Public transport travel planning application

Here it is presented an application that plans out travel on public transports and that chooses the best ones, according to preference criteria provided by the user. These criteria are: the time spent on the travel, the price of the tickets and the quality of the transports. The application combines different means of transport. Algorithms and heuristics were developed to draw up transport plans and to choose the best ones. The best plans are determined using the multi-attributes decision techniques. The application uses a database that was developed in a Relational Database Management System. To draw the database at the conceptual and the applicational level, it was used one of the models based on the object, the Entity-Relationship Mode

Intelligent predictive control for thermal comfort and energy savings in public buildings

This talk addresses the problem of controlling a heating ventilating and air conditioning system with the purpose of achieving a desired thermal comfort level and energy savings. The formulation uses the thermal comfort, assessed using the predicted mean vote (PMV) index, as a restriction and minimises the energy spent to comply with it. This results in the maintenance of thermal comfort and on the minimisation of energy, which in most operating conditions are conflicting goals requiring some sort of optimisation method to find appropriate solutions over time. In this work a discrete model based predictive control methodology is applied to the problem. It consists of three major components: the predictive models, implemented by radial basis function neural networks identifed by means of a multi-objective genetic algorithm [1]; the cost function that will be optimised to minimise energy consumption and provide adequate thermal comfort; and finally the optimisation method, in this case a discrete branch and bound approach. Each component will be described, with a special emphasis on a fast and accurate computation of the PMV indices [2]. Experimental results obtained within different rooms in a building of the University of Algarve will be presented, both in summer [3] and winter [4] conditions, demonstrating the feasibility and performance of the approach. Energy savings resulting from the application of the method are estimated to be greater than 50%.