Abstract
This paper describes a study that sought to analyse the impact of an active demand response on the frequency stability of the Iberian Peninsula for operation scenarios extending to 2040. For that purpose, one developed dynamic models for primary and secondary frequency control provision from demand-side resources, namely Electric Vehicles (EV), thermostatically controlled loads (TCL), and electrolysers. Those models were developed under a Matlab/Simulink environment, and added to a two-area control model representative of the Iberian Peninsula interconnected to the CESA area. Then, one ran simulations of reference disturbances (loss of a large generator or distributed generation) in the developed platform, once it was fully implemented.

Abstract
Assessing the societal contributions of research is not simple, especially for research projects that produce outputs with low technology readiness level. This paper analyses the potential societal impacts of research resulting in technologies with low maturity, but with the potential to be further developed in the long-term. It uses the case of the ESGRIDS (Enhancing Smart Grids for Sustainability) collaborative research project and its outputs aimed at enhancing smart grids for sustainability. Data was collected from the four participant research teams through two sequential questionnaires about technologies' state of development and expected long-term societal effects. Among the main results, we underscore the influence of individual perceptions and organisational contexts over the process of eliciting future developments. The analysis of technologies' status, barriers for market uptake, and potential future developments was translated into a technology roadmap, which outlined the time-dimension for technology maturity evolution and implementation impacts. The technologies developed within the ESGRIDS project can contribute to support consumers' energy decision-making and to encourage them to have a more active role in the electricity market. Those technologies can also create job opportunities associated with the development of new products and services, and contribute to mitigating climate change by promoting the use of renewable energies thus reducing carbon dioxide emissions, in addition to contributing to energy cost reduction by optimizing the use of supply and demand resources. Future research avenues point towards a methodology that can be used for assessing the potential impacts of research projects with low technology readiness outputs.

Abstract
Taking advantage of the flexibility of Distributed Energy Resources (DER) can help improve distribution network efficiency, reliability and resilience. EUniversal project aims to facilitate the use of flexibility services and interlink active system management of distribution system operators with electricity markets. congestion management and voltage control have been identified has the most relevant needs, within different operation timeframes, namely: from day, weeks and years ahead. This paper considers long-term flexibility services to support maintenance actions, increasing the periods where is technically possible to perform maintenance actions maintaining security of operation. The methodology developed to schedule planned maintenance actions based on forecasted network profiles, maintenance costs, network reconfiguration capability and flexibility contracted in long-term flexible markets will be presented. © The Institution of Engineering and Technology 2023.

Abstract
The increasing integration of renewable energy sources (RES) at different voltage levels of the distribution grid has led to technical challenges, namely voltage and congestion problems. Conversely, the integration of new Distributed Energy Resources (DER) provides the necessary flexibility to accommodate higher RES integration levels. This work describes the development of innovative functional modules, based on optimal power flow calculations and grid forecasting, dedicated to the predictive management of the distribution grid considering DER flexibility, which are integrated into a commercial SCADA/DMS solution. © The Institution of Engineering and Technology 2023.

Abstract
This article presents original probabilistic forecasting models for day-ahead hourly energy generation forecasts for a photovoltaic (PV) plant, based on a semi-parametric approach using three deterministic forecasts. Input information of these new models consists of data of hourly weather forecasts obtained from a Numerical Weather Prediction model and variables related to the sun position for future instants. The proposed models were satisfactorily applied to the case study of a real-life PV plant in Portugal. Probabilistic benchmark models were also applied to the same case study and their forecasting results compared with the ones of the proposed models. The computer results obtained with these proposed models achieve better point and probabilistic forecasting evaluation indexes values than the ones obtained with the benchmark models. (c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under theCCBY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Abstract
Low voltage (LV) grids face a challenge of effectively managing the growing presence of new loads like electric vehicles and heat pumps, along with the equally growing installation of rooftop photovoltaic panels. This paper describes practical applications of sensitivity factors, extracted from smart meter data (i.e., without resorting to grid models), to i) link voltage problems to different costumers/devices and their location in the grid, ii) manage the flexibility provided by distributed energy resources (DERs) to regulate voltage, and iii) assess favorable locations for DER capacity extensions, all with the aim of supporting the decision-making process of distribution system operators (DSOs) and the design of incentives for customers to invest in DERs. The methods are tested by running simulations based on historical meter data on six grid models provided by the EU-Joint Research Center. The results prove that it is feasible to implement advanced LV grid analysis and management tools despite the typical limitations in its electrical and topological characterisation, while avoiding the use of computationally heavy tools such as optimal power flows.