Abstract
Current residential electricity tariffs often combine a flat energy price with a fixed charge linked to contracted power, resulting in electricity bills that are weakly responsive to changes in consumption. This lack of proportionality reduces incentives for energy savings and may undermine demand-side efficiency.This paper proposes a novel Power-Conditioned Pricing (PCP) tariff, in which unit energy prices depend on the power level at which electricity is consumed. By associating higher prices with higher consumption intensity, the proposed tariff introduces progressivity while preserving transparency and regulatory feasibility. The tariff is calibrated to ensure revenue neutrality with respect to the current tariff for each contracted power level.Two complementary calibration strategies are analysed: a profile-based approach using representative regulatory load profiles, and an empirical approach based on statistical distributions derived from real consumer data. To assess consumer responsiveness, electricity bills are evaluated under both vertical and horizontal consumption adjustment models.Results show that bill elasticity increases from values between 0.43–0.73 under the current tariff to values close to unity under PCP, while maintaining revenue neutrality across contracted power levels. These findings suggest that power-conditioned pricing constitutes a promising alternative to current residential tariff structures, better aligned with energy-efficiency and conservation objectives.

Abstract
The European Union Internal Electricity Market is undergoing major reforms to support the transition to a fully decarbonized energy system by 2050, where non-dispatchable renewable energy sources play a central role. To enhance market efficiency, renewable energy sources integration, and power system balancing, the European Union promotes increased cross-border interconnection and cooperation among Member States. This paper reviews existing literature and market models addressing multi-zone interconnection capacity allocation and proposes a novel inter-zonal co-optimization mechanism for the joint allocation of energy and automatic balancing reserve capacity based on system cost minimization. Unlike previous approaches that treat energy and reserve coordination separately or sequentially, this study introduces a unified optimization framework that captures the interdependencies of intra-and inter-zonal dispatch. The proposed mechanism is implemented within the CEVESA market model and applied to a realistic Iberian case study, assessing its economic and operational impacts under varying interconnection capacity scenarios. Results show that while energy coordination alone achieves significant cost reductions, joint coordination of energy and reserves delivers further efficiency gains, reduces reserve price volatility, and enhances cross-border system flexibility.

Abstract
The expected development and massification of Local Energy Markets (LEM), in particular the ones associated with Renewable Energy Communities, poses new challenges, and requires new operations strategies to their promoters, aggregators, and end-consumers. One of the mechanisms that can be used to speed up the spreading of this kind of market is the use of Demand Response (DR) programs since they can be designed to increase the community's savings and profits. In this framework, the end customers are induced to change their normal consumption patterns by temporarily reducing and/or shifting their electricity consumption away from periods with low local generation in response to a signal from a service provider, i.e., aggregator. To this purpose, this paper presents an Agent Based Model (ABM) using the Q-Learning mechanism to implement and to simulate a LEM and its interaction with the Wholesale Market (WSM), using also and incentive-based DR program. The overall objective of this design is to decrease average energy costs by moving the demand to periods of large availability of wind or solar resources or to store energy for future use. The developed model was tested considering real data regarding energy consumption and PV generation. The proposed paper describes and discusses the obtained market strategy and the profits that can be obtained with this approach.

Abstract
Reducing the gap between renewable energy needs and supply is crucial to achieve sustainable growth. Hydroelectric power production predictions in several Madeira Island catchment regions are shown in this article using Long Short-Term Memory, LSTM, networks. In order to foresee hydro reservoirs inflows, our models take into account the island's dynamic precipitation and flow rates and simplify the process of water moving from the cloud to the turbine. The model developed for the Socorridos Faja Rodrigues system demonstrates the proficiency of LSTMs in capturing the unexpected flow behavior through its low RMSE. When it comes to energy planning, the model built for the CTIII Paul Velho system gives useful information despite its lower accuracy when it comes to anticipating problems.

Abstract
The member states of the European Union (EU) are actively reassessing their National Energy and Climate Plans (NECPs) [1] to jointly address climate challenges and the impacts of the COVID pandemic and gas supply crisis. This study extends the analyses described in [2] by assessing the impact of the updated NECP drafts for Portugal and Spain [3], [4] on the Iberian Electricity Market (MIBEL). For this, we use CEVESA, a market model for the long-term planning and operation of MIBEL that computes the joint dispatch of energy and secondary reserve of the two interconnected single-price zones. Departing from the expected evolution of the electricity generation technologies and demand available in the NECP drafts, joint scenarios for Portugal and Spain are built with the latest CO2 allowances and fuel prices projections and the latest available historical data of hydro and renewable generation profiles. Simulations provide estimates for the expected market prices, technology generation dispatch, and the usage of the capacity of the interconnection lines between both countries, highlighting potential concerns and knowledge on future NECPs.