Abstract
Future electrical grids, particularly the distribution networks, may face more severe voltage rises/drops, and in general, more power quality problems in the presence of new loads such as electric vehicle chargers and renewable energy generation units like photovoltaic systems. This necessitates investing in additional high-cost infrastructure to increase the capability of the feeder in hosting higher levels of loads and generation units while the existing capacity is not utilized effectively. In the stated condition, effective voltage stabilization strategies in electrical distribution networks can contribute to hosting capacity improvement and the better utilization of the existing infrastructure. Accordingly, in this paper, the application of Open-UPQC in voltage profile improvement and hosting capacity enhancement is evaluated in low-voltage distribution networks. Furthermore, a dynamic reference voltage adjustment strategy is applied to the device to improve its capabilities in power quality improvement and hosting capacity enhancement. Simulation studies have been implemented to evaluate the capability of Open-UPQC either with static reference voltage or the dynamically-adjusted one in low-voltage networks with real measured data while different cases are assessed regarding the topology and the length of the feeder. The simulation results approved the capability of Open-UPQC especially with the dynamic reference voltage in hosting capacity enhancement while providing the highest level of voltage profile improvement among all the assessed custom power devices in the studied low-voltage networks.

Abstract
This paper investigates the financial benefits stemming from the potential installation of battery energy storage systems behind the meter of a hybrid offshore farm including wind turbines and floating photovoltaic panels. The optimal investment and operation decisions concerning the energy storage system in the hybrid site are assessed by means of a mixed integer linear programming optimization model. The operation is also subject to technical constraints such as limitations on the connection capacity and ramping constraints imposed by the grid operator at the point of common coupling. Three design configurations for the battery system are analysed: I) offshore with the hybrid farm, II) onshore where the grid connection point is, III) both offshore and onshore. The results indicate the financial value of installing battery storage units, and other benefits deriving from this investment, as the reduction of curtailment.

Abstract
Due to the current focus on offshore renewable energies worldwide, more capacity of them is expected in the future. The electrical layout design considerably affects overall implementation cost of these offshore power plants as well as the losses of energy inside the farms. Considering the increasing size of offshore wind farms, it is necessary to develop more robust and computationally efficient methods to design the electrical layout of these farms. In this work, a two-phase approach is proposed for the optimization of the electrical layout of the offshore wind farms; the proposed framework aims at the minimization of the ohmic losses and the cost of the cables. To solve the optimization problem, Simulated Annealing (SA) is applied in this study. A tool is also developed using Python programming language to implement the framework for the optimization of the electrical layout of the offshore farms. The proposed method is then applied to a farm with 100 turbines and an overall rated capacity of 1GW. The results approved the accuracy of the two-phase approach in finding the optimal electrical layout as well as the high efficiency in terms of the computational burden.

Abstract
This paper introduces a detailed procedure for executing a black start service from an offshore wind farm (OWF) through the integration of grid-forming (GFM) control. The proposed strategy involves exploiting a grid-forming battery energy storage system (BESS) to deliver black start service within an OWF equipped with grid-following wind turbines. Controller modelling, and operation methodology are explained. To illustrate the efficacy of the suggested control and operation principles, the study employs an OWF as a case study. Simulation analyses are conducted using the Matlab/Simulink software to demonstrate the viability of the presented strategy.

Abstract
This paper presents a comprehensive procedure for conducting a black start service from an offshore wind farm (OWF) by integrating grid-forming (GFM) control. The proposed strategy utilizes a grid-forming battery energy storage system (BESS) to provide black start service within an OWF that is equipped with grid-following wind turbines. The paper elaborates on the modeling of controllers and the operational methodology taking wind variability during the black start procedure. To showcase the effectiveness of the proposed control and operation principles, the study utilizes an OWF as a case study. Simulation analyses are performed using Matlab/Simulink software to validate the feasibility of the proposed strategy. © Energynautics GmbH.

Abstract
In this paper, the performance analysis of Machine Learning (ML) algorithms for fault analysis in photovoltaic (PV) plants, is given for different algorithms. To make the comparison more relevant, this study is made based on a real dataset. The goal was to use electric and environmental data from a PV system to provide a framework for analysing, comparing, and discussing five ML algorithms, such as: Multilayer Perceptron (MLP), Decision Tree (DT), K-Nearest Neighbors (KNN), Support Vector Machine (SVM) and Light Gradient Boosting Machine (LightGBM). The research findings suggest that an algorithm from the Gradient Boosting family called LightGBM can offer comparable or better performance in fault diagnosis for PV system.