Dr Bright is a postdoctoral research fellow with the Fenner School of Environment and Society at The Australian National University. He has a passion for solar energy technologies. Previously, his research focused on applying mathematical stochastic principles to meteorological variables to produce high resolution solar data. This has been applied to evaluating the impact of solar panels in the distribution grid. His current focus is on solar energy forecasting, wherein he is working to generate estimates of the power output from large groups of distributed solar energy systems. He works with satellite imagery and power data from solar panels in the grid to provide state-of-the-art forecasts of solar energy on a research project funded by the Australian Renewable Energy Agency (ARENA).
Solar Energy | Solar resource assessment | Solar photovoltaics | Grid integration | Solar variability | Atmospheric modelling | Computational modelling and simulations | Solar forecasting | Satellite imagery | Remote sensing | Validation studies | Statistical analysis | Data analysis
- S Killinger, JM Bright, D Lingfors, Y-M Saint-Drenan, P Moriatis, W van Sark, J Taylor, NA Engerer. 2018. On the search for representative characteristics of PV systems: Data collection and analysis of PV system azimuth, tilt, capacity, yield and shading. Submitted to Solar Energy.
- D Lingfors, S Killinger, NA Engerer, J Widén, JM Bright. 2008. Identification of PV system shading using a LiDAR-based solar resource assessment model: an evaluation and cross-validation. . Solar Energy 159, 157-172
- JM Bright, S Killinger, D Lingfors, NA Engerer. 2017. Improved satellite-derived PV power nowcasting using real-time power data from reference PV systems. Solar Energy. In press.
- S Killinger, JM Bright, D Lingfors, NA Engerer. 2017. A tuning routine to correct systematic influences in reference PV systems’ power outputs. Solar Energy 157, 1082-1094
- D Lingfors, JM Bright, NA Engerer, J Ahlberg, S Killinger, J Widén. 2017. Comparing the capability of low-and high-resolution LiDAR data with application to solar resource assessment, roof type classification and shading analysis. Applied Energy 205, 1216-1230
- S Killinger, JM Bright, D Lingfors, NA Engerer. 2017. Towards a Tuning Method of PV Power Measurements to Balance Systematic Influences. ISES Solar World Congress 2017, Abu Dhabi, United Arab Emirates, October 29
- JM Bright, S Killinger, D Lingfors, NA Engerer. 2017. Integration of distributed solar forecasting with distribution network operations in Australia. ISES Solar World Congress 2017, Abu Dhabi, United Arab Emirates, October 29
- NA Engerer, JM Bright, S Killinger. 2017. Himawari-8 enabled real-time distributed PV simulations for distribution networks. PVSC44 Conference, Washington, USA.
- JM Bright, O Babacan, J Kleissl, PG Taylor, R Crook. 2017. A synthetic, spatially decorrelating solar irradiance generator and application to a LV grid model with high PV penetration. Solar Energy 147, 83-98
- CJ Smith, JM Bright, R Crook. 2017. Cloud cover effect of clear-sky index distributions and differences between human and automatic cloud observations. Solar Energy 144, 10-21
- JM Bright, PG Taylor, R Crook. 2015. Methodology to stochastically generate synthetic 1-minute irradiance time-series derived from mean hourly weather observational data. ISES Solar World Congress 2015, Daegu, South Korea, November 8-12.
- JM Bright, CJ Smith, PG Taylor, R Crook. 2015. Stochastic generation of synthetic minutely irradiance time series derived from mean hourly weather observation data. Solar Energy 115, 229-242
- J Bright, P Taylor, R Crook. 2015. Methodology to Stochastically Generate Spatially Relevant 1-Minute Resolution Irradiance Time Series from Mean Hourly Weather Data. 5th Solar Integration workshop 2015, Brussels, Belgium.
- J Bright, B Cotter, J Cottom, M Thatchell-Evans, Y Ding, R Crook. 2012. Carbon and economic analysis of side-by-side photovoltaic and solar thermal panels. PVSAT-9, Swansea UK