Abstract
This paper proposes a novel probabilistic model for quantifying the impact of demand flexibility (DF) on the long-term generation system adequacy via Sequential Monte Carlo Simulation (SMCS) method. Unlike load shedding, DF can be considered an important instrument to postpone bulk consumption from periods with limited reserves to periods with more generating capacity available, avoiding load shedding and increasing the integration of variable renewable generation, such as wind power. DF has been widely studied in terms of its contribution to the system's social welfare, resulting in numerous innovative approaches ranging from the flexibility modeling of individual electric loads to the definition of aggregation strategies for optimally deploying this lever in competitive markets. To add to the current state-of-the-art, a new model is proposed to quantify DF impact on the traditional reliability indices, such as the Loss of Load Expectation (LOLE) and the Expected Energy Not Supplied (EENS), enabling a new perspective for the DF value. Given the diverse mechanisms associated with DF of different consumer types, the model considers the uncertainties associated with the demand flexibility available in each hour of the year and with the rebound effect, i.e., the subsequent change of consumption patterns following a DF mobilization event. Case studies based on a configuration of the IEEE-RTS 79 test system with wind power demonstrate that the DF can substantially improve the reliability indices of the static and operational reserve while decreasing the curtailment of variable generation cause by unit scheduling priorities or by short-term generation/demand imbalances.

Abstract
This paper investigates the contribution of hydrogen electrolysers (HEs) for frequency related Ancillary Services (AS), namely Frequency Containment Reserve (FCR), Synthetic Inertia (SI) , Fast Frequency Response (FFR) in future operation scenarios in the Iberian Peninsula (IP) considering low system iner-tia. The proposed framework for analysis consists of a dynamic model developed in MATLAB/Simulink. Simulations show that an instantaneous inverter based resource (IBR) trip induced by a grid fault may lead to the occurrence of values of Rate of Change of Frequency (RoCoF) close to undesirable thresholds if the FCR is provided solely by the conventional generators. The obtained results illustrate that HEs can outperform conventional generators on the provision of FCR. Furthermore, the FCR is unable to unlock the full potential of fast responding HEs. This suggests the advantage of providing additional AS such as SI or FFR in critical periods. Simulations also show that the benefit of additional AS can be limited in specific conditions, especially depending on the evolution of HEs' ramping capabilities, but are still a relevant complement to other solutions designed to deal with low inertia in power systems such as synchronous compensators.& COPY; 2023 Elsevier Ltd. All rights reserved.

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
The replacement of fossil fuel power plants by variable renewable energy sources is reducing the flexibility of the energy system, which puts at risk its security. Exploiting the flexibility of distributed multi-energy resources through aggregators presents a solution for this problem. In this context, this paper presents a new hierarchical model predictive control framework to assist multi-energy aggregators in the network-secure delivery of multi-energy services traded in electricity, natural gas, green hydrogen, and carbon markets. This work builds upon and complements a previous work from the same authors related to bidding strategies for day-ahead markets - it closes the cycle of aggregators' participation in multi-energy markets, i.e., day-ahead bidding and real-time activation of flexibility services. This new model predictive control framework uses the alternating direction method of multipliers on a rolling horizon to negotiate the network-secure delivery of multi-energy services between aggregators and distribution system operators of electricity, gas, and heat networks. We used the new model predictive control framework to conduct two studies. In the first study, we found that considering multi-energy network constraints at both day-ahead and real-time optimization stages produces the most cost-effective and reliable solution to aggregators, outperforming state-of-the-art approaches in terms of cost and network security. In the second study, we found that the adoption of a green hydrogen policy by multi-energy aggregators can reduce their consumption of natural gas and respective CO2 emissions significantly if carbon and green hydrogen prices are competitive.& COPY; 2023 Elsevier Ltd. All rights reserved.

Abstract
In isolated power systems with very high instantaneous shares of renewables, additional inertia should be used as a complementary resource to battery energy storage systems (BESSs) for improving frequency stability, which can be provided by synchronous condensers (SCs) integrated into the system. Therefore, this paper presents a methodology to infer the system dynamic security, with respect to key frequency indicators, following critical disturbances. Of particular interest is the evidence that multiple short-circuit locations should be considered as reference disturbances regarding the frequency stability in isolated power grids with high shares of renewables. Thus, an artificial neural network (ANN) structure was developed, aiming to predict the network frequency nadir and Rate of Change of Frequency (RoCoF), considering a certain operating scenario and disturbances. For the operating conditions where the system frequency indicators are violated, a methodology is proposed based on a gradient descent technique, which quantifies the minimum amount of additional synchronous inertia (SCs which need to be dispatch) that moves the system towards its dynamic security region, exploiting the trained ANN, and computing the sensitivity of its outputs with respect to the input defining the SC inertia.

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.