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.

In this study, we conduct an analysis of power control in a Voltage Source Converter (VSC) connected to a Weak Grid (WG), focusing on the system's stability and performance. Our main objective is to predict the behaviour of the VSC under different conditions. To address this analysis and enhance the control capabilities, we propose a two-parameter control structure and we develop a controller design methodology that ensures specific criteria are met, such as maintaining maximum voltage deviations at the Point of Common Coupling (PCC), achieving a minimum acceptable Short Circuit Ratio (SCR), and attaining the desired time response. Additionally, we establish criteria to avoid problems associated with grid synchronization using a Phase-Locked Loop (PLL). Finally, through representative simulations, we validate the accuracy of our predictions regarding the system's behaviour. Furthermore, the proposed design procedure proves to be highly effective in achieving the desired outcomes. This study contributes to the understanding of power control in VSCs connected to Weak Grids, providing valuable insights for designing robust and high-performing systems in such scenarios.

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.

Takagi-Sugeno fuzzy models are exact representations of nonlinear systems in a compact region. Guaranteed-cost linear matrix inequalities produce controllers which minimize a shape-independent bound on a quadratic cost; however, the controller has a fixed structure (possibly suboptimal), say a Parallel Distributed Compensator (PDC), and does not allow input saturation. By posing the problem as a Model Predictive Control one, the ideas of terminal set, terminal controller and feasible set can be used in order to improve the performance of usual guaranteed-cost controllers for Takagi-Sugeno systems via Quadratic Programming. A Polya-based approach has been introduced in order to (conservatively) transform the invariant set problem into a polytopic one, as well as computing the controller feasibility region. The optimal controller is computed iteratively.

TS fuzzy models are exact representations of nonlinear systems in a compact zone (sector nonlinearity). Once a controller is found by Lyapunov methods, determining the set of initial conditions such that the state does not leave the modelling region is an important problem to be solved. Also, determining the set to which the disturbances will steer the system is also necessary to ensure that the size of the modelling region has been correctly estimated. This paper proposes polytopic approximation to such sets based in algorithms from [1]. A Polya-based approach has been introduced in order to (conservatively) transform the nonlinear invariant set problem into a polytopic one.