Abstract
This paper deals with cost-effective strategies for controlling indoor temperature using different technologies, including inverter-based and thermostatic control systems. In this regard, the indoor temperature control model incorporates instant heat loss coefficient, heat transfer capability, and heat energy conversion coefficient. The decision variable is the power setpoint of the energy conversion system, which can be operated in both cooling and heating modes. The thermal system coefficients have been estimated based on historical data for energy consumption, indoor, and outdoor temperatures of the case study presented, which are the minimal datasets required for the coefficient estimation. The inverter-based model benefits from the quasi-continuous power consumption model, while the thermostatic model has a hysteresis functionality resulting in discrete power consumption with several turn-on and turn-off modes, which can be controlled by changing the thresholds. The flexible thermal range resulted in 4.715% and 6.235% cost reductions for thermostat-based and inverter-driven heat pumps, respectively. © 2025 Elsevier B.V., All rights reserved.

Abstract
Volatility in energy prices, alongside the European Commission's decarbonization strategy, has led to reforming the European electricity market and the creation of a hydrogen strategy. Hydrogen and electricity have a symbiotic relationship: hydrogen production through electrolysis relies on electricity, while its production provides flexibility to the power system utilizing renewable energy surpluses. This research provides a joint electricity and hydrogen market model based on Cournot equilibrium, solved with an equivalent optimization problem, incorporating contracts for both goods. Results for the MIBEL show that contracts increase market competition, reduce prices, and enhance renewable energy utilization. Wholesale electricity and hydrogen prices decrease by 10 % and 8 %, respectively, while electrolytic hydrogen production rises by 10 %. Profits increase by over 20 %, with the hydrogen sector doubling its gains. The model also identifies contract prices that ensure profitability and emissions reduction. These findings highlight the potential of PPAs and HPAs to support energy transition goals.

Abstract
The recent updates of the National Energy and Climate Plans (NECPs) for Portugal and Spain have some significant changes compared to the previous 2019 versions, especially for the Portuguese side where a greater demand and renewable generation capacity are foreseen. This work assesses the impact of these new plans on the Iberian electricity market (MIBEL) main outcomes using CEVESA market model. Simulation results allow the analysis of the expected generation mix and prices, CO2 emissions, system cost, system adequacy, interconnections capacity usage, H2 demand impact and its contribution to provide balancing flexibility, under different simulation scenarios.

Abstract
The mobility sector is expected to significantly impact the power system by deploying battery electric vehicles (BEV) and fuel cell vehicles (FCEV). This work improves CEVESA, a market model for the long-term planning and operation of the Iberian Electricity Market, by modelling FCEV as an alternative to BEV and internal combustion vehicles (ICEV), and its impact on the H-2 demand and storage. The mobility and H-2 economy models interact with the power system through the electricity needs and price. CEVESA is then applied to estimate potential expansion paths of ICEV, BEV and FCEV mobility alternatives considering the total system costs and the EU decarbonization strategy. The findings suggest that if FCEVs technology matures, it could rival BEVs, offering greater system flexibility via electrolyzers and extended driving ranges for users.

Abstract
This paper presents a Local Energy Market (LEM) model based on Walrasian Auctions for near real-time energy trading among peers in an Energy Community. The market operates with minimal information exchange, where peers only indicate trade decisions and quantities. The auctioneer updates prices iteratively to balance supply and demand. Two core algorithms support the LEM: (1) the Auctioneer Price Decision Algorithm, which adjusts prices based on past imbalances, and (2) a real-time bidding optimization algorithm, which optimizes peers' energy dispatch and local energy trading decisions based on expected demand, generation, storage, and opportunity costs of external trading. This work details the design and implementation of the bidding optimization algorithm and evaluates its performance through simulations. The results compare the LEM to a centralized pool-based market and individual optimizations, assessing its efficiency and imbalance control. The findings support the development of innovative and decentralized energy markets and smart grid applications.