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

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

Climate change mitigation by means of sustainable development of energy, water and environment systems

Integrated approaches in energy, water and environmental systems can improve the climate change reduction process. New scientific developments and advancements have provided numerous opportunities in the comprehensive human progress direction. In this regard, we have reviewed the 16th Conference on Sustainable Development of Energy, Water and Environment Systems presented in this editorial. Examining recent scientific developments, eight research articles on this special issue are related to eight main topics. The solar energy technology and storage section reviewed the first four articles. These articles include topics such as: 1) advanced technologies to form a new TT PS-TIM window system for adaptive daylight control and advanced thermal insulation combination, 2) using experimental data for field testing located in an area with Mediterranean climate conditions, of newly installed FPVS in these areas, 3) possibilities described in short rotation of willow type and energy crop Miscanthus cultivation dedicated to former coal mining areas, 4) using solar and geothermal energy with boiling water purification and reverse osmosis. Furthermore, the following four articles are reviewed in the energy management systems section. These articles include topics such as, 5) deep analysis of facial expression and eye tracking using samples of non-expert participants to determine emotions caused by electricity consumption graphs in different time scales, 6) studying the electric vehicles (EVs) main life cycle activities using an exploratory survey and their potential inequities, 7) the biodiesel fuel production from waste sardine fish oil using methanol, ethanol or isopropanol and a solid heterogeneous catalyst prepared using eggshell and copper oxide [CaCu(OCH3)2] is analyzed. Finally, 8) biotechnology microalgae have been studied in 70-litre vertical photobioreactors that use unsupplemented secondary brewery wastewater as growth media using two collecting cells mechanically methods under hydrothermal (autohydrolysis) and dilute acid hydrolysis

Thermo-economic assessment and optimization of a multigeneration system powered by geothermal and solar energy

A novel multigeneration system using dual renewable energy sources (i.e., geothermal and solar) is introduced, analyzed, and optimized. The integration of a geothermal line, a solar tower, a steam Rankine cycle, two organic Rankine cycles, an ejector refrigeration cycle, a thermoelectric generator unit, and a reverse osmosis subsystem forms the entire system. The outputs of this energy-conversion system are heating load, cooling load, electricity, and freshwater. Regarding methodology, the energy, exergy, and exergoeconomic approaches are implemented to assess the system from thermodynamic and economic viewpoints. Moreover, an optimization process based on exergy efficiency and the total unit cost of products is executed to determine the system's optimal decision variables. The results obtained from the optimization process show that the proposed system is able to achieve 25.4% exergy efficiency and 34.1 $/GJ total unit cost of products, exhibiting 48% and 43% improvement compared to a base case study. Furthermore, the methodology is demonstrated on a case study where the system operates at its optimum condition in a specific location. Having monthly average values of direct normal irradiation for this spot, the average hourly performance of the system is evaluated for each month. Based on the obtained results, the minimum and maximum freshwater production rates are 3.06 kg/s and 3.84 kg/s, respectively. It can be estimated that a range of 1224 to 1536 individuals, varying from month to month, can receive the produced freshwater

Energy and Exergy Analyses on Seasonal Comparative Evaluation of Water Flow Cooling for Improving the Performance of Monocrystalline PV Module in Hot-Arid Climate

Solar irradiation in hot-arid climatic countries results in increased temperatures, which is one of the major factors affecting the power generation efficiency of monocrystalline photovoltaic (PV) systems, posing performance and degradation challenges. In this paper, the efficiency of a water-flow cooling system to increase the output of a monocrystalline PV module with a rated capacity of 80 W is studied from both energy and exergy perspectives. The energy and exergy tests are performed for each season of the year, with and without cooling. The energy and exergy efficiencies, as well as the commodity exergy values, are used to compare the photovoltaic device with and without cooling. The findings are based on the experimental data that were collected in Tehran, Iran as an investigated case study in a country with a hot-arid climate. The findings show that when water-flow cooling is used, the values of the three efficiency metrics change significantly. In various seasons, improvements in regular average energy efficiency vary from 7.3% to 12.4%. Furthermore, the achieved increase in exergy efficiency is in the 13.0% to 19.6% range. Using water flow cooling also results in a 12.1% to 18.4% rise in product exergy