In this paper, a new optimal design method for buildings and urban energy systems is proposed. Alsoits applicability is analyzed through a simple case study. Genetic Algorithms (GA) which can deal withnonlinear optimization problems is adopted for this optimal design method. This method has twooptimization steps, selection of equipment capacity and selection of the best operational planning.These optimization problems cannot be solved separately due to the strong relation between thecapacity size and operation efficiency of equipment.
In order to improve the user acceptance of an automatic shading device controller, user wishes concerning the blind position are learned and integrated in the automatic controller through an innovative adaptation system developed with the use of Genetic Algorithms. Simulations with virtual users have shown learning and anticipating capabilities of the system. This paper explains in detail the adaptation process and shows one typical example of simulation results.
In order to achieve a satisfactory level of hygiene and comfort in premises and to assess the pollutant transfers, it is necessary to control the air flow distribution. An intermediate approach between predictive numerical simulation and experimental determination of aerodynamic parameters characterizing air distribution in rooms, is the systemic approach. The paper presents the principles of this approach which is based on the residence times distribution (RTD) theory, commonly used in chemical engineering.