A frequency modulation method and system for a multi-direct-current feed-in receiving end power grid flywheel energy storage

Abstract

A frequency regulation method and system for flywheel energy storage in a multi-DC-feed receiving-end power grid belongs to the technical field of frequency control methods for receiving-end power grid energy storage. The method includes the following steps: real-time monitoring of fluctuations in the receiving-end power grid frequency value; collecting the difference between the receiving-end power grid frequency value and the standard frequency and inputting it into a data processing system; determining whether the difference exceeds a limit; predicting short-term power grid changes based on the difference using a short-term state disturbance estimation algorithm; constructing a power state prediction fitness function; and adjusting the operating state of the flywheel energy storage unit to optimal parameters according to an improved automatic generation control strategy. The system monitors the power grid frequency in real time and switches the operating state and output of the flywheel energy storage unit to keep the frequency within a certain range. This invention enhances the frequency stability of receiving-end power grids with a high proportion of new energy access, making frequency regulation more flexible and precise.

Description

Technical Field

[0001] This invention belongs to the technical field of frequency control methods for energy storage in receiving-end power grids, specifically relating to a frequency regulation method and system for flywheel energy storage in multi-DC-feed receiving-end power grids. Background Technology

[0002] Frequency is a crucial indicator of power quality. For the power grid, frequency fluctuations reflect the balance between power supply and demand. When power generation exceeds load consumption, the system frequency rises; conversely, when load consumption exceeds power generation, the system frequency falls. Frequency variations in the power system negatively impact users, power plants, and the power system itself. Therefore, it is essential to maintain the frequency around the rated value of 50Hz, with deviations not exceeding a certain range. With the increasing integration of new energy generating units into the grid and the rise of impact loads, the grid's frequency regulation requirements for generating units are becoming increasingly stringent in order to ensure safe and economical grid operation and improve power quality for users. Currently, in China's major regional power grids, large hydropower and thermal power units are the primary frequency regulation sources, responding to system frequency changes by continuously adjusting their output. However, each has its limitations and shortcomings, affecting the security and quality of the grid frequency. The insufficient existing frequency regulation capacity is becoming increasingly apparent, necessitating the development of new frequency regulation methods.

[0003] With the continuous increase in DC transmission power, the impact of DC faults on the power grid is becoming increasingly significant, potentially causing frequency or power angle stability issues, and in severe cases, voltage instability. However, with the rapid development of UHV AC / DC transmission, existing control methods and measures for multiple DC feeds into the receiving-end power grid are no longer sufficient to simultaneously meet the needs of wide-area clean energy consumption and ensuring grid operation safety. There is an urgent need to find solutions to these problems and to research and develop frequency regulation control methods and systems for flywheel energy storage based on short-time state disturbance estimation algorithms to address frequency stability issues in multi-DC feed-in receiving-end power grids.

[0004] Battery energy storage systems, characterized by rapid response and precise tracking, are more efficient than traditional frequency regulation methods. In recent years, replacing power plants with large-scale energy storage systems for frequency regulation has attracted industry attention. Compared to traditional power sources, energy storage offers significant technological advantages for grid frequency regulation, and its economic viability is gradually becoming apparent, effectively improving the operating efficiency of the power system. Flywheel energy storage (FES) is an advanced physical energy storage technology that utilizes electrical energy to drive a flywheel at high speed, converting electrical energy into mechanical energy. When needed, the flywheel's inertia drives a motor to generate electricity, converting the stored mechanical energy into electrical output (i.e., flywheel discharge). It features high power density, fast response, long lifespan, maintenance-free operation, good scalability, and zero pollution. Compared to other types of energy storage, such as lithium batteries, lead-acid batteries, and pumped hydro storage, flywheel energy storage power stations offer advantages such as high output power, fast instantaneous response, low long-term operation and maintenance costs, safety and reliability, and environmental friendliness. In particular, the discharge power response speed of the flywheel energy storage system is fast, reaching the millisecond level, which can meet the requirements of primary frequency regulation control. The flywheel energy storage and the generator unit can be combined for primary frequency regulation control. Summary of the Invention

[0005] This invention addresses the shortcomings of existing technologies by providing a frequency regulation method and system for flywheel energy storage in a multi-DC-feed receiving-end power grid.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A frequency regulation method for flywheel energy storage in a multi-DC-feed receiving-end power grid, characterized by comprising the following steps:

[0008] Step 1: Monitor the fluctuation of the receiving-end power grid frequency value in real time and collect the difference between the receiving-end power grid frequency value and the standard frequency;

[0009] Step 2: Determine whether the difference exceeds the limit, and use the disturbance estimation algorithm to predict the short-term power grid changes based on the difference, and find the optimal state and parameters of the flywheel energy storage unit;

[0010] Step 3: Based on the optimal state and parameters, adjust the state and parameters of the flywheel energy storage unit through an automatic power generation control strategy to keep its frequency within the set range.

[0011] To optimize the above technical solution, the specific measures also include:

[0012] Furthermore, in step 2, when the difference is within the upper and lower limits, the flywheel energy storage unit operates in the energy holding state for a short period of time; when the difference exceeds the upper limit, the flywheel energy storage unit operates in the charging state; when the difference exceeds the lower limit, the flywheel energy storage unit operates in the discharging state.

[0013] Furthermore, in step 2, the prediction of short-term grid power fluctuations based on the difference using a disturbance estimation algorithm to find the optimal state and parameters of the flywheel energy storage unit is as follows:

[0014] Step 2.1: Filter the frequency difference Δf collected within a short time limit (second level, such as between 10 and 15 seconds) to form a 2×N matrix. Each element x(i, j) (i≤2, j≤N) in the matrix is ​​regarded as a state perturbation. The numerical fluctuation between each difference is within [0, 2].

[0015] Step 2.2: The matrix formed by the frequency difference Δf is processed using the Gauss-Seidel method. The processed frequency difference is used as the initial value, and the initial state is generated using the embedded Chebyshev map chaotic sequence.

[0016] Step 2.3: Design a power state prediction fitness function for predicting short-term grid power variations;

[0017] Step 2.4: Based on the power state prediction fitness function, find the optimal operating state and parameters of the energy storage unit.

[0018] Furthermore, the power state prediction fitness function is:

[0019]

[0020] In the formula, f(u, v) is the state parameter function of the flywheel energy storage unit, u represents the state, v represents the parameter, and u takes values ​​of -1, 0, and 1 to represent the discharge state, energy holding state, and charging state, respectively; g(x, y) is the frequency time function; and h(z, y) is the active load time function.

[0021] Furthermore, in step 2.4, the process of finding the optimal operating state and parameters of the energy storage unit is as follows:

[0022] The initial state parameter function of the flywheel energy storage unit is f0(u, v). Adding a disturbance (Δu, Δv), the state parameter function after the disturbance is f0(u, v). i+1 (u, v) = f i (u+Δu i ,v+Δv i ), and g is obtained under the corresponding state. i+1 (x, y), where the subscript i represents the iteration number; design an optimal solution memory, where the value of G(f(u, v)) is greater than a set value. When, the corresponding f n(u, v) is stored in memory, and the subscript n indicates the nth iteration. The state parameter function G(f(u, v)) corresponding to each unit is compared with the state parameter function G(f(u, v)) corresponding to the memory. If it is greater than the value in memory, the state parameter function f in memory is replaced. n (u, v), then perform 2 × 10 4 Output the optimal state and parameters after the first perturbation.

[0023] Furthermore, in step 3, the automatic power generation control strategy is specifically as follows:

[0024] In the control time domain, the proportions of units in the charging state and units in the discharging state are λ and μ, respectively, as expressed below:

[0025]

[0026]

[0027] In the formula, P RECN (k) and P DISCN (k) represents the predicted charging and discharging power of the flywheel energy storage unit at time k; N REC (k) and N DISC (k) represents the number of units in the charging state and the number of units in the discharging state at time k, respectively;

[0028] The constraints are as follows:

[0029] -P BN ≤P B (k)≤P BN

[0030] ηN T ≤N REC (k)≤θN T ηN T ≤N DISC (k)≤θN T

[0031] 0≤ΔN REC ≤θN T

[0032] 0≤ΔN DISC ≤θN T

[0033] 20%≤λ≤70%, 20%≤μ≤70%, λ+μ≤80%

[0034] In the formula, P B (k) represents the output power of the flywheel energy storage system at time k; P BN N is the rated power of the flywheel energy storage system. Tη represents the total number of flywheel energy storage units; η and θ are values ​​less than 1, and η < θ; ΔN REC ΔN represents the value indicating a change in the state of a unit that is in a charging state. DISC This represents the value indicating a change in the state of a unit that is in a discharge state.

[0035] Furthermore, in step 3, the flywheel energy storage unit is controlled by constraints based on the optimal state and parameters to keep the frequency within the set upper and lower limits.

[0036] This invention further proposes a frequency regulation system for flywheel energy storage in a multi-DC-feed receiving-end power grid, characterized in that it includes:

[0037] The data acquisition module is used to acquire the frequency value of the receiving-end power grid and obtain the difference between the frequency value of the receiving-end power grid and the standard frequency through processing;

[0038] The data processing module is used to process the input difference and predict the short-term power grid changes based on the difference using a disturbance estimation algorithm, and output the optimal state and parameters of the flywheel energy storage unit.

[0039] The unit operating status adjustment module is used to adjust the status and parameters of the flywheel energy storage unit according to the optimal output status and parameters, and to keep its frequency within the set range through an automatic power generation control strategy.

[0040] The present invention further proposes a computer-readable storage medium storing a computer program, characterized in that the computer program enables a computer to execute the frequency regulation method for flywheel energy storage in a multi-DC-feed receiving-end power grid as described above.

[0041] The present invention further proposes an electronic device, characterized in that it includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the frequency regulation method for flywheel energy storage of multiple DC-fed receiving-end power grids as described above.

[0042] The beneficial effects of this invention are: This invention effectively utilizes the flywheel energy storage system to store and release electrical energy, and mobilizes the flywheel energy storage unit to improve the frequency stability of the receiving-end grid under the background of multiple DC feeds through charging and discharging. It utilizes the advantage of the fast discharge power response speed of the flywheel energy storage system to achieve efficient primary frequency regulation, improves the frequency stability of the receiving-end grid with a high proportion of new energy access, makes frequency regulation more flexible and precise, and improves the grid's ability to absorb new energy. Attached Figure Description

[0043] Figure 1 This is a flowchart of the method of the present invention.

[0044] Figure 2This is a schematic diagram of the power grid structure based on the flywheel energy storage system of the present invention.

[0045] Figure 3 This is a wiring diagram of the flywheel energy storage system of the present invention. Detailed Implementation

[0046] The invention will now be described in further detail with reference to the accompanying drawings.

[0047] like Figure 1 The frequency regulation method of flywheel energy storage with multiple DC feeds to the receiving end of the grid, shown in the figure, mainly includes the following three steps.

[0048] Step 1: Monitor the fluctuation of the receiving-end power grid frequency value in real time and collect the difference Δf between the receiving-end power grid frequency value and the standard frequency.

[0049] Step 2: Determine whether the difference Δf exceeds the limit. Based on the difference Δf, use the short-term state disturbance estimation algorithm to predict the short-term power grid changes and find the optimal state and parameters of the flywheel energy storage unit.

[0050] When the difference is within the upper and lower limits, the flywheel energy storage unit operates in energy-holding mode in the short term; when the difference exceeds the upper limit, the system will adjust the flywheel energy storage unit to charge mode to the optimal parameters based on the short-term power grid change prediction results; when the difference exceeds the lower limit, the system will adjust the flywheel energy storage unit to discharge mode to the optimal parameters based on the short-term power grid change prediction results.

[0051] In this embodiment, the flywheel energy storage unit can be a single flywheel energy storage system with a fixed capacity or a flywheel array energy storage system with a large capacity that can be scaled up significantly. The grid structure based on the flywheel energy storage system is as follows: Figure 2 As shown, the wiring diagram of the flywheel energy storage system is as follows: Figure 3 As shown.

[0052] Short-duration state perturbation estimation algorithms include:

[0053] a. Numerical encoding: The frequency difference Δf collected within a short time limit is filtered to form a 2×N matrix. Each element x(i,j) (i≤2,j≤N) in the matrix is ​​regarded as a state perturbation. The numerical fluctuation between each difference is a value within [0,2].

[0054] b. Initializing the System State: To avoid the slow convergence caused by random initialization of the system state, the frequency values ​​processed by the traditional Gauss-Seidel method are used as initial values. An embedded Chebyshev mapping is used to generate the initial state from the chaotic sequence. The data X0 processed by the Gauss-Seidel method is used as the initial value. X0 is a matrix whose elements are short-time frequency differences. Each element x0(i,j) in X0 is mapped to the interval [0, 100].

[0055]

[0056] In the formula, x0(i,j) are the elements in the frequency difference matrix X0.

[0057] Using X0 as the initial value, matrix X is obtained using Chebyshev chaotic mapping. L (L = 1, 2, ..., K), then X L The element value x in L The sequence obtained by inverse mapping of (i, j):

[0058] X K =0+(100-0)X L (2)

[0059] In the formula, X K This is the new sequence obtained after K inverse mappings.

[0060] Each frequency difference is subjected to chaotic perturbation on the original basis. The ergodicity of the chaotic perturbation ensures the diversity of the initial state, and at the same time, it also ensures the continuity of the frequency difference variation to a certain extent, which is more in line with the frequency variation law of the power system.

[0061] c. Design of Power State Prediction Fitness Function: This algorithm aims to determine the optimal operating state and parameters of the energy storage unit. The optimal operating state must be compared with various different operating states and parameters to determine its optimality. In reality, the operating states and parameters that the energy storage unit needs to adjust are unknowns. The analysis utilizes the frequency-time function g(x, y) and the active load-time function h(z, y) within a short timeframe when the frequency is stable (i.e., before the frequency difference exceeds the limit). h(z, y) can be estimated from the daily load curve based on the grid load before the frequency difference exceeds the limit. Based on the adjusted state and parameters f(u, v) of the energy storage unit, the short-term frequency-time function g′(x, y) can be obtained. When g′(x, y) is very close to g(x, y), the adjusted state and output f(u, v) of the energy storage unit can be considered the optimal operating state and parameters. Based on the above, the power state prediction fitness function is constructed as follows:

[0062]

[0063] In the formula, f(u, v) is the state parameter function of the flywheel energy storage unit, u represents the state, v represents the parameter, and u takes values ​​of -1, 0, and 1 to represent the discharge state, energy holding state, and charging state, respectively; g(x, y) is the frequency time function; and h(z, y) is the active load time function.

[0064] Finding the optimal operating state and parameters of the energy storage unit is the process of maximizing G(f(u,v)). The larger G(f(u,v)) is, the more stable the grid frequency will be after the flywheel energy storage frequency adjustment.

[0065] d. The process of adjusting the state and parameters f(u, v) of the energy storage unit is as follows: The initial state of the unit is f0(u, v). A disturbance (Δu, Δv) is added. The state and parameters of the unit after adding the disturbance are f0(u, v). i+1 (u, v) = f i (u+Δu i ,v+Δv i ), and g can be obtained under the corresponding state. i+1 (x, y), where the subscript i represents the iteration number. Design an optimal solution memory, where the value of G(f(u, v)) is greater than a set value. When, the corresponding f n (u, v) is stored in memory, and each time the value of G(f(u, v)) is greater than the set value, the value of G(f(u, v)) is stored in memory. The unit state parameters are compared with the corresponding G(f(u,v)) in the memory. If the value is greater than the value in the memory, then the unit state parameter f in the memory is replaced. n (u, v), then perform 2 × 10 4 The optimal solution is output after the perturbation.

[0066] Step 3: The flywheel energy storage unit control center controls the working status and parameters of the flywheel energy storage unit and keeps the frequency within a certain range.

[0067] First, create an improved automatic generation control strategy (AGC), specifically including:

[0068] Within the control time domain, the proportions of units in charging state and discharging state at each time are λ and μ, respectively, as expressed below:

[0069]

[0070]

[0071] In the formula, P RECN and P DISCN N represents the charging and discharging power of the flywheel energy storage unit, respectively, derived from ultra-short-term power prediction. REC and NDISC These represent the number of units in the charging state and the number of units in the discharging state, respectively; (k) is the corresponding value at time k.

[0072] The constraints of the improved AGC system model are as follows:

[0073] -P BN ≤P B (k)≤P BN (6)

[0074] ηN T ≤N REC (k)≤θN T ηN T ≤N DISC (k)≤θN T (7)

[0075] 0≤ΔN REC ≤θN T (8)

[0076] 0≤ΔN DISC ≤θN T (9)

[0077] 20%≤λ≤70%, 20%≤μ≤70%, λ+μ≤80% (10)

[0078] In the formula, P B P represents the output power of the flywheel energy storage system. BN N is the rated power of the energy storage system. T Let be the total number of flywheel energy storage units in the system; η and θ are specific values ​​less than 1, and η < θ; ΔN REC ΔN represents the value indicating a change in the state of a unit that is in a charging state. DISC The numerical value of the change in state of a unit in a discharge state; (k) is the corresponding value at time k.

[0079] Then, based on the optimal state and parameters of the flywheel storage system obtained in step 2, the flywheel storage system is controlled by the above constraints to keep the frequency within the upper and lower limits.

[0080] In the frequency regulation stage, this embodiment neglects the impact of the flywheel energy storage unit on the primary frequency regulation, that is, it does not consider the unit regulation power K of the flywheel energy storage unit. G The unit regulating power K of the system S The impact. Adjusting the system's power deficit ΔP solely through secondary frequency modulation. S To achieve frequency stability, when the frequency is within the allowable range, based on Δf, some generating units are adjusted to charging mode without affecting the receiving-end grid frequency, to ensure stability in the event of a significant power deficit ΔP in the grid. SThere is sufficient regulation capacity to maintain the grid frequency within the allowable range.

[0081] This invention also proposes a frequency regulation system for flywheel energy storage in a multi-DC-feed receiving-end power grid, comprising:

[0082] The data acquisition module is used to acquire the frequency value of the receiving-end power grid and obtain the difference between the frequency value of the receiving-end power grid and the standard frequency through processing;

[0083] The data processing module is used to process the input difference and predict the short-term power grid changes based on the difference using a disturbance estimation algorithm, and output the optimal state and parameters of the flywheel energy storage unit.

[0084] The unit operating status adjustment module is used to adjust the status and parameters of the flywheel energy storage unit according to the optimal output status and parameters, and to keep its frequency within the set range through an automatic power generation control strategy.

[0085] The present invention also proposes a computer-readable storage medium storing a computer program that enables a computer to execute the frequency regulation method for flywheel energy storage in a multi-DC-feed receiving-end power grid as described above.

[0086] The present invention also proposes an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the frequency regulation method for flywheel energy storage in a multi-DC-feed receiving-end power grid as described above.

[0087] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A frequency regulation method for flywheel energy storage in a multi-DC-feed receiving-end power grid, characterized in that, Includes the following steps: Step 1: Monitor the fluctuation of the receiving-end power grid frequency value in real time and collect the difference between the receiving-end power grid frequency value and the standard frequency; Step 2: Determine if the difference exceeds the limit, and based on the difference, use the disturbance estimation algorithm to predict the short-term grid power changes to find the optimal state and parameters of the flywheel energy storage unit; details are as follows: Step 2.1: Collect frequency differences within a short time period The selection process is performed to form a 2×N matrix, where each element... x ( i , j ()( i ≤2, j ≤N) are considered as state perturbations, and the numerical fluctuations between the differences are within [0, 2]. Step 2.2: Use the Gauss-Seidel method to measure the frequency difference. The matrix is ​​processed, and the resulting frequency difference is used as the initial value. The initial state is generated by using an embedded Chebyshev map chaotic sequence. Step 2.3: Design a power state prediction fitness function for predicting short-term power fluctuations in the power grid; the power state prediction fitness function is: In the formula, For the state parameter function of the flywheel energy storage unit, u Indicates state, v Indicates parameters, u The values ​​-1, 0, and 1 represent the discharge state, energy retention state, and charging state, respectively. It is a frequency-time function; It is a time function of active power load; Step 2.4: Based on the power state prediction fitness function, find the optimal operating state and parameters of the energy storage unit; the process is as follows: The initial state parameter function of the flywheel energy storage unit is Add a perturbation amount The state parameter function after adding the perturbation is , obtain in the corresponding state subscript i Indicates the number of iterations; Design an optimal solution memory, when The value is greater than the set value At that time, the corresponding Store in memory, index n Indicates the first n In the next iteration, the state parameter function corresponding to each unit will be... Corresponding to the state parameter function of the memory In comparison, if the value is greater than the value in memory, then the state parameter function in memory is replaced. Then perform 2×10 4 After the disturbance, output the optimal state and parameters; Step 3: Based on the optimal state and parameters, adjust the state and parameters of the flywheel energy storage unit through the automatic power generation control strategy to keep its frequency within the set range.

2. The frequency regulation method for flywheel energy storage in a multi-DC-feed receiving-end power grid as described in claim 1, characterized in that: In step 2, when the difference is within the upper and lower limits, the flywheel energy storage unit operates in the energy holding state for a short period of time; when the difference exceeds the upper limit, the flywheel energy storage unit operates in the charging state; when the difference exceeds the lower limit, the flywheel energy storage unit operates in the discharging state.

3. The frequency regulation method for flywheel energy storage in a multi-DC-feed receiving-end power grid as described in claim 1, characterized in that: In step 3, the automatic power generation control strategy is as follows: Within the control time domain, the proportions of units in charging state and units in discharging state are respectively... and The expression is as follows: In the formula, and They are respectively k The charging and discharging power of the flywheel energy storage unit is predicted in real time; and They are respectively k The number of units in the charging and discharging states at any given time; The constraints are as follows: In the formula, for k Output power of the instantaneous flywheel energy storage system; This refers to the rated power of the flywheel energy storage system. This represents the total number of flywheel energy storage units; and It is a value less than 1, and ; The value representing the change in status of a unit that is in a charging state; This represents the value indicating a change in the state of a unit that is in a discharge state.

4. The frequency regulation method for flywheel energy storage in a multi-DC-feed receiving-end power grid as described in claim 3, characterized in that: In step 3, the flywheel energy storage unit is controlled by constraints based on the optimal state and parameters to keep the frequency within the set upper and lower limits.

5. A computer-readable storage medium storing a computer program, characterized in that, The computer program causes the computer to execute the frequency regulation method for flywheel energy storage in a multi-DC-feed receiving-end power grid as described in any one of claims 1-4.

6. An electronic device, characterized in that, include: The memory, the processor, and the computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the frequency regulation method for flywheel energy storage in a multi-DC-feed receiving-end grid as described in any one of claims 1-4.

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