We investigated the synergetic effect between light-emitting diode (LED) lighting efficiency and building energy savings in heating and cooling using an alternative thermal operating system (ATOS) of indoor LED lighting integrated with the ventilation system of a building as an active cooling device. The heat generated from LED lighting and the indoor lighting illuminance were experimentally de...

A predictive and adaptive heating controller, using artificial neural networks to allow the adaptation of the control model to the real conditions (climate, building characteristics, user's behaviour) is described. The choice of a predictive control strategy, combined with the nonlinear modelling of the building, the user's behaviour and the weather prediction, allows the NEUROBAT controller to...

This paper presents a stable, nonlinear, adaptive control scheme for building heating and cooling systems. The proposed controller utilizes the principle of adaptive one step ahead control and aims at reducing the energy consumed for heating or cooling a building. The design steps are discussed in details and a proof of global stability is also provided. Also, the performance of the proposed co...

The energy performance of buildings depends on how effectively the building envelope responds to climate. Architects, therefore, need to design building envelopes with the consideration of local climate characteristics in the early design stage. Simplified formulas were used that evaluate the heating and cooling energy demand of building envelopes, which were applied to a model building with en...

Building heating and cooling accounts for nearly 18-24% of all energy usage. Building energy management can reduce both its operating costs and its carbon footprint. We propose the use of a factored Partially Observable Markov Decision Process (POMDP) to model and efficiently control a commercial building heating system. We use supervised learning and ground truth data to capture the parameters...

This paper is concerned with the development of data-driven predictive models capable of forecasting commercial building heating loads based on BEM (Building Energy Management) systems recorded variables, as well as weather data. To address the lack of available complete datasets from actual commercial building BEM systems, a detailed representation of a reference building using EnergyPlus was ...

Thermal effects impact the flow around and within structures. This computational study assesses features that affect the heating and buoyancy, and thus, the resulting flow both internal and external to a building. Considerations include the importance of time of day, building materials, sky cover, etc. on the local thermal heating of a passive solar building. Such impacts are assessed using ful...