Impacts of renewable generation on the operation of gas network – A statistical analysis

Abstract

Several countries have been accelerating their plans to increase the share of renewables as a source of energy to combat the climate change and reduce pollution. In the United Kingdom, wind power has become the highest contributing source of energy among renewables. Despite the progress of renewable energy in the United Kingdom, the variation and uncertainty of renewable sources still poses a real challenge to this progress. In order for renewable energy systems to maintain a high percentage of energy share, they need to be coupled with a reliable system of production such as gas fired power stations. This integration will need to support renewables in meeting the demand as well as compensate when there is a lack in the renewable source such as wind or solar. This dissertation starts by discussing the motivation behind reducing the carbon footprint and the progress of renewable energy in the developed nations. Also, it highlights the role of gas fired station to increase the penetration of renewable sources and their operation principles as well as their types and their performance metrics. Then the dissertation highlights previous research which have been done to further understand the relationship between renewable energy and gas network. The paper analysed the data from Great Britain gas network in order to study the relationship between Close Cycle Gas Turbine (CCGT) generation, electricity demand, gas demand, wind generation and linepack. The first analysis was done over a long term, this meant that the 12-month data from November 2015 – October 2016 is compared with 12-month data from November 2016 – October 2017 and it is hence repeated up to September 2020. This generated five figures and each figure illustrated the CCGT generation, wind generation, electricity and gas demand and linepack. The 12-month data is obtained by averaging the daily values for each month. The second part focused on higher resolution data between CCGT and electric demand and the wind generation and linepack. This higher resolution means, the collection of all hourly data between November 2015 – October 2016 and plot a scatter graph to understand the correlation between them. Finally, the relationship between the linepack and wind generation was studied on a smaller scale. This was done over the first days in November 2015 to understand how the linepack follows the drop in wind generation production. That period was chosen as the wind generation and linepack were noted to have had variations over a smaller period of time and it was a point of interest in this study. All these results were collected and

visualised as full analysis of their changes (long and short) using Microsoft Excel software. The dissertation concluded with future work recommendation and citing all relevant references.