Abstract
Community-based electricity markets, which are defined as groups of members that share common interests in renewable distributed generation, allow prosumers to embrace more active roles by opening up several opportunities for trading electricity. At the same time, such markets may favor conventional consumers by allowing them to choose cheaper electricity providers. Due to trends in power sector modernization, community-based electricity markets are of great research interest, and there are already some associated models. However, there is a research gap in searching for integrated and holistic approaches that go beyond economic aspects, consider social and environmental aspects, and assume the balanced co-existence of community-based and conventional markets. This work fills this critical research gap by adapting/applying the optimized tariff model, Bass diffusion model, life cycle assessment, and multi-objective optimization to the context of community-based markets. Results indicate that favoring conventional markets in the short term and community-based markets in the medium term is beneficial. Moreover, regulated tariffs should increase slightly in the short/medium-term to accommodate DG growth. Additionally, community-based markets can decrease electricity expenses by around 13.6 % considering the market participants. Thus, such markets can be significantly beneficial in mitigating energy poverty.

Abstract
Local flexibility markets are a promising solution to aid system operators in managing the network as it faces the growth of distributed resources and the resulting impacts on voltage control, among other factors. This paper presents and simulates a proposal for an intra-day local flexibility market based on grid segmentation. The design provides a market-based solution for distribution system operators (DSOs) to address near-real-time grid issues. The grid segmentation computes the virtual buses that represent each zone and the sensitivity indices that approximate the impact of activating active power flexibility in the buses within the zone. This approach allows DSOs to manage and publish their flexibility needs per zone and enables aggregators to offer flexibility by optimizing their resource portfolios per zone. The simulation outcomes allow for the assessment of market performance according to the number of zones computed and show that addressing overloading and voltage control through zonal approaches can be cost-effective and counterbalance minor errors compared to node-based approaches.

Abstract
Research around the co-location of different renewable energy technologies in offshore sites is increasing due to the potential complementarity of different sources that could decrease the power output variability, and increase reliability. However, further decrease of the power fluctuations and higher economic profitability could be achieved with energy storage. In this work, a model is developed for optimal sizing and energy management of energy storage and delivery solutions to accommodate the hybridisation of an offshore wind park. A set of options is considered for energy storage: the integration of a battery energy storage system (BESS), hydrogen production for direct sale or hydrogen/fuel cell system. For energy delivery, an expansion of the transmission cable, hydrogen pipeline or transportation by ship is evaluated. The case study used to test the model is the offshore farm WindFloat Atlantic located near the coast of Viana do Castelo, Portugal, which is proposed to be hybridised with wave energy converters (WEC). Sensitivity analyses are performed on possible components' cost variations, hydrogen shipping frequency or sale price. The results show that hydrogen production from the studied offshore hybrid park is profitable, and the transmission through submarine pipeline is competitive with electrical connections by cable. The highest profitability is achieved when pipeline and cable expansion are combined. Hydrogen transportation by ship also appears profitable, in the eventuality that additional submarine transmission facilities cannot be installed.

Abstract

Abstract
This work focuses on designing nonlinear control algorithms for dual half-bridge converters (DHBs). We propose a two-layer controller to regulate the current and voltage of the DHB. The first layer utilizes a change in the control variable to obtain a quasi-linear representation of the DHB, allowing for the application of simple linear controllers to regulate current and power flow. The second layer employs a nonlinear control allocation algorithm to select control actions that fulfill (pseudo) power setpoints specified by the first control layer; it also minimizes peak-to-peak currents in the DHB and enforces voltage balance constraints. We apply the DHB and this new control strategy to manage power flow in a hybrid energy storage system comprising of a battery and supercapacitors. Numerical simulation results demonstrate that, in comparison with state-of-the-art approaches, our control algorithm is capable of maintaining good transient behavior over a wide operating range, while reducing peak-to-peak current by up to 80%.

Abstract
The objective of this paper is to delineate the ongoing doctoral research work that is focused on the development of a digital model intended to emulate the real-Time operation of an electrolyzer that is powered by a DC/DC converter. The digital model of the converter and the proton exchange membrane (PEM) electrolyzer (EL) is presented, and it is based on an electrical equivalent model. A primary contribution of this study is the analysis of the errors resulting from the discretization process. Furthermore, the implementation and development of the digital model requires a comprehensive study of the errors and key affecting factors. Additionally, the formulation of a mechanism to reduce these errors is essential for advancing this topic. Preliminary results obtained using the digital emulator developed demonstrated its capacity to reproduce the voltage and current response applied to the electrolyzer with a reduced error compared to the continuous-Time model. © 2025 Elsevier B.V., All rights reserved.