Abstract
Distributed energy resources (DERs) offer untapped potential to meet the flexibility needs of power systems with a high share of non-dispatchable renewable generation, and local flexibility markets (LFMs) can be effective mechanisms for procuring it. In LFMs, energy communities (ECs) can aggregate and offer flexibility from their members' DERs to other parties. However, since flexibility prices are only known after markets clear, flexibility bidding curves can be used to deal with this price uncertainty. Building on previous work by the authors, this paper employs a two-stage methodology to calculate flexibility bids for an EC participating in an LFM, including not only batteries and photovoltaic panels, but also cross-sector (CS) flexible assets like thermal loads and electric vehicles (EVs) to assess their impact. In Stage 1, the EC manager minimizes the energy bill without flexibility to define its baseline. In Stage 2, it computes the optimal flexibility to be offered for each flexibility price to build the flexibility bidding curve. Case examples allow to assess the impact of CS flexible assets on the final flexibility offered.

Abstract
Planning Energy communities (ECs) requires engaging members, designing business models and governance rules, and sizing distributed energy resources (DERs) for a cost-effective investment. Meanwhile, the growing share of non-dispatchable renewable generation demands more flexible energy systems. Local flexibility markets (LFMs) are emerging as effective mechanisms to procure this flexibility, granting ECs a new revenue stream. Since sizing with flexibility becomes a highly complex problem, we propose a 2-stage methodology for estimating DERs size in an EC with collective self-consumption, flexibility provision and cross-sector (CS) assets such as thermal loads and electric vehicles (EVs). The first stage computes the optimal DER capacities to be installed for each member without flexibility provision. The second stage departs from the first stage capacities to assess how to modify the initial capacities to profit from providing flexibility. The impact of data clustering and flexibility provision are assessed through a case study.

Abstract
Purpose of Review: This paper reviews the flexibility-centric value chain (FCVC) and analyses how coordinating digital platforms along the FCVC is essential for enabling FCVC activities and supporting key actors. Based on the FCVC, the digital infrastructure needed to support flexibility provision in power systems is reviewed, with special focus on the role of energy communities (ECs) as emerging relevant actors and potential aggregators of its members. Recent Findings: We review the Grid Data and Business Network (GDBN), a platform developed by the authors to support the FCVC, with special focus on those stages of the FCVC not properly supported by existing solutions. It also analyses platforms used in local flexibility markets (LFMs), and it presents the RECreation digital platform designed to manage ECs to support the participation in flexibility markets. Summary: Digital platforms are necessary for scaling flexibility services. The GDBN offers a comprehensive approach by enabling the FCVC and facilitating interoperability with existing platforms dedicated to specific segments, such as ECs and LFMs. By addressing current limitations in platform integration, this paper contributes to a clearer understanding of how digital tools can enable an efficient flexibility ecosystem. © The Author(s) 2025.

Abstract
Portugal's electricity generation relies heavily on renewable sources, which accounted for over half of the country's production in recent years. The Portuguese government has set ambitious renewable energy targets for 2030. The R3EA project (https://r3ea.web.ua.pt/pt/projeto) evaluates the impact of new investments in solar and wind energy capacity in the Centro Region of Portugal, focusing on the costs and benefits of externalities. This study examines Portugal's electricity market outcomes in terms of prices, generation mix, and emissions for different wind and solar capacities, using the National Energy and Climate Plans (NECP) of Portugal and Spain as the reference scenario. The electricity markets of both countries are modelled together, reflecting the integrated Iberian market with significant interconnections. The NECP scenario results in lower market prices and emissions, but less significantly than scenarios with lower demand and higher renewable energy share. In all scenarios, increasing renewable energy sources drives market prices down from over 200/MWh in 2022 to under 100/MWh during peak hours in 2030. Demand is the main driver of emissions, as higher demand leads to more reliance on fossil fuel plants. Lower demand scenarios in 2030 show 20 % fewer CO2 emissions per TWh than higher demand ones.

Abstract
The Renewable Energy Communities (RECs) and self-consumption frameworks defined in Directive (EU) 2023/2413 and Directive (EU) 2024/1711 are currently being integrated into national regulations across EU member states, adapting legislation to incorporate these new entities. These regulations establish key principles for individual and collective self-consumption, outlining operational rules such as proximity constraints, electricity sharing mechanisms, surplus electricity management, grid tariffs, and various organizational aspects, including asset sizing, licensing, metering, data exchange, and role definitions. This study introduces a model tailored to optimize investment and energy-sharing decisions within RECs, enabling multiple members to invest in solar photovoltaic (PV) and wind generation assets. The model determines the optimal generation capacity each REC member should install for each technology and calculates the energy shared between members in each period, considering site-specific constraints on renewable deployment. A case study with a four-member REC is used to showcase the model's functionality, with simulation results underscoring the benefits of CSC over ISC.

Abstract
Ensuring robust semantic interoperability is essential for efficient data exchange in the energy sector. This paper introduces SEMAPTIC, a lightweight framework that simplifies semantic interoperability by providing a standardized approach for attaching metadata to exchanged data. SEMAPTIC utilizes ontologies to define the meaning of data elements and employs a new structured metadata map to guide data interpretation. This approach simplifies data exchange, minimizes maintenance effort, and fosters unambiguous data understanding across heterogeneous systems. Compared to traditional methods that often require complex data transformations, SEMAPTIC offers greater flexibility and reduced overhead. The paper explores the benefits of SEMAPTIC, including simplified integration, minimal maintenance, enhanced interoperability, reduced misinterpretation, facilitated data reuse, and future-proofing. A practical example showcases how SEMAPTIC enriches a JSON data structure with semantic context without the need of modifying the original structure and without inflating data size. Finally, the importance of well-defined ontologies is emphasized, highlighting how SEMAPTIC empowers the energy sector to achieve seamless and reliable data exchange, paving the way for a more efficient and intelligent energy ecosystem. © The Institution of Engineering & Technology 2024.