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To achieve an energy sector independent from fossil fuels, a significant increase in the penetration of variable renewable energy sources, such as solar and wind power, is imperative. However, these sources lack the inertia provided by conventional thermo-electric power stations, which is essential for maintaining grid frequency stability. In this study, a grid resembling Madeira Island's power generation mix was modeled using the Matlab/Simulink platform. The model included solar, wind, hydro, and thermo-electric generation to accurately represent the energy landscape of Madeira Island. Three scenarios were examined: one reflecting the current power generation on Madeira Island, a future scenario with a substantial rise in the percentage of photovoltaic (PV) generation, and the same future scenario but incorporating a battery energy storage system (BESS). Various analyses were conducted to assess the impact on frequency stability during a ground fault and rapid load/generation changes. In the future scenario without a BESS, the thermoelectric power plant generator desynchronized, leading to system collapse in several simulations. However, with the addition of a BESS, a significant improvement in frequency stability was observed. The thermoelectric power plant generator could return to a steady state after each disturbance. Furthermore, both the maximum frequency deviation and the absolute value of the Rate of Change of Frequency (ROCOF) were reduced, indicating enhanced system performance and stability. [ABSTRACT FROM AUTHOR]

The need for decarbonization has become an urgent objective being pursued across borders and sectors. The energy sector is one example to follow, with the penetrations of renewable energy sources increasing year after year and already having an impact on carbon emissions. Despite their benefits, as these penetration levels grow, grid frequency is likely to be affected, namely in small, isolated power systems. Part of this instability is caused by the different types of connections to the grid used by most renewable energy sources. These converter-connected technologies do not contribute to the grid's inertia the same way synchronous generators do, therefore the difficulties in keeping the frequency under control. Focusing on the behaviour of the system's frequency, following some disturbances, a grid model of the Portuguese Terceira Island is created to assess the potential benefits of using hydrogen technologies (electrolysers and fuel cells) to provide grid services. In this paper, two scenarios are analyzed, the system's frequency response to large imbalances and steady-state imbalances stemming from load and wind power forecasting errors. The results reflect how the frequency behaviour is affected by the amount of the system's inertia, synchronous generators characteristics, and the presence of electrolysers and fuel cells. Hydrogen systems impact positively on the frequency containment after large disturbances, the impact related to the response to steady-state imbalances being lesser and prone to affect the stacks lifespan. • A grid model of a Portuguese island is created to assess the benefits of hydrogen to provide frequency control. • Models are developed for electrolysers, fuel cells and synchronous generators. • Two scenarios are analyzed: the response to large imbalances and steady-state imbalances (load and wind forecasting errors). • Hydrogen systems positively impact the frequency containment after large disturbances. • The impact related to the response to steady-state imbalances is lesser and prone to affect the stacks lifespan. [ABSTRACT FROM AUTHOR]

Offshore wind energy has the potential to be associated with hydrogen production to overcome certain disadvantages, such as the high cost of electrical transmission systems. In this work, two hydrogen producing systems are modelled, one with the electrolyzer offshore, the other with the electrolyzer onshore, along with a conventional offshore wind farm. To do so, each component is individually modelled and combined to construct the systems. Furthermore, an hourly optimisation algorithm is used to control the operation of the systems and a neural network is implemented to forecast day ahead power production and electricity price, so that regulation costs could be modelled. This study extends the existing literature by modelling the regulation costs in the day ahead electricity market using neural networks to provide day ahead forecasts along with analysing the flexibility of using an electrolyzer coupled with an offshore wind farm. Furthermore, innovative floating offshore wind turbines were considered, enabling the assessment for offshore hydrogen production in deeper waters. Results show that, for the present case study, the onshore electrolyzer system is always more economically interesting than the offshore electrolyzer system, mainly due to its ability of purchasing electricity from the grid. The first has a levelized cost of hydrogen of 5.84 €/kg, 3.42 €/kg and 2.57 €/kg for 2020, 2030 and 2050, respectively, compared to 8.98 €/kg, 4.37 €/kg and 2.68 €/kg. • Coupling hydrogen production with offshore wind farms reduces costs from forecasting errors. • 2020 prices for floating offshore wind and electrolyzers result in LCOH of at least 6 €/kg. • Cost estimates for 2030 show LCOH of around 3–4 €/kg and around 2€/kg for 2050. • For the specific case study, onshore electrolyzer is always more economically attractive. [ABSTRACT FROM AUTHOR]

With the increase in renewable energy connected to the grid, new challenges arise due to its variable supply of power. Therefore, it is crucial to develop new methods of storing energy. Hydrogen can fulfil the role of energy storage and even act as an energy carrier, since it has a much higher energetic density than batteries and can be easily stored. Considering that the offshore wind sector is facing significant growth and technical advances, hydrogen has the potential to be combined with offshore wind energy to aid in overcoming disadvantages such as the high installation cost of electrical transmission systems and transmission losses. This paper aims to outline and discuss the main features of the integration of hydrogen solutions in offshore wind power and to offer a literature review of the current state of hydrogen production from offshore wind. The paper provides a summary of the technologies involved in hydrogen production along with an analysis of two possible hydrogen producing systems from offshore wind energy. The analysis covers the system components, including hydrogen storage, the system configuration (i.e., offshore vs. onshore electrolyzer), and the potential uses of hydrogen, e.g., Power to Mobility, Power to Power, and Power to Gas. [ABSTRACT FROM AUTHOR]

Because wind has a high volatility and the respective energy produced cannot be stored on a large scale because of excessive costs, it is of utmost importance to be able to forecast wind power generation with the highest accuracy possible. The aim of this paper is to compare 1‐h‐ahead wind power forecasts performance using artificial intelligence‐based methods, such as artificial neural networks (ANNs), adaptive neural fuzzy inference system (ANFIS), and radial basis function network (RBFN). The latter was implemented using three different learning algorithms: stochastic gradient descent (SGD), hybrid, and orthogonal least squares (OLS). The application dataset is the injected wind power in the Portuguese power systems throughout the years 2010–2014. The network architecture optimization and the learning algorithms are presented. An initial data analysis showed data seasonality; therefore, the wind power forecasts were performed according to the seasons of the year. The results showed that ANFIS was the best performer method, and ANN and RBFN‐OLS also showed strong performances. RBFN‐Hybrid and RBFN‐SGD performed poorly. In general, all methods outperformed persistence. [ABSTRACT FROM AUTHOR]

The integration of intermittent renewable energy sources (RES) represents a great challenge for any energy system. In particular, islanded microgrids with a high penetration of renewables experience a strong need for technologies that allow to match demand and production at any moment. This work aims at proposing an optimised design for the energy system of Faial, an island in the Azores archipelago, featuring the highest possible renewable energy penetration that can be obtained respecting the technological and financial feasibility constraints. To this purpose, a model has been developed, using weather and electric demand measured data to combine and size optimally the components of a hybrid energy system. The model can be varied in its constraints to fit at best the multi-objective nature of the problem, where the conflicting objectives are the Net Present Value, its Renewable Energy Fraction and the Energy Index of Reliability. Once a set of possible optimal design has been determined, a system design featuring 5504 kW of geothermal installed power and 6208 kWh of BESS (Battery Energy Storage System) capacity, together with the already present thermal generators and 4250 kW of wind turbines, has been analysed more in detail. Monte Carlo simulations with synthetic time series have been performed to investigate the impact on the project of the variability in wind speed and in energy demand, highlighting the robustness of the selected design. • We propose an optimised design for the energy system of Faial, an island in the Azores archipelago. • The model features the highest possible renewable energy penetration respecting the technological and financial constraints. • Monte Carlo simulations were performed to investigate the impact of the variability in wind speed and energy demand. [ABSTRACT FROM AUTHOR]

The incorporation of clean energy sources in the power system is a topic of discussion almost everywhere. After the "wind (farms) of change", small, dispersed, urban photovoltaic (PV) generators are being installed in the roofs of the buildings, connected to the local Low Voltage (LV) grid. A boost in this type of renewable micro generation is expected in the near future. Due to the domestic loads, LV grids are inherently unbalanced, its analysis requiring the use of three-phase load flow methods. This same methodology is used in this paper to assess the problem of the concurrent unbalanced generation and load and to cope with the presence of both single and three-phase equipment in the same grid. A review of existent models for three-phase equipment is performed. The issue of modelling three-phase loads (isolated star and delta connected) and singlephase PV generators and associated power electronics is given special attention. Finally, a case-study is presented, enabling to draw some conclusions regarding the impacts on the Medium Voltage (MV) grid and the behaviour of the system facing different climacteric conditions. [ABSTRACT FROM AUTHOR]

As the onshore wind resource is running shorter, wind power promoters are paying attention to the offshore resources. As in most cases there is no load offshore, wind power must be transmitted to the main land. To do so, two options are available: HVAC and HVDC transmission systems. In this paper, the two options are analysed from a power flow point of view. The influence in the voltage regulation of the onshore connection busbar is investigated in a 57 bus test power system. The simulation results obtained for each one of the above mentioned transmission system configurations allow the conclusion that HVAC solution is limited by the distance to shore and by the wind transmitted power. HVDC options do not show these limitations, but are more expensive and more delicate to deal with, because there is a lack of operational experience, so far. [ABSTRACT FROM AUTHOR]

Presents a study which addressed the issue of the capacity credit provided by wind energy conversion systems. Method of the study; Results and discussion; Conclusion.

Describes proposed wind park model designed to measure wind penetration on utility grids. Application of singular perturbations theory; Background on Wind Energy Conversion Systems (WECS); Characteristics of model.

Offshore wind farms, while strategically positioned to maximise wind energy capture, are exposed to harsh environments, impacting their reliability and accessibility. Low reliability and accessibility in turn translate into high Operation and Maintenance (O&M) costs, which represent approximately 30% of the total lifetime costs of the project. One approach to reduce O&M costs is to improve maintenance planning decisions. The present paper presents a novel O&M scheduling methodology for offshore wind farm operations based on wind and wave forecasts. The methodology forecasts farm yield considering farm wake effects to identify optimal operation schedules, vessel routing, and turbine maintenance sequences that minimise costs and revenue losses due to downtime. Weather forecast uncertainty is modelled and integrated into the decision-making process to minimise weather risks. A case study inspired by the WindFloat Atlantic floating wind project was used to demonstrate the optimisation potential. Results suggest that adopting the proposed methodology over business-as-usual scheduling significantly boosts offshore wind farm operational profits during the forecasted period, with increases ranging from 2% to 24%, depending on the scenario considered. It was found that integrating the wind farm wake losses into the scheduling decisions can improve the optimal scheduling solution and further minimise total operation costs. • A novel O&M planning methodology for offshore wind farm operation is proposed. • Model generates optimal maintenance schedules based on weather forecasts. • Model integrates weather forecast uncertainty and farm wake effects into planning. • The WindFloat Atlantic floating wind project was used as a case study. • Factoring in wake effects enhances maintenance scheduling and reduces energy losses. [ABSTRACT FROM AUTHOR]