Flexigy Smart-grid Architecture Tiago Fonseca 1 a , Luis Lino Ferreira 1 b , Lurian Klein 2 c , Jorge Landeck 3 d and Paulo Sousa 1 e 1 School of Engineering of the Polytechnical Institute of Porto, Porto, Portugal 2 Cleanwatts, MIT Portugal Programme, Energy for Sustainability Initiative, Coimbra, Portugal 3 Univ. Coimbra, LIBPhys, Department of Physics, Coimbra, Portugal Keywords: Internet of Things, System Architecture, Energy, Demand-side Flexibility, Renewable Energy Community. Abstract: The electricity field is facing major challenges in the implementation of Renewable Energy Sources (RES) at a large scale. End users are taking on the role of electricity producers and consumers simultaneously (prosumers), acting like Distributed Energy Resources (DER), injecting their excess electricity into the grid. This challenges the management of grid load balance, increases running costs, and is later reflected in the tariffs paid by consumers, thus threatening the widespread of RES. The Flexigy project explores a solution to this topic by proposing a smart-grid architecture for day-ahead flexibility scheduling of individual and Renewable Energy Community (REC) resources. Our solution is prepared to allow Transmission System Operators (TSO) to request Demand Response (DR) services in emergency situations. This paper overviews the grid balance problematic, introduces the main concepts of energy flexibility and DR, and focuses its content on explaining the Flexigy architecture. 1 INTRODUCTION The adoption of Renewable Energy Sources (RES) like wind and solar is growing at a significant rate, with the annual installed capacity growing almost 45% in 2020 (International Energy Agency, 2021). The prices for installing solar photovoltaic (PV) panels keep dropping, household systems are now capable of injecting their self-production surplus into the grid (SEIA, 2021), hence owners become producers and consumers – (prosumers). The high penetration of RES into power grids results in difficulties maintaining the necessary grid balance. As a result, over the course of the day, the grid energy demand generates a duck-shaped energy consumption curve which highlights the increasingly problematic grid unbalance phenomenon happening with the increase of PV installations (CAISO, 2013). Figure 1 illustrates the duck-shaped energy consumption curve in California on the 31 st of March a https://orcid.org/0000-0002-5592-3107 b https://orcid.org/0000-0002-5976-8853 c https://orcid.org/0000-0003-4666-9722 d https://orcid.org/0000-0003-4666-9722 e https://orcid.org/0000-0002-4478-1000 throughout several years; it represents the total energy consumption minus the energy input from solar generation. The imbalance between peak demand (at 21:00) and its minimum (at 14:00) is due to the peak production from PV panels. This is particularly problematic since conventional power plants require long periods to start or stop producing energy. Figure 1: Energy consumption curve (CAISO, 2013). 176 Fonseca, T., Ferreira, L., Klein, L., Landeck, J. and Sousa, P. Flexigy Smart-grid Architecture. DOI: 10.5220/0010918400003118 In Proceedings of the 11th International Conference on Sensor Networks (SENSORNETS 2022), pages 176-183 ISBN: 978-989-758-551-7; ISSN: 2184-4380 Copyright c  2022 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved