Springer Smart Meters: Artificial Intelligence to Support Proactive Management of Energy Consumption: 97 (Lecture Notes in Energy, 97)

This book describes how equipping buildings with smart meters is essential to improve the prediction of energy costs within smart grids and to help end-users optimize their energy consumption. The book reports on the results of the European Upper Rhine INTERREG project SMI (www.smi.uha.fr), which connects artificial intelligence and micro-societal analysis. It is multidisciplinary and addresses the following aspects: social, legal, environmental, and technical. One of the critical factors for the transition to clean energy is the flexibility of the power grid. A flexible grid requires a constant flow of data about the network and its demand, on the other hand, clients who produce electrical power can be an active part of the demand response if they are informed about the power needs of their appliances. “If you cannot measure it, you cannot improve it.” This common management saying also holds true for the area energy efficiency. Without a clear understanding of their energy usage, consumers are unable to take steps to reduce their consumption. A new intelligent tool is presented that is more efficient, safe, and acceptable to consumers. Thus, users of this intelligent tool will be able to collect and predict the consumption of their electrical appliances. At the same time, the consumption information is anonymized before being relayed to the energy supplier. In parallel, new techniques will be evaluated to improve the security level of the smart meter in a highly heterogeneous network.