摘 要
发电厂作为电力系统的核心组成部分，其电气自动化系统的优化对于提高发电效率、保障电网安全稳定运行具有重要意义。随着信息技术的飞速发展和智能电网建设的深入推进，发电厂电气自动化系统的优化研究成为当前电力行业的热点课题。本文旨在探讨发电厂电气自动化系统的优化策略与技术路径，以期为提升发电厂整体运行效率和智能化水平提供参考。本文分析了发电厂电气自动化系统的现状与存在的问题。当前，发电厂电气自动化系统已广泛应用于发电生产各个环节，实现了对机组运行状态的实时监测、控制与保护。然而，在实际运行中，系统仍面临着设备老化、通信协议不统一、数据处理能力不足等问题，制约了发电厂整体运行效率的提升。针对上述问题，本文提出了发电厂电气自动化系统的优化策略。一方面，通过引入先进的传感器技术、物联网技术和云计算技术，提升系统对发电设备的实时监测和数据分析能力，为优化运行提供精准数据支持；另一方面，加强系统间的集成与互联，统一通信协议和数据标准，实现信息的无缝共享与高效传输；同时，优化控制算法和策略，提高系统对机组运行的自动化控制水平，降低人为干预和误操作的风险。在优化技术路径方面，本文重点探讨了智能控制技术、大数据处理技术和网络安全防护技术的应用。智能控制技术通过模拟人类专家的决策过程，实现对机组运行状态的智能判断与调节；大数据处理技术则能够深入挖掘系统运行数据中的潜在价值，为优化决策提供科学依据；网络安全防护技术则确保系统在复杂网络环境下的安全稳定运行。发电厂电气自动化系统的优化研究是提升发电厂整体运行效率和智能化水平的关键途径。通过引入先进技术、优化系统架构和强化安全管理等措施，可以推动发电厂电气自动化系统向更加高效、智能、安全的方向发展。
关键词：发电厂 电气自动化系统 优化研究
Abstract
As the core component of power system, the optimization of electrical automation system of power plant is of great significance to improve power generation efficiency and ensure the safe and stable operation of power grid. With the rapid development of information technology and the deepening of the construction of smart grid, the optimization of electrical automation system in power plants has become a hot topic in the electric power industry. This paper aims to discuss the optimization strategy and technical path of electrical automation system in power plants, in order to provide reference for improving the overall operation efficiency and intelligence level of power plants. This paper analyzes the current situation and existing problems of electric automation system in power plant. At present, the electrical automation system of power plant has been widely used in all aspects of power generation production, realizing the real-time monitoring, control and protection of the unit running state. However, in actual operation, the system is still faced with aging equipment, inconsistent communication protocols, insufficient data processing capacity and other problems, which restricts the overall operation efficiency of the power plant. Aiming at the above problems, this paper puts forward the optimization strategy of electric automation system in power plant. On the one hand, through the introduction of advanced sensor technology, Internet of Things technology and cloud computing technology, improve the system's real-time monitoring and data analysis capabilities for power generation equipment, and provide accurate data support for optimized operation; On the other hand, strengthen the integration and interconnection between systems, unify communication protocols and data standards, and realize seamless sharing and efficient transmission of information; At the same time, the control algorithm and strategy are optimized to improve the automatic control level of the unit operation and reduce the risk of human intervention and misoperation. In terms of optimizing technology path, this paper focuses on the application of intelligent control technology, big data processing technology and network security protection technology. By simulating the decision-making process of human experts, the intelligent control technology realizes the intelligent judgment and adjustment of the unit running state. Big data processing technology can dig deep into the potential value of system operation data and provide scientific basis for optimization decision. The network security protection technology ensures the safe and stable operation of the system in the complex network environment. The optimization research of electrical automation system in power plant is the key way to improve the overall operation efficiency and intelligence level of power plant. By introducing advanced technology, optimizing system architecture and strengthening safety management measures, the electrical automation system of power plants can be promoted to a more efficient, intelligent and safe direction.
Keyword:Power plants Electrical automation system Optimization study
目 录
1引言 1
2相关技术与理论基础 1
2.1电气自动化技术概述 1
2.2系统优化理论 2
2.3智能化技术现状 3
3电气自动化系统优化需求分析 4
3.1优化目标明确 4
3.2用户需求调研 4
3.3技术需求分析 5
3.4分析的准确性与实用性分析 5
4电气自动化系统优化策略与实施 6
4.1系统架构优化设计 6
4.2智能化技术应用 7
4.3数据分析与决策支持 7
4.4策略的创新性与有效性分析 8
5结论 8
参考文献 9
致谢 10
