publications

2022

1. Wind Power Potential in Highlands of the Bolivian Andes: A Numerical Approach

   Rober Mamani and Patrick Hendrick

   Energies, 2022

   Abs DOI

   Wind resource assessment is a key factor for the development and implementation of wind farms with the purpose of generating green, eco-friendly and clean electricity. The Bolivian Andes, as a large dry region, represents an important source of renewable energy. However, the altitude and high wind energy resources of the Bolivian Andes require further knowledge and understanding of the wind energy resources. In this study, the GWA have been used to determine the total area available to install wind farms considering the protected areas, roads, cities and transmission lines. In addition, the Weather Research and Forecasting (WRF v3.8.1) model is employed to complement the results of the GWA based on the validation of WRF simulations with measurements from Qollpana wind farm. The main purpose is to estimate the wind power potential along the Bolivian Andes and its variability in time. The wind power simulations have been compared with the power generated by the Qollpana wind farm to verify the WRF’s performance. The wind power potential in the highlands of the Bolivian Andes could reach between 225 (WRF) and 277 (GWA) GW, distributed mainly over the Western and Eastern Cordillera of the Altiplano.

2021

1. WRF Model Parameterization Around the Highland Titicaca Lake

   Rober Mamani and Patrick Hendrick

   Earth and Space Science, Dec 2021

   https://doi.org/10.1029/2021EA001649

   Abs DOI

   Abstract The computational advances and many times the lack of meteorological measurements in some regions of the world impulse the employment of numerical methods for covering this deficiency of data, and the parameterization is a key factor for use and operation of numerical weather prediction models. The Weather Research & Forecasting (WRF) as one of the most important models has been scarcely parameterized in the Bolivian Altiplano and Titicaca Lake. This work evaluates different physics models and focus the parameterization in the planetary boundary layer (PBL) schemes. This study evaluates the performance of land surface, radiation, convective and microphysics models using WRFv3.8.1. The results showed well-prediction with NOAH, THOMPSON, and RRTMG for land surface, microphysics and radiation schemes, respectively. For the PBL parameterization QNSE, YSU, MYJ, MYNN, and QNSE-FDDA were evaluated for wind speed, temperature, and mixing ratio. The minimum root mean square error were 2.025 m s?1 (QNSE-FDDA) for wind speed, 1.721 K (YSU) for temperature, and 0.786 g kg?1 (MJY) for mixing ratio. In summary, the results have shown that QNSE scheme well-predicts wind speed and water mixing ratio. However, using FDDA only wind speed and water mixing ratio were improved, and the temperature prediction becomes worse. These results suggest an underprediction of incoming solar radiation due to temperature and water mixing ratio were underestimated near the Titicaca Lake.

2. Weather research & forecasting model and MERRA-2 data for wind energy evaluation at different altitudes in Bolivia

   Rober Mamani and Patrick Hendrick

   Wind Engineering, May 2021

   doi: 10.1177/0309524X211019701

   Abs DOI

   Wind energy is one of the most promising alternatives for a clean and ecological electricity generation. However, the implementation of efficient wind farms requires accurate data and measurements. This work analyses the MERRA-2 satellite datasets to compare and complement it with WRF simulations in different regions and altitudes in Bolivia, such as the Altiplano, Amazon and Chaco. A 41?years of hourly wind speed from MERRA-2 was used to analyze wind averages and characteristics over the year. WRF simulations for representative months were used to analyze wind shear and wind flows along Bolivia. The main results are related to wind speed index in different sites which varied between 0.90 and 1.09 and the periods of high wind speeds that is May?October in the Altiplano, and June?December in the Amazon and Chaco. However, the main findings are the differences between MERRA-2 data and WRF simulations that is linked to the topography of the sites in study.

2019

1. Wind farm power short-term prediction using WRF model and Kalman filtering

   Rober Mamani and Patrick Hendrick

   In ECOS 2019 - Proceedings of the 32nd International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, May 2019

   Abs

   The growing wind power industry requires more reliable power forecasting due to higher penetration of this technology in electricity generation. Due to the stochastic behaviour of wind, additional tools for improving the electricity forecast are required. This research parameterizes WRF model for wind power forecasting in Qollpana wind farm -Bolivia. Qollpana is a wind farm over a very complex terrain and 2800 meters above sea level (masl) located on the Andes. Wind power forecasting is performed for different periods of the year, such as, January, April, June, and October. Finally, the results are improved using a Kalman filter and compared with the power generated in Qollpana wind farm. The simulated WRF results of energy generated in the wind farm showed between 50 and 30 % of error. However using a Kalman filter the errors diminished up to 10 % of the energy generated by the wind farm. The time of the highest errors (at sunlight time) suggests that topographic conditions play an important role in the wind farm electricity production.

2. Evaluación numérica de diferentes alternativas de energías renovables en Raqaypampa

   Rober Mamani, Claudia Sanchez, Evelyn Cardozo, and 1 more author

   Cientifica UMSS, May 2019

   Abs

   Este trabajo presenta la energía eólica y solar como dos alternativas para la generación eléctrica en la Autonomía Indígena Originaria Campesina de Raqaypampa, a partir de la necesidad de los pobladores por conocer sus potencialidades energéticas. La evaluación del potencial eólico y solar se realiza mediante datos de reanálisis (MERRA-2) y modelos de numéricos predicción meteorológica (WRF-ARW). La identificación de las zonas con potencial energético partió por observaciones de los pobladores y que fueron corroborados mediante simulaciones numéricas. Uno de los sitios presento un alto potencial eólico y solar, con velocidades viento de hasta 8 m/s y radiación solar de hasta 1130 W/m 2. Los resultados de esta investigación abren las puertas a la universidad de generar conocimiento desde una visión de desarrollo inclusivo.

2018

1. Efficiency of High Altitude On-shore Wind Turbines: Air Density and Turbulence Effects—Qollpana Wind Farm (Bolivia)

   Rober Mamani, Norbert Hackenberg, and Patrick Hendrick

   Proceedings, Jul 2018

   Abs DOI

   The wind energy is one of the most important alternatives for renewable and clean electricity generation. During the last decade the number of wind farms has largely increased in South America. Qollpana is only one case of an on-shore wind farm but it is located at 2900 m above sea level over a complex terrain. Due to high altitude, the air density is reduced by 27% compared with sea level and the topographic characteristics induce a high level of turbulence. Qollpana wind farm has ten wind turbines reaching 27 MW of installed capacity. October is the month of highest wind average velocity and February with the lowest one. This work analyses the capacity factor of the wind farm, also the air density and the turbulence effects on wind turbine efficiency. The main results show that monthly capacity factor varies between 0.08 and 0.67 in the wind farm. Moreover, the results have shown a considerable effect of the turbulence intensity on the turbines efficiency.