Abstract
This paper analyzes the activation of the manual balancing reserve of the Portuguese system and its prices for the period 2015-2017. Standard, logistic and LASSO regression models, causal analysis based on Bayesian networks and random forests are applied. Results show that the variables that better explain the activation of the manual reserve are the imbalances of both renewable generation and demand, but surprisingly forecasted with persistence models based on the last verified measurements (available 15 minutes before the reserve activation), instead of using more elaborated models based on production forecasts. Prices, however, are harder to explain suggesting the need for additional information, such as bidding prices not used in this study.

Abstract
This paper presents how the InterConnect project is enhancing the relationship between smart buildings, energy communities and grids, enabling the potential of interoperable flexibility mechanisms and the offer of new energy and non-energy services. Within this framework DSO will leverage its role of neutral market facilitator acting as key enabler for new business models. The paper presents the first technical definition of the DSO Interface of the H2020 InterConnect project that will ensure interoperable integration of flexibility services between DSOs and the different market parties to support the grid operation towards an increasingly decentralized, digitalized and decarbonized electric system. © 2021 The Institution of Engineering and Technology.

Abstract
As AI algorithms thrive on data, SCADA would be considered a natural ground for Artificial Intelligence (AI) applications to be developed, translating that avalanche of information into meaningful and fast insights to human operators. However, presently, the high complexity of the events, the data semantics, the large variety of equipment and technologies translate into very few AI applications developed in SCADA. Aware of the enormous potential yet to be explored, E-REDES partnered with INESC TEC to experiment on the development of two novel AI applications based on SCADA data. The first tool, called Alarm2Insights, identifies anomalous behaviours regarding the performance of the protection functions associated with HV and MV line panels. The second tool, called EventProfiler, uses unsupervised learning to identify similar events (i.e., with similar log messages) in HV line panels, and supervised learning to classify new events into previously defined clusters and detect unique or rare events. Aspects associated to data handling and pre-processing are also discussed. The project's results show a very promising potential of applying AI to SCADA data, enhancing the role of the operator and support him in doing better and more informed decisions. © 2021 The Institution of Engineering and Technology.

Abstract
Electricity systems around the world are decarbonizing, driven by reductions in the cost of renewable energy and encouraged by supportive regulatory policy. Electricity market designs are increasingly being tested to ensure that the bulk power system can deliver reliable, cost-effective energy to all consumers.

Abstract

Abstract
Flexibility is key for the decarbonization of the energy sector, contributing to decrease uncertainty in the operation of distribution networks, due to the connection of renewable energy sources and electric vehicles. However, effective deployment requires interoperable and replicable solutions, technologically agnostic and independent from the role of each actor and market models adopted. This paper presents an overview of ongoing projects that aim to deliver and demonstrate interoperable solutions across the full value chain of the energy sector. The main objective and expected results of the H2020 InterConnect, EUniversal and OneNet projects will be presented. © 2021 The Institution of Engineering and Technology.