爆发式数据处理模型在电力调度系统中的应用

随着大型能源基地特高压项目的相继运行、新能源发电的深入推进和电动汽车等新型负荷的快速发展,电网监控爆发式海量数据的出现频率大幅增加,给电力调度监控和数据采集SCADA系统的数据管理带来了极大的挑战。文中分析了电力调度存储数据量大、随机性强的特点以及当前数据库抗压性能不稳定的现状,提出了爆发式数据处理模型EDPM(erupt data processing model),介绍了该模型下的多级缓存策略、基于模型控制器的自适应缓存管理机制、线程闭环控制自愈技术等关键技术。工程应用实践表明,EDPM模型在面对海量数据存储请求时仍可保持较快的系统响应和较高的系统吞吐量,能够有效抵御爆发式数据的冲击,保证电力调度SCADA系统的安全、稳定运行。

Application of Erupt Data Processing Model to Electric Power Dispatching System

With the successive operation of ultra-high voltage(UHV)projects in a large energy base,the substantial advancement of new energy power generation,and the rapid development of new electric loads such as electric vehi?cles,the occurrence frequency of erupt massive data monitored by power grid increases dramatically,which brings a great challenge to the data management of supervisory control and data acquisition(SCADA)system used in electric power dispatching.In this paper,the characteristics of large storage data and strong randomness in electric power dis?patching,as well as the current situation of unstable database performance under high pressure,are analyzed.Then,an erupt data processing model(EDPM)is proposed,and the key technologies including multi-level cache strategy,adaptive cache management mechanism based on the model controller,and the thread closed-loop control self-healing technology,are introduced.Results of engineering applications show that when facing massive data storage requests,EDPM can still maintain a faster system response and a higher system throughput,and it can effectively resist the im?pact of erupt data,thus ensuring the safe and stable operation of the SCADA system used in electric power dispatching.