Power system control method and device based on network construction type energy storage, and storage medium

Abstract

The embodiment of the application provides a kind of power system control method and device based on network type energy storage, storage medium, it is related to power system field, wherein, method includes: determining the first synchronous machine with minimum inertia time constant from power system, and determining the second synchronous machine farthest from the first synchronous machine and the third synchronous machine closest to the first synchronous machine from power system;Network type energy storage is deployed on the second synchronous machine, and power disturbance is set in the third synchronous machine;Frequency variation rate during power disturbance is obtained in the first synchronous machine;In the case where frequency variation rate is greater than expected threshold, the difference between frequency variation rate and expected threshold is based on the difference between frequency variation rate and expected threshold, and the control response parameter of network type energy storage is corrected until frequency variation rate is less than or equal to expected threshold.

Description

Technical Field

[0001] This application relates to the field of power systems, and more specifically, to a power system control method and apparatus, and a storage medium based on grid-type energy storage. Background Technology

[0002] When existing grid-based energy storage systems participate in the inertial response of power systems, their control parameters mostly rely on engineering experience or static simulation settings. Especially when facing the problem of rapid frequency changes caused by high-power disturbances, inappropriate parameter configuration can lead to a mismatch between the energy storage response and the actual risks of the power system, resulting in resource waste, power system instability, and thus low control efficiency of the power system.

[0003] Therefore, there is a technical problem of low control efficiency in power systems in related technologies. Summary of the Invention

[0004] This application provides a power system control method and apparatus, and a storage medium based on grid-type energy storage, to at least solve the technical problem of low control efficiency of power systems in related technologies.

[0005] According to one embodiment of this application, a power system control method based on grid-type energy storage is provided, comprising: determining a first synchronous machine with the smallest inertia time constant from the power system, and determining a second synchronous machine farthest from the first synchronous machine and a third synchronous machine closest to the first synchronous machine from the power system; deploying grid-type energy storage on the second synchronous machine, and setting a power disturbance on the third synchronous machine; obtaining the frequency change rate of the first synchronous machine during the power disturbance; and, if the frequency change rate is greater than a expected threshold, correcting the control response parameters of the grid-type energy storage based on the difference between the frequency change rate and the expected threshold until the frequency change rate is less than or equal to the expected threshold.

[0006] According to another embodiment of this application, a power system control device based on grid-type energy storage is provided, comprising: a determining unit, configured to determine a first synchronous machine with the smallest inertia time constant from the power system, and a second synchronous machine that is farthest from the first synchronous machine and a third synchronous machine that is closest to the first synchronous machine from the power system; a deployment unit, configured to deploy grid-type energy storage on the second synchronous machine and set a power disturbance on the third synchronous machine; an acquisition unit, configured to acquire the frequency change rate of the first synchronous machine during the power disturbance; and a correction unit, configured to correct the control response parameters of the grid-type energy storage based on the difference between the frequency change rate and the expected threshold when the frequency change rate is greater than an expected threshold, until the frequency change rate is less than or equal to the expected threshold.

[0007] According to yet another embodiment of this application, a computer-readable storage medium is also provided, in which a computer program is stored, wherein the computer program is configured to perform the steps in any of the above method embodiments when it is run.

[0008] According to yet another embodiment of this application, an electronic device is also provided, including a memory and a processor, wherein a computer program is stored in the memory and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0009] In the embodiments provided in this application, the synchronous machine with the smallest inertia time constant in the power system (the first synchronous machine) is the "weak node" most sensitive to frequency dynamic response and most prone to instability. Deploying grid-type energy storage at the node with the longest electrical distance (the second synchronous machine) can minimize the influence of local impedance coupling, ensuring that the active power output from the energy storage reaches this weak node via the weakest damped path. This maximizes its control efficiency over the target frequency dynamics and avoids power attenuation or phase lag caused by proximity to the disturbance side or weak tie lines. Applying the maximum permissible power disturbance at the node closest to the first synchronous machine (the third synchronous machine) ensures that the disturbance energy acts on the target node with the shortest electrical path and the highest coupling strength, thus most realistically reflecting the power response information and providing an "extreme stress test" scenario for parameter optimization. Using the measured frequency change rate of the first synchronous machine as a feedback signal, the difference is compared with a preset threshold, and the control response parameters of the grid-type energy storage are automatically iteratively adjusted. This allows the system to automatically converge the parameters to the optimal solution that "satisfies the frequency change rate constraint" without manual intervention or a preset model.

[0010] In summary, this embodiment achieves integrated self-optimization of the "space-dynamic-feedback" parameters of grid-based energy storage for the first time through a four-fold collaborative mechanism of "weakest node - furthest deployment - nearest disturbance - closed-loop correction". It solves the problems of response failure and resource waste caused by topology neglect and static parameters in traditional methods. Thus, based on grid-based energy storage, it achieves the technical effect of improving the control efficiency of the power system and solves the technical problem of low control efficiency of the power system in related technologies. Attached Figure Description

[0011] Figure 1 This is a hardware structure block diagram of a power system control method based on grid-connected energy storage according to an embodiment of this application;

[0012] Figure 2 This is a flowchart of a power system control method based on grid-connected energy storage according to an embodiment of this application;

[0013] Figure 3This is a flowchart illustrating a method for optimizing the inertia and power parameters of a grid-type energy storage system that satisfies the maximum rate of change of frequency constraint, according to an embodiment of this application.

[0014] Figure 4 This is a structural block diagram of a power system control device based on grid-type energy storage according to an embodiment of this application. Detailed Implementation

[0015] The embodiments of this application will be described in detail below with reference to the accompanying drawings and examples.

[0016] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0017] The methods and embodiments provided in this application can be executed on a computer terminal or similar computing device. Taking running on a computer terminal as an example, Figure 1 This is a hardware structure block diagram of a computer terminal for a power system control method based on grid-connected energy storage, according to an embodiment of this application. Figure 1 As shown, a computer terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. The computer terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the computer terminal described above. For example, the computer terminal may also include components that are more complex than those described above. Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0018] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the power system control method based on grid-connected energy storage in this embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thereby implementing the above-described method. The memory 104 may include high-speed random access memory and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to a computer terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0019] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider for the computer terminal. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module used for wireless communication with the Internet.

[0020] As an alternative, a power system control method based on grid-connected energy storage, such as... Figure 2 As shown, the specific steps include:

[0021] S202, determine the first synchronous machine with the smallest inertia time constant from the power system, and determine the second synchronous machine that is farthest from the first synchronous machine and the third synchronous machine that is closest to the first synchronous machine from the power system;

[0022] S204, deploy grid-type energy storage on the second synchronous machine and set power disturbances on the third synchronous machine;

[0023] S206, Obtain the frequency change rate of the first synchronizer during power disturbance;

[0024] S208, when the frequency change rate is greater than the expected threshold, the control response parameters of the grid-type energy storage are corrected based on the difference between the frequency change rate and the expected threshold until the frequency change rate is less than or equal to the expected threshold.

[0025] Optionally, in this embodiment, grid-based energy storage refers to an energy storage converter system with the ability to actively construct AC voltage and frequency. Its control architecture can simulate the inertia and damping characteristics of a synchronous generator, and can provide virtual inertia and active power support in weak power grids or new energy high-penetration systems without large synchronous machines to suppress dynamic fluctuations in system frequency.

[0026] Optionally, in this embodiment, the inertia time constant is a physical parameter characterizing the ability of a synchronous generator or equivalent synchronization unit to resist frequency changes. Electrical distance is used to represent the equivalent impedance relationship between two nodes (such as a bus or synchronous machine) in a power system, and is used to quantify the electrical coupling strength of the power transmission path.

[0027] Optionally, in this embodiment, the rate of frequency change indicates the rate at which the system frequency changes over time, expressed in Hz / s. This is a core indicator for measuring the transient stability of a power system; a larger rate indicates insufficient system inertial response and proximity to the edge of instability.

[0028] Optionally, in this embodiment, the inertia time constant data of all synchronous generator sets (such as thermal power, hydropower, and nuclear power) in the power system are collected, and the synchronous machine with the smallest inertia time constant is identified by comparison and denoted as the first synchronous machine (M1). This node is the "risk core area" where the system inertia is weakest and the frequency response is most sensitive.

[0029] Secondly, based on the system network topology and node impedance matrix, the electrical distance between the first synchronous machine and the other synchronous machines in the system is calculated. The node with the largest electrical distance is selected and denoted as the second synchronous machine (M2). This node is the "farthest point" with the weakest coupling to the weakest node. Deploying a grid-type energy storage at this point can ensure that its output power reaches M1 through the lowest damped path, maximizing control efficiency.

[0030] Next, among all the synchronous machines, the node with the smallest electrical distance is selected and denoted as the third synchronous machine (M3). This node is the "nearest neighbor point" with the strongest electrical coupling to M1 and the most direct transmission of power disturbances. Applying a disturbance here can most realistically excite the most severe frequency dynamic response of M1.

[0031] By using topological positioning, a spatial correlation is established for the first time between energy storage deployment and the location of disturbance application and the dynamic vulnerability of the system, fundamentally solving the drawbacks of traditional methods such as "random deployment and blind configuration".

[0032] Connect and configure a grid-type energy storage system on the second synchronous machine M2. Its initial control parameters (virtual inertia, active power response capability) can be set to engineering experience values ​​or default values ​​(such as H=5s, P=20MW) as the starting point for optimization.

[0033] A maximum permissible power disturbance ΔP is applied to the third synchronizing machine M3. Its amplitude is determined based on historical operating data (e.g., taking the 95th percentile of the maximum power imbalance events in the past five years to ensure coverage of the vast majority of real operating conditions). The disturbance duration is set to 30 seconds to fully excite the system transient response.

[0034] By employing a reverse symmetric design of "farthest deployment and nearest disturbance," a high-excitation-strong-target testing environment was constructed, enabling the energy storage response to be realistically tested under the most severe conditions.

[0035] Optionally, in this embodiment, the frequency data of the first synchronizing machine M1 is acquired in real time using a wide-area measurement system or a high sampling rate PMU (phasor measurement unit) to obtain its frequency-time curve (f(t)) during the disturbance period (0–30s) at a sampling rate of not less than 100Hz.

[0036] The curve is numerically differentiated, and its maximum frequency change rate during the initial disturbance period (e.g., 0–2s) is calculated as a quantitative indicator of the current energy storage response performance.

[0037] The measured rate of change of frequency is compared with the preset expected threshold RoCoF_max:

[0038] If the rate of change of frequency is less than or equal to the expected threshold, then the current parameters meet the requirements and the optimization ends.

[0039] If the rate of change of frequency is greater than the expected threshold, then the iterative correction process begins until the corrected rate is less than or equal to the expected threshold.

[0040] Through the embodiments provided in this application, the synchronous machine with the smallest inertia time constant in the power system (the first synchronous machine) is the "weak node" most sensitive to frequency dynamic response and most prone to instability. Deploying grid-type energy storage at the node with the longest electrical distance (the second synchronous machine) can minimize the influence of local impedance coupling, ensuring that the active power output from the energy storage reaches this weak node via the weakest damped path. This maximizes its control efficiency over the target frequency dynamics and avoids power attenuation or phase lag caused by proximity to the disturbance side or weak tie lines. Applying the maximum permissible power disturbance at the node closest to the first synchronous machine (the third synchronous machine) ensures that the disturbance energy acts on the target node with the shortest electrical path and the highest coupling strength, thereby most realistically stimulating the worst RoCoF response of the system and providing an "extreme stress test" scenario for parameter optimization. Using the measured RoCoF of the first synchronous machine as a feedback signal, the difference is compared with a preset threshold, and the control response parameters of the grid-type energy storage are automatically iteratively adjusted. This allows the system to automatically converge the parameters to the optimal solution that "satisfies the RoCoF constraint" without manual intervention or a preset model. In other words, this embodiment achieves the first-ever integrated self-optimization of the "space-dynamic-feedback" parameters of grid-based energy storage through a four-fold collaborative mechanism of "weakest node - furthest deployment - nearest disturbance - closed-loop correction". This solves the problem of response failure and resource waste caused by topology neglect and static parameters in traditional methods, thereby achieving the technical effect of improving the control efficiency of the power system based on grid-based energy storage.

[0041] As an optional approach, the control response parameters of grid-type energy storage are modified based on the difference between the rate of frequency change and the expected threshold, including:

[0042] The virtual inertia parameters and active power parameters of the grid-type energy storage are obtained, wherein the control response parameters include the virtual inertia parameters and active power parameters;

[0043] The corrected virtual inertia parameter is obtained by adding the first weight parameter multiplied by the first product of the difference to the virtual inertia parameter, and the corrected active power parameter is obtained by adding the second weight parameter multiplied by the second product of the difference to the active power parameter.

[0044] The corrected control response parameters include the corrected virtual inertia parameters and the corrected active power parameters.

[0045] Optionally, in this embodiment, the virtual inertia parameter refers to the synchronous generator inertia characteristic artificially simulated by the grid-type energy storage system in the control algorithm. The larger the value, the stronger the buffering ability of the energy storage system to frequency changes, but the slower the response speed, and the more likely it is to increase the power output pressure.

[0046] Optionally, in this embodiment, the active power parameter refers to the active power value that the grid-type energy storage system can actively output (or absorb) during transient periods. During the inertial response phase, this parameter reflects the energy storage system's direct compensation capability for power deficits. A larger parameter indicates a stronger "pull-back" effect against frequency drops, but this is limited by the energy storage battery's SOC, PCS rated power, and thermal management constraints.

[0047] Optionally, in this embodiment, when performing parameter correction, the system first reads two core control parameters of the current grid-type energy storage: the current virtual inertia value and the current active power output capacity value. These two are the values ​​from the previous iteration or the initial setting, constituting the "starting point" for parameter correction.

[0048] The difference between the current rate of frequency change and the expected threshold is calculated to correct the virtual inertia. The greater the RoCoF exceedance, the more inertia needs to be increased, and the correction amount is proportional to the exceedance magnitude. Weights control the "intensity" of the inertia adjustment. Active power is also corrected; the greater the RoCoF exceedance, the greater the power compensation capability needs to be improved. This is suitable for extreme cases where inertia adjustment is insufficient to quickly suppress RoCoF.

[0049] Optionally, in this embodiment, a linear superposition correction is adopted, which has the advantages of being easy to embed into the controller and having proven convergence, and conforms to engineering implementation conventions.

[0050] Optionally, in this embodiment, the corrected parameters and the controller parameter register written to the grid-type energy storage are used as the control input for the next round of simulation or actual operation.

[0051] The embodiments provided in this application realize a two-parameter collaborative correction mechanism of "linear weighted difference," transforming the abstract problem of "insufficient frequency response" into a computable, programmable, and adjustable control engineering problem. By simultaneously adjusting the two core parameters at the same frequency and in the same direction, a "momentum-power" dual-channel response enhancement mechanism is constructed, significantly improving the parameter convergence speed and robustness.

[0052] As an optional approach, before adding the first product of the first weighting parameter and the difference to the virtual inertia parameter to obtain the corrected virtual inertia parameter, and before adding the second product of the second weighting parameter and the difference to the active power parameter to obtain the corrected active power parameter, the method further includes:

[0053] Obtain the ratio between the difference and the rate of change of frequency, and obtain the target ratio interval to which the ratio belongs in multiple ratio intervals. Each ratio interval corresponds to a pair of weighting coefficients. Each pair of weighting coefficients includes a weighting coefficient for correcting the virtual inertia parameter and a weighting coefficient for correcting the active power parameter.

[0054] Obtain the target weight coefficient pair corresponding to the target interval, wherein the target weight coefficient pair includes the first weight coefficient and the second weight coefficient.

[0055] Optionally, in this embodiment, after obtaining the current frequency change rate and the expected threshold, the calculated ratio is compared with a number of preset ratio intervals by normalizing the ratio to determine which interval it falls into.

[0056] Based on the target ratio range, the corresponding parameters are read from the preset weight coefficient mapping table and used as the dynamic gain parameters for this correction; the same RoCoF will trigger different parameter combinations in different ranges.

[0057] Through the embodiments provided in this application, a technological leap from fixed-gain linear correction to risk-aware nonlinear response is achieved through a relative overlimit ratio-segmented weight matching mechanism.

[0058] As an optional approach, after adding a first weighting parameter multiplied by the difference to the virtual inertia parameters to obtain the corrected virtual inertia parameters, and adding a second weighting parameter multiplied by the difference to the active power parameters to obtain the corrected active power parameters, the method further includes:

[0059] To obtain information on changes in the operating status of the power system;

[0060] Update the expected thresholds based on changes in operational status;

[0061] After obtaining the corrected control response parameters for the grid-connected energy storage, the updated frequency change rate of the first synchronous machine during power disturbances;

[0062] The updated rate of change and the updated expected threshold are verified.

[0063] Optionally, in this embodiment, the operational status change information refers to real-time or near-real-time status change data that occurs during the operation of the power system and may affect the system's inertia level, impedance characteristics, or frequency safety standards. This includes, but is not limited to: synchronous machine start-up / shutdown or output changes (such as thermal power unit disconnection from the grid, hydropower output increase); sudden output changes at renewable energy plants (such as wind farm wind shedding, photovoltaic power sudden drop); power flow redistribution at transmission sections (such as line tripping, DC blocking); step changes in load levels (such as large industrial load switching); and changes in regional grid interconnection methods (such as switching from islanded operation to grid-connected operation). This information can be obtained through real-time data, dispatch instructions, fault recording files, etc., and its essence is a dynamic representation of the system's inertia support capacity and safety margin.

[0064] Optionally, in this embodiment, the expected threshold is not a fixed constant, but a variable that is dynamically adjusted according to changes in the operating status. For example, in a "weak grid" with high penetration of new energy sources and a low proportion of synchronous machines, the expected threshold can be strictly set to 0.7 Hz / s; in a "traditional grid" with sufficient synchronous machines and strong system inertia, the expected threshold can be relaxed to 1.2 Hz / s.

[0065] The expected threshold is set before the start of the next disturbance cycle after parameter correction is completed, or when the system detects a critical change in operating status (such as the issuance of a dispatch command or the PMU detecting a frequency change). The system will actively collect information on the changes in the current operating status. This information can be pushed by the dispatch center through the communication interface or obtained in real time by the local PMU / SCADA module of the energy storage controller.

[0066] The system converts the current running status information into a new expected threshold based on the preset threshold mapping rules.

[0067] After updating the expected threshold, the system applies the same power disturbance ΔP to the third synchronizer again (keeping the disturbance strength constant); re-acquires the frequency response curve of the first synchronizer and calculates the new frequency change rate; compares the new frequency change rate with the new expected threshold: realizing a dual closed-loop adaptive mechanism of "correction - environmental change - re-verification".

[0068] As an optional approach, a second synchronous machine that is furthest from the first synchronous machine and a third synchronous machine that is closest to the first synchronous machine are identified from the power system, including:

[0069] The electrical distance between the other synchronous machines in the power system and the first synchronous machine is obtained. The electrical distance between each of the other synchronous machines and the first synchronous machine is obtained by adding the first internal impedance of each synchronous machine to the second internal impedance of the first synchronous machine and then subtracting the mutual impedance between each synchronous machine and the first synchronous machine.

[0070] The synchronous machine that is closest to the first synchronous machine among the other synchronous machines is designated as the second synchronous machine, and the synchronous machine that is furthest from the first synchronous machine among the other synchronous machines is designated as the third synchronous machine.

[0071] Optionally, in this embodiment, the nodal impedance matrix of the power system is acquired, which can be obtained in the following way:

[0072] Offline: Exported after short-circuit calculation based on power grid flow model;

[0073] Online: Identify network topology and impedance parameters in real time through the WAMS system (applicable to smart grids).

[0074] For each "other synchronizer", calculate the electrical distance between it and the first synchronizer M1.

[0075] Find the maximum value among all calculated electrical distance values, and determine the synchronous machine (M_k) corresponding to this maximum value as the second synchronous machine.

[0076] Among all the calculated electrical distance values, find the minimum value and determine the synchronous machine (M_j) corresponding to this minimum value as the third synchronous machine.

[0077] As an optional approach, the frequency change rate of the first synchronizer during power disturbances is obtained, including:

[0078] During the power disturbance, the system frequency response curve over time at the bus where the first synchronizing machine is located is obtained, wherein the response curve is used to indicate the mapping relationship between system frequency and time.

[0079] The frequency change rate is obtained by numerically differentiating the response curve.

[0080] Optionally, in this embodiment, the system frequency response curve at the bus refers to the discrete data sequence of system frequency changes over time, continuously acquired by a high sampling rate phasor measurement unit (PMU) or a high-speed data acquisition system at the bus node connected to the first synchronizing machine.

[0081] Optionally, in this embodiment, numerical differentiation calculation refers to applying a numerical differentiation algorithm to the discretely sampled frequency sequence to approximately calculate its derivative with respect to time, thereby obtaining the frequency change rate sequence. Common methods include forward differencing, backward differencing, central differencing, polynomial fitting differentiation, etc.

[0082] Optionally, in this embodiment, after a power disturbance is applied, a high-precision synchronous data acquisition system is activated to acquire frequency data of the bus connected to the first synchronization. The data acquisition device is an industrial-grade PMU (such as Siemens, ABB, NARI, etc.), with a sampling rate ≥100Hz and a time synchronization accuracy ≤1µs (IEEE C37.118 standard). The acquired data is a time series (f(t)), which includes the entire process of steady state before disturbance (e.g., 1s), disturbance start-up (0s), and transient response (0–30s). The data format is the standard IEEE C37.118 format or a custom CSV / ASCII format, which includes timestamps and frequency values ​​to ensure traceability and reusability.

[0083] The acquired frequency sequence is numerically differentiated using the central difference method (or an equivalent high-precision method) to obtain a discrete RoCoF sequence; the maximum value in the initial stage of the disturbance (0–2 seconds) is extracted as the final measurement value.

[0084] As an optional solution, power disturbances are incorporated into the third synchronizer, including:

[0085] Acquire multiple active power imbalance events recorded by the power system in a historical time period, and acquire the power deficit corresponding to each active power imbalance event;

[0086] The cumulative distribution of multiple power deficits corresponding to multiple active power imbalance events is calculated to obtain disturbance parameters, where the disturbance parameters are the quantiles of preset thresholds corresponding to multiple power deficits.

[0087] Set the power disturbance corresponding to the disturbance parameters in the third synchronizer.

[0088] Optionally, in this embodiment, all active power imbalance event data from the past 3-5 years or other historical periods are collected from the power system dispatch center, fault recording system, and SCADA historical database to ensure that the sample has statistical representativeness; for each event, the power deficit is calculated by the following methods: extracting the steady-state total active power in the 5 seconds before the fault from the event record; extracting the measured total active power of the system in the 5 seconds after the fault.

[0089] Sort all (N) power deficits in ascending order; calculate their empirical cumulative distribution function, i.e., calculate the cumulative proportion of each value in the sample; select the deficit value corresponding to a preset quantile (e.g., 95%) as the perturbation parameter. This value means that in all historical events, the power deficit does not exceed this value for 95% of the events.

[0090] The calculated disturbance parameters are used as simulation or test disturbance quantities and injected into the active power control channel of the third synchronous machine (M3); the disturbance is step-type and lasts for no less than 30 seconds to fully observe the frequency dynamic response.

[0091] As an alternative, the aforementioned power system control method based on grid-connected energy storage can be applied to a scenario where the inertia and power parameters of grid-connected energy storage are optimized to meet the maximum rate of frequency change constraint. In this scenario, grid-connected energy storage can be used for inertia response during frequency disturbances, providing active power support and assisting the system in reducing the rate of frequency change. However, most current parameters related to grid-connected energy storage (such as inertia and power) are based on engineering practice, and there is no standardized procedure for determining these parameters.

[0092] This embodiment proposes a method for optimizing the inertia and power parameters of a grid-type energy storage system that satisfies the maximum rate of change of frequency constraint. A flowchart is shown below. Figure 3 As shown, the specific steps include:

[0093] S301, set up grid-type energy storage nodes;

[0094] S302, set the power disturbance point;

[0095] S303, initialize grid-type energy storage H (virtual inertia of grid-type energy storage) and P (active power of grid-type energy storage), apply power perturbation, and detect RoCoF (rate of frequency change).

[0096] S304, determine whether RoCoF is less than or equal to RoCoFmax (expected threshold for rate of change of frequency).

[0097] S305 means: obtaining the optimization conclusions for H and P;

[0098] S306, No: Correct H and P according to preset rules.

[0099] Specifically, for the target power system, the synchronous machine M with the smallest inertia time constant in the search system is selected, and the grid-type energy storage is placed at the furthest electrical distance from M. The electrical distance is defined as: the electrical distance between node i and node j is their equivalent impedance, i.e., Dij = |Zii + Zjj - 2Zij|, where Zii is the internal impedance of node i, Zjj is the internal impedance of node j, and Zij is the mutual impedance between nodes i and j.

[0100] Set a power disturbance at the point closest to M, with the disturbance amount being the maximum allowable value ΔP. This value can be flexibly adjusted according to different power grids or operating environments.

[0101] The virtual inertia H and active power P of the grid-type energy storage are set, and the grid-type energy storage duration is set to 30s. A perturbation is applied, and the frequency curve ft at point M is obtained through simulation. The RoCoF is then detected. RoCoF is the rate of change of frequency, which is Δf / Δt, and is the rate of change of the measured frequency over time.

[0102] The virtual inertia H and active power P of the grid-type energy storage are automatically modified based on the difference between RoCoF and the threshold RoCoFmax.

[0103] It should be noted that the virtual inertia H is modified as follows: The method for modifying the active power P is as follows: H' and P' are the modified H and P;

[0104] Repeat until RoCoF ≤ RoCoFmax is detected.

[0105] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this application.

[0106] This embodiment also provides a power system control device based on grid-connected energy storage, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0107] Figure 4 This is a structural block diagram of a power system control device based on grid-connected energy storage according to an embodiment of this application, such as... Figure 4 As shown, the device includes:

[0108] The determining unit 402 is used to determine the first synchronous machine with the smallest inertia time constant from the power system, and to determine the second synchronous machine that is farthest from the first synchronous machine and the third synchronous machine that is closest to the first synchronous machine from the power system.

[0109] Deployment unit 404 is used to deploy grid-type energy storage on the second synchronous machine and to set power disturbances on the third synchronous machine;

[0110] Acquisition unit 406 is used to acquire the frequency change rate of the first synchronizer during power disturbance;

[0111] The correction unit 408 is used to correct the control response parameters of the grid-type energy storage based on the difference between the frequency change rate and the expected threshold when the frequency change rate is greater than the expected threshold, until the frequency change rate is less than or equal to the expected threshold.

[0112] As an optional solution, the correction unit 408 includes:

[0113] The first acquisition module is used to acquire the virtual inertia parameters and active power parameters of the grid-type energy storage, wherein the control response parameters include the virtual inertia parameters and active power parameters.

[0114] The correction module is used to add the first product of the first weight parameter and the difference to the virtual inertia parameter to obtain the corrected virtual inertia parameter, and to add the second product of the second weight parameter and the difference to the active power parameter to obtain the corrected active power parameter.

[0115] The corrected control response parameters include the corrected virtual inertia parameters and the corrected active power parameters.

[0116] As an optional solution, the device also includes:

[0117] The second acquisition module is used to obtain the corrected virtual inertia parameter by adding the first weight parameter multiplied by the difference to the virtual inertia parameter, and to obtain the corrected active power parameter by adding the second weight parameter multiplied by the difference to the active power parameter. Before obtaining the corrected active power parameter, the module acquires the ratio between the difference and the frequency change rate, and acquires the target ratio interval to which the ratio belongs in multiple ratio intervals. Here, one ratio interval corresponds to one weight coefficient pair, and one weight coefficient pair includes a weight coefficient for correcting the virtual inertia parameter and a weight coefficient for correcting the active power parameter.

[0118] The third acquisition module is used to obtain the corrected virtual inertia parameter by adding the first weight parameter multiplied by the difference to the virtual inertia parameter and to obtain the corrected active power parameter by adding the second weight parameter multiplied by the difference to the active power parameter. Before obtaining the corrected active power parameter, the module acquires the target weight coefficient pair corresponding to the target interval, wherein the target weight coefficient pair includes the first weight coefficient and the second weight coefficient.

[0119] As an optional solution, the device also includes:

[0120] The fourth acquisition module is used to obtain the corrected virtual inertia parameters by adding the first weight parameter multiplied by the difference to the virtual inertia parameters and the corrected active power parameters by adding the second weight parameter multiplied by the difference to the active power parameters. Then, it acquires the operating status change information of the power system.

[0121] The update module is used to add the first weight parameter multiplied by the difference to the virtual inertia parameter to obtain the corrected virtual inertia parameter, and add the second weight parameter multiplied by the difference to the active power parameter to obtain the corrected active power parameter. Then, based on the change information of the operating status, the expected threshold is updated.

[0122] The fifth acquisition module is used to obtain the corrected virtual inertia parameters by adding the first weight parameter multiplied by the difference to the virtual inertia parameters, and to obtain the corrected active power parameters by adding the second weight parameter multiplied by the difference to the active power parameters. After obtaining the corrected active power parameters, the module acquires the frequency change rate of the first synchronous machine updated during power disturbances after the control response parameters of the grid-type energy storage are corrected.

[0123] The verification module is used to verify the updated frequency change rate and the updated expected threshold after adding the first weight parameter multiplied by the difference to the virtual inertia parameter to obtain the corrected virtual inertia parameter, and adding the second weight parameter multiplied by the difference to the active power parameter to obtain the corrected active power parameter.

[0124] As an optional solution, determining unit 402 includes:

[0125] The sixth acquisition module is used to acquire the electrical distance between the first synchronous machine and other synchronous machines in the power system, except for the first synchronous machine. The electrical distance between each of the other synchronous machines and the first synchronous machine is obtained by adding the first internal impedance of each synchronous machine to the second internal impedance of the first synchronous machine and then subtracting the mutual impedance between each synchronous machine and the first synchronous machine.

[0126] The determination module is used to determine the synchronous machine that is closest to the first synchronous machine among other synchronous machines as the second synchronous machine, and to determine the synchronous machine that is furthest from the first synchronous machine among other synchronous machines as the third synchronous machine.

[0127] As an optional solution, the acquisition unit 406 includes:

[0128] The seventh acquisition module is used to acquire the response curve of the system frequency over time at the bus where the first synchronizer is located during power disturbance, wherein the response curve is used to indicate the mapping relationship between system frequency and time.

[0129] The first calculation module is used to perform numerical differentiation calculations on the response curve to obtain the frequency change rate.

[0130] As an optional solution, deployment unit 404 includes:

[0131] The eighth acquisition module is used to acquire multiple active power imbalance events recorded by the power system in a historical time period, and to acquire the power deficit corresponding to each active power imbalance event.

[0132] The second calculation module is used to perform cumulative distribution calculation on multiple power deficits corresponding to multiple active power imbalance events to obtain disturbance parameters, wherein the disturbance parameters are the quantiles of preset thresholds corresponding to multiple power deficits.

[0133] The deployment module is used to set the power disturbance corresponding to the disturbance parameters in the third synchronizer.

[0134] Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0135] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this application.

[0136] It should be noted that the above modules can be implemented by software or hardware. For the latter, they can be implemented in the following ways, but are not limited to: all the above modules are located in the same processor; or, the above modules are located in different processors in any combination.

[0137] Embodiments of this application also provide a computer-readable storage medium storing a computer program, wherein the computer program is configured to execute the steps in any of the above method embodiments when run.

[0138] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard disk, magnetic disk, or optical disk.

[0139] Embodiments of this application also provide an electronic device, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0140] In one exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0141] Embodiments of this application also provide a computer program product, including a non-volatile computer-readable storage medium storing the computer program product, wherein the computer program, when executed by a processor, implements the steps of the methods in various embodiments of this application.

[0142] Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0143] Obviously, those skilled in the art should understand that the modules or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, this application is not limited to any particular combination of hardware and software.

[0144] The above are merely preferred embodiments of this application and are not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. A power system control method based on grid-connected energy storage, characterized in that, include: The first synchronous machine with the smallest inertia time constant is determined from the power system, and the second synchronous machine that is farthest from the first synchronous machine and the third synchronous machine that is closest to the first synchronous machine are determined from the power system. Grid-based energy storage is deployed on the second synchronous machine, and power disturbances are set on the third synchronous machine; Obtain the rate of frequency change of the first synchronizer during the power disturbance; If the frequency change rate is greater than the expected threshold, the control response parameters of the grid-type energy storage are corrected based on the difference between the frequency change rate and the expected threshold until the frequency change rate is less than or equal to the expected threshold.

2. The method according to claim 1, characterized in that, The step of correcting the control response parameters of the grid-type energy storage based on the difference between the frequency change rate and the expected threshold includes: The virtual inertia parameter and active power parameter of the grid-type energy storage are obtained, wherein the control response parameter includes the virtual inertia parameter and the active power parameter; The corrected virtual inertia parameter is obtained by adding a first weight parameter multiplied by the first product of the difference to the virtual inertia parameter, and the corrected active power parameter is obtained by adding a second weight parameter multiplied by the second product of the difference to the active power parameter. The corrected control response parameters include the corrected virtual inertia parameters and the corrected active power parameters.

3. The method according to claim 2, characterized in that, Before adding a first product of the first weighting parameter and the difference to the virtual inertia parameter to obtain the corrected virtual inertia parameter, and adding a second product of the second weighting parameter and the difference to the active power parameter to obtain the corrected active power parameter, the method further includes: Obtain the ratio between the difference and the rate of change of frequency, and obtain the target ratio interval to which the ratio belongs in a plurality of ratio intervals, wherein a ratio interval corresponds to a weighting coefficient pair, and a weighting coefficient pair includes a weighting coefficient for correcting the virtual inertia parameter and a weighting coefficient for correcting the active power parameter. Obtain the target weight coefficient pair corresponding to the target interval, wherein the target weight coefficient pair includes the first weight coefficient and the second weight coefficient.

4. The method according to claim 2, characterized in that, After adding a first product of the first weighting parameter and the difference to the virtual inertia parameter to obtain the corrected virtual inertia parameter, and adding a second product of the second weighting parameter and the difference to the active power parameter to obtain the corrected active power parameter, the method further includes: Obtain information on changes in the operating status of the power system; The expected threshold is updated based on the changes in the operating status. After the control response parameters of the grid-type energy storage are corrected, the frequency change rate of the first synchronous machine is updated during the power disturbance. The updated rate of change and the updated expected threshold are verified.

5. The method according to any one of claims 1 to 4, characterized in that, The step of determining the second synchronizer that is furthest from the first synchronizer and the third synchronizer that is closest to the first synchronizer from the power system includes: The electrical distance between the first synchronous machine and other synchronous machines in the power system is obtained, wherein the electrical distance between each of the other synchronous machines and the first synchronous machine is obtained by adding the first internal impedance of each synchronous machine to the second internal impedance of the first synchronous machine and then subtracting the mutual impedance between each synchronous machine and the first synchronous machine. The synchronizer that is closest in electrical distance to the first synchronizer among the other synchronizers is identified as the second synchronizer, and the synchronizer that is furthest in electrical distance from the first synchronizer among the other synchronizers is identified as the third synchronizer.

6. The method according to any one of claims 1 to 4, characterized in that, The step of obtaining the frequency change rate of the first synchronizer during the power disturbance includes: During the power disturbance, the system frequency response curve over time at the bus where the first synchronizer is located is obtained, wherein the response curve is used to indicate the mapping relationship between the system frequency and the time; The frequency change rate is obtained by performing numerical differentiation on the response curve.

7. The method according to any one of claims 1 to 4, characterized in that, The provision of power disturbance in the third synchronizer includes: The system acquires multiple active power imbalance events recorded in the power system over a historical period, and acquires the power deficit corresponding to each active power imbalance event. The cumulative distribution of multiple power deficits corresponding to the multiple active power imbalance events is calculated to obtain disturbance parameters, wherein the disturbance parameters are the quantiles of preset thresholds corresponding to the multiple power deficits; The power disturbance corresponding to the disturbance parameter is set in the third synchronizer.

8. A power system control device based on grid-connected energy storage, characterized in that, include: The determining unit is used to determine the first synchronous machine with the smallest inertia time constant from the power system, and to determine the second synchronous machine that is farthest from the first synchronous machine and the third synchronous machine that is closest to the first synchronous machine from the power system. A deployment unit is used to deploy grid-type energy storage on the second synchronizer and to set power disturbances on the third synchronizer; The acquisition unit is used to acquire the frequency change rate of the first synchronizer during the power disturbance; The correction unit is used to correct the control response parameters of the grid-type energy storage based on the difference between the frequency change rate and the expected threshold when the frequency change rate is greater than the expected threshold, until the frequency change rate is less than or equal to the expected threshold.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program, when executed by a processor, implements the steps of the method according to any one of claims 1 to 7.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

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