CN-122021045-A - Multi-time scale unified modeling and equivalence method and system for network-structured energy storage system

CN122021045ACN 122021045 ACN122021045 ACN 122021045ACN-122021045-A

Abstract

The invention provides a multi-time scale unified modeling and equivalence method and system for a grid-built energy storage system, and belongs to the technical field of modeling of electric power systems; the method comprises the steps of classifying all state variables of a network-structured energy storage system according to a time scale of dominant dynamics, constructing three-layer nested differential manifolds based on the time scale classification to obtain a geometric state space, establishing a generalized Lagrange unified dynamics equation of the network-structured energy storage system, carrying out collaborative optimization on the parameterized equivalent model, deploying a layering parallel self-adaptive updating mechanism, enabling the parameterized equivalent model to continuously evolve in a whole life cycle, and realizing multi-time scale unified modeling and physical consistency equivalence of the network-structured energy storage system. The invention establishes a unified dynamic equation based on a generalized Lagrangian framework, and utilizes Li Kuohao operation to analyze, calculate and quantitatively map the cross-scale coupling, thereby realizing accurate quantitative description of different time scale dynamic coupling mechanisms.

Inventors

ZHANG FENG
LI WENJING
DING LEI
LIU TINGXIANG
FANG BAOMIN
ZHOU WANPENG
CHEN XUE
WANG KAI
WANG ZIMING

Assignees

山东大学
国网青海省电力公司经济技术研究院
国网青海省电力公司清洁能源发展研究院
国网青海省电力公司

Dates

Publication Date: 20260512
Application Date: 20260211

Claims (10)

1. A multi-time scale unified modeling and equivalence method of a network-structured energy storage system is characterized by comprising the following steps: classifying all state variables of the network-structured energy storage system according to a time scale of dominant dynamics, and constructing three-layer nested differential manifolds based on the time scale classification to obtain a geometric state space; Based on the geometric state space, establishing a generalized Lagrange unified dynamics equation of the grid-structured energy storage system, explicitly separating multi-time-scale dynamics by introducing scale parameters, and quantifying the coupling relation between different time-scale dynamics by utilizing Li Kuohao operation; Constructing a parameterized equivalent model according to the unified dynamics equation and the quantized coupling relation, and performing cooperative optimization on the parameterized equivalent model; And carrying out full-working-condition verification on the parameterized equivalent model after collaborative optimization, and deploying a layering parallel self-adaptive updating mechanism to enable the parameterized equivalent model to continuously evolve in a full life cycle, so as to realize multi-time scale unified modeling and physical consistency equivalent of the network-structured energy storage system.
2. The multi-time scale unified modeling and equivalence method of a grid-structured energy storage system of claim 1, wherein the full state variables are classified into a fast scale state set, a mesoscale state set, and a slow scale state set according to a time scale of dominant dynamics.
3. The method for unified modeling and equivalence of multiple time scales of a grid-structured energy storage system according to claim 2, wherein the constructing three-layer nested differential manifolds based on the time scale classification, to obtain a geometric state space, comprises: Respectively constructing corresponding sub-manifolds for the fast scale state set, the medium scale state set and the slow scale state set; combining the sub-manifolds into a smooth product manifold to form a three-layer nested differential manifold; the ratio of the time constants of the fast scale dynamics and the mesoscale dynamics is defined as a first scale separation parameter, and the ratio of the time constants of the mesoscale dynamics and the slow scale dynamics is defined as a second scale separation parameter.
4. The method for unified modeling and equivalence of multiple time scales of a grid-structured energy storage system according to claim 1, wherein the constructing three-layer nested differential manifolds based on the time scale classification, to obtain a geometric state space, further comprises: Defining a geometry on a geometry state space; the geometry includes a kinetic energy metric tensor, a canonical Xin Jiegou, and a rayleigh dissipation function, where, The kinetic energy metric tensor is configured to quantitatively characterize the inertial coupling strength between the state variables by its matrix elements; The regular octyl structure is configured to uniquely determine a plurality of regular coordinate pairs, each of which corresponds to one physical conservation constant pair; The rayleigh dissipation function is configured to characterize energy losses in the mesh energy storage system, including switch conduction losses, virtual synchromesh damping losses, thermal conduction losses, and battery internal resistance losses.
5. The method for uniformly modeling and equating multiple time scales of a network-structured energy storage system according to claim 3, wherein the explicit separation of the multiple time scales by introducing scale parameters comprises: Introducing the first scale separation parameter and the second scale separation parameter into the generalized Lagrangian unified dynamics equation as time scale transformation factors of corresponding dynamics items; multiplying the first scale separation parameter by all generalized inertia terms related to mesoscale dynamics in the equation, and multiplying the second scale separation parameter by all generalized inertia terms related to slow scale dynamics in the equation to obtain a generalized Lagrange unified dynamics equation of scale recombination; Reconstructing the scale recombined generalized Lagrangian unified dynamics equation into three mutually coupled subsystems so as to realize the explicit separation of multi-time scale dynamics; The three mutually coupled subsystems are a first time scale subsystem, a second time scale subsystem and a third time scale subsystem respectively, The first time scale subsystem characterizes an electromagnetic transient dominated by a natural time constant of the networked energy storage system, The second time scale subsystem characterizes the electromechanical transient process and the control dynamic process dominated by the time constant which is slowed down by the first scale separation parameter, The third time scale subsystem characterizes an energy scheduling process and an aging evolution process dominated by a time constant that is subject to the second scale separation parameter slowing down.
6. The method for unified modeling and equivalence of multiple time scales of a grid-structured energy storage system according to claim 2, wherein the quantification of the coupling relationship between different time scale dynamics using Li Kuohao operations comprises: based on the generalized Lagrangian unified dynamics equation, respectively aiming at a fast scale state set, a mesoscale state set and a slow scale state set, defining a fast scale vector field, a mesoscale vector field and a slow scale vector field; Calculating a first bracket between the fast scale vector field and the mesoscale vector field, a second Li Kuohao between the mesoscale vector field and the slow scale vector field, and a third bracket between the fast scale vector field and the slow scale vector field; Quantifying nonlinear coupling strengths between the fast-scale and the mesoscale, between the mesoscale and the slow-scale, and between the fast-scale and the slow-scale according to the modular lengths of the first Li Kuohao, the second Li Kuohao, and the third Li Kuohao, respectively; the quantized nonlinear coupling strengths are mapped into engineering parameters that include coupling gain and coupling delay.
7. The method for unified modeling and equivalence of multiple time scales of a grid-structured energy storage system according to claim 6, wherein the constructing a parameterized equivalence model and performing collaborative optimization on the parameterized equivalence model comprises: constructing a parameterized equivalent model, wherein the parameterized equivalent model comprises a first equivalent module, a second equivalent module, a third equivalent module and a trans-scale coupling module; the first equivalent module corresponds to the fast scale dynamic, and comprises a controlled voltage source and a frequency-dependent impedance network; the second equivalent module corresponds to the mesoscale dynamics, and is an extended virtual synchronous machine model; the third equivalent module corresponds to the slow-scale dynamics, the third equivalent module including a time-varying parameter and a time-varying parameter battery thermal coupling model integrating the aging prediction.
8. The method for unified modeling and equivalence of multiple time scales of a grid-structured energy storage system according to claim 7, wherein the constructing a parameterized equivalence model and performing collaborative optimization on the parameterized equivalence model further comprises: Step-by-step primary identification is carried out on the parameters of the parameterized equivalent model to obtain the parameter initial values of all the modules of the parameterized equivalent model; taking the coupling gain and the coupling delay of the cross-scale coupling module as coupling constraint and taking the initial value of the parameter as a starting point to cooperatively optimize the parameters of all the modules; the collaborative optimization is to minimize the output error of the parameterized equivalent model under the condition that the coupling constraint is satisfied.
9. The multi-time scale unified modeling and equivalence method of the grid-structured energy storage system according to claim 1, wherein the constraint feedforward updating layer in the hierarchical parallel self-adaptive updating mechanism is used for online updating parameters of the parameterized equivalence model by using a constrained recursive estimation algorithm in the grid-connected operation process of the grid-structured energy storage system.
10. A multi-time scale unified modeling and equivalence system of a grid-built energy storage system, characterized in that the system comprises a control module, the control module comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, and the processor executes the computer program to realize the multi-time scale unified modeling and equivalence method of the grid-built energy storage system according to any one of claims 1-9.

Description

Multi-time scale unified modeling and equivalence method and system for network-structured energy storage system Technical Field The invention relates to the technical field of modeling of power systems, in particular to a multi-time scale unified modeling and equivalence method and system of a grid-built energy storage system. Background With the continuous deepening of high-proportion renewable energy grid connection and power electronics, the dynamic characteristics of a power system become more complex, and the stability analysis and operation control of the power system bring higher requirements on the accuracy of a key equipment model. The network-structured energy storage system is used as a new generation of power grid stable support core equipment, can autonomously construct power grid voltage and frequency, provides rapid active and reactive power support and virtual inertia, and has increasingly outstanding importance. Correspondingly, the modeling and simulation technology of the network-structured energy storage system is subjected to a development process from simple to complex, early research focuses on an electromagnetic transient model of a converter and a quasi-steady-state model based on active frequency and reactive voltage sag, and in order to achieve simulation efficiency and precision, the multi-rate simulation and interface technology is applied, and in particular, asynchronous long calculation is adopted for the electromagnetic transient process and the electromechanical transient process in simulation. In recent years, in order to more truly represent the electromechanical transient characteristics of a virtual synchronous machine, a detailed control model covering a rotor motion equation and a voltage regulation link becomes a research hot spot, and meanwhile, an electrothermal coupling model combining slow dynamics and electric dynamics above the electrochemical, thermodynamic and other seconds gradually enters an exploration stage along with the improvement of attention to the full life cycle economy and reliability of an energy storage system. The lack of a unified theoretical framework in the above scheme can lead to failure of accurate description and quantification of the coupling mechanism between the different time scale dynamics, thereby losing model prediction accuracy in analyzing the system level complex problem. Disclosure of Invention The invention aims to provide a multi-time scale unified modeling and equivalence method and system of a network-structured energy storage system, which are used for providing a multi-time scale equivalence model of the network-structured energy storage system, which can automatically maintain physical consistency and continuously evolve in a full life cycle, for power system simulation and analysis. The invention provides a multi-time scale unified modeling and equivalence method of a network-structured energy storage system, which comprises the steps of classifying all state variables of the network-structured energy storage system according to time scales of dominant dynamics, constructing three layers of nested differential manifolds based on the time scale classification to obtain a geometric state space, establishing a generalized Lagrange unified dynamics equation of the network-structured energy storage system based on the geometric state space, explicitly separating multi-time scale dynamics by introducing scale parameters, quantifying coupling relations among different time scale dynamics by utilizing Li Kuohao operation, constructing a parameterized equivalence model according to the unified dynamics equation and the quantized coupling relations, performing collaborative optimization on the parameterized equivalence model, performing full-time condition verification on the parameterized equivalence model after collaborative optimization, deploying a layered parallel self-adaptive update mechanism, enabling the parameterized equivalence model to continuously evolve in a full life cycle, and realizing unified and physical consistency equivalence of the multi-time scale modeling of the network-structured energy storage system. Optionally, the full state variables are classified into a fast scale state set, a mesoscale state set, and a slow scale state set according to a time scale of dominant dynamics. Optionally, the three-layer nested differential manifold is constructed based on the time scale classification to obtain a geometric state space, and the geometric state space comprises the steps of respectively constructing corresponding sub-manifolds for a fast scale state set, a mesoscale state set and a slow scale state set, combining the sub-manifolds into a smooth product manifold to form the three-layer nested differential manifold, defining the ratio of time constants of the fast scale dynamic state and the mesoscale dynamic state as a first scale separation parameter, and defining the ratio of time constants of the mesosc