Modeling, Identification and Control at Telemark University College

Master studies in process automation started in 1989 at what soon became Telemark University College, and the 20 year anniversary marks the start of our own PhD degree in Process, Energy and Automation Engineering. The paper gives an overview of research activities related to control engineering at Department of Electrical Engineering, Information Technology and Cybernetics

Modeling, Identification and Control at Telemark University College

Master studies in process automation started in 1989 at what soon became Telemark University College, and the 20 year anniversary marks the start of our own PhD degree in Process, Energy and Automation Engineering. The paper gives an overview of research activities related to control engineering at Department of Electrical Engineering, Information Technology and Cybernetics

A Simultaneous and Continuous Excitation Method for High-Speed Electrical Impedance Tomography with Reduced Transients and Noise Sensitivity

This paper presents a concept for soft field tomographic scan of all the projections of electromagnetic waves emanating from an array of electrodes. Instead of the sequential excitation of all pairs of electrodes in the list of all projections, the new method present here consists of a single and continuous excitation. This excitation signal is the linear combination of the excitation signals in the projection set at different AC frequencies. The response to a given projection is discriminated by selecting the corresponding AC frequency component in the signal spectra of the digitally demodulated signals. The main advantage of this method is the suppression of transients after each projection, which is particularly problematic in electrical impedance tomography due to contact impedance phenomena and skin effect. The second benefit over the sequential scan method is the increased number of samples for each measurement for reduced noise sensitivity with digital demodulation. The third benefit is the increased temporal resolution in high-speed applications. The main drawback is the increased number of signal sources required (one per electrode). This paper focuses on electrical impedance tomography, based on earlier work by the authors. An experimental proof-of-concept using a simple 4-electrodes electrical impedance tomographic system is presented using simulations and laboratory data. The method presented here may be extended to other modalities (ultrasonic, microwave, optical, etc.)

Soft Sensing of Non-Newtonian Fluid Flow in Open Venturi Channel Using an Array of Ultrasonic Level Sensors—AI Models and Their Validations

In oil and gas and geothermal installations, open channels followed by sieves for removal of drill cuttings, are used to monitor the quality and quantity of the drilling fluids. Drilling fluid flow rate is difficult to measure due to the varying flow conditions (e.g., wavy, turbulent and irregular) and the presence of drilling cuttings and gas bubbles. Inclusion of a Venturi section in the open channel and an array of ultrasonic level sensors above it at locations in the vicinity of and above the Venturi constriction gives the varying levels of the drilling fluid in the channel. The time series of the levels from this array of ultrasonic level sensors are used to estimate the drilling fluid flow rate, which is compared with Coriolis meter measurements. Fuzzy logic, neural networks and support vector regression algorithms applied to the data from temporal and spatial ultrasonic level measurements of the drilling fluid in the open channel give estimates of its flow rate with sufficient reliability, repeatability and uncertainty, providing a novel soft sensing of an important process variable. Simulations, cross-validations and experimental results show that feedforward neural networks with the Bayesian regularization learning algorithm provide the best flow rate estimates. Finally, the benefits of using this soft sensing technique combined with Venturi constriction in open channels are discussed

System Identification of a Non-Uniformly Sampled Multi-Rate System in Aluminium Electrolysis Cells

Standard system identification algorithms are usually designed to generate mathematical models with equidistant sampling instants, that are equal for both input variables and output variables. Unfortunately, real industrial data sets are often disrupted by missing samples, variations of sampling rates in the different variables (also known as multi-rate systems), and intermittent measurements. In industries with varying events based maintenance or manual operational measures, intermittent measurements are performed leading to uneven sampling rates. Such is the case with aluminium smelters, where in addition the materials fed into the cell create even more irregularity in sampling. Both measurements and feeding are mostly manually controlled. A simplified simulation of the metal level in an aluminium electrolysis cell is performed based on mass balance considerations. System identification methods based on Prediction Error Methods (PEM) such as Ordinary Least Squares (OLS), and the sub-space method combined Deterministic and Stochastic system identification and Realization (DSR), and its variants are applied to the model of a single electrolysis cell as found in the aluminium smelters. Aliasing phenomena due to large sampling intervals can be crucial in avoiding unsuitable models, but with knowledge about the system dynamics, it is easier to optimize the sampling performance, and hence achieve successful models. The results based on the simulation studies of molten aluminium height in the cells using the various algorithms give results which tally well with the synthetic data sets used. System identification on a smaller data set from a real plant is also implemented in this work. Finally, some concrete suggestions are made for using these models in the smelters

Off-field Testing of Grid Scenarios at Medium Voltage in Flexible AC Transmission Systems involving Wind Energy

As a result of the geographical location of north-western Germany, the local grid operator EWE NETZ has a pioneer role with respect to the integration of renewable energy sources in existing AC transmission systems. About 7kWh out of 10kWh from EWE NETZ are from renewable sources, which are fed into existing AC transmission systems using FACTS (Flexible AC Transmission System). Currently, electricity from renewable sources such as on- and offshore wind energy farms, biomass, photovoltaics and hydropower are fed into existing power grids in northern Germany. This process drives the medium voltage grid networks into power utilization limits, leading to various operational problems of the modules used in the networks. In areas away from big cities, such as villages and small towns, the low load demand and the high value of power fed into the grid frequently leads to outages of medium power transformers and/or the associated switchgears. In addition, due to long transmission lines, the allowable limits of voltage escalations are often violated. In the context of FACTS, observations by EWE NETZ show that the number of curtailments within the last decade has increased by 7200%! There is an increasing need to study various unstable grid behaviours by looking at switching stations, switch gears, load impedances, frequency variations etc. with respect to varying levels of renewable energy fed into the grid. By emulating the scenarios encountered in the field using a dedicated laboratory at Jade University of Applied Sciences (JUAS), measurements, modelling and model predictive control can be performed successfully

Sustainability Awareness through STEAM+

Innovative technology enterprises have been working closely with OECD countries to address issues related to sustainability. There are many acronyms associated with STEM, e.g. STEM+, incorporating the humanities, community needs, and global concerns indicated by the seventeen Sustainable Development Goals (SDG) of the UN. UN Department of Economic and Social Affairs (UNDESA) supports capacity-building for the SDGs and their related thematic issues, including water, energy, climate, oceans, urbanization, transport, science and technology. We prefer to use STEAM+ based on our earlier work, indicating the inclusion of Arts in the curricula to attract female students and interdisciplinarity. Following Briggs’ constructive alignment paradigm with focus on learning objectives, activities, and assessments (LO-A-A) in a STEAM+ curricula, sustainability can be included with critical reflective thinking addressing air pollution, microplastics in the ocean, renewable energy, food wastage, circular economy, poverty etc. The paradigm “Student in Centre and Front (CSF)” discussed in our earlier study promotes the idea of the student as a responsible member in the society giving due attention to pressing socioeconomic issues such as the SDGs. In this paper, means of extending the responsibility of the students in developing awareness of issues related to SDGs through curricula and projects are presented. The focus of this paper is on addressing STEAM+ tuned for awakening interest in SDGs, with some examples from courses held in our universities. Examples are taken from learning activities involving group of students as part of selected courses and projects/problem-based learning (PPBL) with reflective practice