Towards a common benchmark for long-term process control and monitoring performance evaluation

Author:

Rosen C.1,Jeppsson U.1,Vanrolleghem P.A.2

Affiliation:

1. Department of Industrial Electrical Engineering and Automation, Lund University, Box 118, SE-221 00 Lund, Sweden (E-mail: christian.rosen@iea.lth.se, ulf.jeppsson@iea.lth.se)

2. BIOMATH, Department of Applied Mathematics, Biometrics and Process Control, Ghent University, Coupure Links 653, B-9000 Gent, Belgium (E-mail: peter.vanrolleghem@ugent.be)

Abstract

The COST/IWA benchmark simulation model has been available for seven years. Its primary purpose has been to create a platform for control strategy benchmarking of biological wastewater treatment processes. The fact that the benchmark has resulted in more than 100 publications, not only in Europe but also worldwide, demonstrates the interest for such a tool in the research community. In this paper, an extension of the benchmark simulation model no. 1 (BSM1) is proposed. It aims at facilitating evaluation of two closely related operational tasks: long-term control strategy performance and process monitoring performance. The motivation for the extension is that these two tasks typically act on longer time scales. The extension proposed here consists of 1) prolonging the evaluation period to one year (including influent files), 2) specifying time varying process parameters and 3) including sensor and actuator failures. The prolonged evaluation period is necessary to obtain a relevant and realistic assessment of the effects of such disturbances. Also, a prolonged evaluation period allows for a number of long-term control actions/handles that cannot be evaluated in a realistic fashion in the one week BSM1 evaluation period. In the paper, models for influent file design, parameter changes and sensor failures, initialization procedure and evaluation criteria are discussed. Important remaining topics, for which consensus is required, are identified. The potential of a long-term benchmark is illustrated with an example of process monitoring algorithm benchmarking.

Publisher

IWA Publishing

Subject

Water Science and Technology,Environmental Engineering

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