ABSTRACT

Model-based evaluation of real time control and model predictive control strategies is often performed by estimating the yearly reduction in combined sewer overflow (CSO) volumes. This requires sufficiently long data series, but the necessary input data are often lacking in the case of complex control strategies. This article compares a new method to extrapolate yearly CSO volume reduction by simulating a limited number of CSO events. The method showed a good accuracy (2–3% deviation) when applied to a synthetic example. When applied to a real case study in Copenhagen (Denmark), the method showed a tendency to overestimate the performance of the control. The results underline how performance of real time control strategies is strongly affected by yearly variation, non-linearity and interactions among the elements of the system. It is thus suggested to use a mix of different performance indicators when evaluating control performance in conditions of data scarcity.

摘要

实时控制和模型预测控制策略的基于模型的评估通常通过估计联合下水道溢流 (CSO) 量的年度减少量来执行。这需要足够长的数据序列，但在复杂控制策略的情况下，通常缺乏必要的输入数据。本文比较了一种通过模拟有限数量的 CSO 事件来推断年度 CSO 体积减少的新方法。当应用于合成示例时，该方法显示出良好的准确性（2-3% 的偏差）。当应用于哥本哈根（丹麦）的实际案例研究时，该方法显示出高估控制性能的趋势。结果强调了实时控制策略的性能如何受到系统元素之间的年度变化、非线性和相互作用的强烈影响。