Comprehensive renewable energy system based on distributed intelligent network security and control architecture thereof

Abstract

The invention belongs to the technical field of control systems, particularly relates to a comprehensive renewable energy system based on distributed intelligent network security and a control architecture thereof, and aims to solve the problems that an existing comprehensive renewable energy system is poor in security and control limitation and cannot meet the requirements of safe and reliable self-adaptive control and the like. The method comprises the following steps: a distributed adaptive access control module distributes control tasks on each node in a network, acquires data on each node, and dynamically adjusts and controls an access strategy; the distributed intrusion detection and response module arranges intrusion monitoring sensors on each node in a network in a distributed manner, obtains network flow data, mines abnormal behaviors and security threats, and generates a corresponding response strategy; and the control strategy conflict monitoring module is used for automatically discovering and solving conflicts. According to the invention, the efficiency, accuracy and expandability of network security control are improved, the risk of single-point failure is reduced, and the workload of network security management personnel is reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of control systems, and in particular relates to a distributed intelligent network-based integrated renewable energy system and a control architecture thereof. Background Art

[0002] With the growing global demand for sustainable energy, Integrated Renewable Energy Systems (IRES) have developed rapidly in recent years because of their ability to effectively integrate multiple renewable energy sources (such as solar energy, wind energy, hydropower, etc.), realize the trigeneration of "cooling, heating and electricity", and combine "source, grid and load" (i.e. energy supply, grid dispatching and load management) in an efficient operation mode. This system not only helps to improve energy utilization efficiency and reduce environmental pollution, but also provides new ideas for solving energy security issues.

[0003] However, with the widespread application of IRES system, the network security threats it faces are becoming increasingly severe. Traditional network security measures are incapable of dealing with modern network attacks, mainly in the following aspects:

[0004] Password cracking: Attackers obtain system login credentials through brute force or social engineering, thereby illegally entering the system to perform operations or steal data.

[0005] Hacker attacks: Exploiting system vulnerabilities to carry out denial of service attacks (DoS / DDoS), SQL injection, cross-site scripting (XSS) and other attacks, resulting in system paralysis or data leakage.

[0006] Malware: Spread viruses, Trojans, ransomware, etc. through email, download links and other channels, destroying system files and affecting normal operation.

[0007] In addition, the existing IRES system has the following shortcomings:

[0008] Lack of security: Traditional protection mechanisms are difficult to defend against advanced persistent threat (APT) attacks, and the system is easily targeted.

[0009] Poor adaptability and scalability: With technological advancement and changes in application scenarios, the system needs to be continuously upgraded to meet new needs, but the existing architecture often does not have good flexibility and scalability.

[0010] Dependence on centralized control: Highly dependent on central nodes for management and scheduling. Once the central node fails, the entire system may fall into chaos, affecting control efficiency and accuracy.

[0011] Based on this, the present invention proposes an integrated renewable energy system based on distributed intelligent network security and its control architecture. Summary of the invention

[0012] In order to solve the above-mentioned problems in the prior art, namely, the shortcomings and control limitations of the existing integrated renewable energy systems, poor system security and poor control adaptability, and the inability to meet the needs of safe and reliable adaptive control, the present invention provides an integrated renewable energy system based on distributed intelligent network security and its control architecture.

[0013] In a first aspect of the present invention, a comprehensive renewable energy system based on distributed intelligent network security is proposed, the system comprising: a distributed adaptive access control module, a distributed intrusion detection and response module and a control strategy conflict monitoring module;

[0014] The distributed adaptive access control module deploys the control tasks on each node in the network and obtains data on each node, the data including at least access requests, network security situation and user behavior data, continuously learns, adapts and feedbacks user behavior patterns and changes in the network environment, and dynamically adjusts access policies;

[0015] The distributed intrusion detection and response module deploys intrusion monitoring sensors on various network nodes to obtain network traffic data, mine abnormal behaviors and security threats in the network traffic data based on data mining algorithms, and intelligently generate corresponding response strategies according to the network environment and the nature of security threats;

[0016] The control strategy conflict monitoring module automatically discovers and resolves conflicts based on the priority, application scope and effective time of the control strategy and based on online learning and feedback mechanism.

[0017] In some preferred implementations, the distributed adaptive access control module obtains data on each node, and the data at least includes:

[0018] Each child node is based on its own sensor data, user request data during network access, behavioral pattern characteristics and network security situation.

[0019] In some preferred embodiments, the method of continuously learning, adapting to and feeding back the user's behavior patterns and changes in the network environment includes a machine learning algorithm and a data analysis algorithm. In some preferred embodiments, the control access strategy includes at least power station total parameters, primary frequency regulation, voltage control, active power control, reactive power control, full power support control, fluctuation control, multi-energy coordinated control, over-generation prevention control, power distribution and PID control.

[0020] In some preferred embodiments, the distributed intrusion detection and response module distributes intrusion monitoring sensors on each node in the network, and the specific method is as follows:

[0021] An intrusion detection sensor is arranged on each node in the network, and the network flow data is monitored and acquired in a distributed manner through the intrusion detection sensor.

[0022] In another aspect of the present invention, a control architecture of an integrated renewable energy system based on distributed intelligent network security is proposed, based on an integrated renewable energy system based on distributed intelligent network security, comprising a perception layer, a network layer, a control layer, an application layer and a management layer;

[0023] The sensing layer is used to arrange various types of signal sensing devices;

[0024] The network layer is used to transmit the sensing data acquired by the signal sensing device to the application layer;

[0025] An integrated renewable energy system is arranged in the application layer, and control tasks of the integrated renewable energy system are arranged on each node of the network layer. Each node monitors and controls energy data based on perception data, and the energy data at least includes energy assets, energy efficiency, energy consumption and energy planning;

[0026] The control layer is used to obtain control access policies and send them to on-site devices;

[0027] The management layer is used to provide management of resources, tasks, users and security.

[0028] In some preferred embodiments, the sensing device includes at least a sensor, a camera, an intelligent gateway and a data acquisition device.

[0029] In some preferred embodiments, the sensing device is connected to a first security assurance module, and the first security assurance module at least includes a hardware security assurance module, an access security assurance module, and a terminal data security assurance module.

[0030] In some preferred embodiments, the network layer transmits the sensing data via a transmission device, and the transmission device includes at least one or more of optical fiber, mobile communication and GPRS.

[0031] In some preferred embodiments, the transmission device is connected to a second security assurance module, and the second security assurance module at least includes a network security assurance module and a data transmission security assurance module.

[0032] Beneficial effects of the present invention:

[0033] The present invention distributes the network security control function on multiple nodes. Each node is responsible for the network security control of a specific function. It uses artificial intelligence, machine learning and other technologies to analyze and predict the network security situation, and then automatically adjusts the network security control strategy according to the analysis results. It also supports the access of multiple network security technologies and equipment, and ultimately improves the efficiency, accuracy and scalability of network security control, reduces the risk of single point failures, and reduces the workload of network security managers. Specifically:

[0034] Enhance system security and control adaptability: Through the application of distributed adaptive access control modules, distributed intrusion detection and response modules, and control strategy conflict monitoring modules, the system can effectively improve its ability to resist password cracking, hacker attacks, and malware, and dynamically adjust control strategies to adapt to various complex scenarios. Especially for advanced persistent threat (APT) attacks, the system can more quickly identify abnormal behaviors and take corresponding defensive measures, thereby significantly improving the overall security of the system.

[0035] Improve adaptability and scalability: The invention adopts a distributed architecture design, which enables the system to more flexibly adapt to the needs of different scenarios and technological advances. For example, when it is necessary to add new energy types or adjust existing energy configurations, only local modifications need to be made on the corresponding nodes without large-scale changes to the entire system architecture, which greatly reduces the system maintenance cost and complexity.

[0036] Reduce the risk of single point failure: Compared with traditional centralized control systems, the distributed intelligent network security solution proposed in this invention reduces the dependence on central nodes. Even if a node fails, other nodes can continue to work, ensuring the stability and reliability of the system.

[0037] Optimize resource utilization: The data obtained through the perception layer, combined with the intelligent decision-making of the control layer, can achieve accurate evaluation of energy assets, optimization of energy efficiency and effective monitoring of energy consumption, thereby promoting the rational allocation and efficient use of resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0039] Figure 1 It is a structural schematic diagram of a distributed intelligent network security integrated renewable energy system according to the present invention;

[0040] Figure 2 It is a functional module diagram of a distributed intelligent network-based integrated renewable energy system of the present invention;

[0041] Figure 3 is a schematic diagram of a control architecture of a distributed intelligent network-based integrated renewable energy system according to the present invention;

[0042] Figure 4 It is a flow chart of an energy storage charging and discharging and inverter photovoltaic power automatic control strategy of the present invention. DETAILED DESCRIPTION

[0043] The present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the relevant invention, rather than to limit the invention. It is also necessary to explain that, for ease of description, only the parts related to the relevant invention are shown in the accompanying drawings.

[0044] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0045] like Figure 1 and Figure 2 As shown, the first embodiment of the present invention provides an integrated renewable energy system based on distributed intelligent network security, the system comprising: a distributed adaptive access control module, a distributed intrusion detection and response module and a control strategy conflict monitoring module;

[0046] The distributed adaptive access control module deploys the control tasks on each node in the network and obtains data on each node, the data including at least access requests, network security situation and user behavior data, continuously learns, adapts and feedbacks user behavior patterns and changes in the network environment, and dynamically adjusts the access control strategy;

[0047] The distributed intrusion detection and response module deploys intrusion monitoring sensors on various network nodes to obtain network traffic data, mine abnormal behaviors and security threats in the network traffic data based on data mining algorithms, and intelligently generate corresponding response strategies according to the network environment and the nature of security threats;

[0048] The control strategy conflict monitoring module automatically discovers and resolves conflicts based on the priority, scope of application and effective time of the control strategy and based on online learning and feedback mechanisms.

[0049] In order to more clearly explain the present invention, a comprehensive renewable energy system based on distributed intelligent network security is described below in conjunction with Figure 1 and Figure 2 , each module in the embodiment of the present invention is described in detail, and each module is described in detail as follows:

[0050] The distributed adaptive access control module does not complete its control tasks on a central controller, but is deployed in a distributed manner on each node in the network to implement localized access control decisions, reduce decision delays and reduce sensitivity to single point failures, and obtain data on each node, continuously learn, adapt and feedback user behavior patterns and changes in the network environment, and dynamically adjust access control strategies;

[0051] In this embodiment, the distributed adaptive access control module obtains data on each network node, and the data at least includes: each child node based on its own sensor data, user request data during network access, behavior pattern characteristics and network security situation.

[0052] The method of continuously learning, adapting and feeding back the user's behavior patterns and changes in the network environment includes a machine learning algorithm and a data analysis algorithm; specifically, the machine learning algorithm can use supervised learning, unsupervised learning or reinforcement learning techniques to train the model to identify the difference between legitimate access and malicious behavior. For example, a random forest or a support vector machine (SVM) can be used to classify user behavior.

[0053] Data analysis algorithms can use statistical analysis, cluster analysis and other methods to process large amounts of raw data, extract valuable information, and help optimize access control decisions.

[0054] The control access strategy includes at least the total parameters of the power station, primary frequency regulation, voltage control, active power control, reactive power control, full power support control, fluctuation control, multi-energy coordinated control, over-generation prevention control, power distribution and PID control.

[0055] The sensor in this embodiment may be a physical or environmental sensor (such as temperature, humidity, light intensity, etc.) installed at each node, which collects data to evaluate the working status and environmental conditions of the device.

[0056] In this embodiment, the user request data may be a record of all requests generated when the user interacts with the system, including but not limited to login attempts, operation instructions, etc., so as to analyze the user's behavior pattern.

[0057] Behavioral pattern features are used to identify normal user behaviors and activity patterns of potential attackers by learning from historical data.

[0058] Network security status can be to continuously monitor the overall health of the network, including but not limited to network connection status, abnormal traffic detection, etc.

[0059] In this embodiment, the specific implementation steps of the distributed adaptive access control module are as follows:

[0060] Step S1, initialization phase: define initial security policies and control parameters, and establish basic access rules.

[0061] Step S2, data collection: start the data collection task of each node to ensure the integrity and accuracy of the data.

[0062] Step S3, model training: Use the collected data to train the machine learning model and continuously optimize the accuracy of the model.

[0063] Step S4, policy generation: dynamically generate or adjust access control policies based on model prediction results and real-time data analysis.

[0064] Step S5, execution and feedback: Apply the updated control strategy to the system and collect the execution effect as the basis for subsequent optimization.

[0065] Through the above process, the distributed adaptive access control module can effectively protect the integrated renewable energy system from illegal access while ensuring the efficient operation of the system.

[0066] The distributed intrusion detection and response module deploys intrusion monitoring sensors on various network nodes to obtain network traffic data, mine abnormal behaviors and security threats in the network traffic data based on data mining algorithms, and intelligently generate corresponding response strategies according to the network environment and the nature of security threats;

[0067] The distributed intrusion detection and response module in this embodiment takes into account that traditional intrusion detection systems are usually analyzed by security experts to summarize attack features, and then the rules required for intrusion detection are established through complex manual coding to identify intrusions. In addition, intruders can also train the intrusion detection system so that behaviors that were initially considered abnormal are considered normal after a period of training. Therefore, this paper deploys intrusion detection sensors on various nodes in the network, monitors network traffic data in a distributed manner, introduces data mining technology into intrusion detection, mines normal and intrusion behavior patterns from a large number of audit records, and automatically generates rules to identify abnormal behaviors and security threats. It also intelligently selects appropriate response measures based on the network environment and the nature of security threats to effectively respond to security threats.

[0068] Among them, the intrusion detection sensor is mainly used to capture all network traffic data passing through the node, including but not limited to data packet header information, data packet payload content, etc., and convert the captured raw traffic data into a format suitable for analysis to facilitate subsequent data mining processing.

[0069] The data mining algorithm in this embodiment can use association rule learning, cluster analysis, classification algorithms, etc. to extract useful features from a large amount of network traffic data, such as access frequency, data packet size distribution, etc., and identify new potential threats by comparing known normal behaviors and intrusion behavior patterns. Intrusion detection rules are automatically generated based on the mined behavior patterns, and the rule base is continuously updated and optimized.

[0070] The corresponding response strategy generated in this embodiment is specifically:

[0071] Continuously monitor changes in the network environment, including network topology, traffic patterns, etc.; evaluate security threat levels based on the severity and impact of detected intrusion behaviors; intelligently select the most appropriate response strategy based on threat assessment results, such as disconnecting, restricting access rights, triggering alarms, etc.; apply the selected response strategy to affected nodes or the entire network to mitigate or eliminate threats.

[0072] This embodiment can automatically generate and adjust intrusion detection rules according to changes in the network environment, thereby improving the flexibility and adaptability of the system. It uses data mining technology to automatically identify intrusion behaviors, reduces the need for manual intervention, and improves detection efficiency. Each node works independently and collaborates with each other, enhancing the robustness and scalability of the system. It can intelligently select response strategies based on real-time threat situations, ensuring the security and stability of the system.

[0073] The control strategy conflict monitoring module automatically discovers and resolves conflicts based on the priority, scope of application and effective time of the control strategy and based on online learning and feedback mechanisms.

[0074] The control strategy conflict monitoring module in the present invention can store all defined control strategies, including but not limited to power station total parameter control, primary frequency regulation, voltage control, active power control, reactive power control, full power support control, fluctuation control, multi-energy coordinated control, over-generation prevention control, power distribution and PID control, etc. The priority, scope of application and effective time of each strategy are recorded, and an efficient indexing mechanism is established to facilitate rapid search and matching of related strategies.

[0075] The control strategy conflict monitoring module in this embodiment is used to continuously monitor the execution of control strategies of each node in the system and collect real-time data. Potential conflict points are detected by comparing the priority, scope of application and effective time of different strategies. Different types of conflicts are identified, such as priority conflicts, time window overlaps, resource competition, etc.

[0076] The strategy of the control strategy conflict monitoring module is specifically:

[0077] Sort conflicting policies according to their priorities, and execute the policies with higher priorities first. For policies with overlapping time windows, adjust their effective time to ensure that they do not interfere with each other. In the case of limited resources, allocate resources reasonably to avoid conflicts caused by resource competition. For policies that can be merged, generate new comprehensive policies to simplify the control logic.

[0078] The control strategy conflict monitoring module in this embodiment also includes self-learning and adaptation functions, specifically:

[0079] Collect various data generated during the system operation, including control strategy execution results, system performance indicators, etc.

[0080] Use machine learning algorithms (such as decision trees, neural networks, etc.) to train conflict detection and resolution models to improve the accuracy and robustness of the models.

[0081] Based on the model prediction results and actual execution effects, the conflict detection and resolution strategies are dynamically adjusted to form a closed-loop feedback mechanism.

[0082] The control strategy conflict monitoring module in this embodiment automatically discovers potential control strategy conflicts through real-time monitoring and intelligent analysis, reducing human intervention. Combined with online learning and feedback mechanisms, the conflict resolution strategy is dynamically adjusted to improve the system's adaptive ability. Ensure that each control strategy works in a coordinated and consistent manner to avoid system instability or failure caused by strategy conflicts. Through a closed-loop feedback mechanism, the conflict detection and resolution model is continuously optimized to improve the overall performance and reliability of the system.

[0083] It should be noted that the above embodiment provides a comprehensive renewable energy system based on distributed intelligent network security, which is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the modules or steps in the embodiments of the present invention can be decomposed or combined. For example, the modules in the above embodiments can be combined into one module, or further divided into multiple sub-modules to complete all or part of the functions described above. The names of the modules and steps involved in the embodiments of the present invention are only for distinguishing the modules or steps, and are not regarded as improper limitations of the present invention.

[0084] In order to overcome the control limitations of integrated renewable energy systems, improve the adaptability, safety and accuracy of system control, make up for a series of problems such as low control efficiency of existing integrated renewable energy systems, and accurately and quickly guide the control process of integrated renewable energy systems, a control architecture for integrated renewable energy systems based on distributed intelligent network security is proposed. The framework is scalable and highly secure.

[0085] like Figure 3As shown, the second embodiment of the present invention proposes a control architecture of a comprehensive renewable energy system based on distributed intelligent network security, based on a comprehensive renewable energy system based on distributed intelligent network security, including a perception layer, a network layer, a control layer, an application layer and a management layer;

[0086] The sensing layer is used to arrange various types of signal sensing devices;

[0087] The network layer is used to transmit the sensing data acquired by the signal sensing device to the application layer;

[0088] An integrated renewable energy system is arranged in the application layer, and control tasks of the integrated renewable energy system are arranged on each node of the network layer. Each node monitors and controls energy data based on perception data, and the energy data at least includes energy assets, energy efficiency, energy consumption and energy planning;

[0089] The control layer is used to obtain control access policies and send them to on-site devices;

[0090] The management layer is used to provide management of resources, tasks, users and security.

[0091] The sensing device at least includes a sensor, a camera, an intelligent gateway and a data acquisition instrument. The sensing device is connected to a first security assurance module, which at least includes a hardware security assurance module, an access security assurance module and a terminal data security assurance module.

[0092] In this embodiment, the sensor can be used to measure various physical quantities such as temperature, humidity, light intensity, etc. The camera can be used for video monitoring and image acquisition.

[0093] The intelligent gateway serves as a communication hub to achieve interconnection between different types of devices.

[0094] The data collector is used for centrally collecting and preliminarily processing data from multiple sensors.

[0095] These sensing devices interact with devices at other levels through different communication protocols (such as MQTT, HTTP, etc.).

[0096] In order to ensure the security and integrity of the sensing data in this embodiment, the sensing device needs to be connected to the first security module. The first security module includes the following submodules:

[0097] Hardware security module: ensures the physical security of the sensing device itself to prevent unauthorized access and damage.

[0098] In this embodiment, the hardware security module can select an anti-theft device, a waterproof device, an anti-interference device and an encryption device. Specifically,

[0099] For equipment anti-theft devices, a miniature GPS receiver is embedded in the device, enabling it to report its current location and automatically send an alert to a monitoring center if the device leaves a pre-set secure area.

[0100] Each device can also be equipped with a unique RFID tag, and when the device passes a specific reading point, the device's presence and status can be read via RFID.

[0101] Integrated sound or light alarms activate when unusual movement is detected to draw attention.

[0102] For waterproof devices, you can choose shell materials that meet IP67 and above standards to ensure that the device can still work normally after being temporarily immersed in water. Use waterproof rubber rings or silicone sealing strips at all interfaces to ensure a good sealing effect. Without affecting the waterproof performance, set drainage holes appropriately to avoid internal water accumulation.

[0103] For anti-interference devices, you can use metal shielding covers to cover electronic components to reduce the impact of external electromagnetic waves. Install EMI / RFI filters on power lines and signal lines to filter out unnecessary noise. Use technologies such as photoelectric isolation or transformer isolation to further enhance anti-interference capabilities.

[0104] For encryption devices, strong encryption algorithms (such as AES-256) can be used to encrypt the transmitted data to ensure that even if the data is intercepted, it cannot be interpreted. Implement a strict key management process, including key generation, distribution, storage and update, to ensure the security of the key. Use a two-way authentication mechanism to ensure that the sender and receiver of the data are both verified legal entities.

[0105] Access security module: through device identity authentication and authorization, ensure that only legitimate devices can access the network.

[0106] The access security module in this embodiment includes a mandatory authentication module, an intrusion protection module, an encrypted communication module and an abnormal alarm module. Specifically:

[0107] The mandatory authentication module can use digital certificates or pre-shared keys (PSK) to authenticate devices. Each device needs to provide valid identification when it connects for the first time. It can also combine multiple factors such as device hardware feature codes and MAC addresses for authentication to increase the reliability of authentication. It can also use a one-time password (OTP) or a time-synchronized dynamic password (such as TOTP) to generate a new password each time you connect to ensure the security of the password.

[0108] The intrusion prevention module can deploy firewalls at the network boundary and configure rules to restrict unauthorized access requests, allowing only necessary communication traffic to pass. It can also deploy an intrusion detection system based on signature and behavior analysis to monitor network traffic in real time, detect abnormal behavior and issue alarms.

[0109] The encrypted communication module can use the TLS / SSL protocol to encrypt the transmitted data to ensure the security of the data during transmission. It can also establish an end-to-end encrypted channel between the device and the server and encrypt the data using a symmetric encryption algorithm (such as AES-256).

[0110] The abnormal alarm module can use network monitoring tools to monitor network traffic and device status in real time and detect abnormal behavior. It can also set thresholds for key indicators (such as bandwidth usage, number of login attempts, etc.) and trigger alarms when the thresholds are exceeded. It can also configure automated scripts or tools to automatically perform predefined actions when anomalies are detected, such as disconnecting and logging.

[0111] Terminal data security module: protects the security of perception data during transmission, such as using encryption technology to prevent data from being stolen or tampered with.

[0112] In this embodiment, the terminal data security assurance module includes a data encryption module, a data leakage prevention module, a data copy prevention module, and a whitelist and blacklist setting module.

[0113] The data encryption module can be encrypted using a key.

[0114] For the data leakage prevention module, data can be classified and labeled to distinguish between sensitive data and non-sensitive data to ensure that sensitive data is strictly protected. Fine-grained access control policies can also be implemented to ensure that only authorized users and applications can access sensitive data.

[0115] The data anti-copying module can set file and directory permissions to prohibit unauthorized users from copying or modifying data. It can also embed invisible watermarks in sensitive data so that the source can be traced after the data is leaked.

[0116] Set up whitelist and blacklist modules:

[0117] Whitelist management: Maintain a list of trusted applications and users. Only whitelisted applications and users can access sensitive data.

[0118] Blacklist management: Maintain a list of untrusted applications and users and prohibit blacklisted applications and users from accessing data.

[0119] Dynamic updates: Whitelists and blacklists are updated regularly to ensure that the latest security policies are effectively implemented.

[0120] The sensing device captures various changes in the surrounding environment in real time through built-in sensors or other sensing elements, and converts these data into electrical signals or digital signals. These signals are then transmitted to the intelligent gateway or other intermediate devices through wireless or wired communication, and finally converged to the data collector. The data collector will perform preliminary processing on the collected data, such as denoising and filtering, and then transmit it to the application layer through the network layer.

[0121] During the entire process, the first security module will monitor the flow of data throughout the process to ensure the safe transmission of data. The hardware security module will regularly check the status of the sensing device to promptly discover and repair possible security risks. The access security module will perform identity authentication when the device is connected to prevent illegal devices from accessing the network. The terminal data security module will use encryption technology during data transmission to ensure that the data will not be intercepted or tampered with by a third party.

[0122] The perception layer has a wide range of application scenarios, especially in integrated renewable energy systems, where it can be used to monitor the working status of key facilities such as wind farms, solar photovoltaic panels, and energy storage devices, as well as changes in surrounding environmental conditions. By collecting and analyzing this data in real time, the system can more accurately predict and regulate energy production and consumption, thereby improving energy efficiency and reducing energy costs.

[0123] The perception layer is the foundation of the integrated renewable energy system. By deploying various types of signal perception devices, it realizes comprehensive perception and data collection of the physical world, laying a solid foundation for subsequent data processing and analysis. At the same time, through the protection of the first security module, the security and integrity of the perception data are ensured, providing an important guarantee for the stable operation of the system.

[0124] The network layer in this embodiment transmits the sensing data through a transmission device, and the transmission device includes at least one or more of optical fiber, mobile communication and GPRS.

[0125] The transmission device is connected to a second security assurance module, which at least includes a network security assurance module and a data transmission security assurance module.

[0126] The optical fiber can provide high-speed, high-bandwidth data transmission, and is suitable for long-distance, large-capacity data transmission needs.

[0127] The mobile communication includes 4G, 5G, WIFI and other mobile communication technologies, which are suitable for data transmission between mobile devices and remote nodes.

[0128] The GPRS general packet radio service technology is suitable for low-speed, low-cost data transmission requirements.

[0129] These transmission devices can be flexibly selected and used in combination according to actual application scenarios and requirements.

[0130] Among them, the network security assurance module in this embodiment includes a network security isolation module, a device access authentication module, and a network attack warning module. Specifically:

[0131] The network security isolation module can be set up in the form of a firewall.

[0132] For device access authentication module, digital certificate authentication or MAC address binding can be used.

[0133] For the network attack warning module, you can deploy an IDS based on signature and behavior analysis to monitor network traffic in real time, detect abnormal behavior and issue an alarm. You can also automatically take measures to block the attack source and protect the network from harm when intrusion behavior is detected.

[0134] In this embodiment, the data transmission security guarantee module includes a data transmission encryption module, a data backup and recovery module, a data breakpoint resume module and a data integrity protection module. Specifically:

[0135] The data transmission encryption module can also be encrypted by means of a key.

[0136] For the data backup and recovery module, important data can be backed up regularly to a secure storage device or cloud. In addition to full backup, incremental backup can also be performed regularly to reduce backup time and storage space.

[0137] The data breakpoint resume module is used to ensure that data transmission can continue in the event of a network interruption or failure to prevent data loss. This can be achieved in the following ways:

[0138] Breakpoint recording: During data transmission, the location and status of the transmitted data are recorded.

[0139] Retransmission mechanism: After a network interruption, the transmission will automatically restart from the breakpoint to avoid repeated transmission of successfully transmitted data.

[0140] Timeout retry: Set a reasonable timeout period. If no confirmation information is received within the specified time, the transmission will be automatically retried.

[0141] The data integrity protection module can be implemented through hash verification, digital signature and other methods.

[0142] The application layer in the present invention also includes an application security module, which is used for business authority management, access authentication and application detection. Specifically:

[0143] Business permission management is used to ensure that users can only access authorized business functions to prevent unauthorized operations. Different roles are defined according to business needs, such as administrator, operator, auditor, etc. Corresponding permissions are assigned to each role, such as viewing data, modifying settings, performing operations, etc. Permission inheritance between roles is supported to simplify permission management. User permissions are dynamically adjusted according to business changes to ensure the timeliness and accuracy of permissions.

[0144] Access authentication is used to ensure that only authenticated users can access the system, preventing unauthorized access.

[0145] Application detection is used to monitor the running status of applications in real time and detect and handle potential security threats.

[0146] like Figure 4 As shown, based on the contents of the first and second embodiments, the third embodiment of the present invention proposes an energy storage charging and discharging and inverter photovoltaic power automatic control strategy, such as Figure 4 As shown, the size of renewable energy generation power (Pv for short) and load power (PI) is judged once every minute: when Pv>PI, ① the percentage of the remaining power of the energy storage battery to the rated capacity of the battery (SOC for short) ≥97% or =0, if the reverse power is>55kw, then enter photovoltaic power control, if the reverse power is <50kw, then the power limit is released and the grid is connected normally; ② if SOC<97%, the energy storage system is charged; when Pv≤PI, ① if SOC≤10% or =0, if the forward power is ≤55kw, normal grid connection operation is possible, if the normal power is greater than 55kw, the controllable load is cut off; ② if SOC>10%, the energy storage system is discharged.

[0147] The terms "first", "second", etc. are used to distinguish similar objects rather than to describe or indicate a particular order or sequence.

[0148] The term "comprise" or any other similar term is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus / device that includes a list of elements includes not only those elements but also other elements not expressly listed, or also includes elements inherent to such process, method, article, or apparatus / device.

[0149] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. A comprehensive renewable energy system based on distributed intelligent network security, characterized in that: The system includes: a distributed adaptive access control module, a distributed intrusion detection and response module and a control strategy conflict monitoring module; The distributed adaptive access control module deploys the control tasks on each node in the network and obtains data on each node, the data including at least access requests, network security situation and user behavior data, continuously learns, adapts and feedbacks user behavior patterns and changes in the network environment, and dynamically adjusts the access control strategy; The distributed intrusion detection and response module deploys intrusion monitoring sensors on various network nodes to obtain network traffic data, mine abnormal behaviors and security threats in the network traffic data based on data mining algorithms, and intelligently generate corresponding response strategies according to the network environment and the nature of security threats; The control strategy conflict monitoring module automatically discovers and resolves conflicts based on the priority, application scope and effective time of the control strategy and based on online learning and feedback mechanism.

2. The integrated renewable energy system based on distributed intelligent network security according to claim 1, characterized in that: The distributed adaptive access control module obtains data on each node, and the data at least includes: Each child node is based on its own sensor data, user request data during network access, behavioral pattern characteristics and network security situation.

3. The integrated renewable energy system based on distributed intelligent network security according to claim 1, characterized in that: The method of continuously learning, adapting to and feeding back changes in user behavior patterns and network environments includes a machine learning algorithm and a data analysis algorithm.

4. The integrated renewable energy system based on distributed intelligent network security according to claim 1, characterized in that: The control access strategy includes at least the total parameters of the power station, primary frequency regulation, voltage control, active power control, reactive power control, full power support control, fluctuation control, multi-energy coordinated control, over-generation prevention control, power distribution and PID control.

5. The integrated renewable energy system based on distributed intelligent network security according to claim 1, characterized in that: The distributed intrusion detection and response module distributes the intrusion monitoring sensors on each node in the network. The specific method is as follows: An intrusion detection sensor is arranged on each node in the network, and the network flow data is monitored and acquired in a distributed manner through the intrusion detection sensor.

6. A control architecture of a distributed intelligent network-based integrated renewable energy system, based on a distributed intelligent network-based integrated renewable energy system as claimed in any one of claims 1 to 5, characterized in that: Includes perception layer, network layer, control layer, application layer and management layer; The sensing layer is used to arrange various types of signal sensing devices; The network layer is used to transmit the sensing data acquired by the signal sensing device to the application layer; An integrated renewable energy system is arranged in the application layer, and control tasks of the integrated renewable energy system are arranged on each node of the network layer. Each node monitors and controls energy data based on perception data, and the energy data at least includes energy assets, energy efficiency, energy consumption and energy planning; The control layer is used to obtain control access policies and send them to on-site devices; The management layer is used to provide management of resources, tasks, users and security.

7. The control architecture of the integrated renewable energy system based on distributed intelligent network security according to claim 6, characterized in that: The sensing device includes at least a sensor, a camera, an intelligent gateway and a data acquisition device.

8. The control architecture of the integrated renewable energy system based on distributed intelligent network security according to claim 7, characterized in that: The sensing device is connected to a first security assurance module, which includes at least a hardware security assurance module, an access security assurance module and a terminal data security assurance module.

9. The control architecture of a distributed intelligent network-based integrated renewable energy system according to claim 6, characterized in that: The network layer transmits the sensing data through a transmission device, and the transmission device includes at least one or more of optical fiber, mobile communication and GPRS.

10. The control architecture of the integrated renewable energy system based on distributed intelligent network security according to claim 9, characterized in that: The transmission device is connected to a second security assurance module, which at least includes a network security assurance module and a data transmission security assurance module.

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