基于工况划分的大规模电厂机组控制数据可视化探索

对电厂控制过程中的历史数据进行有效展示与探索,能帮助用户快速深入理解机组的运行状况.由于历史数据涉及时间跨度长,具有多尺度和高密度的特点,并且包含高维多元的复杂参数集合,为可视化设计带来了很大挑战.从机组运行工况和参数相关性角度研究时序数据空间和高维参数空间的集成可视化映射方法,设计了多角度概览视图和多分辨率层次化工况视图用于导航机组的整体运行状态,有效地支持多层次运行工况的展示与探索;然后,设计了高维多元参数分层导航视图,实现了机组参数的灵活筛选和过滤,并与工况视图联动支持用户对不同时段和不同系统层级的参数特征进行探索.基于上述方法,开发了可视化工具iDCS,并将其应用于实际机组控制数据的可视化与分析中,验证了该系统的有效性和适用性.

Visualization of Large-Scale Power Plant Control Data Based on Condition Division

The effective demonstration and exploration of the historical data from power plant’s control process can help users to understand the operating condition of power units quickly and deeply.Since historical data has the characteristics of long time span,multi-scale and high density,and contains complex,high-dimensional and multivariate parameter sets simultaneously,it has brought great challenges to visual design.In this paper,the integrated visual mapping for time-series data space and high-dimensional parameter space is studied from the perspective of power unit operating conditions and parameter correlation.First,a multi-facet overview is de-signed to navigate the global operating state of the power unit,followed by a multi-resolution operating condition view,which can effectively support the display and exploration of multi-level operating conditions.Then,to realize the flexible selection and filtration of parameters of the power unit,a parameter navigation view is designed to support the hierarchical exploration of multivariate parameters.It can be also well-coordinated with the operating condition view to support users to explore the parameter characteristics of different time periods and different system levels.Based on the above methods,a visualization tool,called iDCS,is designed and applied to the visualization and analysis of the real power unit control data,and the validity and applicability of the system are verified.