A security decoupling method and system for micro-grid cluster collaborative control

Abstract

The application discloses a kind of micro-grid cluster cooperative control safety decoupling method and system.The system includes energy management layer, communication layer and distributed power DG individual layer connected in turn, and energy management system of energy management layer is used to give scheduling task instruction, and communication layer is used to transmit scheduling task instruction to DG individual layer, and DG individual layer includes distributed power individual, heterogeneous state safety constraint coupling model set, small gain theory safety gain decomposer, linear temporal logic scheduling module and secondary controller set, and DG individual layer is used to carry out information cooperative processing according to scheduling task instruction, by heterogeneous state safety constraint coupling model set, small gain theory safety gain decomposer, linear temporal logic scheduling module and secondary controller set, and based on secondary controller set, safety decoupling is carried out, high inertia, high damping and strong voltage support are provided, and system strength and stability margin are improved.

Description

Technical Field

[0001] This application relates to the field of microgrid cluster technology, specifically to a secure decoupling method and system for collaborative control of microgrid clusters. Background Technology

[0002] Microgrid clusters (MGCs) are an important and typical application scenario for green and low-carbon buildings. MGs, composed of various distributed energy resources (DERs), represent an emerging technological trend in urban architecture.

[0003] MGC (Multi-Generation Grid Conversion) is a crucial core component of the new power system, possessing three key characteristics: low carbon emissions, high efficiency, and safety. The new power system primarily relies on clean energy as its supply source. Through the interaction of power generation, grid, load, and storage, and the complementarity of various energy sources, it exhibits significant characteristics such as green and low carbon emissions, safety and controllability, intelligence and flexibility, openness and interaction, digital empowerment, and economic efficiency. It promotes green electricity consumption and ensures the secure supply of energy and electricity. MGC technology, based on digital technology, coordinates the management of power generation, grid, load, and storage resources, improves the dispatch and operation mechanism, and enhances the flexible adjustment capability, safety assurance level, and overall operational efficiency of the new power system from multiple dimensions, thus meeting the comprehensive goals of secure electricity supply, green consumption, and economic efficiency.

[0004] The high proportion of power electronic structure brought about by the grid connection of new energy sources has gradually weakened the synchronization characteristics of traditional power systems in MGC, resulting in low inertia, low damping, and weak voltage support. This reduces the system strength and stability margin, leading to safety hazards.

[0005] The above statements are for the purpose of providing background information in relation to this application only and do not necessarily constitute prior art. Summary of the Invention

[0006] The purpose of this application is to provide a secure decoupling method and system for collaborative control of microgrid clusters. To provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended as a general commentary, nor is it intended to identify key / important components or describe the scope of protection of these embodiments. Its sole purpose is to present some concepts in a simple form as a prelude to the detailed description that follows.

[0007] According to one aspect of the embodiments of this application, a secure decoupling system for collaborative control of a microgrid cluster is provided, comprising an energy management layer, a communication layer, and a distributed power source individual layer connected in sequence.

[0008] The energy management layer is used to issue scheduling task instructions;

[0009] The communication layer is used to transmit the scheduling task instructions to the distributed power supply individual layer;

[0010] The distributed power supply individual layer includes distributed power supply individuals, a heterogeneous state security constraint coupling model set, a small-gain theoretical security gain decomposer, a linear timing logic scheduling module, and a set of secondary controllers. The distributed power supply individual layer is used to perform information collaborative processing according to the scheduling task instructions through the heterogeneous state security constraint coupling model set, the small-gain theoretical security gain decomposer, the linear timing logic scheduling module, and the set of secondary controllers, and to perform security decoupling based on the set of secondary controllers.

[0011] In some embodiments of this application, the set of secondary controllers includes a set of secondary controllers for scheduling instruction tracking power and a set of secondary controllers for voltage and frequency.

[0012] In some embodiments of this application, the heterogeneous state security constraint coupling model set includes the SCBF set or SBLF set for each DG microsource;

[0013] The heterogeneous state security constraint coupling model set includes:

[0014] DG's switching security set

[0015] ,

[0016] in, It is a piecewise Lipschitz continuous function related to state safety.

[0017] In some embodiments of this application, the switching control barrier function SCBF is:

[0018] For the dynamics of the DG model, if the function Piecewise continuous differentiable and satisfying:

[0019]

[0020]

[0021] Then it is called It is DG's dynamic SCBF; among which, It is a control set. It is a local Lipschitz continuous extension of K ∞ Class function;

[0022] Switching barrier Lyapunov function SBLF:

[0023] Opening Collection The above-defined follow signal r and σPiecewise scalar function satisfy:

[0024] exist The upper surface is smooth and positively definite, that is... ,and ;

[0025] When the state Approaching the boundary of the region hour, ;

[0026] , making ;

[0027] ;

[0028] but It is called DG dynamic SBLF.

[0029] In some embodiments of this application, the small-gain theoretically secure gain resolver satisfies:

[0030] enter State safety ISSf is used for state safety performance analysis under control input based on the ISSf barrier function. For DG model dynamics, if the function Piecewise continuous differentiable and satisfying

[0031]

[0032] Then it is called It is a DG-dynamic switching type ISSf-BF barrier function. To expand K ∞ Class function, Functions of type K;

[0033] Based on the analysis of small gain theory, from arrive The safety constraint transfer gain is

[0034] ,

[0035] in" "Represents the composition of functions, It is an arbitrary extension of K ∞ Function-like.

[0036] In some embodiments of this application, the linear timing logic scheduling module satisfies:

[0037]

[0038] This indicates overall safety. Indicates the first A DG security constraint satisfies, where ∧ represents logical AND and ∨ represents logical OR. This indicates the Next in the sequence.

[0039] In some embodiments of this application, the controllers in the set of secondary controllers are SCBF-based secondary safety controllers or SBLF-based secondary safety controllers;

[0040] The SCBF-based secondary safety controller satisfies:

[0041] set up Given positive definite, continuously differentiable, and radially unbounded Lyapunov functions, the heterogeneous safety constraints combine to form the following quadratic programming QP problem:

[0042]

[0043] It is a local Lipschitz continuous extension of K ∞ Function-like; using slack variables The CLF and CBF conditions are combined into a QP problem; when the state The initial value is located in the safe set. hour, There always exists Satisfy the SCBF constraint; This ensures that the CLF constraint is always guaranteed.

[0044] According to another aspect of the embodiments of this application, a secure decoupling method for microgrid cluster collaborative control is provided, applied to the secure decoupling system of any embodiment of this application; the method includes:

[0045] The energy management layer provides scheduling task instructions;

[0046] The communication layer transmits the scheduling task instructions to the distributed power supply individual layer;

[0047] The distributed power supply individual layer performs information collaborative processing based on the scheduling task instruction through the heterogeneous state security constraint coupling model set, the small gain theoretical security gain decomposer, the linear time-series logic scheduling module, and the secondary controller set, and performs security decoupling based on the secondary controller set.

[0048] One aspect of the technical solution provided in this application embodiment may include the following beneficial effects:

[0049] The microgrid cluster collaborative control safety decoupling system provided in this application embodiment includes an energy management layer, a communication layer, and a distributed power source individual layer connected in sequence. The energy management layer is used to issue scheduling task instructions, and the communication layer is used to transmit the scheduling task instructions to the distributed power source individual layer. The distributed power source individual layer includes distributed power source individuals, a heterogeneous state safety constraint coupling model set, a small-gain theoretical safety gain decomposer, a linear time-series logic scheduling module, and a set of secondary controllers. The distributed power source individual layer is used to perform information collaborative processing according to the scheduling task instructions through the heterogeneous state safety constraint coupling model set, the small-gain theoretical safety gain decomposer, the linear time-series logic scheduling module, and the set of secondary controllers, and to perform safety decoupling based on the set of secondary controllers. This provides high inertia, high damping, and strong voltage support, improves system strength and stability margin, and reduces safety hazards.

[0050] The above description is merely an overview of the technical solutions of the embodiments of this application. In order to better understand the technical means of the embodiments of this application and to implement them in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the embodiments of this application more obvious and understandable, specific implementation methods of this application are described below. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments or related technologies of this application, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 A schematic diagram of a microgrid cluster (MGC) architecture according to an embodiment of this application is shown.

[0053] Figure 2 A block diagram of a secure decoupling system for collaborative control of a microgrid cluster according to an embodiment of this application is shown.

[0054] Figure 3 A block diagram of a secure decoupling system for collaborative control of a microgrid cluster, according to another embodiment of this application, is shown.

[0055] Figure 4 A flowchart illustrating a secure decoupling method for collaborative control of a microgrid cluster according to an embodiment of this application is shown.

[0056] Figure 5 A block diagram of an electronic device structure according to an embodiment of this application is shown.

[0057] Figure 6A schematic diagram of a computer-readable storage medium according to an embodiment of this application is shown. Detailed Implementation

[0058] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0059] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have a meaning consistent with their meaning in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0060] As a crucial cutting-edge technology for new power systems in urban buildings, the safe operation and control of MGC systems still face many key technical challenges. For example, the high proportion of power electronic structures has adverse effects on safe and stable operation. The high proportion of power electronic structures brought about by the grid connection of new energy sources gradually weakens the synchronization characteristics of traditional power systems in MGC, exhibiting characteristics of low inertia, low damping, and weak voltage support, which reduces the system strength and stability margin, leading to safety hazards.

[0061] To address the problems existing in related technologies, the microgrid cluster collaborative control safety decoupling system provided in this application includes an energy management layer, a communication layer, and a distributed power source individual layer connected in sequence. The energy management layer is used to issue scheduling task instructions, and the communication layer is used to transmit the scheduling task instructions to the distributed power source individual layer. The distributed power source individual layer includes distributed power source individuals, a heterogeneous state safety constraint coupling model set, a small-gain theoretical safety gain decomposer, a linear time-series logic scheduling module, and a set of secondary controllers. The distributed power source individual layer is used to perform information collaborative processing according to the scheduling task instructions through the heterogeneous state safety constraint coupling model set, the small-gain theoretical safety gain decomposer, the linear time-series logic scheduling module, and the set of secondary controllers, and to perform safety decoupling based on the set of secondary controllers. This provides high inertia, high damping, and strong voltage support, improves system strength and stability margin, and reduces safety hazards.

[0062] Furthermore, related technologies also present the challenge of ensuring the safe adjustment of renewable energy consumption and power supply balance. The high proportion of renewable energy generation connected to the grid is transforming the MGC system from "controllable units balancing predictable loads" to "fluctuating renewable energy balancing random loads," making the challenge of supporting real-time supply and demand balance while ensuring security increasingly severe. Additionally, related technologies also present communication security and cyberattack issues. With the increasing integration of computing, control, and communication technologies, MGC forms a Cyber-Physical System (CPS). While CPS improves the operational efficiency of microgrids, it also brings new cybersecurity challenges. When the communication network undergoes real-time changes or is attacked, the corresponding physical system will also be damaged to varying degrees, potentially leading to power supply interruptions or even severe economic losses.

[0063] Microgrid cluster MGC architecture diagram as shown Figure 1 As shown, in the hierarchical MGC architecture, each sub-microgrid is connected to the bus via a tie point. The first level (upper layer) is for control and connection between the main grid and the MGC. The upper-level energy management system is responsible for power scheduling and switching between MGs and between the main grid and the main grid. The second level is for control within the microgrid group, i.e., the energy management systems of each MG. It performs power scheduling on the MGs according to the upper-level scheduling instructions to achieve voltage and frequency stability of the microgrid group. The third level is for sub-microgrid collaborative control, which mainly focuses on distributed control of the distributed generators (DGs) within the MGs, applying a peer-to-peer control strategy.

[0064] In the three levels of control mentioned above, the first and second levels require interconnected topology communication, and the third-level sub-microgrid also requires interconnected topology communication. The project mainly considers the secondary recovery coordinated control of voltage and frequency in the third level, as well as the secondary recovery coordinated control between sub-microgrids in the second level, while also achieving the control objectives of scheduling command tracking and power equalization.

[0065] Microgrid clusters (MGCs) require power sharing via tie lines, and the subgrid safety boundaries are constrained by both energy storage capacity and power transmission capability. Furthermore, the MGC as a whole must maintain instantaneous power balance, and fluctuations in a single subgrid can affect the operating status of other subgrids through the tie lines. Differences in control delays between diesel generators, energy storage, and power electronics interfaces also necessitate that fast-regulating devices compensate for the dynamic lag of slower devices, requiring time-domain coordination of state constraints across subsystems. The coupling of safety constraints among the various distributed generation (DG) systems within an MGC is essentially a concentrated manifestation of the contradiction between its dual attributes of "local autonomy" and "global coordination." Currently, a coordinated decoupling mechanism to resolve this safety coupling within an MGC has not yet been established.

[0066] An MGC system is a composite MAS system composed of multiple interconnected MGs or DGs. Global state security depends on the individual security of each component, but individual security is not equivalent to global state security. Due to the implementation of distributed cooperative control, this complex interplay exacerbates security coupling.

[0067] This application addresses the safety constraint coupling problem in microgrid clusters during coordinated secondary control, where each sub-microgrid and each distributed generation (DG) has safety constraints, and these constraints are coupled to each other through interfaces, ensuring safe and stable operation. This application proposes a decoupling control method and system that can decouple the voltage, frequency, and power state safety constraints of each DG, ensuring that each DG satisfies its respective coupled safety constraints.

[0068] The following describes, with reference to the accompanying drawings, a secure decoupling system for microgrid cluster collaborative control, a secure decoupling method for microgrid cluster collaborative control, an electronic device, and a computer-readable storage medium according to embodiments of this application.

[0069] refer to Figure 2 As shown, one embodiment of this application provides a secure decoupling system for collaborative control of a microgrid cluster, comprising an energy management layer, a communication layer, and a distributed power source individual layer connected in sequence.

[0070] The energy management layer is used to issue scheduling task instructions; the communication layer is used to transmit the scheduling task instructions to the distributed power source individual layer; the distributed power source individual layer includes distributed power source individuals, a heterogeneous state security constraint coupling model set, a small-gain theoretical security gain decomposer, a linear time-series logic scheduling module, and a set of secondary controllers; the distributed power source individual layer is used to perform information collaborative processing according to the scheduling task instructions through the heterogeneous state security constraint coupling model set, the small-gain theoretical security gain decomposer, the linear time-series logic scheduling module, and the set of secondary controllers, and to perform security decoupling based on the set of secondary controllers.

[0071] For example, the energy management layer includes an energy management system, which is used to issue scheduling task instructions.

[0072] In some implementations, the secondary controller set may include a scheduling instruction tracking power secondary controller set and a voltage-frequency secondary controller set. Specifically, the distributed power source individual layer is used to perform information collaborative processing based on scheduling task instructions through a heterogeneous state security constraint coupling model set, a small-gain theoretical security gain decomposer, a linear timing logic scheduling module, and a scheduling instruction tracking power secondary controller set, and to perform security decoupling based on the voltage-frequency secondary controller set.

[0073] For example, the controllers in the set of secondary controllers can be controllers based on switching control barrier functions or switching barrier Lyapunov functions.

[0074] In some implementations, the heterogeneous state safety constraint coupling model set includes the SCBF set or SBLF set for each DG microsource.

[0075] The set of heterogeneous state safety constraint coupling models includes:

[0076] DG's switching security set

[0077] ,

[0078] in, It is a piecewise Lipschitz continuous function related to state safety.

[0079] Switching Control Barrier Function (SCBF):

[0080] For the dynamics of the DG model, if the function Piecewise continuous differentiable and satisfying:

[0081]

[0082]

[0083] Then it is called It is DG's dynamic SCBF; among which, It is a control set. It is a local Lipschitz continuous extension of K ∞ Class function;

[0084] Switching barrier Lyapunov function SBLF:

[0085] Opening Collection The above-defined follow signal r and σ Piecewise scalar function satisfy:

[0086] exist The upper surface is smooth and positively definite, that is... ,and ;

[0087] When the state Approaching the boundary of the region hour, ;

[0088] , making ;

[0089] ;

[0090] but It is called DG dynamic SBLF.

[0091] For example, a small-gain theoretically secure gain resolver satisfies:

[0092] enter State safety ISSf is used for state safety performance analysis under control input based on the ISSf barrier function. For DG model dynamics, if the function Piecewise continuous differentiable and satisfying

[0093]

[0094] Then it is called It is a DG-dynamic switching type ISSf-BF barrier function. To expand K ∞ Class function, Functions of type K;

[0095] Based on the analysis of small gain theory, from arrive The safety constraint transfer gain is

[0096] ,

[0097] in" "Represents the composition of functions, It is an arbitrary extension of K ∞ Function-like.

[0098] For example, the linear sequential logic scheduling module satisfies:

[0099]

[0100] This indicates overall safety. Indicates the first A DG security constraint satisfies, where ∧ represents logical AND and ∨ represents logical OR. This indicates the Next in the sequence.

[0101] For example, the controllers in the set of secondary controllers are SCBF-based secondary safety controllers or SBLF-based secondary safety controllers;

[0102] The SCBF-based secondary safety controller satisfies:

[0103] set up Given positive definite, continuously differentiable, and radially unbounded Lyapunov functions, the heterogeneous safety constraints combine to form the following quadratic programming QP problem:

[0104]

[0105] It is a local Lipschitz continuous extension of K ∞ Function-like; using slack variables The CLF and CBF conditions are combined into a QP problem; when the state The initial value is located in the safe set. hour, There always exists Satisfy the SCBF constraint; This ensures that the CLF constraint is always guaranteed. The SCBF implements safety constraints and improves dynamic safety, while the secondary safety controller optimizes performance based on the safety constraints. The combination of the two forms an SCBF-based secondary safety controller, which is an effective framework for realizing the safety control of the complex microgrid cluster system, and significantly improves the safety of the microgrid cluster system.

[0106] refer to Figure 3 As shown, in a specific example, the safety decoupling system for microgrid cluster collaborative control can include an energy management layer, a communication layer, and a DG individual layer; the structure and function of the DG individual layer are the main components for achieving the safety decoupling objective.

[0107] The energy management layer can include the energy management system. The energy management layer mainly makes decisions and issues scheduling task instructions by the energy management system.

[0108] When a building multi-energy microgrid system is in operation, it coordinates and controls the micro-sources, loads, and inverters in the microgrid to meet the economic operation needs and scheduling task changes of the upper level, and makes decisions to optimize scheduling so as to ensure that the MGC can meet the building's energy-saving operation needs.

[0109] The given scheduling task instructions are transmitted from the communication layer to the lower-level sub-micronets and DG individuals.

[0110] The communication layer consists of communication device hardware and software systems, transmitting two main categories of information: neighbor and individual status signals, and scheduling task instructions. The neighbor and individual status signals are obtained by each sub-micronet and DG individual based on the data acquisition system and transmitted to the communication layer according to the communication topology. The scheduling task instructions are issued by the energy management layer and transmitted along the communication topology formed by the communication devices in the communication layer. Thus, the information transmitted from the communication layer to the DG individual layer consists of two main categories: neighbor and individual status signals and scheduling task instructions.

[0111] When a building multi-energy microgrid system is in operation, the communication topology of the communication layer will change due to factors such as network congestion, transmission delay, and system changes. The scheduling task instructions will also change according to the status of the entire microgrid cluster (tripping, closing, heavy load switching, faults, maintenance, etc.) and correspond to various scheduling tasks and instructions of the power grid.

[0112] Thus, the DG individual layer faces changes in both communication topology and scheduling tasks. The control scheme structure proposed in this application considers these two types of switching changes at the interface between the communication layer and the DG individual layer.

[0113] Considering the aforementioned dual handover changes, the DG individual layer and the communication layer have three information interfaces: the communication topology interface (transmitting neighbor and individual state information), the scheduling task instruction interface (transmitting scheduling instructions), and the neighbor state information flow of the MGC system. For the collaborative operation of multi-energy microgrid systems, the DG individual layer mainly consists of two parts: the DG individual itself and the individual controller.

[0114] To achieve the goal of secure decoupling, this embodiment of the application sets up a heterogeneous state security constraint coupling model set, a small-gain theoretical security gain decomposer, a linear timing logic scheduling module, and a set of secondary controllers within the DG individual layer. The set of secondary controllers consists of secondary security controllers based on SCBF or SBLF. Specifically, the SCBF- or SBLF-based secondary security controllers include a scheduling command tracking power secondary control set and a voltage-frequency secondary control set. Through the coordinated information processing of these components, based on the voltage, frequency, and scheduling command tracking power secondary controller sets, the proposed DG individual layer system structure can achieve the goal of secure decoupling. The functional modules of each part of the DG individual layer are described below.

[0115] (1) DG individual level:

[0116] Considering that the state security limits of each DG are affected by changes in scheduling task instructions and network topology, define the scheduling task instruction switching signal at the EM layer. ( (is a set of positive integers), and communication connection topology switching signals. (abbreviated as) r , σ The dynamics of the i-th DG individual model are...

[0117]

[0118] in, This represents the model dynamic function of the i-th DG itself. This represents the dynamic function corresponding to the i-th DG after being affected by two switching signals; This represents the control input matrix of the i-th DG, and the effect of the control input on the state variables. This represents the control input matrix of the i-th DG after being affected by the switching signal; u i It is the input of the voltage-frequency secondary control loop; It is the input of the power secondary control loop; The voltage, frequency, and power equations of the leader represent the state variables. This indicates the dynamics of the Leader DG model, and its specific meaning is the same as that of the DG Individual model dynamics. It is the input of the leader's voltage frequency secondary control loop. It is the input of the leader power secondary control loop. Represents the DG status, where Represents frequency, Indicates voltage. Indicates the state of charge of the battery; subscript Indicates the first Each DG. The power control module is located within the secondary control module, and together with the voltage and frequency secondary controls, it forms the MGC collaborative control. Output power Small-signal analysis is used to model microgrid inverters. Represents the power state of DG, where This represents the change in the inverter's power angle. and These represent the active power and reactive power output by the inverter, respectively.

[0119] (2) Set of heterogeneous state safety constraint coupling models:

[0120] First, the DG's switching security set is given:

[0121] ,

[0122] in, It is a piecewise Lipschitz continuous function related to state safety, for example, it can be taken as:

[0123] ,

[0124] in, It is a constant scalar representing the safe range; These are the voltage, frequency state, and power equation state variables of the leader of each sub-microgrid; , It is a segmented, continuously differentiable scheduling instruction.

[0125] The following definition is given:

[0126] a) Switched Control Barrier Function (SCBF):

[0127] For the dynamics of the DG model, if the function Piecewise continuous differentiable and satisfying:

[0128]

[0129]

[0130] Then it is called It is DG's dynamic SCBF. Among them, It is a control set. It is a local Lipschitz continuous extension of K ∞ Function-like.

[0131] b) Switched Barrier Lyapunov Function (SBLF):

[0132] Opening Collection The above-defined follow signal r and σ Piecewise scalar function satisfy:

[0133] 1) exist The upper surface is smooth and positively definite, that is... ,and ;

[0134] 2) When the state Approaching the boundary of the region hour, ;

[0135] 3) , making ;

[0136] 4) ;

[0137] but It is called DG dynamic SBLF.

[0138] In this way, the SCBF set or SBLF set of each DG microsource constitutes a set of heterogeneous state safety constraint coupling models.

[0139] (3) Small gain theoretical safe gain resolver

[0140] The principle of the low-gain theoretical secure gain resolver is described below. Input Input-to-state safety (ISSf) is a method for characterizing external inputs. u This is an important tool for assessing the impact on system safety. It performs state safety performance analysis under control inputs based on the existing ISSf Barrier Function (ISSf-BF). Using this mechanism, the ISSf-BF of the DG is defined as follows.

[0141] Definition: For the dynamics of the DG model, if the function Piecewise continuous differentiable and satisfying

[0142]

[0143] Then it is called It is a DG dynamically switching type ISSf-BF. (Regarding the status) (The definition of the switching type ISSf-BF is omitted here.) To expand K ∞ Class function, This is a K-type function. The switching type ISSf-BF description given in this embodiment... This fully demonstrates the security performance coupling between the various DG or MG subsystems. Thus, the decoupling problem evolves into... Analysis and processing of items.

[0144] Based on the analysis of small gain theory, from arrive The safety constraint transfer gain is

[0145] ,

[0146] in" "Represents the composition of functions, It is an arbitrary extension of K ∞ Class function. Furthermore, if the gain... Under certain conditions, the security of a subsystem is equivalent to the security of the global system. Thus, the security constraint coupling of each DG can be determined based on the above formula and the transfer gain. and They decompose into one another.

[0147] (4) Linear sequential logic scheduling module

[0148] The behavior of the MGC control system consists of upper-level scheduling logic and lower-level dynamic actions, and its security needs to be guaranteed at both levels. Global security requires that physical security constraints be met at the lower level, but this is not necessarily a prerequisite. In practice, the MGC system must also meet preset timing logic constraints at the upper level, completing a series of operations in the correct safe sequence. The linear timing logic scheduling module can perform linear timing logic analysis.

[0149] The security decoupling method and system of this application introduces LTL (Linear Temporal Logic) analysis to perform logical decoupling analysis of individual, local, and global security. For example, a typical description could be:

[0150]

[0151] here This indicates overall safety. Indicates the first A DG security constraint satisfies, where ∧ represents logical AND and ∨ represents logical OR. The term "Next" indicates a temporal sequence. This statement shows that overall MGC security requires not only the security of each subsystem but also a sequential relationship. Based on LTL analysis, hybrid security analysis can be performed by combining automata theory. LTL-based security coupling analysis has excellent reliability for MGC systems, enabling a more refined temporal logic for overall security, and is closer to the upper-level dispatch and command operations of microgrids.

[0152] (5) Secondary safety controller based on SCBF or SBLF

[0153] After the heterogeneous state safety constraint coupling model set is analyzed and processed by the small gain theoretical safety gain decomposer and the linear timing logic scheduling module, it outputs the decoupled SCBF or SBLF, and the secondary safety controller can be designed based on this.

[0154] a) SCBF-based secondary safety controller

[0155] This embodiment employs two technical approaches to design a secure collaborative control protocol using SCBF. The first approach is control. When a specific form is not available, the CLF method is combined with the SCBF method, and then an online optimization algorithm is used to calculate the cooperative control. Let... Given a positive definite, continuously differentiable, and radially unbounded Lyapunov function, the heterogeneous safety constraints combine to form the following quadratic programming (QP) problem (about...). (QP issues omitted)

[0156]

[0157] here, It is a local Lipschitz continuous extension of K ∞ Function-like. Through slack variables. This combines the CLF and CBF conditions into a single QP problem. When the state... The initial value is located in the safe set. hour, There always exists It satisfies the SCBF constraint. This ensures that CLF constraints are always guaranteed. As long as the control objective described by CLF and the safety constraints described by SCBF do not conflict, the safety control objective will be achieved; otherwise, control performance will be sacrificed to ensure that the safety constraints are not violated.

[0158] b) SBLF-based secondary safety controller

[0159] By searching for SBLF as mentioned above The key to designing a secondary security control protocol lies in finding a suitable SBLF. Traditional BLFs are highly conservative, but the dual switching mechanism introduced in this embodiment makes... The parameters can be varied depending on the situation, such as tangent-type BLF combinations with different parameters. The resulting SBLF is a piecewise, continuously differentiable Lyapunov function, which can then be used for stability analysis and controller design using switching system control theory.

[0160] Thus, the secondary security controller based on SBLF has the following advantages: (i) the output voltage and frequency of each DG fully comply with the constraints, and can also achieve precise allocation of reactive power; (ii) adaptive methods can be used for some unknown parameters and uncertainties in the model dynamics, and the consistency control is more adaptive; (iii) under the SBLF-based design mechanism, network attack observers are easier to design and implement.

[0161] (6) Design of voltage and frequency secondary controller assembly

[0162] Set different tasks It might be a constant at a certain time, a variable, or a trajectory. Furthermore, the leader state of the sub-micronet also changes accordingly. At the DG individual level of the MGC system, for the state under different command switching, and considering communication topology changes, a set of voltage and frequency secondary controllers is designed based on a general multi-agent robust cooperative control method. Thus, each controller is a robust control protocol oriented towards dual switching scenarios. In this way, the secondary controller set pre-sets robust switching logic for different command scenarios (such as voltage regulation commands, frequency support commands, and power allocation commands), reducing the probability of system oscillations caused by command mutations. Based on the multi-agent cooperative framework, the controllers do not need to rely on a fixed communication topology. When the topology changes (e.g., a DG node communication is interrupted), the remaining nodes can maintain cooperation through local information exchange, significantly improving system robustness. When the sub-micronet leader state switches, the controller set can avoid system instability caused by leader switching by dynamically adjusting the cooperation target.

[0163] (7) Design of a set of secondary power controllers for dispatching instructions

[0164] Referring to the secondary safety controllers based on SCBF or SBLF mentioned earlier, different tasks are configured. At that time, each MGC individual must correspond to a different secondary controller 1-γ, including voltage, frequency secondary controllers and scheduling command tracking power secondary controllers, forming their own controller sets.

[0165] The security decoupling method and system proposed in this application include a heterogeneous state security constraint coupling model, small-gain theoretical security gain decomposition, linear sequential logic scheduling, and a secondary security controller based on SCBF or SBLF. The security decoupling problem is solved through the collaborative operation of these multiple information processing subsystems.

[0166] This application proposes a security decoupling system for microgrid clusters (MGC) systems. In the context of high-proportion distributed energy resource integration and heterogeneous device collaborative operation, it solves the critical challenge of balancing global and local security due to complex internal coupling relationships. This method integrates four core technology modules: heterogeneous state security constraint coupling modeling, security gain decomposition based on small-gain theory, linear time-sequential logic scheduling mechanism, and a secondary security controller based on the Security Control Barrier Function (SCBF) or Security Barrier Lyapunov Function (SBLF). These subsystems work collaboratively to construct a full-link security decoupling architecture from modeling, analysis, scheduling to control, significantly improving the overall security and coordination capabilities of MGC during dynamic operation.

[0167] At the functional level, the embodiments of this application can effectively identify and decouple multiple security coupling problems caused by factors such as power mutual assistance, device heterogeneity, and latency differences in MGC. By establishing a heterogeneous state security constraint model, the system can take into account the differentiated security needs of different distributed units under diverse operating conditions, achieving a seamless transition from "local autonomy" to "global collaboration". Combining the switching barrier function and the dual switching model, the system can transform complex coupling dynamics into processable switching signals, thereby designing a robust security control protocol to ensure that voltage and frequency remain consistent and stable during dynamic processes. In addition, with the help of timing logic scheduling and a secondary security controller, the system has the ability to coordinate responses at multiple time scales, which not only copes with rapid power fluctuations but also compensates for the dynamic lag of slow devices, thereby effectively suppressing adverse interactions between subnets while ensuring the instantaneous power balance of the system.

[0168] From a scientific and technological perspective, the embodiments of this application achieve theoretical innovation and methodological breakthroughs at multiple levels. First, at the modeling level, the proposed heterogeneous security constraint description system breaks through the limitations of traditional homogenized security boundaries, providing a new paradigm for the security analysis of heterogeneous systems. Second, the introduction of small-gain theory into the decomposition process of security gain provides a theoretical tool for understanding the intrinsic relationship between local and global security in coupled systems. This enables the safe adjustment of new energy consumption and power supply balance goals, and significantly reduces communication security and network attack issues. Third, the introduction of linear sequential logic for scheduling decisions enhances the system's ability to handle time-domain security constraints, making the scheduling process both flexible and verifiable. Finally, the secondary control design based on SCBF / SBLF not only strengthens the online execution capability of security constraints but also expands the engineering applicability of nonlinear control in power systems. This reduces damage to the corresponding physical system when the communication network undergoes real-time changes or is attacked, lowers the probability of power supply interruptions, reduces the risk of economic losses, and greatly alleviates the trend of increased security coupling caused by the implementation of distributed collaborative control.

[0169] The results of this application are of great significance for promoting the intelligent and highly resilient development of energy systems. They not only provide an feasible technical path for building safe and reliable microgrid clusters, but also offer interdisciplinary theoretical guidance for fields such as multi-agent collaborative control and heterogeneous system integration, and are expected to play a key supporting role in the construction of new power systems and the large-scale deployment of distributed energy.

[0170] The description of the various embodiments above tends to emphasize the differences between the various embodiments. The similarities or similarities between them can be referred to, and for the sake of brevity, they will not be repeated here.

[0171] refer to Figure 4As shown, another embodiment of this application provides a secure decoupling method for microgrid cluster cooperative control, applicable to the secure decoupling system described in any embodiment of this application; the method may include steps S10-S30:

[0172] S10, The energy management layer issues scheduling task instructions;

[0173] S20. The communication layer transmits the scheduling task instruction to the distributed power supply individual layer.

[0174] S30. The distributed power supply individual layer performs information collaborative processing according to the scheduling task instruction through the heterogeneous state security constraint coupling model set, the small gain theoretical security gain decomposer, the linear time-series logic scheduling module and the secondary controller set, and performs security decoupling based on the secondary controller set.

[0175] In some implementations, the distributed power supply individual layer performs information collaborative processing based on the scheduling task instructions through a set of heterogeneous state security constraint coupling models, a small gain theoretical security gain decomposer, a linear timing logic scheduling module, and a set of scheduling instruction tracking power secondary controllers, and performs security decoupling based on the set of voltage and frequency secondary controllers.

[0176] For example, input Input-to-state safety (ISSf) is based on the existing ISSf Barrier Function (ISSf-BF) to analyze the state safety performance under control input.

[0177] LTL analysis is introduced to perform logical decoupling analysis between individual, local, and global security. For example:

[0178]

[0179] This indicates overall safety. Indicates the first A DG security constraint satisfies, where ∧ represents logical AND and ∨ represents logical OR. The term "Next" indicates a temporal sequence. This statement shows that overall MGC security requires not only the security of each subsystem but also a sequential relationship. Based on LTL analysis, hybrid security analysis can be performed by combining automata theory. LTL-based security coupling analysis has excellent reliability for MGC systems, enabling a more refined temporal logic for overall security, and is closer to the upper-level dispatch and command operations of microgrids.

[0180] For example, after the heterogeneous state security constraint coupling model set is analyzed and processed by the small gain theoretical security gain decomposer and the linear time-series logic scheduling module, it outputs the decoupled SCBF or SBLF.

[0181] For example, a small-gain theoretically secure gain resolver satisfies:

[0182] enter State safety ISSf is used for state safety performance analysis under control input based on the ISSf barrier function. For DG model dynamics, if the function Piecewise continuous differentiable and satisfying

[0183]

[0184] Then it is called It is a DG-dynamic switching type ISSf barrier function. To expand K ∞ Class function, Functions of type K;

[0185] Based on the analysis of small gain theory, from arrive The safety constraint transfer gain is

[0186] ,

[0187] in" "Represents the composition of functions, It is an arbitrary extension of K ∞ Function-like.

[0188] The secondary safety controller based on SCBF or SBLF includes a set of secondary control units for dispatch command tracking power and a set of secondary control units for voltage and frequency. Through the coordinated information processing of these components, the proposed DG individual-layer system architecture can achieve the goal of safe decoupling based on the sets of voltage and frequency secondary controllers and the set of secondary controllers for dispatch command tracking power.

[0189] The safe decoupling method for microgrid cluster collaborative control provided in this application provides high inertia, high damping, and strong voltage support, which improves system strength and stability margin and reduces safety hazards.

[0190] The description of the various embodiments above tends to emphasize the differences between the various embodiments. The similarities or similarities between them can be referred to, and for the sake of brevity, they will not be repeated here.

[0191] Another embodiment of this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the computer program to implement the secure decoupling method for microgrid cluster collaborative control in any of the above embodiments.

[0192] refer to Figure 5 As shown, the electronic device 10 may include: a processor 100, a memory 101, a bus 102 and a communication interface 103. The processor 100, the communication interface 103 and the memory 101 are connected through the bus 102. The memory 101 stores a computer program that can run on the processor 100. When the processor 100 runs the computer program, it executes the security decoupling method for microgrid cluster collaborative control provided in any of the foregoing embodiments of this application.

[0193] The memory 101 may include high-speed random access memory (RAM), and may also include non-volatile memory, such as at least one disk storage device. Communication between the device network element and at least one other network element is achieved through at least one communication interface 103 (which may be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc.

[0194] Bus 102 can be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. Memory 101 is used to store programs. After receiving an execution instruction, processor 100 executes the program. The methods disclosed in any of the foregoing embodiments of this application can be applied to processor 100, or implemented by processor 100.

[0195] Processor 100 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 100 or by instructions in software form. The processor 100 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application-Specific Integrated Circuit (ASIC), an Off-the-shelf Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules may reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in memory 101. The processor 100 reads the information in memory 101 and, in conjunction with its hardware, completes the steps of the above method.

[0196] The electronic devices and methods provided in the embodiments of this application are based on the same inventive concept and have the same beneficial effects as the methods they employ, operate, or implement.

[0197] Another embodiment of this application provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement the secure decoupling method for microgrid cluster cooperative control in any of the above embodiments. Reference Figure 6 As shown, the computer-readable storage medium is an optical disc 20, on which a computer program (i.e., a program product) is stored. When the computer program is run by a processor, it executes the secure decoupling method for microgrid cluster cooperative control provided in any of the aforementioned embodiments.

[0198] It should be noted that examples of computer-readable storage media may also include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical and magnetic storage media, which will not be elaborated here.

[0199] The computer-readable storage medium provided in the above embodiments of this application and the method provided in the embodiments of this application are based on the same inventive concept and have the same beneficial effects as the methods adopted, run or implemented by the applications stored therein.

[0200] It should be noted that:

[0201] The term "module" is not intended to be limited to a specific physical form. Depending on the application, a module can be implemented as hardware, firmware, software, and / or a combination thereof. Furthermore, different modules may share common components or even be implemented using the same components. Clear boundaries may or may not exist between different modules.

[0202] The algorithms and displays provided herein are not inherently related to any particular computer, virtual device, or other equipment. Various general-purpose devices can also be used with the examples based on this. The required structure for constructing such devices is obvious from the above description. Furthermore, this application is not directed to any particular programming language. It should be understood that the content of this application described herein can be implemented using various programming languages, and the above description of specific languages ​​is for the purpose of disclosing the best mode of implementation of this application.

[0203] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0204] The above embodiments merely illustrate the implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A secure decoupling system for collaborative control of a microgrid cluster, characterized in that, It includes an energy management layer, a communication layer, and a distributed power source individual layer connected in sequence; the distributed power source individual layer and the communication layer are connected through an information interface. The energy management layer is used to issue scheduling task instructions; The communication layer is used to transmit the scheduling task instructions to the distributed power supply individual layer; The distributed power source individual layer includes distributed power source individuals, a heterogeneous state security constraint coupling model set, a small-gain theoretical security gain decomposer, a linear timing logic scheduling module, and a set of secondary controllers. The distributed power source individual layer is used to perform information collaborative processing according to the scheduling task instructions through the heterogeneous state security constraint coupling model set, the small-gain theoretical security gain decomposer, the linear timing logic scheduling module, and the set of secondary controllers, and to perform security decoupling based on the set of secondary controllers. In the distributed power supply individual layer, define the EM layer scheduling task instruction switching signal. Communication connection topology switching signal , It is a set of positive integers, and the dynamics of the i-th DG individual model are: in, This represents the model dynamic function of the i-th DG itself. This represents the dynamic function corresponding to the i-th DG after being affected by two switching signals; This represents the i-th DG control input matrix. This represents the control input matrix of the i-th DG after being affected by the switching signal; u i It is the input of the voltage-frequency secondary control loop; It is the input of the power secondary control loop; The voltage, frequency, and power equations of the leader represent the state variables. This indicates the dynamics of the Leader DG model; It is the input of the leader's voltage frequency secondary control loop. It is the input of the leader power secondary control loop; This represents the state of the distributed generation (DG). Represents frequency, Indicates voltage. Indicates the state of charge of the battery; subscript Indicates the first One DG; Represents the DG power status. This represents the change in the inverter's power angle. and These represent the active power and reactive power output by the inverter, respectively. The heterogeneous state security constraint coupling model set includes the SCBF set or SBLF set for each DG microsource; The heterogeneous state security constraint coupling model set includes: DG's switching security set , in, It is a piecewise Lipschitz continuous function related to state safety; Switching Control Barrier Function (SCBF): For the dynamics of the DG model, if the function Piecewise continuously differentiable and satisfying: Then it is called It is DG's dynamic SCBF; among which, It is a control set. It is a local Lipschitz continuous extension of K ∞ Class function; Switching barrier Lyapunov function SBLF: Opening Collection The above-defined follow signal r and σ Piecewise scalar function satisfy: exist The upper surface is smooth and positively definite, that is... ,and ; When the state Approaching the boundary of the region hour, ; , making ; ； but It is called DG dynamic SBLF.

2. The system according to claim 1, characterized in that, The set of secondary controllers includes a set of secondary controllers for scheduling command tracking power and a set of secondary controllers for voltage and frequency.

3. The system according to claim 1, characterized in that, The small-gain theoretically secure gain resolver satisfies: enter State safety ISSf is used for state safety performance analysis under control input based on the ISSf barrier function. For DG model dynamics, if the function Piecewise continuous differentiable and satisfying Then it is called It is a DG-dynamic switching type ISSf-BF barrier function. To expand K ∞ Class function, Functions of type K; Based on the analysis of small gain theory, from arrive The safety constraint transfer gain is , in" "Represents the composition of functions, It is an arbitrary extension of K ∞ Function-like.

4. The system according to claim 1, characterized in that, The linear time-series logic scheduling module satisfies: This indicates overall safety. Indicates the first A DG security constraint satisfies, where ∧ represents logical AND and ∨ represents logical OR. This indicates the Next in the sequence.

5. The system according to any one of claims 2-4, characterized in that, The controllers in the set of secondary controllers are either SCBF-based secondary safety controllers or SBLF-based secondary safety controllers. The SCBF-based secondary safety controller satisfies: set up Given positive definite, continuously differentiable, and radially unbounded Lyapunov functions, the heterogeneous safety constraints combine to form the following quadratic programming QP problem: It is a local Lipschitz continuous extension of K ∞ Function-like; using slack variables The CLF and CBF conditions are combined into a QP problem; when the state The initial value is located in the safe set. hour, There always exists Satisfy the SCBF constraint; This ensures that the CLF constraint is always guaranteed.

6. A secure decoupling method for collaborative control of a microgrid cluster, characterized in that, Applied to a secure decoupling system as described in any one of claims 1-5; the method comprises: The energy management layer provides scheduling task instructions; The communication layer transmits the scheduling task instructions to the distributed power supply individual layer; The distributed power supply individual layer performs information collaborative processing based on the scheduling task instruction through the heterogeneous state security constraint coupling model set, the small gain theoretical security gain decomposer, the linear time-series logic scheduling module, and the secondary controller set, and performs security decoupling based on the secondary controller set.

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