Abstract
Hybrid storage systems that combine high energy density and high power density technologies can enhance the flexibility and stability of microgrids and local energy communities under high renewable energy shares. This work introduces a novel approach integrating rule-based (RB) methods with evolutionary strategies (ES)-based reinforcement learning. Unlike conventional RB methods, this approach involves encoding rules in a domain-specific language and leveraging ES to evolve the symbolic model via data-driven interactions between the control agent and the environment. The results of a case study with Li-ion and redox flow batteries show that the method effectively extracted rules that minimize the energy exchanged between the community and the grid. © 2024 IEEE.

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. © 2024 IEEE.

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. © 2024 IEEE.

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. © 2024 IEEE.

Abstract
To continue to make successful progress towards the achievement of net zero emissions by 2050, a significant number of new facilities based on renewable technologies must continue to be deployed at large scale. However, the integration of large capacities of renewable generation sources into power systems leads to a series of challenges that must be urgently addressed. On the one hand, the intermittent character of renewable resources may lead to imbalances between generation and demand curves, and on the other hand, transmission and distribution system operators will have to carefully consider the impact of reduced power system inertia due to the increase in the number of renewable power plants. Under this framework, stricter technical requirements will be demanded to new power plants that will be integrated into the grid to guarantee quality of electricity supply. These requirements are included within increasingly modern and up-to-date network connection-or grid-codes. Thus, grid codes have a significant role to play in the years to come towards the transition of a more sustainable future, and therefore this paper presents an overview of two grid codes for connecting new generation units across Europe, focusing on the current situation of Iberia. A special emphasis is given on the detailing of certain grid code requirements based on a comparison between the Portuguese and the Spanish grid codes, together with few highlights on the operational procedures for connecting new generation units on both regions. © 2022, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.

Abstract
With the recent advancements in the development of hybrid offshore parks and the expected large-scale implementation of them in the near future, it becomes paramount to investigate proper energy management strategies to improve the integrability of these parks into the power systems. This paper addresses a multiobjective energy management approach using a hybrid energy storage system comprising batteries and hydrogen/fuel-cell systems applied to multi-source wind-wave and wind-solar offshore parks to maximize the delivered energy while minimizing the variations of the power output. To find the solution of the optimization problem defined for energy management, a strategy is proposed based on the examination of a set of weighting factors to form the Pareto front while the problem associated with each of them is assessed in a mixed-integer linear programming framework. Subsequently, fuzzy decision making is applied to select the final solution among the ones existing in the Pareto front. The studies are implemented in different locations considering scenarios for electrical system limitation and the place of the storage units. According to the results, applying the proposed multiobjective framework successfully addresses the enhancement of energy delivery and the decrease in power output fluctuations in the hybrid offshore parks across all scenarios of electrical system limitation and combinational storage locations. Based on the results, in addition to the increase in delivered energy, a decrease in power variations by around 40 % up to over 80 % is observed in the studied cases.