A 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 filed with the China Patent Office on January 28, 2022, bearing application number 202210108260.5 and entitled "Distributed adaptive control method for microgrid energy storage system under unknown disturbances", 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] Microgrid, as an intelligent autonomous small-scale power generation distribution network consisting of distributed generation units, energy storage systems, loads and related energy conversion and protection devices, is an important link to promote the access of renewable energy to the large-scale grid. In order to maximize the benefits of microgrid, renewable energy such as solar power generation and wind power generation usually operates in maximum power tracking mode, at which time, the energy storage system needs to suppress power fluctuations and maintain the supply-demand balance between renewable energy and loads. In addition, the energy storage system also plays an important role in peak shaving, improving power quality, and improving system stability. Therefore, the control problem of microgrid energy storage system has attracted wide attention.

[0005] Distributed cooperative control is widely used in microgrid energy storage systems. In the multi-agent system framework, energy storage systems can communicate with only their neighbors through a sparse communication network to achieve cooperative control objectives 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 distributed adaptive control method for micro-grid energy storage system under unknown disturbances. Based on the distributed coordinated control theory, the present invention introduces dynamic control gain and proposes an adaptive control method to solve the coordinated control problems of frequency recovery, active power distribution and charge state balance of the micro-grid energy storage system, and effectively improves the disturbance resistance capability of the micro-grid energy storage system and ensures 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 distributed adaptive control of a microgrid energy storage system under unknown disturbances, comprising: Establishing a control framework for a 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 balance 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 to consider 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] As a more specific embodiment, the dynamic control gain

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[0014] As 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] 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 is configured to introduce a dynamic control gain according to the frequency global output error of the energy storage system based on the consistency theory to formulate a distributed adaptive frequency recovery strategy, and introduce a dynamic control gain according to the charge state and the 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, complete the steps of the method.

[0018] A computer-readable storage medium is adapted to store computer instructions which, when executed by a processor, complete the steps of the above method. Effect of the Invention

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

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

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

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

[0023] [Figure 1] FIG. 2 is a block diagram of distributed control of the energy storage system in the present embodiment. [Diagram 2] FIG. 1 is a communication topology diagram of an AC microgrid test system. [Figure 3(a)] 13 is a diagram showing a simulation result of a load conversion test. [Figure 3(b)] 13 is a diagram showing a simulation result of a load conversion test. [Figure 3(c)] 13 is a diagram showing a simulation result of a load conversion test. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

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

[0025] However, the following detailed description is all illustrative and is intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art.

[0026] It should be noted that the terminology used herein is for the purpose of describing specific 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 "comprise" 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 balance 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 embodiment will be given and will be described in detail from the following aspects.

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

[0030] 2: Considering the effect of unknown interference on the energy storage system, a decentralized adaptive control method is designed.

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

[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 is composed of multiple batteries, an inverter and an LC filter. Using the output current of the energy storage system, the state of charge level of the i-th energy storage system can be calculated as follows:

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[0034]

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[0035] 1.2: Control framework for energy storage systems Based on the droop control strategy, the energy storage system can quickly respond to the fluctuation of the load 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, the droop control will cause the actual frequency to deviate from the set value, which will affect the accuracy of the active power dispatch. Therefore, a secondary control is designed to compensate for the frequency deviation caused by the droop control, consider the effect 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 the microgrid energy storage system, we construct a communication topology between the energy storage systems based on algebraic graph theory. Let us assume that the microgrid contains N agents (energy storage systems), and the node set V = {v1, v2, … v 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. Let the set of neighbors of the i-th node be 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 system under unknown interference, the following distributed adaptive frequency recovery strategy is designed based on consistency theory.

[0042]

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[0044] 2.3: Active power and charge state controller In order 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.

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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: Constructing Lyapunov functions To achieve the control objective of restoring the frequency of the energy storage system to a set reference value, the frequency tracking error is defined as follows:

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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 the frequency consistency tracking error e ω is 2ηλ min We prove that the control objective of frequency recovery is realized by exponentially converging to 0 at a rate of 0 or more, where λ min is the smallest nonzero eigenvalue of the matrix.

[0055] Based on the above analysis, it is proved that the energy storage system distributed adaptive control method of 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 to carry out load change tests. 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 E(0) = [68%, 67.8%, 67.6%, 67.4%, 67.2%]. T and set the bounded interference to f i We set (·) = 0.2sin(t) and the communication topology is shown in Figure 2.

[0057] The total time of the load change simulation test is 35 s, and the specific step design is 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: 15~25s. At t=15s, 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 result diagrams are shown in Figure 3(a)-(c). As can be seen, after the distributed secondary control is accessed, frequency compensation, active power distribution and charge state balance are realized. When the load 3 is plugged into or removed from the system, the frequency quickly recovers to stability after a small fluctuation, and the active power distribution and charge state balance are also ensured.

[0063] Those skilled in the art should understand that the 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. And, 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 present 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 generate a machine, whereby the instructions executed by the processor of the computer or other programmable data processing device generate an apparatus for implementing the function specified in a process or processes in the flowcharts and / or a 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 generate 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 to perform a series of operational steps on the computer or other programmable device to generate a computer-implemented process, whereby the instructions executing on the computer or other programmable device provide steps for implementing the function specified in a process or processes in the flowcharts and / or a block or blocks in the block diagrams.

[0067] The above describes specific embodiments of the present invention with reference to the drawings, but this does not limit the scope of protection of the present invention. 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 creative labor still fall within the scope of protection of the present invention.

Claims

1. A method for distributed adaptive control of a microgrid energy storage system under unknown disturbances, comprising: Establishing a control framework for a 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 balance strategy; and controlling the microgrid energy storage system using a distributed adaptive frequency restoration strategy, an active power dispatch and a charge state balancing strategy.

2. The method for distributed adaptive control of micro-grid energy storage system under unknown disturbances as claimed in claim 1, characterized in that the specific process of establishing a control framework of 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 the frequency deviation caused by droop control, and considering the influence of unknown bounded interference on the energy storage system.

3. 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. The distributed adaptive frequency restoration strategy comprises: [0044] and During the ceremony, [0045] is the frequency global output error of the energy storage system i, and ω ｒｅｆ is the set reference frequency, sgn(.) represents the sign function, [0046] The method for distributed adaptive control of a microgrid energy storage system under unknown disturbances as claimed in claim 1, characterized in that:

5. Dynamic Control Gain [0047] The adaptation rate of [0048] and In the formula, b １ , b ２ , c １ , c ２ , d １ , d ２ is a normal number, [0049] The method for distributed adaptive control of a microgrid energy storage system under unknown disturbances as claimed in claim 4, characterized in that:

6. A decentralized adaptive active power dispatch and charge state balancing strategy is provided. [Number 50] and During the ceremony, [0051] is the global output error of the state of charge and active power of the energy storage system i, [0052] The method for distributed adaptive control of a microgrid energy storage system under unknown disturbances as claimed in claim 1, characterized in that: 【Request 7】 【Number 53】 is the dynamic control gain, and its adaptation rate is [0,54] and In the formula, b ３ , b ４ , c ３ , c ４ , d ３ , d ４ is a normal number, [0.55] The method for distributed adaptive control of a microgrid energy storage system under unknown disturbances as claimed in claim 6, characterized in that:

8. 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 is configured to introduce a dynamic control gain according to the frequency global output error of the energy storage system based on the consistency theory to formulate a distributed adaptive frequency recovery strategy, and introduce a dynamic control gain according to the charge state and the 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.

9. 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 according to any one of claims 1 to 7.

10. A computer readable storage medium adapted to store computer instructions which, when executed by a processor, complete the steps of the method according to any one of claims 1 to 7.

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