Methodology for optimal design and control of wind energy system based on simplifying assumptions

The study presented in this paper concerns the development of a new methodology for design and controlling a wind energy generation chain. This methodology is based on combined Analytical-Finite Element-Experimental method. This type of converter chosen is an AC-DC inverter with IGBTs to improve the robustness of the power chain structure. It offers a reduction of the cost of the power chain and the improvement of the performances of the global studied system, as the control at power factor equal to unity and providing an electromagnetic torque which is added to the useful torque in order to extract the maximal energy. The control algorithms permit to regulate Le charging voltage and current in their rated values considered as optimal battery charging voltage and current. The global model of the power chain is implemented under the Matlab-Sumilink simulation environment for performance and efficiency analysis.

Higher Wind: Highlighted Expansion Opportunities to Repower Wind Energy

Decarbonizing the world economy, before the most damaging effects of climate change become irreversible, requires substantially increasing renewable energy generation in the near future. However, this may be challenging in mature wind energy markets, where many advantageous wind locations are already engaged by older wind farms, potentially generating suboptimal wind harvesting. This research developed a novel method to systematically analyze diverse factors to determine the level of maturity of wind markets and evaluate the adequacy of wind farm repowering at regional and individual levels. The approach was applied to wind markets in the United States (U.S.), in which several states were identified as having diverse levels of maturity. Results obtained from case studies in Texas indicated a consequential number of wind farms that have reached their twenty-year end-of-life term and earlier obsolescence levels. The proposed approach aided in determining wind farms that may benefit from total or partial repowering. The method indicated that total repowering of selected installations would significantly increase overall wind energy generation, considering that these older installations have access to some of the best wind speeds, infrastructure and areas to grow. The proposed method can be applied to different world wind markets.

A Cooperation Project in Lesotho: Renewable Energy Potential Maps Embedded in a WebGIS Tool

In this paper the background, activities undertaken, and main outcomes of the cooperation project “Renewable Energy Potential Maps for Lesotho” are presented. The project was launched in 2018 in fulfilment of the Paris Agreement by the Italian Ministry for the Environment and the Lesotho Ministry of Energy and Meteorology, with the aim to facilitate the local Government in the future planning and development of renewable energy in the country. A user-oriented WebGIS platform was utilised to share and analyse the outcomes of the project: a hydrological map to recognize potential areas for power generation; a wind atlas to identify specific sites with the most potential for wind energy generation; a solar radiation map, defining the different levels of radiation intensity, useful to localise sites for photovoltaic production. Human capacity building and technology transfer were carried out to strengthen the local expertise and ability to manage and plan renewable energy sources exploitation. The implementation of the project was based on a fruitful collaboration between scientists and stakeholders at the same time giving the local authorities a useful dataset and tool for renewable energy growth in Lesotho.

Wind Energy Analysis in the Coastal Region of Bangladesh

Diversifying the energy mix of Bangladesh is becoming indispensable not only to improve its energy security, but also for a more sustainable economic development. This study focused on mapping the wind potential of southern coastal areas of Bangladesh to estimate the wind energy potential, along with the reduction in carbon emissions due to wind energy. Analysis of the carbon footprint was based on the annual energy production (AEP) from the selected low-wind turbine generators (WTGs). The time series-measured and -predicted wind data were incorporated with the high-resolution mesoscale and microscale wind re-source mapping technique at 60, 80, and 100 m above ground level (AGL). Coupling mesoscale and microscale modeling provided reliable mapping results for the commercially exploitable wind resource and was verified by ground-based wind measurement. The results revealed that, among the selected areas, two sites named Charfashion and Monpura have a promising annual mean wind speed of 7.3 m/s at 100 m AGL for energy generation. Different WTGs with ranges of 1–3.3 MW were used to estimate the wind energy generation capacity at different sites in the study area. A WTG with a 1 MW wind energy generation capacity installed at 60 m AGL in the selected site has the potential to produce 2.79 GWh/year of clean energy, reducing 1781.689 tons of CO2 per year, whereas a 3.3 MW WTG at 80 m AGL can produce 18.99 GWh/year of energy, reducing 12,098.54 tons of CO2 per year, and a 1.6 MW WTG at 100 m AGL produces 11.04 GWh/year of energy, cutting 7035.028 tons of CO2 per year. With its reliable scientific and time-tested wind energy estimation method, this research is very important for the development of wind energy in the southern coastal areas of Bangladesh to meet the increasing energy demands through initiating the development of renewable energy to improve the energy security and reduce the carbon emissions of the country.