Assessing the saving potential of blind controller via multi-objective optimization

Abstract

This paper presents the results of computational experiments where multi-objective algorithms were used to tune a controller for blind movements in a residential building and a room of the LESO (Solar Energy and Building Physics Laboratory) experimental building. The blind controller, which is based on fuzzy logic, was optimized not only in terms of energy consumption but also in terms of thermal comfort. The goal is to show saving potential for intelligent blind controller in a real world example rather than in tailored idealized test rooms. Therefore, a state of the art simulation program with a multi-objective evolutionary algorithm was combined. It was found that with elementary control systems, like schedules for the lighting in a building, almost 40% of the energy could be saved. With the help of more advanced controllers this can be further increased.Also discussed in this paper are the results and the feasibility of implementing such a controller. Keywords multi-objective optimization, simulation, smart blind controller, fuzzy logic, energy efficiency

A personalized measure of thermal comfort for building controls

“…According to the BS EN ISO 7730 [3] the accepted range of comfort is defined as PMV˛[À0.5, 0.5] according to that we define the answers Très chaud, Chaud, Légèrement chaud, as too hot; the answers Très froid, Froid as Légèrement frais, too cold; and the central answers Comfortable, as comfortable. 2 (Table 1). …”

“…Additional, the opening of the windows and the set point of the HVAC system are other central issues. Nevertheless, in a previous publication of the first author it has been shown that blind operation has a strong impact on energy consumption of a building [2,15]. It is essential for the blind control to define solar gains allowance during daytime in order to save heating energy in the evening and during night time.…”

“…The second possibility occurs when 1 For an introduction into statistical modeling we refer to Powers [24]. 2 Naming the central category "Comfortable" instead of "neutral" according to the ASHRAE scale will not change the location where the highest probability of comfort is reached. It can only steepen (central category may cover a smaller semantic range) or flatten (central category may cover a wider semantic range) the curve, which makes no difference in regard of controlling decisions.…”

“…In Northern Europe, most of the residential houses do not have air cooling units. Nevertheless, if no air cooling is available, a good control of shading devices is even more important to provide good thermal comfort and avoid overheating during summer time [2]. Since the control of these and other complex systems in a building are not trivial, automatic controllers for technical equipment are more and more used.…”

Cyclic overlapping block coordinate search for optimizing building design

“…Simulation-assisted optimization strategies in building design are today mostly used for fine-tuning in specific, later-stage types of inquiry (Augenbroe, 2003), characterized by relatively clear goals and relatively few variables in play; or targeted to specific, constrained types of problems, determined by building type, or use, or objective function, and by the selection of specific issues of inquiry (Daum et al, 2009;Shin, 2011;Khan et al, 2012). This happens in spite of the fact that the variables influencing building performance are numerous and interrelated.…”