The UK Solar Farm Fleet: A Challenge for the National Grid? †

Currently, in the UK, it is widely believed that supply from renewable energy sources is capable of reaching proportions too great for the transmission system. This research investigates this topic objectively by offering an understanding of year-to-year and area-to-area variability of PV (photovoltaic) performance, measured in terms of specific yield (kWh/kWp). The dataset is created using publicly available data that gives an indication of impact on the grid. The daily and seasonal variance is determined, demonstrating a surprisingly good energy yield in April (second only to August). The geographic divergence of generation from large scale solar systems is studied for various sized regions. Generation is compared to demand. Timing of output is analyzed and probability of achieving peak output ascertained. Output and demand are not well matched, as regards location. Nevertheless, the existing grid infrastructure is shown to have sufficient capacity to handle electricity flow from large scale PV. Full nameplate capacity is never reached by the examples studied. Although little information is available about oversizing of array-to-inverter ratios, this is considered unlikely to be a major contributor to grid instability. It is determined that output from UK solar farms currently presents scant danger to grid stability

The UK Solar Farm Fleet: A Challenge for the National Grid? †

This is an Open Access Article. It is published by MDPI under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/Currently, in the UK, it is widely believed that supply from renewable energy sources is capable of reaching proportions too great for the transmission system. This research investigates this topic objectively by offering an understanding of year-to-year and area-to-area variability of PV (photovoltaic) performance, measured in terms of specific yield (kWh/kWp). The dataset is created using publicly available data that gives an indication of impact on the grid. The daily and seasonal variance is determined, demonstrating a surprisingly good energy yield in April (second only to August). The geographic divergence of generation from large scale solar systems is studied for various sized regions. Generation is compared to demand. Timing of output is analyzed and probability of achieving peak output ascertained. Output and demand are not well matched, as regards location. Nevertheless, the existing grid infrastructure is shown to have sufficient capacity to handle electricity flow from large scale PV. Full nameplate capacity is never reached by the examples studied. Although little information is available about oversizing of array-to-inverter ratios, this is considered unlikely to be a major contributor to grid instability. It is determined that output from UK solar farms currently presents scant danger to grid stability

Extensive validation of CM SAF surface radiation products over Europe

This work presents a validation of three satellite-based radiation products over an extensive network of 313 pyranometers across Europe, from 2005 to 2015. The products used have been developed by the Satellite Application Facility on Climate Monitoring (CM SAF) and are one geostationary climate dataset (SARAH-JRC), one polar-orbiting climate dataset (CLARA-A2) and one geostationary operational product. Further, the ERA-Interim reanalysis is also included in the comparison. The main objective is to determine the quality level of the daily means of CM SAF datasets, identifying their limitations, as well as analyzing the different factors that can interfere in the adequate validation of the products. The quality of the pyranometer was the most critical source of uncertainty identified. In this respect, the use of records from Second Class pyranometers and silicon-based photodiodes increased the absolute error and the bias, as well as the dispersion of both metrics, preventing an adequate validation of the daily means. The best spatial estimates for the three datasets were obtained in Central Europe with a Mean Absolute Deviation (MAD) within 813 W/m2, whereas the MAD always increased at high-latitudes, snow-covered surfaces, high mountain ranges and coastal areas. Overall, the SARAH-JRC's accuracy was demonstrated over a dense network of stations making it the most consistent dataset for climate monitoring applications. The operational dataset was comparable to SARAH-JRC in Central Europe, but lacked of the temporal stability of climate datasets, while CLARA-A2 did not achieve the same level of accuracy despite predictions obtained showed high uniformity with a small negative bias. The ERA-Interim reanalysis shows the by-far largest deviations from the surface reference measurements. © 2017 The Author