Abstract
The rapid expansion of offshore wind farms and the development of energy islands for green hydrogen production have introduced futuristic off-grid systems. These systems can experience total shutdowns, necessitating black start solutions to ensure reliable restoration capabilities for isolated offshore wind farms. This paper investigates a grid-forming converter sizing strategy to enable black start capabilities in off-grid offshore wind farms. The study evaluates the impact of different energization strategies on battery energy storage system (BESS) sizing, focusing on soft energization with droop control in wind turbines and electrolyzers, the effects of wind turbine ramp rates on BESS requirements, and the role of switchable shunt reactors at the offshore substation for reactive power management. A comparative analysis is conducted between soft + hard and pure soft energization sequences to assess their impact on BESS converter sizing. Results demonstrate that the combined soft + hard energization strategy significantly reduces BESS converter size, offering a more cost-effective black start solution compared to pure soft energization.

Abstract
Flexibility markets are emerging across Europe to improve the efficiency and reliability of distribution networks. This paper presents a methodology that integrates local flexibility markets into network maintenance scheduling, optimizing the process by contracting flexibility to avoid technical issues under the topology defined to operate the network during maintenance. A meta-heuristic approach, Evolutionary Particle Swarm Optimization (EPSO), is used to determine the optimal network topology.

Abstract
The purpose of an Advanced Distribution Management System (ADMS) is to consolidate the key operational functions of a SCADA system, Outage management System (OMS) and Distribution Management System (DMS) into a unified platform. This includes several key functions: SCADA operation, incidents and outages management, teams and field works management including switching operations and advanced applications for network analysis and optimization. The new generation of ADMS also implements a predictive operation strategy to enhance real-time operator responsiveness. The innovative aspects related to the new generation of ADMS built on top of an open architecture will be presented in this paper. © The Institution of Engineering & Technology 2025.

Abstract
A Renewable Energy Management System (REMS) is designed to enhance the operation and efficiency of renewable energy assets, such as wind and solar power, by addressing their inherent variability. Through integration with Supervisory Control and Data Acquisition (SCADA) systems, REMS facilitates real-time adjustments and forecast-based decisions, enabling grid security, optimizing energy dispatch, and maximizing economic benefits. This paper introduces a versatile active power control methodology for renewable energy plants, capable of operating across various time scales to address technical and market-driven requirements. The proposed framework processes inputs from power system measurements to generate forecasts using two distinct approaches, optimizing setpoints for energy dispatch and control processes. Four optimization methods—merit order, weighted allocation, proportional allocation, and linear optimization—are employed to maximize power utilization while adhering to system constraints. The approach is validated for two control intervals: 4 seconds, representing rapid response for converter-based resources, and 15 minutes, simulating broader operational adjustments for reserve provision programs. This dynamic and scalable control framework demonstrates its potential to enhance the management, efficiency, and sustainability of renewable energy systems. © The Institution of Engineering & Technology 2025.

Abstract
This work proposes a robust methodology for the location and sizing of grid forming (GFM) converters that simultaneously considers the solution costs and the security gains while accounting for the TSO nonlinear cost-security sensitivity. Such methodology, which includes a collection of techniques to reduce the problem dimensionality, formulates the placement problem as a non-linear multi-criteria decision support problem and uses a solution-seeking algorithm based on Bayesian Optimisation to determine the solution. To ease comprehension, a modified version of the IEEE 39 Test System is used as a case study throughout the method's detailed explanation and application example. A sensitivity analysis of the GFM converter's over-current capacity in the solution of the formulated placement problem is also performed. The results show that the proposed method is successful in finding solutions with physical meaning and that respect the decision agent preferences.

Abstract
Accurate power forecasting from renewable energy sources (RES) is crucial for integrating additional RES capacity into the power system and realizing sustainability goals. This work emphasizes the importance of integrating decentralized spatio-temporal data into forecasting models. However, decentralized data ownership presents a critical obstacle to the success of such spatio-temporal models, and incentive mechanisms to foster data-sharing need to be considered. The main contributions are a) a comparative analysis of the forecasting models, advocating for efficient and interpretable spline LASSO regression models, and b) a bidding mechanism within the data/analytics market to ensure fair compensation for data providers and enable both buyers and sellers to express their data price requirements. Furthermore, an incentive mechanism for time series forecasting is proposed, effectively incorporating price constraints and preventing redundant feature allocation. Results show significant accuracy improvements and potential monetary gains for data sellers. For wind power data, an average root mean squared error improvement of over 10% was achieved by comparing forecasts generated by the proposal with locally generated ones.