Search

This paper proposes a novel Case Based Reasoning (CBR) application for intelligent management of energy resources in residential buildings. The proposed CBR approach enables analyzing the history of previous cases of energy reduction in buildings, and using them to provide a suggestion on the ideal level of energy reduction that should be applied in the consumption of houses. The innovations of the proposed CBR model are the application of the k -Nearest Neighbors algorithm (k-NN) clustering algorithm to identify similar past cases, the adaptation of Particle Swarm Optimization (PSO) meta-heuristic optimization method to optimize the choice of the variables that characterize each case, and the development of expert systems to adapt and refine the final solution. A case study is presented, which considers a knowledge base containing a set of scenarios obtained from the consumption of a residential building. In order to provide a response for a new case, the proposed CBR application selects the most similar cases and elaborates a response, which is provided to the SCADA House Intelligent Management (SHIM) system as input data. SHIM uses this specification to determine the loads that should be reduced in order to fulfill the reduction suggested by the CBR approach. Results show that the proposed approach is capable of suggesting the most adequate levels of reduction for the considered house, without compromising the comfort of the users. [ABSTRACT FROM AUTHOR]

In the UK, heating systems in the built environment consume a substantial proportion of its total energy and are responsible for about 25% of the total carbon emission. A similar pattern is also exhibited in many other European countries. Despite the enormous effort made over the last decades to improve the energy efficiency of these heating systems, a huge potential for further energy saving still persists. This paper investigates the potential for energy saving in heating systems that can be achieved through improving boiler controls. This investigation was carried out through surveys, simulation and experimental study. Through the surveys, typical boiler control schemes widely used in current practice were identified. The performance of some systems surveyed was monitored through the survey. The data obtained is used to demonstrate the problems associated with the control of boilers in heating systems. These typical control schemes identified through surveys were studied using a simulator that had been rigorously validated. An experiment was carried out to demonstrate how the overall performance of a heating system could be improved by using a better boiler controller. The result shows that improving boiler controls can lead to up to 20% of energy saving and a significant improvement in thermal comfort. [Copyright &y& Elsevier]