Identifying services for short-term load forecasting using data driven models in a Smart City platform. (January 2017) - Massana, Joaquim; Pous, Carles; Burgas, Llorenç; Melendez, Joaquim; Colomer, Joan
Abstract : Highlights: A framework to support monitoring procedures in Smart Cities is defined. Several services are identified according to the layers architecture. A short-term load forecasting in non-residential buildings use case is provided. The short-term load forecasting method is based on an AR model. The work is based on a real data of the University of Girona. Abstract: The paper describes an ongoing work to embed several services in a Smart City architecture with the aim of achieving a sustainable city. In particular, the main goal is to identify services required in such framework to define the requirements and features of a reference architecture to support the data-driven methods for energy efficiency monitoring or load prediction. With this object in mind, a use case of short-term load forecasting in non-residential buildings in the University of Girona is provided, in order to practically explain the services embedded in the described general layers architecture. In the work, classic data-driven models for load forecasting in buildings are used as an example.