Grid-connected renewable energy systems flexibility in Norway islands’ Decarbonization

In recent decades, investing in renewable and eco-friendly energy technologies, such as replacing clean energy systems instead of traditional ones and equipment management, is an interesting and practical topic in all sectors. This research analyzes the optimization of a hydro plant, wind turbines, and photovoltaic (PV) panels with a careful examination of three scenarios in the Hinnoya region, Norway. Three consumption scenarios—including an industrial/domestic load scenario, transportation load, and household load alone—for this region are considered. HOMER software is used to simulate and analyze the techno-economic performance of solar panels/wind turbines/grid/batteries and converters. The results of this research show that using renewable and eco-friendly systems in accordance with the region's potential leads to a lower cost of electricity generation. The COE production is at least 50% less than the normal sales price of the electricity grid. The use of electric grid exchanges results in energy modification at night. The potential for the use of onshore wind turbines is more than offshore turbines. The results also indicate that using renewable systems in the household field can reduce the COE by nearly 70% (0.0296 €/kWh), and in other energy fields (transportation and industrial) can diminish the COE by nearly 50% (0.055 €/kWh). Thus, increasing the percentage of employing renewable and eco-friendly energy systems leads to reduce greenhouse gas (GHG) emissions (particularly carbon dioxide)

Analyzing the impact of demand response and reserves in islands energy planning

Small Islands usually rely on fossil fuels for their energy supply and face common challenges such as high energy costs and carbon dioxide emissions. For these reasons they represent interesting cases for analysing the transition towards a clean and secure energy system. Nevertheless, integrating non-dispatchable Renewable Energy Sources in the power grid causes stability issues and this is particularly true for island grids. Such issue is not fully considered in long-term energy planning; indeed, an important factor that should be considered in order to ensure the reliability of the grid are Reserves. There are different types of Reserves depending on the reactiveness/response time and the duration of the service. In this paper, primary and secondary reserves have been analysed in order to plan the long-term energy transition of the small island of Favignana, Italy by means of the new version of H2RES, a Linear Programming single-objective optimisation model able to provide a long-term capacity investment and dispatching optimisation. It has been found that biomass generators are favoured to both photovoltaic and wind turbines for their ability to provide reserves and also decrease the unpredictability of the supply. Batteries and Electrolysers are also used mostly for reserve provision

Designing high-share 50% and 100% renewable energy scenarios for Ragusa by sustainable energy toolkit application

Increasing renewable energy production and integrating it into the current energy systems may lead to conditional solutions linked to the context of applications as well as regulatory and techno-socioeconomic issues. The PRISMI Plus toolkit is a powerful tool that can be improved to entail rural areas and energy islands for effective planning of the various renewable energy system scenarios associated with urban contexts. The target Flagship Case Study is Ragusa, a Municipality located in Southern Italy, analyzed with the EnergyPLAN software. The simulation and validation were carried out by the HOMER software. The input dataset was created jointly in collaboration with the Municipality, the updated Sustainable Energy Action Plan was inserted into the PRISMI Plus toolkit, and three transition scenarios based on different renewable energy uses were considered within the post-processing stage. For the baseline scenario, no green energy is considered and the whole electricity consumption is taken into account. In scenarios two and three, 50% and 100% renewable energy shares are secured through optimal investment in Photovoltaic (PV) panels, Wind Turbines (WT), and Battery Energy Storage (BES) technologies. From an economic point of view, it was concluded that the best scenario is the second one thanks to the increased technical capacity of the investment ratio compared with the two other scenarios, showing an energy price reduction of up to 10 %

Hourly energy profile determination technique from monthly energy bills

Hourly energy consumption profiles are of primary interest for measures to apply to the dynamics of the energy system. Indeed, during the planning phase, the required data availability and their quality is essential for a successful scenarios’ projection. As a matter of fact, the resolution of available data is not the requested one, especially in the field of their hourly distribution when the objective function is the production-demand matching for effective renewables integration. To fill this gap, there are several data analysis techniques but most of them require strong statistical skills and proper size of the original database. Referring to the built environment data, the monthly energy bills are the most common and easy to find source of data. This is why the authors in this paper propose, test and validate an expeditious mathematical method to extract the building energy demand on an hourly basis. A benchmark hourly profile is considered for a specific type of building, in this case an office one. The benchmark profile is used to normalize the consumption extracted from the 3 tariffs the bill is divided into, accounting for weekdays, Saturdays and Sundays. The calibration is carried out together with a sensitivity analysis of on-site solar electricity production. The method gives a predicted result with an average 25% MAPE and a 32% cvRMSE during one year of hourly profile reconstruction when compared with the measured data given by the Distributor System Operator (DSO)

Short-Term Wind Speed Forecasting Model Using Hybrid Neural Networks and Wavelet Packet Decomposition

Wind speed is one of the most vital, imperative meteorological parameters, thus the prediction of which is of fundamental importance in the studies related to energy management, building construction, damages caused by strong winds, aquatic needs of power plants, the prevalence and spread of diseases, snowmelt, and air pollution. Due to the discrete and nonlinear structure of wind speed, wind speed forecasting at regular intervals is a crucial problem. In this regard, a wide variety of prediction methods have been applied. So far, many activities have been done in order to make optimal use of renewable energy sources such as wind, which have led to the present diverse types of wind speed and strength measuring methods in the various geographical locations. In this paper, a novel forecasting model based on hybrid neural networks (HNNs) and wavelet packet decomposition (WPD) processor has been proposed to predict wind speed. Considering this scenario, the accuracy of the proposed method is compared with other wind speed prediction methods to ensure performance improvement

Interval prediction algorithm and optimal scenario making model for wind power producers bidding strategy

Nowadays, renewable energies are important sources for supplying electric power demand and a key entity of future energy markets. Therefore, wind power producers (WPPs) in most of the power systems in the world have a key role. On the other hand, the wind speed uncertainty makes WPPs deferent power generators, which in turn causes adequate bidding strategies, that leads to market rules, and the functional abilities of the turbines to penetrate the market. In this paper, a new bidding strategy has been proposed based on optimal scenario making for WPPs in a competitive power market. As known, the WPP generation is uncertain, and different scenarios must be created for wind power production. Therefore, a prediction intervals method has been improved in making scenarios and increase the accuracy of the presence of WPPs in the balancing market. Besides, a new optimization algorithm has been proposed called the grasshopper optimization algorithm to simulate the optimal bidding problem of WPPs. A set of numerical examples, as well as a case-study based on real-world data, allows illustrating and discussing the properties of the proposed method

Methodology framework for prioritisation of renewable energy sources in port areas

Ports play a crucial role in increasing the decarbonisation of urban environments to mitigate the environmental impacts of maritime transport and promote sustainable intermodal mobility. Various efforts have been made to increase energy self-sufficiency using renewable energy sources (RESs) in different ports worldwide. However, the ports played an essential role in the pollution process of the nearest cities due to the short distance and merging with urban areas. In this case, solar and wind were measured using the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) data of four Lazio province ports. Each RES was evaluated using 10 years of monthly data for mapping and 1 year of hourly data for potential assessment and energy converters installation. Furthermore, the time series method has been considered to design and develop better management of RESs for decision making monitoring the energy needs of ports. This time series method has been applied to the generated energy source based on various parameters of the RESs used in port

A parametric study of wave energy converter layouts in real wave models

Ocean wave energy is a broadly accessible renewable energy source; however, it is not fully developed. Further studies on wave energy converter (WEC) technologies are required in order to achieve more commercial developments. In this study, four CETO6 spherical WEC arrangements have been investigated, in which a fully submerged spherical converter is modelled. The numerical model is applied using linear potential theory, frequency-domain analysis, and irregular wave scenario. We investigate a parametric study of the distance influence between WECs and the effect of rotation regarding significant wave direction in each arrangement compared to the pre-defined layout. Moreover, we perform a numerical landscape analysis using a grid search technique to validate the best-found power output of the layout in real wave models of four locations on the southern Australian coast. The results specify the prominent role of the distance between WECs, along with the relative angle of the layout to dominant wave direction, in harnessing more power from the waves. Furthermore, it is observed that a rise in the number of WECs contributed to an increase in the optimum distance between converters. Consequently, the maximum exploited power from each buoy array has been found, indicating the optimum values of the distance between buoys in different real wave scenarios and the relative angle of the designed layout with respect to the dominant in-site wave direction