A power smoothing control method applied to a chain drive gravity energy storage system

Abstract

The application discloses a power smoothing control method applied to a chain drive gravity energy storage system, and the method comprises the following steps: collecting active power of a grid-side grid-connected point, flywheel rotating speed and data of a load vehicle. Based on a system physical model, real-time active power and data of the load vehicle, a total fluctuation power prediction sequence containing multiple superimposed fluctuations in a future period of time is predicted, and the total fluctuation power prediction sequence is updated and iterated according to historical measured power data. According to the current flywheel rotating speed and the predicted fluctuation power, the flywheel optimal rotating speed sequence for smoothing the grid-connected power of the whole hybrid energy storage system in the future period of time is calculated. The flywheel energy storage device is adjusted according to the flywheel optimal rotating speed sequence, and corresponding compensation power is output to the grid, so that power balance is realized. Through the use of the application, the total fluctuation power containing multiple superimposed fluctuations of the system can be actively predicted and precisely compensated in advance, and high-quality smooth output of the grid-connected power is realized. The application can be widely applied to the technical field of new energy storage and smart grid.

Description

Technical Field

[0001] This invention relates to the field of new energy storage and smart grid technology, and in particular to a power smoothing control method applied to a chain-driven gravity energy storage system. Background Technology

[0002] Gravity energy storage, as a novel physical energy storage method, boasts advantages such as long lifespan, high safety, and environmental friendliness. One approach, employing a chain-driven mechanism to circulate and pull a loaded trolley, enables continuous energy storage and release. However, this energy storage system inherently suffers from power fluctuations during operation, primarily stemming from: the inherent "polygonal effect" of the chain drive causing high-frequency periodic fluctuations in transmission speed and load; and changes in the number of loaded trolleys operating on the inclined track causing step fluctuations in the total system load, resulting in low-frequency power surges. These fluctuations, transmitted to the motor, lead to continuous fluctuations in active power output to the grid, severely impacting power quality and grid stability.

[0003] To address power fluctuations during system operation, existing technologies employ flywheels or supercapacitors as auxiliary energy storage devices. By monitoring active power data at the grid connection point in real time, when a power deviation is detected, the auxiliary energy storage device is controlled to absorb or release energy accordingly to maintain stable grid-connected power. However, this method suffers from response lag, offering limited compensation for high-frequency periodic power fluctuations (such as those caused by polygonal effects), and is also ill-equipped to handle rapid step power changes. Summary of the Invention

[0004] In view of this, in order to solve the technical problem that most existing power compensation methods applied to chain-driven gravity energy storage systems adjust after detecting power deviation, resulting in response lag, this invention proposes a power smoothing control method for chain-driven gravity energy storage systems, which includes the following steps:

[0005] Real-time monitoring: Collect active power, flywheel speed and load data of the grid connection point on the power grid side.

[0006] Fluctuation prediction: Based on the system physical model, real-time active power and heavy vehicle data, predict the total fluctuation power sequence containing multiple superimposed fluctuations over a period of time, and update and iterate it based on historical measured power data.

[0007] Speed ​​optimization: Based on the current flywheel speed and the predicted fluctuating power, calculate the optimal flywheel speed sequence to smooth the grid-connected power of the entire hybrid energy storage system over a period of time.

[0008] Power compensation: Adjust the flywheel energy storage device according to the optimal flywheel speed sequence to output corresponding compensation power to the power grid and achieve power balance.

[0009] Based on the above scheme, this invention provides a power smoothing control method for chain-driven gravity energy storage systems. It calculates the power fluctuations of the chain-driven gravity energy storage system over a future period using a power fluctuation prediction module, and employs a model predictive control algorithm to calculate the flywheel compensation power and optimal speed sequence, thus avoiding the lag in flywheel energy storage compensation for system power fluctuations. This shifts from a "passive response" to "active cancellation," smoothing the grid-connected operating power of the hybrid energy storage system and effectively solving the power fluctuation problem during the operation of chain-driven gravity energy storage systems. Attached Figure Description

[0010] Figure 1 This is a flowchart of the steps of a power smoothing control method applied to a chain-driven gravity energy storage system according to the present invention;

[0011] Figure 2 This is a partial structural schematic diagram of a chain-driven gravity energy storage system according to a specific embodiment of the present invention. Detailed Implementation

[0012] In existing technologies, power fluctuations still occur during the operation of chain-driven gravity energy storage systems. These fluctuations manifest as the superposition of different frequency components, including periodic fluctuations and step changes, which affect the continuity and stability of the system's output power.

[0013] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0014] It should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this application can be combined with each other.

[0015] It should be understood that the terms "system," "apparatus," "unit," and / or "module" used in this application are a method of distinguishing different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

[0016] Unless the context explicitly indicates an exception, words such as "a," "an," "a kind," and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list; a method or apparatus may also include other steps or elements. An element defined by the phrase "comprising a..." does not exclude the presence of other identical elements in the process, method, product, or apparatus that includes the element.

[0017] In the description of the embodiments of this application, "a plurality of" refers to two or more. The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature.

[0018] Furthermore, flowcharts are used in this application to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, the steps can be processed in reverse order or simultaneously. Additionally, other operations can be added to these processes, or one or more steps can be removed from them.

[0019] Reference Figure 1 This is a schematic flowchart of an optional example of the power smoothing control method for a chain-driven gravity energy storage system proposed in this invention. This method can be applied to computer equipment, and the control method proposed in this embodiment may include, but is not limited to, the following steps:

[0020] S0, System initialization;

[0021] S1. Real-time acquisition of active power data, flywheel speed, and truck data at the grid connection point of the chain-driven gravity energy storage system;

[0022] S2. Based on the physical model of the chain-driven gravity energy storage system, active power data, and truck data, calculate the total fluctuation power prediction sequence.

[0023] S3. Calculate the optimal speed sequence of the flywheel based on the predicted sequence of flywheel speed and total ripple power;

[0024] S4. Control the flywheel energy storage device in the chain drive gravity energy storage system according to the optimal flywheel speed sequence and output compensation power;

[0025] S5. Repeat steps S1 to S4 to continuously update the compensation power output of the flywheel energy storage device.

[0026] In particular, the gravity energy storage part of the chain-driven gravity energy storage system in the specific embodiment of the present invention refers to... Figure 2 The working process is as follows: A motor drives a sprocket to rotate, which in turn drives a chain, pulling a heavy-duty vehicle carrying a load up a slope. During this process, electrical energy from the grid is converted into the gravitational potential energy of the load and the vehicle, constituting energy storage. As the load and vehicle move down the slope, the chain drives the sprocket to reverse direction, which in turn reverses the motor, supplying power to the grid. During this process, the gravitational potential energy of the load and vehicle is converted into electrical energy, constituting energy release. During both energy storage and release, the power output of the chain-driven gravity energy storage system exhibits periodic fluctuations. By adjusting the flywheel speed using predicted compensation power, the periodic power fluctuations of the chain-driven gravity energy storage system are compensated, thus smoothing the grid-connected power of the entire system.

[0027] In some feasible embodiments, step S1 specifically includes:

[0028] Input system parameters: slope angle Length of slope Slope height sprocket radius Number of sprocket teeth sprocket tooth angle The overall mass of the truck and the heavy-duty truck The linear speed of the truck flywheel moment of inertia ideal operating point of flywheel The flywheel speed range is The flywheel power range is The weighting coefficient for the power tracking term is set to Weight coefficient of state penalty term Control action penalty coefficient The flywheel speed control cycle is The initial speed of the sprocket is Initial number of trucks Initial speed of the flywheel .

[0029] In some feasible embodiments, step S2 specifically includes:

[0030] "Active power data" refers to the instantaneous active power value measured at the grid connection point of the chain-driven gravity energy storage system connected to the public power grid, which reflects the actual power output of the hybrid energy storage system to the grid; "flywheel speed" refers to the angular velocity of the rotating body in the flywheel energy storage device at the current moment, in rad / s or r / min, used to characterize the current kinetic energy level stored in the flywheel; "cargo vehicle data" includes the number, location, linear velocity, and time information of the entry and exit of the inclined track of the cargo vehicles, used to characterize the current mechanical motion state and energy release / absorption trend of the gravity energy storage subsystem; the three types of data together constitute the observable input set of the real-time operating state of the system, providing basic data support for subsequent fluctuation modeling and compensation decisions.

[0031] The calculation process for the final total fluctuation power prediction is as follows:

[0032]

[0033] in, This represents the final predicted total fluctuation power. This represents the measured total grid-connected power, i.e., the active power data of the grid-side grid connection point of the chain-driven gravity energy storage system collected in step S1; This refers to the low-frequency step power fluctuation when a truck enters or leaves the working ramp section. This refers to the high-frequency power fluctuations caused by the "polygonal effect" in chain drives.

[0034] The final total fluctuation power prediction value will be used for subsequent calculation of the optimal flywheel speed;

[0035] High-frequency power fluctuations caused by the polygonal effect in chain drives The specific calculation method is as follows:

[0036]

[0037] in, This represents the amplitude of the high-frequency oscillation. The frequency of high-frequency oscillations. For phase;

[0038] Amplitude of high frequency oscillation The specific calculation method is as follows:

[0039]

[0040] in, For the number of trucks, For the mass of the truck and the heavy object, It is the acceleration due to gravity. To maintain a constant angular velocity of the sprocket during system operation, The sprocket pitch circle radius; This is the engagement phase angle; The tooth angle;

[0041] The frequency of high-frequency oscillation is:

[0042]

[0043] in, The sprocket speed, This represents the number of sprocket teeth.

[0044]

[0045] in, For the overall weight of the truck, This is the transmission efficiency coefficient. For the running linear velocity, The slope angle is denoted by .

[0046] In addition, the total grid-connected power during operation It can also be calculated in the following ways:

[0047]

[0048] in, To provide a reference power output for gravity-based energy storage that ignores power fluctuations, This includes fluctuating power that contains both high and low frequencies. For the flywheel in The actual compensation power at any given time;

[0049] The predicted total fluctuating power of the chain-driven gravity energy storage system over the next period is as follows:

[0050] ;

[0051] It should be noted that the relevant sequence is a series of data corresponding to the values.

[0052] This embodiment achieves structured modeling of the causes of power fluctuations by integrating physical models and real-time measurement data without requiring a large number of labeled samples. This makes the prediction results both mechanisticly reliable and timely, providing traceable and verifiable prior information on disturbances for flywheel compensation strategies.

[0053] In some feasible embodiments, step S3 specifically includes:

[0054] The objective function for calculating the optimal flywheel speed sequence to smooth the grid-connected power of the entire hybrid energy storage system over a future period, using a model predictive control algorithm, is as follows:

[0055]

[0056] in, For grid-connected power setting value, For prediction The flywheel compensation speed at any given moment, The ideal operating speed of the flywheel. express The theoretical compensation power of the flywheel at any given moment. express The theoretical compensation power of the flywheel at any given moment. These are the weighting coefficients for the power tracking term. The weight coefficient for the state penalty term. To control the coefficient of the action penalty term, To predict the step size.

[0057] Its relevant constraints include:

[0058] Flywheel speed constraint:

[0059]

[0060] Flywheel power constraints:

[0061]

[0062] Flywheel dynamics constraints:

[0063]

[0064] The flywheel speed prediction module iteratively solves for the optimal flywheel speed sequence, including error compensation, over a future period to smooth the grid-connected power of the entire hybrid energy storage system, resulting in... Optimal flywheel speed sequence within a step , , .

[0065] This embodiment incorporates the current flywheel state and disturbance prediction into the optimization framework, enabling the flywheel compensation strategy to combine feedforward initiative and feedback robustness, avoiding response lag caused by relying solely on error feedback, and improving the collaborative suppression capability against composite frequency fluctuations.

[0066] In some feasible embodiments, step S4 specifically includes:

[0067] Will As the speed control command at the current moment;

[0068] The speed of the flywheel energy storage device is controlled according to the speed command, so that its output power compensation smooths the power fluctuation of the chain-driven gravity energy storage system.

[0069] The flywheel energy storage device operates under two different conditions based on the instantaneous power of the chain-driven gravity energy storage system, including:

[0070] Energy release condition, at this time The flywheel decelerates and releases kinetic energy to compensate for the insufficient power of the chain drive's gravity-stored energy.

[0071] Energy storage operating conditions, at this time The flywheel accelerates and absorbs kinetic energy, absorbing excess power stored in gravity by the chain drive.

[0072] in, This indicates the actual power of the flywheel.

[0073] The instantaneous rate of change of the flywheel kinetic energy with respect to time during the change of flywheel speed is:

[0074] .

[0075] This embodiment precisely maps high-level optimization instructions to low-level actuators, forming a "prediction-decision-execution" closed loop. This upgrades the flywheel energy storage device from a passive energy storage unit to an active power regulator, ultimately achieving full-frequency, high-precision, fast-response smooth control of grid-connected power fluctuations in the chain-driven gravity energy storage system.

[0076] A storage medium storing processor-executable instructions, which, when executed by a processor, are used to implement a power smoothing control method for a chain-driven gravity energy storage system as described above.

[0077] The content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0078] The above is a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the embodiments described. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of this application.

Claims

1. A power smoothing control method applied to a chain-driven gravity energy storage system, characterized in that, Includes the following steps: S1. Real-time acquisition of active power data, flywheel speed, and truck data at the grid connection point of the chain-driven gravity energy storage system; S2. Based on the physical model of the chain-driven gravity energy storage system, the active power data, and the truck data, calculate the total fluctuation power prediction sequence; S3. Calculate the optimal flywheel speed sequence based on the flywheel speed and the total fluctuation power prediction sequence; S4. Control the flywheel energy storage device in the chain drive gravity energy storage system according to the optimal flywheel speed sequence, and output compensation power; The calculation process of the total fluctuation power prediction sequence specifically includes: in, This represents the predicted total fluctuation power, which includes the superposition of multiple fluctuations. Indicates time, This indicates the total power measured at the grid connection point. This indicates the high-frequency power fluctuations caused by the polygonal effect in chain drives. This indicates the low-frequency step power fluctuation caused when a heavy-duty vehicle interacts with a slope. This represents the amplitude of high-frequency power fluctuations. This indicates the frequency of high-frequency power fluctuations. Indicates phase, This represents the transmission efficiency coefficient. This indicates the overall mass of the truck. Represents gravitational acceleration. Indicates the linear velocity of the running line. Indicates the slope angle; The objective function of the optimization model for calculating the optimal speed sequence of the flywheel is: ； in, For grid-connected power setting value, For prediction The flywheel compensation speed at any given moment, The ideal operating speed of the flywheel. express The theoretical compensation power of the flywheel at any given moment. express The theoretical compensation power of the flywheel at any given moment. These are the weighting coefficients for the power tracking term. The weight coefficient for the state penalty term. To control the coefficient of the action penalty term, To predict the step size.

2. The power smoothing control method for a chain-driven gravity energy storage system according to claim 1, characterized in that, The constraints of its optimization model include: Flywheel speed constraint: in, This is the lower limit of the flywheel speed. This is the upper limit of the flywheel speed; Flywheel power constraints: in, This represents the lower limit of flywheel energy storage capacity. This is the upper limit of flywheel energy storage capacity; Flywheel dynamics constraints: in, Let be the moment of inertia of the flywheel.

3. The power smoothing control method for a chain-driven gravity energy storage system according to claim 2, characterized in that, The flywheel operates under two different conditions based on the instantaneous power of the chain-driven gravity energy storage system, including: Energy release condition, at this time The flywheel decelerates and releases kinetic energy to compensate for the insufficient power of the chain drive's gravity-stored energy. Energy storage operating conditions, at this time The flywheel accelerates and absorbs kinetic energy, absorbing excess power stored in gravity by the chain drive. in, This indicates the actual compensation power of the flywheel.

4. The power smoothing control method for a chain-driven gravity energy storage system according to claim 1, characterized in that, Before the step of real-time acquisition of active power data, flywheel speed, and truck data at the grid-side connection point of the chain-driven gravity energy storage system, the following steps are also included: System initialization: Load the length, height, and angle of the chain drive ramp track, sprocket radius, number of sprocket teeth, overall mass of the truck, truck running linear velocity, flywheel moment of inertia, ideal operating point speed of the flywheel, flywheel speed range, flywheel power range, power tracking term weight coefficient, state penalty term weight coefficient, control action penalty term coefficient, prediction step size, control cycle, initial sprocket speed, initial number of trucks, and initial flywheel speed.

5. The power smoothing control method for a chain-driven gravity energy storage system according to claim 1, characterized in that, Also includes: Repeat steps S1-S4 to continuously update the output compensation power.

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