Risk-driven safety emergency response system for wind and light storage and transmission

Abstract

The invention discloses a risk-driven safety emergency response system for wind and light storage and transmission, and belongs to the field of new energy electric power safety control. The method comprises the following steps: collecting multi-mode operation data of a new energy station; performing fusion analysis according to the multi-mode operation data to obtain a risk level signal; according to the risk level signal, a control instruction sequence is obtained through preset system operation constraints; performing interlocking checking on the execution logic of the control instruction sequence, and planning an execution time sequence to obtain a checked control instruction; and based on the checked control instruction, monitoring a communication link state to obtain a communication health degree, when the communication health degree is lower than a preset threshold value, generating an abdication control strategy result, and performing checking execution to complete risk-driven safety emergency response. The problem of risk identification delay in the prior art can be solved.

Description

Technical Field

[0001] This invention relates to the field of new energy power safety control, specifically to a risk-driven safety emergency response system for wind, solar, energy storage and transmission. Background Technology

[0002] New energy power generation systems are clean energy power supply systems mainly composed of wind, solar, and energy storage units. Their operation involves multiple coupled aspects, including electrical, mechanical, meteorological, and communication systems. With the continuous expansion of new energy grid connection, the system exhibits characteristics such as high dynamism, fast response speed, and complex coupling relationships. To ensure grid stability and the safety of new energy power generation, new energy power plants are generally equipped with monitoring, protection, and dispatching systems to achieve basic data acquisition, power regulation, and remote control functions. These systems are typically based on a hierarchical communication architecture, achieving equipment status visualization and basic emergency control through coordination between master stations, substations, and terminal units.

[0003] However, existing new energy safety monitoring and emergency response systems are mostly based on traditional centralized control models, which have several shortcomings under complex operating conditions: First, monitoring and emergency response are relatively disconnected, risk identification is delayed, and real-time closed-loop control cannot be achieved; second, after the main station communication is interrupted or the link degrades, the power plant lacks autonomous decision-making capabilities, which can easily lead to control instability; third, the existing control command source verification mechanism is insufficient, and the execution process lacks reliable traceability, resulting in limited levels of safety protection. Furthermore, in scenarios involving multi-power plant collaboration or cross-regional wind-solar-storage joint operation, the information exchange standards between systems are not unified, and there is a lack of a unified risk transmission and emergency coordination mechanism. In view of the above problems, new energy power plants urgently need a comprehensive emergency response system capable of risk identification, control coordination, and safety protection under communication-constrained conditions when facing sudden environmental disturbances, communication anomalies, or equipment failures, in order to solve the technical problems of delayed risk identification, interrupted control loops, and unreliable emergency responses in existing technologies. Summary of the Invention

[0004] The purpose of this invention is to provide a risk-driven safety emergency response system for wind, solar, and energy storage to solve the problem of delayed risk identification in the prior art.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: Firstly, a risk-driven safety emergency response method for wind, solar, and energy storage includes the following steps: Collect multimodal operation data from new energy power plants; Based on the multimodal operational data, a fusion analysis is performed to obtain a risk level signal; Based on the risk level signal and through preset system operation constraints, a sequence of control commands is obtained; The execution logic of the control instruction sequence is interlocked and checked, and the execution timing is planned to obtain the checked control instructions; Based on the verified control commands, the communication link status is monitored to obtain the communication health status. When the communication health status is lower than a preset threshold, a fallback control strategy result is generated and verified and executed to complete the risk-driven security emergency response.

[0006] In some implementations, the step of performing fusion analysis based on the multimodal operational data to obtain a risk level signal specifically includes: Based on the topology sensitivity graph attention network model, the multimodal operation data is fused with the electrical topology relationship of the new energy power station and the current control mode parameters to form a model, calculate the risk index, and obtain the risk level signal.

[0007] In some implementations, the sequence of control commands includes: a master control command, a rollback control command, and a supervisory control command.

[0008] In some implementations, the steps of interlocking and verifying the execution logic of the control instruction sequence and planning the execution timing to obtain the verified control instructions specifically include: The logical validity and action interlock relationship of each control command in the control command sequence are checked, and the execution order of each control command is planned based on the relay protection time window to obtain the checked control command.

[0009] In some implementations, the following steps are also included: The verified control command is signed with an identity, and the hash value, timestamp, and readback information of the verified control command are recorded using the blockchain result.

[0010] In some implementations, the step of generating a backoff control strategy result when the communication health is lower than a preset threshold specifically includes: With the goal of minimizing voltage deviation, number of switching operations, and energy loss, a sequence of load reduction, disconnection, and energy storage support is generated as the result of the backoff control strategy.

[0011] In some implementations, the following steps are also included; The verified control commands are simulated and verified, and dynamically optimized and updated using a model distillation mechanism.

[0012] In some implementations, the following steps are also included: The isolation state is switched according to the communication health status, and the isolation state includes: full isolation, semi-isolation and phased isolation.

[0013] Secondly, a risk-driven safety emergency response system for wind, solar, and energy storage includes: The field layer is used to collect multimodal operation data from new energy power plants; The risk assessment engine is used to perform fusion analysis based on the multimodal operating data to obtain risk level signals; A risk-driven control command synthesizer is used to obtain a sequence of control commands based on the risk level signal and preset system operation constraints. The linkage control coordinator is used to perform interlock verification on the execution logic of the control instruction sequence, plan the execution timing, and obtain the verified control instructions. The isolation control module is used to monitor the communication link status based on the verified control command, obtain the communication health status, and when the communication health status is lower than a preset threshold, generate a fallback control strategy result, verify and execute it to complete the risk-driven security emergency response.

[0014] In some implementations, it also includes: The trusted authentication and audit chain module is used to perform identity signature on the verified control command and use the blockchain result to record the hash value, timestamp, and readback information of the verified control command.

[0015] Specifically, a risk-driven safety emergency response system for wind, solar, energy storage and transportation includes a field layer, an edge autonomous layer, a main station collaboration layer, and an emergency linkage layer. The field layer is used to collect and execute control of multimodal information such as electrical, mechanical, environmental and security information. The field layer includes an electrical monitoring unit, a mechanical and structural monitoring unit, an environmental and security monitoring unit, an edge acquisition and synchronization device, and an execution mechanism. The edge autonomous layer is the core of the system's intelligent decision-making and security control. The edge autonomous layer includes a risk assessment engine, a risk-driven control command synthesizer, a linkage control coordinator, an isolation control module, a disconnection and fallback generation module, and a trusted authentication and audit chain module. The main station collaboration layer includes a digital twin sandbox, a strategy training and distillation unit, and a cross-site collaboration module, which are used for global strategy optimization and inter-site collaborative operation. The emergency response coordination layer includes a resource access module, a resource quality modeling module, and a resource scheduling module, which are used to realize the access and coordination control of external emergency resources. The system forms a closed loop of data interaction and command feedback between the various layers through a communication network. The system achieves dynamic safety management and control of the operation status of new energy power stations through risk identification, control order generation, execution verification and isolation protection.

[0016] Furthermore, the risk assessment engine integrates electrical topology, control mode and real-time monitoring data based on the topology sensitivity graph attention network model, calculates risk indicators and outputs risk level and candidate disposal set.

[0017] Furthermore, the risk-driven control command synthesizer generates a sequence of control commands based on a combination of model predictive control and reinforcement learning algorithms, and outputs a main control command, a backoff control command, and a supervisory control command according to the operating constraints.

[0018] Furthermore, the linkage control coordinator performs legality and interlock checks on the control command execution logic, plans the execution sequence according to the relay protection time window, and reads back the feedback results after execution.

[0019] Furthermore, the isolation control module switches between three states—complete isolation, semi-isolation, and phased isolation—based on the communication health determination result, and performs state synchronization and control recovery operations after communication is restored to maintain the continuity and security of system operation.

[0020] Furthermore, the disconnection fallback generation module automatically solves the fallback strategy when communication is interrupted, generating a load reduction, disconnection, and energy storage support sequence with the goal of minimizing voltage deviation, number of switching operations, and energy loss, thereby achieving stable operation in islanded state.

[0021] Furthermore, the trusted authentication and audit chain module generates a unique hardware fingerprint for the device through a physically unclonable function, performs identity signature on control commands and execution receipts, and uses a blockchain structure to record the control command hash value, timestamp, and readback information, thereby achieving verifiability and immutability of the command execution process.

[0022] Furthermore, the digital twin sandbox is used to perform real-time simulation verification of the control strategies executed by the edge autonomous layer. The strategy training and distillation unit distributes the simulated and verified strategies to the edge autonomous layer through a model distillation mechanism to achieve dynamic optimization and continuous updating of the strategies.

[0023] Furthermore, the emergency response layer establishes a resource quality and response priority model. Based on the response capabilities and reliability of external fire protection, security, drones, and mobile energy storage equipment, a priority scheduling algorithm is used to coordinate and schedule resources, thereby achieving multi-system collaborative emergency response.

[0024] Furthermore, communication and functional collaboration relationships are established between the various layers and modules of the system, wherein: The field layer transmits data and aligns time with the edge autonomous layer through the edge acquisition and synchronization device, sending the multimodal operation data collected by the electrical monitoring unit, mechanical and structural monitoring unit and environmental and security monitoring unit to the risk assessment engine; The risk assessment engine combines the collected data with electrical topology and control parameters to generate a risk level signal and transmit it to the risk-driven control synthesizer. The risk-driven control command synthesizer generates a control command sequence based on the risk level signal and system constraints and outputs it to the linkage control coordinator. The linkage control coordinator performs interlock verification on the control command execution logic and sends it to the execution mechanism; The isolation control module determines whether the system is in a state of complete isolation, semi-isolation, or phased isolation based on the communication status signal, and restores normal interaction through the status synchronization unit when communication is restored. The disconnection retreat generation module generates a retreat strategy when a communication interruption is detected and submits it to the linkage control coordinator for execution. The trusted authentication and audit chain module performs identity signing, hash storage, and log comparison on all issued and read-back information, thereby achieving consistency and traceability of the system in the communication, control, and execution processes.

[0025] Compared with the prior art, the present invention has the following beneficial effects: This invention overcomes the perception delay caused by single data and asynchronous perception in traditional systems by synchronously collecting multimodal operational data. Next, it utilizes fusion analysis to directly transform multi-source data into clear risk level signals, avoiding the judgment delays caused by fragmented analysis and complex correlation calculations. Then, based on this signal and coupled with system constraints, it automatically generates a sequence of control commands, solving the decision-making delays caused by slow manual intervention or remote decision-making. Next, it performs automated interlock verification and execution timing planning for the commands, completing security verification in a very short time and eliminating verification delays caused by concerns about command conflicts. Finally, by monitoring communication health in real time and seamlessly switching to local fallback strategies in case of anomalies, it ensures that the response link is not interrupted even under communication constraints, fundamentally avoiding communication dependency delays. These steps are sequentially linked, forming a highly automated, closed-loop, and resilient rapid response path, thus fundamentally solving the core problems of risk identification and response delays in existing technologies. Attached Figure Description

[0026] Figure 1 A flowchart illustrating a risk-driven safety emergency response method for wind, solar, and energy storage and transportation, provided as an embodiment of the present invention; Figure 2 A structural diagram of a risk-driven safety emergency response system for wind, solar, and energy storage provided in an embodiment of the present invention; Figure 3 This is a flowchart illustrating the operation of a risk-driven safety emergency response system for wind, solar, and energy storage, provided as an embodiment of the present invention. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0028] like Figure 1 As shown, this embodiment provides a risk-driven safety emergency response method for wind, solar, and energy storage and transportation, including the following steps: S1 collects multimodal operation data from new energy power plants; S2, Based on the multimodal operation data, perform fusion analysis to obtain a risk level signal; S3. Based on the risk level signal and through preset system operation constraints, a sequence of control commands is obtained; S4, perform interlock verification on the execution logic of the control instruction sequence, and plan the execution timing to obtain the verified control instructions; S5. Based on the verified control command, monitor the communication link status to obtain the communication health. When the communication health is lower than a preset threshold, generate a fallback control strategy result and perform verification and execution to complete the risk-driven security emergency response.

[0029] This invention provides a risk-driven safety emergency response system for wind, solar, and energy storage integration. Based on the need for safe and stable operation of new energy power plants under complex environmental conditions, this system establishes a risk-driven, hierarchical, and collaborative architecture, organically combining risk perception, intelligent analysis, control decision-making, isolation and defense, and emergency response. This invention enables proactive perception, rapid response, and adaptive control in wind, solar, and energy storage integration scenarios, effectively improving the safety, reliability, and intelligence level of new energy power plants.

[0030] The system of this invention adopts a closed-loop structure of "perception-analysis-decision-execution-verification". Through the orderly collaboration of the field layer, edge autonomous layer, main station collaboration layer, and emergency response layer, it constructs a self-governing, verifiable, and traceable security and control system. The system achieves functional layering in structure, information closure in logic, and unity of risk-driven and intelligent feedback in operation.

[0031] In terms of overall architecture, such as Figure 3 As shown, this system comprises a field layer, an edge autonomous layer, a master station collaboration layer, and an emergency response layer. These layers communicate with each other via a network and standardized interfaces to exchange data and provide command feedback, forming a globally collaborative control loop. Specifically, the field layer is responsible for data acquisition and execution control, serving as the system's perception foundation; the edge autonomous layer is the core unit for risk assessment and autonomous decision-making; the master station collaboration layer is responsible for strategy optimization and global scheduling; and the emergency response layer enables cross-domain collaboration and resource integration with external systems.

[0032] The field layer primarily undertakes the system's real-time sensing and execution functions. This layer includes modules for electrical parameter acquisition, mechanical structure monitoring, environmental status perception, and video security monitoring. By monitoring the voltage, current, frequency, phasor, and power of wind turbine generators, the string current, voltage, and inverter operating status of photovoltaic arrays, and the acquisition of BMS data from the energy storage system, it can comprehensively reflect the operating conditions of the new energy power station. In addition, the field layer also includes environmental parameter sensors for temperature, humidity, wind speed, visibility, smoke concentration, and lightning strike signals to capture external disturbance information. All collected data is aggregated and synchronized in time through an edge data acquisition gateway, ensuring unified alignment of multimodal information within millisecond-level time deviations, providing a reliable foundation for subsequent risk analysis. The execution mechanism includes circuit breakers, photovoltaic inverter control modules, energy storage control units, and wind turbine pitch drive modules, enabling rapid response to commands from higher levels and achieving coordinated control of electrical and mechanical actions.

[0033] The edge autonomous layer is the core layer of intelligent control in this system, used for risk identification, decision generation, and autonomous protection. This layer contains multiple functional modules: a risk assessment engine, a control command synthesizer, a linkage control coordinator, an isolation control module, a link failure fallback generation module, a trusted authentication module, and an audit chain recording module. The risk assessment engine, based on a topology sensitivity graph attention network model, integrates electrical topology relationships, control mode parameters, and multimodal monitoring data to dynamically assess system risks. This module can quantify the operating state by establishing a risk function, thereby outputting the risk level and a set of candidate actions. The control command synthesizer, based on the risk assessment results and combined with operating constraints and safety boundaries, uses an algorithm combining model prediction and reinforcement learning to generate a sequence of control commands, enabling joint regulation of wind power, photovoltaic, and energy storage equipment. The linkage control coordinator performs logical consistency checks and timing planning on the control commands to ensure that the execution order of the commands is reasonable and non-conflicting. The isolation control module achieves logical separation between the operating domain and the diagnostic domain through a multi-level isolation strategy, enabling the system to maintain local autonomous control even when the main station communication is abnormal or the network is restricted. The fallback generation module calculates fallback strategies based on real-time status under conditions of communication interruption or isolated operation to ensure system security and stability. The trusted authentication module uses a physically unclonable function to generate a unique hardware fingerprint for authenticating control commands. The audit chain recording module uses distributed hash chain technology to record the entire control command process, achieving traceability and tamper-proof execution of commands.

[0034] The main station collaboration layer serves as the system's global coordination and strategy optimization center. This layer includes a digital twin sandbox, a strategy training and distillation unit, and a cross-site collaboration module. The digital twin sandbox establishes a simulation model encompassing the primary network, control system, and energy storage units to achieve simulation verification and security assessment of risk strategies. The strategy training and distillation unit learns from historical operational data and risk events based on the main station's computing resources, outputs a simulation-verified strategy model, and distributes it to the edge autonomous layer through a distillation mechanism to achieve distributed intelligent optimization. The cross-site collaboration module is used to achieve power sharing and collaborative risk management when multiple sites are connected to the grid, enabling different sites to form a mutually supportive security system within the same area.

[0035] The emergency response coordination layer is responsible for cross-domain collaboration with external systems, enabling efficient linkage between the power system and external emergency resources. This layer includes a resource access module, a resource quality modeling module, and a resource scheduling module. The resource access module enables the access of fire protection systems, security monitoring, drone inspection systems, and mobile energy storage vehicles; the resource quality modeling module establishes a quality service model based on indicators such as response time, energy reserves, and reliability; the resource scheduling module uses a priority-based resource allocation algorithm to uniformly schedule and issue commands for various resources, thereby achieving coordinated linkage between internal power system security control and external emergency response.

[0036] During system operation, multimodal data acquisition and aggregation are first completed at the field layer. After time synchronization via the edge acquisition gateway, the data is transmitted to the risk assessment engine for risk level identification and status analysis. For example... Figure 3 As shown, the system operation flow includes four stages: data acquisition and risk identification, control command synthesis and execution, isolation switching and fallback control, and state recovery and resynchronization. When the risk indicator reaches the preset threshold, the system automatically enters the risk response mode, and the risk-driven control command synthesizer generates the corresponding control sequence. After the control sequence undergoes legality and security verification in the linkage control coordinator, it is issued to the field actuator for execution, completing the real-time control process. During this period, all commands are authenticated by the trusted authentication module, and the execution process and acknowledgment information are synchronously written to the audit chain record module to achieve full-process traceability. When the communication link is abnormal or the master station is unreachable, the isolation control module automatically switches the system to the isolation operation state, and the link failure fallback generation module takes over the control task, calculating the fallback strategy based on real-time power, frequency, and load distribution to ensure the local operation stability of the site. When communication is restored, the system performs a state verification, and the control closed loop is restored through log comparison and state synchronization.

[0037] In typical application scenarios, the system of this invention is suitable for the safety and control of wind-solar-storage integrated power stations. For example, in the event of sudden changes in wind speed, drastic changes in light intensity, or equipment malfunctions, the system can quickly identify the risk level and generate corresponding control strategies through a risk assessment engine. If communication degradation occurs, the system automatically activates an autonomous mode, with the edge layer autonomously adjusting load and supporting voltage based on a local model to ensure the safe operation of critical equipment at the power station. Simultaneously, in the event of a sudden fire, extreme weather, or equipment failure, the emergency response layer can coordinate the intervention of external fire fighting, drone inspections, or energy storage support systems to achieve collaborative handling by multiple systems. After the event, the main station collaboration layer performs a state review and strategy optimization, recalculating the handling process through digital twin simulation to optimize risk model parameters, achieving continuous evolution and self-learning.

[0038] This embodiment provides a risk-driven safety emergency response system for wind, solar, and energy storage. By constructing a layered collaborative architecture consisting of a field layer, an edge autonomous layer, a master station collaboration layer, and an emergency linkage layer, it achieves integrated linkage of real-time acquisition of multimodal operational data, risk identification, control decision-making, and emergency response. The system can maintain safety monitoring and autonomous control of new energy power stations under complex operating conditions and communication constraints, significantly improving operational stability and reliability. The risk assessment engine and risk-driven control command synthesizer of this invention work together, utilizing a combination of topology-sensitive graph attention networks and model predictive control algorithms to achieve adaptive identification and precise control of electrical topology and control modes. Through the setting of isolation control modules and link failure fallback generation modules, the system can still execute local risk control and fallback strategies in the event of communication interruption or master station disconnection, ensuring the continuous safe operation of the power station. Furthermore, this invention introduces physically unclonable functions and audit chain technology to establish a trusted authentication and traceability mechanism for the entire control command process; and through a digital twin sandbox and strategy training and distillation units, it achieves online verification and self-learning optimization of strategies, thereby improving the autonomous defense and emergency response capabilities of new energy power stations in extreme environments.

[0039] In summary, the system of this invention forms a hierarchical and domain-based structure, and functionally achieves a closed-loop integration of risk identification, intelligent control, and emergency response. Through a risk-driven dynamic control mechanism, the system realizes full-process safety management from data perception to command verification. Compared with existing technologies, this invention has significant advantages such as timely risk identification, reliable control commands, reliable isolation and protection, and strong system autonomy. Its application can effectively improve the operational stability of wind-solar-storage-transmission integrated power stations under extreme conditions, providing a unified technical framework and implementation path for the intelligent safety management of new energy power stations.

[0040] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A risk-driven safety emergency response method for wind, solar, and energy storage and transportation, characterized in that, Includes the following steps: Collect multimodal operation data from new energy power plants; Based on the multimodal operational data, a fusion analysis is performed to obtain a risk level signal; Based on the risk level signal and through preset system operation constraints, a sequence of control commands is obtained; The execution logic of the control instruction sequence is interlocked and checked, and the execution timing is planned to obtain the checked control instructions; Based on the verified control commands, the communication link status is monitored to obtain the communication health status. When the communication health status is lower than a preset threshold, a fallback control strategy result is generated and verified and executed to complete the risk-driven security emergency response.

2. The risk-driven safety emergency response method for wind, solar, and energy storage and transportation according to claim 1, characterized in that, The steps for obtaining risk level signals by performing fusion analysis based on the multimodal operational data specifically include: Based on the topology sensitivity graph attention network model, the multimodal operation data is fused with the electrical topology relationship of the new energy power station and the current control mode parameters to form a model, calculate the risk index, and obtain the risk level signal.

3. A risk-driven safety emergency response method for wind, solar, and energy storage and transportation according to claim 1, characterized in that, The control command sequence includes: master control command, rollback control command, and supervisory control command.

4. A risk-driven safety emergency response method for wind, solar, and energy storage and transportation according to claim 1, characterized in that, The steps of interlocking and verifying the execution logic of the control instruction sequence and planning the execution timing to obtain the verified control instructions specifically include: The logical validity and action interlock relationship of each control command in the control command sequence are checked, and the execution order of each control command is planned based on the relay protection time window to obtain the checked control command.

5. A risk-driven safety emergency response method for wind, solar, and energy storage and transportation according to claim 1, characterized in that, It also includes the following steps: The verified control command is signed with an identity, and the hash value, timestamp, and readback information of the verified control command are recorded using the blockchain result.

6. A risk-driven safety emergency response method for wind, solar, and energy storage and transportation according to claim 1, characterized in that, When the communication health status is lower than a preset threshold, the step of generating a fallback control strategy result specifically includes: With the goal of minimizing voltage deviation, number of switching operations, and energy loss, a sequence of load reduction, disconnection, and energy storage support is generated as the result of the backoff control strategy.

7. The risk-driven safety emergency response method for wind, solar, and energy storage and transportation according to claim 1 further includes the following steps; The verified control commands are simulated and verified, and dynamically optimized and updated using a model distillation mechanism.

8. The risk-driven safety emergency response method for wind, solar, and energy storage and transportation according to claim 1 further includes the following steps: The isolation state is switched according to the communication health status, and the isolation state includes: full isolation, semi-isolation and phased isolation.

9. A risk-driven safety emergency response system for wind, solar, and energy storage and transportation, characterized in that, include: The field layer is used to collect multimodal operation data from new energy power plants; The risk assessment engine is used to perform fusion analysis based on the multimodal operating data to obtain risk level signals; A risk-driven control command synthesizer is used to obtain a sequence of control commands based on the risk level signal and preset system operation constraints. The linkage control coordinator is used to perform interlock verification on the execution logic of the control instruction sequence, plan the execution timing, and obtain the verified control instructions. The isolation control module is used to monitor the communication link status based on the verified control command, obtain the communication health status, and when the communication health status is lower than a preset threshold, generate a fallback control strategy result, verify and execute it to complete the risk-driven security emergency response.

10. A risk-driven safety emergency response system for wind, solar, and energy storage and transportation according to claim 9, characterized in that, Also includes: The trusted authentication and audit chain module is used to perform identity signature on the verified control command and use the blockchain result to record the hash value, timestamp, and readback information of the verified control command.

Images