Decentralized adaptive control method for microgrid energy storage systems under unknown disturbances

Abstract

The present invention provides a distributed adaptive control method for microgrid energy storage system under unknown disturbance, establishes a control model of the microgrid energy storage system, formulates a distributed adaptive frequency recovery strategy according to the frequency global output error and dynamic control gain of the energy storage system based on the consistency theory, formulates a distributed adaptive active power dispatch and charge state balancing strategy according to the charge state, active power global output error and dynamic control gain of the energy storage system, and adaptively controls the control model of the microgrid energy storage system using the frequency recovery strategy, active power dispatch and charge state balancing strategy. The present invention effectively improves the disturbance resistance ability of the microgrid energy storage system and ensures the consistency and exponential convergence of the system.

Description

[Technical Field]

[0001] This invention claims priority to a Chinese patent application bearing application number 202210108260.5 and entitled "Distributed adaptive control method for microgrid energy storage system under unknown disturbances," filed with the China Patent Office on January 28, 2022, the entire contents of which are incorporated herein by reference.

[0002] The present invention belongs to the technical field of microgrid control, and particularly to a distributed adaptive control method for microgrid energy storage systems under unknown disturbances. [Background technology]

[0003] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0004] Microgrids, as intelligent, autonomous small-scale power generation and distribution networks consisting of distributed generation units, energy storage systems, loads, and associated energy conversion and protection devices, are an important link in facilitating renewable energy access to the large-scale grid. To maximize the benefits of microgrids, renewable energy sources such as solar and wind power typically operate in maximum power tracking mode, requiring energy storage systems to suppress power fluctuations and maintain a supply-demand balance between renewable energy and loads. Energy storage systems also play an important role in peak shaving, improving power quality, and enhancing system stability. Therefore, the control issues of microgrid energy storage systems have attracted widespread attention.

[0005] Distributed cooperative control is widely used in microgrid energy storage systems. In a multi-agent system framework, energy storage systems communicate only with their neighbors through a sparse communication network, enabling them to achieve cooperative control goals such as frequency and voltage stabilization and power dispatch. Compared with traditional centralized control, distributed control can solve the problems of low reliability and scalability of microgrids.

[0006] However, the commonly used microgrid hierarchical control architecture has difficulty in solving the charge state balance problem of the energy storage system, and also in resisting unknown bounded disturbances (such as current / voltage measurement noise), which affect the stable operation of the system. Summary of the Invention [Problem to be solved by the invention]

[0007] In order to solve the above problems, the present invention proposes a decentralized adaptive control method for microgrid energy storage systems under unknown disturbances. Based on the decentralized coordinated control theory, the present invention introduces dynamic control gains and proposes an adaptive control method to solve the coordinated control problems of frequency recovery, active power distribution and charge state balance of the microgrid energy storage system, while effectively improving the disturbance resistance ability of the microgrid energy storage system and ensuring the consistency and exponential convergence of the system. [Means for solving the problem]

[0008] In some embodiments, the present invention employs the following technical solutions.

[0009] A method for decentralized adaptive control of a microgrid energy storage system under unknown disturbances, comprising: establishing a control framework for the microgrid energy storage system; According to the consistency theory, a dynamic control gain is introduced according to the frequency global output error of the energy storage system to formulate a distributed adaptive frequency recovery strategy, and according to the charge state and the global output error of the active power of the energy storage system, a dynamic control gain is introduced to formulate a distributed adaptive active power dispatch and charge state balancing strategy; and controlling the microgrid energy storage system using a distributed adaptive frequency restoration strategy, active power dispatch and charge state balancing strategy.

[0010] As an optional embodiment, a specific process of establishing a control framework for a microgrid energy storage system includes establishing a state space model of the energy storage system, introducing auxiliary control variables and establishing a secondary control module to compensate for frequency deviation due to droop control and considering the impact of unknown bounded interference on the energy storage system.

[0011] In an optional embodiment, the method further includes constructing a communication topology between the energy storage systems based on algebraic graph theory to describe the communication network of the microgrid energy storage systems.

[0012] In an alternative embodiment, the distributed adaptive frequency restoration strategy comprises:

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[0013] In a more limited embodiment, the dynamic control gain

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[0014] In an alternative embodiment, the distributed adaptive active power dispatch and charge state balancing strategy comprises:

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[0015] As a more limited embodiment,

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[0016] 1. A distributed adaptive control system for a microgrid energy storage system under unknown disturbances, comprising: a control framework establishment module configured to establish a control framework for the microgrid energy storage system; a control strategy determination module configured to, based on consistency theory, introduce a dynamic control gain according to the frequency global output error of the energy storage system to formulate a distributed adaptive frequency recovery strategy, and introduce a dynamic control gain according to the charge state and global output error of the active power of the energy storage system to formulate a distributed adaptive active power dispatch and charge state balancing strategy; and an adaptive control execution module configured to control the microgrid energy storage system using a distributed adaptive frequency restoration strategy, an active power dispatch and a charge state balancing strategy.

[0017] An electronic device includes a memory, a processor, and computer instructions stored in the memory and executable on the processor, the computer instructions, when executed by the processor, completing the steps of the method.

[0018] A computer-readable storage medium for storing computer instructions that, when executed by a processor, complete the steps of the above method. [Effects of the Invention]

[0019] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0020] In order to achieve frequency recovery, active power recovery and charge state balancing of a microgrid energy storage system under unknown interference, this invention proposes a decentralized adaptive control method, and introduces dynamic control gain to improve the disturbance resistance ability of the system, so that the control targets of frequency, active power and charge state can be effectively achieved.

[0021] In order to make the above objects, features and advantages of the present invention more clear and understandable, preferred embodiments will be described in detail below with reference to the accompanying drawings.

[0022] The drawings in the specification that form a part of this invention are intended to provide a further understanding of the invention, and the exemplary embodiments of the invention and their descriptions are used to explain the invention and do not constitute undue limitations on the invention. [Brief explanation of the drawings]

[0023] [Figure 1] FIG. 2 is a block diagram of distributed control of the energy storage system according to the present embodiment. [Figure 2] FIG. 1 is a communication topology diagram of an AC microgrid test system. [Figure 3(a)] 10A and 10B are diagrams showing simulation results of a load conversion test. [Figure 3(b)] 10A and 10B are diagrams showing simulation results of a load conversion test. [Figure 3(c)] 10A and 10B are diagrams showing simulation results of a load conversion test. DETAILED DESCRIPTION OF THE INVENTION

[0024] The present invention will now be further described with reference to the following figures and examples.

[0025] However, the following detailed description is for illustrative purposes only and is intended to provide further explanation of the present invention. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art.

[0026] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments of the present invention. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should be understood that when the terms "comprises" and / or "comprises" are used herein, they specify the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0027] As shown in Figure 1, the specific process of the distributed adaptive control method is as follows: establishing a control model of the microgrid energy storage system; According to the consistency theory, a dynamic control gain is introduced according to the frequency global output error of the energy storage system to formulate a distributed adaptive frequency recovery strategy, and according to the charge state and the global output error of the active power of the energy storage system, a dynamic control gain is introduced to formulate a distributed adaptive active power dispatch and charge state balancing strategy; and controlling the microgrid energy storage system using a distributed adaptive frequency restoration strategy, active power dispatch and charge state balancing strategy.

[0028] Hereinafter, one specific example will be given and will be described in detail from the following points.

[0029] 1: Establish the control framework of the microgrid energy storage system and determine the control objectives.

[0030] 2: Design a decentralized adaptive control method considering the effect of unknown interference on the energy storage system.

[0031] 3: Based on the Lyapunov stability theorem, we prove the consistency and convergence of the control method according to the invention.

[0032] 4: Build a simulation test system for a microgrid energy storage system and verify the effectiveness of the control method of the invention.

[0033] 1: Control framework for microgrid energy storage systems 1.1: State-space model of the energy storage system In a microgrid, the energy storage system consists of multiple batteries, an inverter, and an LC filter. Using the output current of the energy storage systems, the state of charge level of the ith energy storage system can be calculated as follows:

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[0034]

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[0035] 1.2: Energy storage system control framework Based on the droop control strategy, the energy storage system can quickly respond to the load fluctuation in the system, maintain the stability of the system frequency, and establish the fP droop control.

[0036]

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[0037] However, as a peer-to-peer control, droop control causes the actual frequency to deviate from the set value, which affects the accuracy of the active power distribution. Therefore, a secondary control is designed to compensate for the frequency deviation caused by droop control, consider the impact of unknown bounded interference on the energy storage system, and adjust the auxiliary control variable.

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[0038]

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[0039] The above control structure can achieve the control objectives of the microgrid energy storage system: (1) frequency recovery, (2) proportional active power distribution, and (3) charge state balance.

[0040] 2: Distributed adaptive control method 2.1: Communication Topology To describe the communication network of a microgrid energy storage system, we construct a communication topology between energy storage systems based on algebraic graph theory. A microgrid contains N agents (energy storage systems), and the set of nodes V = {v1, v2, ... v} in an undirected graph G(V, E, A) is N} represents the set of all energy storage systems, the edge set E⊆V×V represents the communication links that can exchange information, and A=[a ij ]∈R N×NLet us assume that represents the adjacency matrix, and (v i ,v j )∈E, then a ij >0, otherwise a ij = 0. The set of neighbor nodes of the i-th node is N i ={j|(v j ,v i )∈E}, then the in-degree matrix of an undirected graph G is D=diag{d i}∈R N×N and

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[0041] 2.2: Frequency controller To realize frequency recovery of energy storage systems under unknown interference, the following distributed adaptive frequency recovery strategy is designed based on consistency theory.

[0042]

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[0043]

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[0044] 2.3: Active power and state of charge controller To realize the active power dispatch and charge state balancing of the energy storage system under unknown interference, the following distributed adaptive active power dispatch and charge state balancing strategy is designed based on the consistency theory.

[0045]

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[0046]

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[0047] 3: Consistency and convergence analysis To verify the effectiveness of the invented distributed adaptive control method, a frequency recovery strategy is taken as an example to demonstrate its consistency and convergence in detail.

[0048] 3.1: Construction of Lyapunov functions To achieve the control goal of restoring the frequency of the energy storage system to a set reference value, the frequency tracking error is defined as follows:

[0049]

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[0050] Construct the following Lyapunov function:

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[0052] 3.2: Consistency and convergence analysis Built

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[0053] Scaling equation (18) gives

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[0054] The above process is to obtain the frequency consistency tracking error e ω is 2ηλ min We prove that the control objective of frequency recovery is achieved by exponentially converging to 0 at the rate above, where λ min is the smallest non-zero eigenvalue of the matrix.

[0055] Based on the above analysis, it is proved that the distributed adaptive control method for energy storage systems according to the invention can quickly achieve the control target and effectively resist the influence of unknown bounded disturbances on the system.

[0056] 4: Simulation test To verify the effectiveness of the invented control method, an AC microgrid test system was built based on the MATLAB / Simulink platform and a load change test was carried out. In the simulation test, the reference frequency was set to ω ref = 314 rad / s, and the initial charge state of the energy storage system is set as E(0) = [68%, 67.8%, 67.6%, 67.4%, 67.2%]. T and set the bounded interference to f i We set (·) = 0.2 sin(t), and the communication topology is shown in Figure 2.

[0057] The total time of the load change simulation test was 35 seconds, and the specific step design was as follows:

[0058] (1) Phase 1: 0s to 2s. At t=0s, only the primary control is accessed in the system, and loads 1, 2, 4, and 5 operate normally.

[0059] (2) Phase 2: 2s to 15s. At t=2s, the system is accessed by the distributed secondary control, and loads 1, 2, 4, and 5 operate normally.

[0060] (3) Phase 3: 15-25 s. At t=15 s, Load 3 is plugged into the system, and all loads operate normally.

[0061] (4) Phase 4: 25s to 25s. At t=25s, load 3 is removed, and loads 1, 2, 4, and 5 operate normally.

[0062] The simulation test results are shown in Figures 3(a) to 3(c). As can be seen, after the distributed secondary control is accessed, frequency compensation, active power distribution, and charge state balance are achieved. When load 3 is inserted or removed from the system, the frequency fluctuates slightly and then quickly recovers to a stable state, and active power distribution and charge state balance are also ensured.

[0063] Those skilled in the art should understand that embodiments of the present invention may be provided as a method, a system, or a computer program product. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk memory, CD-ROM, optical memory, etc.) containing computer-usable program code.

[0064] The present invention will be described with reference to flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, and combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processing device, or other programmable data processing device to produce a machine, whereby the instructions, executed by the processor of the computer or other programmable data processing device, produce an apparatus for implementing the function specified in the process or processes in the flowcharts and / or the block or blocks in the block diagrams.

[0065] These computer program instructions may be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture that includes an instruction apparatus that implements the functions specified in a process or processes in the flowcharts and / or a block or blocks in the block diagrams.

[0066] These computer program instructions may be loaded into a computer or other programmable data processing device, which then executes a series of operational steps on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executing on the computer or other programmable device provide steps for implementing the functions specified in a process or processes in the flowcharts and / or a block or blocks in the block diagrams.

[0067] Although specific embodiments of the present invention have been described above with reference to the drawings, they are not intended to limit the scope of protection of the present invention, and those skilled in the art should understand that various modifications and variations made by those skilled in the art based on the technical solutions of the present invention without any creative work still fall within the scope of protection of the present invention.

Claims

1. A method for decentralized adaptive control of a microgrid energy storage system under unknown disturbances, comprising: establishing a control framework for the microgrid energy storage system; Introducing dynamic control gains according to the frequency global output error of the energy storage system to formulate a distributed adaptive frequency recovery strategy, and introducing dynamic control gains according to the charge state and active power global output errors of the energy storage system to formulate a distributed adaptive active power dispatch and charge state balancing strategy, so as to ensure consistency and convergence; and controlling the microgrid energy storage system using a distributed adaptive frequency restoration strategy, active power dispatch and charge state balancing strategy; The distributed adaptive frequency restoration strategy comprises: [0.0000] and During the ceremony, [Equation 45] is the frequency global output error of the energy storage system i, ω ref is the set reference frequency, sgn(·) represents the sign function, [Equation 46] A decentralized adaptive control method for microgrid energy storage systems under unknown disturbances, characterized in that is the dynamic control gain.

2. The method for decentralized adaptive control of a micro-grid energy storage system under unknown disturbances as claimed in claim 1, characterized in that the specific process of establishing a control framework for the micro-grid energy storage system includes: establishing a state space model of the energy storage system; introducing auxiliary control variables and establishing a secondary control module to compensate for frequency deviation caused by droop control and to consider the impact of unknown bounded interference on the energy storage system.

3. 2. The method for distributed adaptive control of micro-grid energy storage systems under unknown disturbances as claimed in claim 1, further comprising: constructing a communication topology between the energy storage systems based on algebraic graph theory to describe the communication network of the micro-grid energy storage systems.

4. Dynamic Control Gain [Equation 47] The adaptation rate of [Number 48] and In the formula, b １ , b ２ , c １ , c ２ , d １ , d ２ is a normal number, [Number 49] The decentralized adaptive control method for a microgrid energy storage system under unknown disturbances as claimed in claim 1, characterized in that:

5. A decentralized adaptive active power dispatch and charge state balancing strategy is [Number 50] and During the ceremony, [0.51] is the global output error of the state of charge and active power of the energy storage system i, [Number 52] 2. The decentralized adaptive control method for microgrid energy storage systems under unknown disturbances as claimed in claim 1, wherein: [Request Item 6] [Number 53] is the dynamic control gain, and its adaptation rate is [Number 54] and In the formula, b ３ , b ４ , c ３ , c ４ , d ３ , d ４ is a normal number, [Number 55] The decentralized adaptive control method for a microgrid energy storage system under unknown disturbances as claimed in claim 5, wherein:

7. 1. A distributed adaptive control system for a microgrid energy storage system under unknown disturbances, comprising: a control framework establishment module configured to establish a control framework for the microgrid energy storage system; a control strategy determination module configured to introduce dynamic control gains according to the frequency global output error of the energy storage system to formulate a distributed adaptive frequency restoration strategy, and introduce dynamic control gains according to the charge state and active power global output errors of the energy storage system to formulate a distributed adaptive active power dispatch and charge state balancing strategy, so as to ensure consistency and convergence; an adaptive control execution module configured to control the microgrid energy storage system using a distributed adaptive frequency restoration strategy, an active power dispatch and a charge state balancing strategy; The distributed adaptive frequency restoration strategy comprises: [Number 56] and During the ceremony, [Number 57] is the frequency global output error of the energy storage system i, ω ref is the set reference frequency, sgn(·) represents the sign function, [Number 58] A decentralized adaptive control system for microgrid energy storage systems under unknown disturbances, characterized in that is the dynamic control gain.

8. An electronic device comprising a memory, a processor, and computer instructions stored in the memory and executed on the processor, the computer instructions, when executed by the processor, completing the steps of the method of any one of claims 1 to 6.

9. A computer-readable storage medium for storing computer instructions that, when executed by a processor, complete the steps of the method of any one of claims 1 to 6.

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