Advanced lidar – Laser hardware development and field performance verification
Wind prediction modelling and validation using LIDAR data
Short-term forecasting is vital for wind farms due to both the intermittent nature of wind and the risks associated with integration of wind farms to the national grid. Error in this forecasting can cost as much as 10% of the total income from selling wind energy. In order to gain maximum power yields with minimum forecasting errors, it is essential to use a combination of advanced data analysis and numerical modelling techniques, augmented with state of the art remote sensing equipment.
This research focuses on developing a technique involving coupling two numerical models of different spatial resolutions using observations from a Coherent Doppler LIDAR (CDL) to contain and validate the modelling.
Measurement and modelling of the wind field at Lake Turkana in northern Kenya will be performed assisted by CDL with an aim to develop a site specific model to generate a wind field and hence power forecasts for wind turbines.
This research will help to build an improved methodology for simulating and predicting the wind structure and turbulence spatial and temporal variation in a given terrain. The results simulated will be compared with actual on site CDL and in situ anemometer observations to establish the validity of the approach. The aim is to achieve wind forecasting out to periods of about half hour to less than 2 hours.
Muhammad has a background in Mechanical Engineering and obtained his Bachelors degree in this field in 2005 from NWFP UET Peshawar, Pakistan. To gain professional experience Muhammad joined a local research and development firm in 2006. During his six years stay he was responsible for motivating, leading and managing a design team comprising of three members and guiding them through several successful projects.
In order to broaden his horizons, Muhammad started a Masters in Mechanical Engineering Design from the same university in parallel with his job in 2007. Muhammad completed the degree in 2010 with distinction. His research thesis was Aerodynamic and strength analysis of wind turbines using computational fluid dynamics and finite element analysis.
Mughal, MO 2014, 'Modelling winds and validation using LIDAR data' presentation at the Weather Forecast and Research Model (WRF) Users Workshop, Kensington, Australia, 27-28 March. and as part of the 3-Minute Thesis competition at the CRC CARE Communicate Conference 2014.
Mugal, MO 2015, presentation 'Numerical Modelling for Optimization of Wind Farm Turbine Performance' and associated paper at the 12th biennial German Wind Energy Conference DEWEK in Bremen, 19-20 May.