The integration of European electricity markets and ancillary services (ASs) is a crucial step toward establishing a unified, efficient, and resilient European energy system. This paper reviews the evolution of European initiatives aimed at harmonizing electricity markets and AS mechanisms, focusing on regulatory frameworks that facilitate cross-border energy exchange and enhance system reliability. Key developments in market coupling, such as single day-ahead and intraday trading platforms, and efforts to unify ASs, including frequency containment and balancing services, are analyzed. The study highlights both progress made and persistent challenges to achieving full integration. The conclusions emphasize the need for regulatory alignment, coordinated action among Transmission System Operators (TSOs), and continued technological advancement to support the EU’s decarbonization and sustainability objectives.

As a consequence of the continuous growth being experienced by renewable energy systems, the role of the different ancillary services is becoming essential for the reliable operation of the electric system. This paper develops a methodology for estimating the secondary reserve marginal band price in the Iberian electricity market using four forecasting techniques: two classical models (ARIMAX and SARIMAX) and two machine learning models (Random Forest and Support Vector Regression). The methodology involves a Pearson correlation analysis and a Sequential Forward Selection algorithm to select the relevant model inputs and exogenous variables. A statistical data analysis is conducted to examine the temporal characteristics of the target variable and a data-preprocessing is performed for the proper implementation of the models. A grid search and a sequential division cross-validation are applied to determine the optimal parameters of the models. The performance is evaluated using three statistical metrics. The results show that the Random Forest model outperforms the other models, achieving the lowest MAE (2.40 €/MW) and RMSE (3.40 €/MW) values.

This paper presents a solution to the challenging problem of estimating the state of charge (SOC) of batteries using a Kalman filter algorithm. The algorithm requires knowledge of the dynamical model and its parameters, along with the covariance matrices associated with measurement noise, process noise, and initial estimation error. However, determining the values for the process noise and initial estimation error matrices is often difficult. To address this issue, we propose a novel method to tune these matrices based on a new tuning parameter, the measurement noise variance, and the expected slope of the open circuit voltage vs. state of charge curve. We demonstrate the effectiveness of the proposed approach through extensive simulations involving various batteries and operating conditions in an electrical driving scenario. We assess the performance of the Kalman filter estimation under noisy environments, wrong initial conditions, and modeling errors, obtaining dimensionless performance indices that quantify its behavior. By analyzing the simulation results, we establish a general design procedure for the process covariance matrix, where the user only needs to set the desired limits for the state of charge error in noisy environments and the convergence time under wrong initializations. This design procedure is applicable to batteries of any type, sampling period, or measurement noise level, providing a practical and efficient solution for accurate state of charge estimation

This work analyses the minimum energy capacity requirements to be demanded to battery energy storage systems used in megawatt-range merchant solar PV plants to grant capacity firming. The operation of such a plant is simulated (with a 2-minute time step, at three different locations of the Iberian Peninsula, and for different battery sizes) after solving a quadratic programming optimization problem. The control algorithm takes into account the irradiance forecast and the intraday electricity market configuration, which presents certain peculiarities in the Iberian region with regard to other European markets. The analysis has been performed in an annual basis and current irradiance measured values have been used.

this paper analyzes the ageing experienced by six different types of batteries used into a large scale grid-connected PV plant that participates in the electricity market and, therefore, has to generate the energy in a controlled way in order to cope with the hourly-production bids matched in the market and minimize deviations since these imply economic penalties. Due to the inherent variability of the PV production, the batteries will assure this controllability goal. The work presented performs a systematic analysis throughout one whole year of operation and uses the rain flow counting algorithm in order to determine the number of cycles experienced by the batteries. Finally, using the cycling capacity curves provided by the battery manufacturers', the total ageing suffered in one year of operation as well as the life expectancies of the batteries are calculated. All the analyses conducted in this paper are based on actual data recorded from an operative PV power plant and use verified models.

VSC-HVDC links have been proposed as a means of connecting large offshore wind power plants to the onshore transmission system. This paper includes the study of a control strategy for the islanded operation of the aforementioned wind power plants. The offshore grid voltage is controlled independently of the HVDC link state. Therefore, offshore grid and HVDC link overvoltage due to onshore short circuits are largely reduced. Moreover, the proposed strategy allows for the contribution of the wind power plant to onshore service restoration after a power outage. The proposed control strategy has been validated in a realistic scenario by means of PSCAD/EMTDC simulations.