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Building's energy demand is influenced by many factors, such as: weather conditions, building structure and characteristics, energy consumption of components (lighting and HVAC systems), level of occupancy and user's behavior. As consequence of multi-variable impact on building's energy consumption, theoretical models based on first principles are not able to forecast actual energy demand of a generic...
An innovative decision support and energy management system (DSEMS) for residential applications is proposed in this paper. The DSEMS is represented as a finite state machine and consists of a series of scenarios that may be selected according to the user preferences. The designing and testing methods are described. These may be used in order to verify its effectiveness both in terms of continuity...
Most advantages that the smart grid will bring derive from its capability of improving reliability performance and customers’ responsiveness and encouraging greater efficiency decisions by the costumers. Demand side management is, therefore, considered as an integral part of the smart grid and one of the most important methods of energy saving. Accordingly, an innovative decision support and energy...
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