequency, the aliasing energy E mixing The formula is as follows:

[0119] E mixing =α i 2 *ω 2 mixing +α 2 i+1 *ω 2 mixing (5)

[0120] Where: i is the index of IMF; α i and α i+1 They are modal components IMF i and IMF i+1 The instantaneous amplitude of mixing is the frequency at which the two modal components alias.

[0121] In order to separate the low-frequency fluctuation component of the lead-carbon battery and the high-frequency fluctuation component of the supercapacitor and reduce aliasing as much as possible, the modal aliasing energy must be as small as possible. The frequency corresponding to the minimum modal aliasing energy is the dividing frequency between high frequency and low frequency ω f Therefore, as shown in the following formulas (6) and (7), the reconstruction is lower than ω f The intrinsic mode functions of the lead-carbon battery are reconstructed to be higher than ω f The intrinsic mode function of and assigned to the supercapacitor is expressed as follows:

[0122]

[0123] Where: P b is the lead-carbon battery power; P c is the supercapacitor power; k is the grid-connected mode number; f is the boundary frequency point between high frequency and low frequency.

[0124] 2.3 Hybrid Energy Storage System Capacity Configuration

[0125] The state of charge (SOC) of the energy storage battery is an important parameter in the hybrid energy storage system, reflecting the ratio of the remaining power to the power in the fully charged state. Reasonable SOC can effectively reduce the deep charge and discharge phenomenon of the energy storage components and extend the service life of the energy storage components while meeting the photovoltaic grid-connected fluctuation standards. The SOC value range is 0 to 1. When SOC = 0, it means that the energy storage component capacity is insufficient, and when SOC = 1, it means that the energy storage component capacity is sufficient. The calculation formula and constraints of SOC are as follows:

[0126]

[0127] SOC min ≤SOC≤SOC max (9)

[0128] Where: E rate is the rated capacity of the energy storage system; E d is the discharge capacity of the energy storage system; SOC max and SOC min It is the maximum and minimum value of the state of charge of the energy storage system.

[0129] According to formulas (6) and (7), the power P of the lead-carbon battery and supercapacitor can be obtained: b and P c , SOC at time s s The formula is as follows:

[0130]

[0131] Where: SOC0 is the initial SOC value of the energy storage system; P t is the power change from 0 to sΔT.

[0132] Combining the above calculations, we can get the following formula:

[0133]

[0134] The rated capacity of the energy storage system is determined by the following formula:

[0135]

[0136] When the capacity of the local energy storage system cannot fully meet the fluctuation demand of the photovoltaic power generation system, the photovoltaic power generation signal is analyzed through the adaptive variational mode decomposition technology, decomposed into low-frequency and high-frequency fluctuation components, and combined with a hybrid energy storage system consisting of supercapacitors and lead-carbon batteries to adjust these fluctuations in a targeted manner. In this process, supercapacitors can be used for rapid response to high-frequency fluctuations, while lead-carbon batteries are responsible for smooth regulation of low-frequency fluctuations. Ultimately, combined with the capacity of local energy storage facilities and the supplement of the hybrid energy storage system, it is ensured that the photovoltaic power generation system maintains a stable output power when its output power fluctuates intermittently and randomly due to environmental changes, thereby improving the reliability and stability of the power grid.

[0137] 3. Photovoltaic-storage integrated coordinated control method based on rolling optimization

[0138] In the coordinated operation of the photovoltaic-storage combined system, the rolling optimization method is used to forward the charge and discharge control strategy of the advanced mode energy storage. The rolling optimization method rolls the plan forward one cycle each time the plan is compiled, organically connecting the various stages in the plan cycle and the pre-arrangements for the next period, and regularly adjusts and supplements it, solving the connection problem of the plans at each stage, timely correcting the errors in the control process, and better coordinating the relative stability of the plan with the variability of the actual situation, so that the plan can more effectively guide the actual operation, which is of great significance to ensure the smooth completion of the project.

[0139] The rolling optimization method is different from the traditional optimization method. The optimization target of the latter is usually fixed, while the optimization target of the rolling optimization method at each moment is only related to a specific period in the future. As time goes by, this specific period continues to move forward, and the target value is also updated accordingly. Based on the advanced perception method, the dynamic behavior of all moments in the future specific period can be obtained at each moment, and only the model state at the current moment is adjusted. At the next moment, the new control action is implemented using the latest measured data to continuously roll and correct the actual state of the model. See Figure 6 , is a schematic diagram of a rolling optimization method according to an embodiment of the present invention; in the figure, T O is the rolling step length, T P is the control period, T is the optimization interval length. Set the rolling step length T O Equal to the original photovoltaic power collection frequency (10 minutes in the figure), the control period T P Equal to the photovoltaic power prediction period (1 hour in the figure), the optimization period is one day. Figure 7 , is a flow chart of the control strategy of the photovoltaic-storage combined system based on rolling optimization according to an embodiment of the present invention. The calculation steps of the rolling optimization method are as follows:

[0140] (1) Preliminary optimization: Based on the photovoltaic output value predicted by the existing day-ahead photovoltaic power prediction model, a constant output power reference value is formulated to perform preliminary optimization on the charging and discharging power of the energy storage battery in the first control cycle, ensuring the stability of the output power of the photovoltaic-storage combined system at all times in the cycle and achieving effective output of the photovoltaic-storage combined system.

[0141] (2) SOC update and re-optimization: Based on the energy storage battery charge and discharge power in the five time periods after the first control cycle, the state of the energy storage battery (SOC) is determined, and the photovoltaic power fluctuations at each moment in the second control cycle are updated. The actual power data in these five time periods provides real-time feedback to help evaluate the performance of the energy storage system and optimize subsequent control strategies. At the same time, combined with the existing intraday ultra-short-term photovoltaic prediction perception model, the constant output power reference value is fine-tuned. Based on the new constant output power reference value, the advanced control strategy is used to optimize the energy storage battery charge and discharge power in the second control cycle. The power of the five time periods overlapping with the first control cycle is updated to more accurately reflect the latest fluctuations in photovoltaic power generation, so that the energy storage charge and discharge strategy can be smoothly transitioned to ensure continuous and stable power.

[0142] (3) Rolling calculation: Roll forward the calculation in sequence until the end of the optimization cycle. The rolling optimization method has the characteristics of accuracy, continuity, adaptability and effectiveness. During the coordinated operation of the photovoltaic-storage combined system, the rolling optimization method is used to continuously correct the charging and discharging power of the energy storage battery, thereby ensuring that the corresponding photovoltaic-storage combined system power remains stable in each time period. By continuously updating the photovoltaic predicted power, the charging and discharging behavior of the energy storage battery can timely reflect the fluctuation of photovoltaic power generation, reduce the fluctuation amplitude and discharge depth of the energy storage system, so as to better play the advantages of predictive control, smooth the photovoltaic-storage combined power during the optimization period, meet the grid-connected power fluctuation limit requirements, and improve the dynamic stability of the power system.

[0143] The present invention predicts the output power of the photovoltaic power generation system in the next day based on the existing day-ahead photovoltaic power prediction model. A day is divided into several time periods, and the time period without power generation (before the sun rises or after the sun sets) is eliminated to obtain the effective power generation time period. After obtaining the effective power generation time period, the average value of the power generation power predicted in the effective power generation time period is used as the constant output power reference value for the light-storage combined system to stably transmit power to the power grid in the current time period. At the same time, combined with the existing intraday ultra-short-term photovoltaic power perception model, the constant output power reference value is fine-tuned in different time periods. Using the integrated light-storage joint coordinated control method, the output of the energy storage system is optimized to ensure that the light-storage combined system can continuously output a stable power in different time periods, and suppress the intermittent random fluctuation of the grid-connected output power of the photovoltaic power generation system under the influence of environmental meteorological factors, so as to achieve the purpose of improving the grid-connected characteristics of the photovoltaic power generation system and maintaining the power balance of the power grid, ensure the safe operation of the power grid, and realize the visual prediction of the photovoltaic power generation output for the power grid, so that it is possible to adjust and control it.

[0144] Through the present invention, on the basis of existing photovoltaic power prediction, it is possible to achieve visual foresight of grid-connected power, and through the charging and discharging of energy storage (including but not limited to battery energy storage, pumped energy storage, flywheel energy storage, wind-solar complementarity, light-photovoltaic complementarity, etc.), continuous, stable and controllable output power can be achieved, so that the photovoltaic power generation system has some basic functions of an ordinary power plant, so as to solve the problem of the intermittent random changes in the grid-connected output power of the photovoltaic power generation system affected by environmental meteorological factors, which has an impact on the safe operation of the power grid, and the problem of large-scale access of photovoltaic power generation to the power grid.

[0145] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution, which should be included in the scope of the claims of the present invention.

Claims

1. A method for controlling the sustainable and stable output power of a photovoltaic power generation system connected to the grid, characterized in that: The following steps are involved: S1. Formulate a constant output power reference value based on the photovoltaic power generation power prediction curve: optimize the photovoltaic power generation power prediction curve for each period, and calculate the average power value of each period as a reference value for sustainable and stable power output to the power grid in each period; S2. Adaptive variational modal decomposition hybrid energy storage configuration based on existing energy storage priority: Optimal configuration of hybrid energy storage resources based on adaptive variational modal decomposition; S3. Combined coordinated control of charging and discharging of photovoltaic and storage based on rolling optimization: A method for controlling the sustainable and stable power output of photovoltaic and storage integrated joint coordination in different time periods based on the rolling optimization of power reference values ​​to execute the charging and discharging operation control of energy storage resources.

2. The method for controlling the sustainable and stable output power of the photovoltaic power generation system connected to the grid according to claim 1, characterized in that: S1 is: during the effective power generation period, the average value of the predicted power of photovoltaic power generation is used as the constant output power reference value P of the photovoltaic-storage combined system to transmit power to the power grid. set ; When the output of the photovoltaic power generation system is higher than P set When the output of the photovoltaic power station is lower than P set When the energy storage system releases the corresponding power, the grid-connected power of the solar-storage combined system is close to the expected value.

3. The method for controlling the sustainable and stable output power of the photovoltaic power generation system connected to the grid according to claim 2, characterized in that: The S1 specifically includes the following steps: Assume that the grid-connected power P N With constant output power reference value P set Same, photovoltaic system output power P W And the energy storage system charging and discharging power P Hess The relationship is expressed as the following formula: P N (t)=P W (t)+P Hess (t) (1) In the formula, t represents a certain moment of system operation; When P N (t)>P W (t), P Hess >0 energy storage system discharge; When P N (t)<P W (t), P Hess <0 Energy storage system charging; The average value of the predicted power in each period during the effective power generation period is used as the constant output power reference value of the current period to reduce the power regulation of the power grid.

4. The method for controlling the sustainable and stable output power of the photovoltaic power generation system connected to the grid according to claim 3 is characterized in that: The S1 further comprises the following steps: If the photovoltaic power generation power forecast value shows a continuous upward or downward trend in a certain period of time, the constant output power reference value in the effective power generation period is adjusted to a linear output power reference value that fits the change of the forecast value, so as to match the large fluctuation characteristics of the photovoltaic power generation system; If a large-capacity energy storage system is available locally, the average value of all predicted powers during the effective power generation period will be used as a constant output power reference value to smooth out the fluctuating characteristics of the photovoltaic power generation system.

5. The method for controlling the sustainable and stable output power of the photovoltaic power generation system connected to the grid according to claim 1, characterized in that: The S2 is: S21, adaptive variational mode: using an adaptive variational mode decomposition algorithm based on the photovoltaic grid-connected power fluctuation standard to adaptively determine the decomposition mode number k and the grid-connected mode number k1; S22. Hybrid energy storage system power allocation: Use the available energy storage methods in the area where the photovoltaic power generation system is installed, and configure energy storage equipment according to local resource conditions; if the capacity of the energy storage method at the installation point can meet the requirements of photovoltaic fluctuations for power stability, no additional energy storage equipment will be configured; if it meets the requirements, a hybrid energy storage system of lead-carbon batteries and supercapacitors will be established according to the configuration requirements; The marginal spectrum of each modal component is obtained by using a signal processing method that combines variational mode decomposition with Hilbert transform adaptively and by time integration. According to the physical characteristics of lead-carbon batteries and supercapacitors, find the high and low frequency dividing point ω f , so that the crossover frequency ω f Adjacent modal components IMF i and IMF i+1 Minimum aliasing; for a non-periodic signal, the instantaneous energy E at a certain frequency k The formula is as follows: E k =a k 2 *oh k 2 (4) In the formula, α k is the instantaneous amplitude; ω k is the instantaneous power; If two modal components have different amplitudes but the same frequency, the aliasing energy E mixing The formula is as follows: E mixing =a i 2 *oh 2 mixing +a 2 i+1 *oh 2 mixing (5) Where i is the index of IMF; α i and α i+1 They are modal components IMF i and IMF i+1 The instantaneous amplitude of mixing is the frequency when two modal components are aliased; Assume that the frequency corresponding to the minimum modal aliasing energy is the dividing frequency ω between high frequency and low frequency. f ; Reconstruction below ω f The intrinsic mode functions of the lead-carbon battery are reconstructed to be higher than ω f The intrinsic mode function of and assigned to the supercapacitor is expressed as follows: Where P b is the lead-carbon battery power; P c is the supercapacitor power; k is the grid-connected mode number; f is the boundary frequency point between high frequency and low frequency; S23. Hybrid energy storage system capacity configuration The value range of the state of charge (SOC) of the energy storage battery is 0 to 1. When SOC = 0, it means that the capacity of the energy storage element is insufficient, and when SOC = 1, it means that the capacity of the energy storage element is sufficient. The calculation formula and constraints of SOC are as follows: SOC min ≤SOC≤SOC max (9) In the formula, E rate is the rated capacity of the energy storage system; E d is the discharge capacity of the energy storage system; SOC max and SOC min is the maximum and minimum value of the state of charge of the energy storage system; According to formulas (6) and (7), the power P of the lead-carbon battery and supercapacitor is obtained: b and P c , SOC at time s s The formula is as follows: Where SOC0 is the initial value of the energy storage system SOC; P t is the power change from 0 to sΔT; The calculation results in the following formula: Determine the rated capacity of the energy storage system, the maximum value E rate The formula is as follows:

6. The method for controlling the sustainable and stable output power of the photovoltaic power generation system connected to the grid according to claim 5, characterized in that: The hybrid energy storage system of lead-carbon battery-supercapacitor established in S22 is specifically as follows: Introducing equivalent time T ET It is expressed as the following formula: In the formula, E s is the rated capacity of the energy storage element; P r is the rated power of the energy storage element; the equivalent time T ET is the rated power charging and discharging time of the energy storage element, and the response time T T It is the time required for a complete charge / discharge cycle of the energy storage element, which is twice the equivalent time, that is, T T =2T ET ; The response frequency of the energy storage element ω T It is expressed as the following formula: Lead-carbon batteries are used to smooth out low-frequency fluctuations, and supercapacitors are used to smooth out high-frequency fluctuations. When the capacity of the lead-carbon battery-supercapacitor energy storage system is insufficient to meet the photovoltaic fluctuation compensation needs, low-frequency fluctuations are smoothed by the pumped energy storage system; high-frequency fluctuations are regulated by the flywheel energy storage system.

7. The method for controlling the sustainable and stable output power of the photovoltaic power generation system connected to the grid according to claim 5, characterized in that: The S23 also The following steps are involved: When the capacity of the local energy storage system cannot fully meet the fluctuation demand of the photovoltaic power generation system, the photovoltaic power generation signal is analyzed into low-frequency and high-frequency fluctuation components through adaptive variational mode decomposition technology, and the hybrid energy storage system composed of supercapacitors and lead-carbon batteries is combined to adjust the above fluctuations in a targeted manner.

8. The method for controlling the sustainable and stable output power of the photovoltaic power generation system connected to the grid according to claim 1, characterized in that: The S3 specifically The following steps are involved: S31. Preliminary optimization: Based on the photovoltaic output value predicted by the existing day-ahead photovoltaic power prediction model, a constant output power reference value is formulated to preliminarily optimize the charging and discharging power of the energy storage battery in the first control cycle; S32, SOC update and re-optimization: According to the charging and discharging power of the energy storage battery in the last five periods of the first control cycle, the SOC is determined, and the photovoltaic power fluctuation at each moment in the second control cycle is updated; The actual power data of the above five periods provide real-time feedback to evaluate the performance of the energy storage system and optimize the subsequent control strategy; Combined with the existing intraday ultra-short-term photovoltaic prediction perception model, the constant output power reference value is fine-tuned; Based on the new constant output power reference value, the advanced control strategy is used to optimize the charging and discharging power of the energy storage battery in the second control cycle; Update the power of the five time periods that coincide with the first control cycle to reflect the latest fluctuations in photovoltaic power generation and enable a smooth transition of the energy storage charging and discharging strategy; S33, rolling calculation: The calculation is rolled forward sequentially until the optimization cycle is completed.

9. The method for controlling the sustainable and stable output power of the photovoltaic power generation system connected to the grid according to claim 1, characterized in that: The energy storage resources described in S2 include electrochemical energy storage, mechanical energy storage, wind-solar complementarity, and photovoltaic complementarity.

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