Loading...
3 results
Search Results
Now showing 1 - 3 of 3
- Fault detection system for the Évora irrigation canalPublication . Louro, Diogo; Mendes, Mário J. G. C.; Valério, Duarte; Costa, José Sá daA model-based fault detection (FD) system was developed for a Simulink simulation of a four pool irrigation canal in ´Evora, Portugal. Incipient and abrupt faults in the gates, the water off-take valves and the water level sensors were considered. Neural Networks were used to model the canal and find the residue. The training algorithm employed for the NNs was found to be an important factor determining the success of the FD system.
- Development of a multi-agent management system for an intelligent charging network of electric vehiclesPublication . Miranda, João; Borges, José; Mendes, Mário J. G. C.; Valério, DuarteThis paper addresses the modelling and simulation of a battery charging infrastructure for electric vehicles, with the objective of pro-actively scheduling the charging of up to fifty vehicles so as not to overcharge the electrical network. Benefits of having the charging stations differ (as much as possible while satisfying end-user requirements) battery charging for those hours when electricity consumption is otherwise low include rendering electricity consumption more uniform along the day. A multi-agent system was used to design a distributed, modular, coordinated and collaborative multi-agent management system for this infrastructure. Simulation results show the effectiveness of this approach under the conditions of four real-life scenarios.
- GA optimized fractional controller for a wind turbine ride through pitch malfunctionPublication . Pandiyan, Surya; Valério, Duarte; Melicio, Rui; Mendes, VictorThis paper is about better integration of wind energy into an electric grid, avoiding wind turbine pitch malfunction to become a failure. A fractional-order controller is used in the two-level converters of the wind turbine to reduce the voltage drops during the malfunction. The reduction is attained by an optimization problem for selection of the parameters of the fractional-order control. The optimization problem is a non-convex one, solved by a genetic algorithm together with a model of the wind turbine pitch malfunction. Kriging metamodeling is used to assist in output prediction due its lower computational requirements and its ability to provide a value for the uncertainty of the estimate. A comparison between the Kriging metamodeling and the complete model is presented and conclusions are stated to show the advantage of the Kriging metamodeling.