Usability evaluation of a web-based tool for supporting holistic building energy management

This paper presents the evaluation of the level of usability of an intelligent monitoring and control interface for energy efficient management of public buildings, called BuildVis, which forms part of a Building Energy Management System (BEMS.) The BEMS ‘intelligence’ is derived from an intelligent algorithm component which brings together ANN-GA rule generation, a fuzzy rule selection engine, and a semantic knowledge base. The knowledge base makes use of linked data and an integrated ontology to uplift heterogeneous data sources relevant to building energy consumption. The developed ontology is based upon the Industry Foundation Classes (IFC), which is a Building Information Modelling (BIM) standard and consists of two different types of rule model to control and manage the buildings adaptively. The populated rules are a mix of an intelligent rule generation approach using Artificial Neural Network (ANN) and Genetic Algorithms (GA), and also data mining rules using Decision Tree techniques on historical data. The resulting rules are triggered by the intelligent controller, which processes available sensor measurements in the building. This generates ‘suggestions’ which are presented to the Facility Manager (FM) on the BuildVis web-based interface. BuildVis uses HTML5 innovations to visualise a 3D interactive model of the building that is accessible over a wide range of desktop and mobile platforms. The suggestions are presented on a zone by zone basis, alerting them to potential energy saving actions. As the usability of the system is seen as a key determinate to success, the paper evaluates the level of usability for both a set of technical users and also the FMs for five European buildings, providing analysis and lessons learned from the approach taken

Design and Implementation of Fuzzy Controller for Non-Linear Thermally Insulated MIMO Greenhouse Building Utilizing Weather Conditions and Ground Temperature

The increased demand of electricity and water consumption for cooling and heating processes together with the continuous increase in earth temperature due to greenhouse gases emission urged the utilization of sustainable, affordable and clean energy resources. Globally, the biggest amount of water is consumed for agricultural purposes. Domestically, in Abu Dhabi Emirate, the agriculture sector consumes over 50% of the supplied water. Part of this consumption is due to the evaporative cooling approach that is typically used in cooling greenhouses. This approach utilizes a large amount of water and energy to maintain the greenhouse temperature within the desired range. Ground Heat-Exchanger is an environmentally-friendly solution used for heating or cooling applications. It is based on seasonal temperature difference between the ground and the ambient which varies with depth. As depth of ground increases, the temperature fluctuation decreases because of the soil high thermal inertia and the time lag in temperature fluctuation between the surface and the ground. The aim of this thesis is to design a control system using fuzzy logic controller to study the feasibility of utilizing weather conditions and soil temperature in cooling or heating processes of a special type of greenhouses. The proposed control system takes a decision of either utilizing the outside weather conditions or using the soil temperature. The study is conducted on a thermally insulated greenhouse system equipped with ground-to-air heat exchanger, actuated windows, fans, and sensors and the proposed controller performance is compared to a logical and conventional ON/OFF controllers. Results show the proposed control system is capable of maintaining the greenhouse temperature within the desired range for most of the day hours in winter utilizing only the weather and soil temperatures. However, when the temperature is extremely hot, especially in summer, the ground heat exchanger can be only used for pre-cooling with a capability of reducing the ambient temperature of about 6ºC on average. In such extremely hot periods, an auxiliary cooling unit has to be deployed for further cooling. In addition, results reveal that fuzzy controller consumes less power than the logical and the ON/OFF controller when operating the system actuators