The optimization of water distribution systems (WDSs) is vital to minimize energy costs required for their operations. A principal approach taken by researchers is identifying an optimal scheme for water pump controls through examining computational simulations of WDSs. However, due to a large number of possible control combinations and the complexity of WDS simulations, it remains non-trivial to identify the best pump controls by reviewing the simulation results. To address this problem, we design a visual analytics system that helps understand relationships between simulation inputs and outputs towards better optimization. Our system incorporates interpretable machine learning as well as multiple linked visualizations to capture essential input-output relationships from complex WDS simulations. We demonstrate our system's effectiveness through a practical case study and evaluate its usability through expert reviews. Our results show that our system can lessen the burden of analysis and assist in determining optimal operating schemes.
翻译:优化水分配系统(WDS)对于最大限度地减少运作所需的能源成本至关重要,研究人员采取的一个主要办法是通过检查WDS的计算模拟,确定水泵控制的最佳办法,然而,由于可能进行的大量控制组合和WDS模拟的复杂性,通过审查模拟结果,确定最佳泵控制方法仍不是三边办法;为解决这一问题,我们设计了一个视觉分析系统,帮助理解模拟投入与产出之间的关系,以便实现更好的优化;我们的系统包括可解释的机器学习以及多个链接的可视化,以捕捉复杂的WDS模拟的基本输入-输出关系;我们通过实际的案例研究展示我们的系统的有效性,并通过专家审查评价其可用性;我们的结果显示,我们的系统可以减轻分析负担,协助确定最佳操作计划。