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Soft Computing Research Group at Intelligent Data Science and Artificial Intelligence Research Center, Universitat Politècnica de Catalunya, Barcelona, Spain

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1 Papers

The Importance of Robust and Reliable Energy Prediction Models: Next Generation of Smart Meters

Topics: Clean Energy and Power Systems; Simulation of Energy Systems

Authors: Sergio Jurado , Àngela Nebot and Francisco Mugica

Affiliation: Soft Computing Research Group at Intelligent Data Science and Artificial Intelligence Research Center, Universitat Politècnica de Catalunya, Barcelona, Spain

Digital Object Identifier: 10.5220/0009885802480254

Proceedings of SIMULTECH 2020, ISBN: 978-989-758-444-2

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In this position paper a discussion is performed related to the importance of Energy Prediction Models (EPM) in the context of trading renewable energy in smart grids and the need to develop a new generation of Smart Meters (SMs) based on edge computing. If the electricity currently produced and consumed in the low voltage is expected to grow due to installations of PVs and the electrification of the system, we need to incentivise local energy trading and provide tools to make it possible. Currently, all energy trading mechanisms in the literature heavily rely on predictions, therefore, inaccuracy would be translated in low profitability of prosumer’s investments or even worse, disappointment with the local energy markets. To guarantee robustness and reliability of predictions, we propose Flexible FIR as EPM to be used during the trading process and to integrate them in a Next Generation of SMs (NGSMs). In this document some reflections about new functionalities of NGSMs and first steps of a prototype are also addressed.