Abstract
Hydrogen is currently getting more and more attention in the European climate strategy as a promising enabling technology to decarbonize industry, transport sector and to provide a long-term, high-capacity energy storage solution. However, to truly contribute to the reduction of CO2 emissions, hydrogen must be produced respecting a principle of additionality, to ensure that it is produced using renewable energy sources and that its production does not decrease the green energy supplied to other loads. This study tracks the share of renewables generation in the energy mix used to produce hydrogen by applying a power flow tracing technique integrated with an optimal power flow analysis. This method allows the minimization of the system operation costs, while maximizing the green hydrogen production and considering the additionality principle. The system cost function is also modified to include the sizing and allocation of conventional batteries in the grid, and assess their ability to further increase the share of green energy in hydrogen production.

Abstract
Due to the complementarity of renewable energy sources, there has been a focus on technology hybridization in recent years. In the area of hybrid offshore power plants, the current research projects mostly focus on the combinational implementation of wind, solar, and wave energy technologies. Accordingly, considering the already existing offshore wind farms, there is the potential for the implementation of hybrid power plants by adding wave energy converters and floating photovoltaics. In this work, a stochastic sizing model is developed for the hybridization of existing offshore wind farms using wave energy converters and floating photovoltaics considering the export cable capacity limitation. The problem is modeled from an investor perspective to maximize the economic profits of the hybridization, while the costs and revenues regarding the existing units and the export cable are excluded. Furthermore, to tackle the uncertainties of renewable energy generation, as well as the energy price, a scenario generation method based on copula theory is proposed to consider the dependency structure between the different random variables. Altogether, the hybridization study is modeled in a mixed integer linear programming optimization framework considering the net present value of the project as the objective function. The results showed that hybrid-sources-based energy generation provided the highest economic profit in the studied cases in the different geographical locations. Furthermore, the technical specifications of the farms have also been considerably improved providing more stable energy generation, guaranteeing a minimum level of power in a high share of the time, and with a better utilization of the capacity of the cable while the curtailment of energy is maintained within the acceptable range.

Abstract
The European Union is pushing its members states to implement regulations that incentivize distribution system operators to procure flexibility to enhance grid operation and planning. Since flexibility should be obtained using market-based solutions, when possible, flexibility market platforms become essential tools to harness consumer-side flexibility, supporting its procurement, trading, dispatch, and settlement. These reasons have led to the appearance of multiple flexibility market platforms with different structure and functionalities. This work provides a comprehensive description of the main flexibility platforms operating in Europe and provides a concise review of the platform main characteristics and functionalities, including their user segment, flexibility trading procedures, settlement processes, and flexibility products supported.

Abstract
Nowadays, human operators at control centers analyze a large volume of alarm information during outage events and must act fast to restore the service. To assist operator decisions this work proposes novel machine learning-based functions aiming to: (a) classify the complexity of a fault occurrence (Occurrences Classifier) and its cause (Fault Cause Classifier) based on its alarm events; (b) provide fast insights to the operator on how to solve it (Data2Actions). The Occurrences Classifier takes alarm information of an occurrence and classifies it as a simpleor complexoccurrence, while the Fault Cause Classifier predicts the cause class of MV lines faults. The Data2Actions takes a sequence of alarm information from the occurrence and suggests a more adequate sequence of switching actions to isolate the fault section. These algorithms were tested on real data from a Distribution System Operator and showed: (a) an accuracy of 86% for the Data2Actions, (b) an accuracy of 68% for the Occurrences Classifier, and (c) an accuracy of 74% for the Fault Cause Classifier. It also proposes a new representation for SCADA event log data using graphs, which can help human operators identify infrequent alarm events or create new features to improve model performance.

Abstract
This paper proposes an original framework for a flexibility-centric value chain and describes the pre-specification of the Grid Data and Business Network (GDBN), a digital platform to provide support to the flexibility value chain activities. First, it outlines the structure of the value chain with the most important tasks and actors in each activity. Next, it describes the GDBN concept, including stakeholders' engagement and conceptual architecture. It presents the main GDBN services to support the flexibility value chain, including, matching consumers and assets and service providers, assets installation and operationalization to provide flexibility, services for energy communities and services, for consumers, aggregators, and distribution systems operators, to participate in flexibility markets. At last, it details the workflow and life cycle management of this platform and discusses candidate business models that could support its implementation in real-life scenarios.

Abstract
The deployment of energy communities (EC) will foster new business models contributing to the decentralization and democratization of energy access and a reduction in the energy bill of final consumers. This decentralization is only possible if investments are made in production and storage technologies, that must be installed near the locals of consumption, according to common rules of the regulatory frameworks of EC. In this paper we propose a methodology for the optimal sizing of production and shared storage assets, and we assess the cost reduction of considering shared storage assets. We then formulate seven business models (BM) that dictate how to share this benefit among the EC members, and we propose two indicators to assess them. Results show the difficulty in choosing a BM as well as the limitations of the BM and of the indicators.