Monique Polit

Control of sludge height in a secondary settler using fuzzy algorithms

During the last years, the efficiency of pollution removal and sludge treatment processes are major concerns because of the more restrictive legislation related to nutrient discharge. A key point in the field of activated sludge wastewater treatment plants (WWTPs) is the secondary settler efficiency. In this paper, the COST 624 Simulation Benchmark (model and data) is used to develop a fuzzy controller of the sludge height in the secondary settler. The presented control strategy is based on simple on-line data (influent, removal and recycle flows) and daily analytical values of the sludge volume index (SVI) allowing the fuzzy algorithm to reduce sludge height variations and thus to increase the settling process efficiency. The developed controller has then been adapted and applied to the Cassa de la Selva activated sludge WWTP (Spain) model, with satisfying results.

Fuzzy logic observers for a biological wastewater treatment process

In order to monitor and control biological processes, on-line measurements of the living part of the system are necessary but difficult or too expensive to obtain. This paper presents fuzzy estimators for the concentration of the substrate at the input, the total and partial alkalinity in the influent and in the effluent and the volatile fatty acid concentration at the output of the reactor. Those observers are built on available on-line measurements like pH, temperature, input flow rate and output gaseous flow rate. The observers are tested on a pilot-scale anaerobic digestion reactor for the treatment of raw industrial wine distillery vinasses.

The development of a mathematical model of a chemical heat pump. The identification of thermal parameters

In this article, we develop a mathematical model to simulate the workings of a chemical heat pump. Simulation results are compared with experimental data. The simulator is able to determine the influence of different parameters associated with heat exchange or with the chemical kinetics of the reaction, and also to simulate the principal operating modes with a view to the automatization of the process.

Optimal Control of a Multi-Energy District Boiler: A Case Study

Abstract The present paper deals with the optimization of a multi-energy district boiler (La Rochelle, France) which supplies domestic hot water and heats residential and public buildings, using renewable and fossil resources. First, a combination of white, grey and black boxes was used to model the plant, thanks to a modular approach. Next, a stratified thermal storage tank was modelled and completed the just-mentioned plant model. Using these models and forecasted sequences about outdoor temperature and thermal power consumption, a model predictive controller allows optimizing the use of both the tank and the wood boiler. As a result, fossil energy consumption and CO 2 emissions are minimized. Energy is stored during low-demand periods and used when demand is high, instead of consuming gas and fuel oil.

Fault detection in a wastewater treatment plant

The wastewater treatment plants are very unstable and the waters to be treated are ill defined. The command of those processes needs to be done with advanced methods of control and supervision. Those methods have to take into account the bad knowledge of the processes. The most important situations that can imply problems for the plant are listed. The parameters that allow the comparison between the crisis situation and normal one are measured. The fuzzy logic method is used to distinguish the different situations in order to take a decision for the working of the plant. The method is tested in simulation and on a real plant.

Modeling of a geothermal and thermal solar process

Abstract This paper is based on a project combining solar and geothermal energies used for heating an individual home located in a mountainous region of southern France (Saint-Pierre Dels Forcats town). A solar field consists of 10 thermal solar collectors, with a total area of 21.25 m 2 which recharge thermally a borehole of 100 m of depth. A heat pump extracts the heat energy to restitute it to the home with a heating floor of 100 m 2 . The long-term objective is to develop a predictive control on the global system to realize financial and energy savings. In order to do this, a modeling of all the subsystems has to be done. This paper focuses of two of these sub-systems, the solar field and the heat pump. Depending on the level of knowledge of each subsystem, a physical model (thermal solar collectors) or a artificial intelligence methodology (heat pump) is used.

Time series and artificial neural networks for short-term electric consumptions forecast

Promoting both energy savings and renewable energy development are two objectives of the actual and national French energy policy. In this sense, the present work takes part in a global development of various tools allowing managing energy demand. So, this paper is focused on estimating short-term electric consumptions for the city of Perpignan (south of France) by means of the Nearest Neighbor Technique (NNT) or Kohonen self-organizing map and multi-layer perceptron neural networks. The analysis of the results allowed comparing the efficiency of both used tools and methods. Future work will first focus on testing other popular tools for trying to improve the obtained results and secondly on integrating a forecast module based on the present work in a virtual power plant for managing energy sources and promoting renewable energy.

Classification of Abnormal Situations in a Waste Water Treatment Plant

The waste water treatment plants are very unstable and the waters to be treated are ill defined. The command of those processes needs to be done with advanced methods of control and supervision. They have to take into account the bad knowledge of the processes. The most important situations that imply problems for the plant are listed. Parameters for comparison between crisis and normal situation are measured. Fuzzy logic and support vector machines methods are used and compared to distinguish the different situations in order to take a decision. The method is tested in simulation and on a real plant.