Research Article
Operation Optimisation Towards Generation Efficiency Improvement in Saudi Arabia, Using Mathematical Programming and Simulation
@INPROCEEDINGS{10.1007/978-3-319-61813-5_5, author={Mohammad Althaqafi and Qingping Yang}, title={Operation Optimisation Towards Generation Efficiency Improvement in Saudi Arabia, Using Mathematical Programming and Simulation}, proceedings={Smart Grid Inspired Future Technologies. Second EAI International Conference, SmartGIFT 2017, London, UK, March 27--28, 2017, Proceedings}, proceedings_a={SMARTGIFT}, year={2017}, month={9}, keywords={Efficiency Electricity Generation Fossil fuel Saudi Arabia}, doi={10.1007/978-3-319-61813-5_5} }
- Mohammad Althaqafi
Qingping Yang
Year: 2017
Operation Optimisation Towards Generation Efficiency Improvement in Saudi Arabia, Using Mathematical Programming and Simulation
SMARTGIFT
Springer
DOI: 10.1007/978-3-319-61813-5_5
Abstract
The efficiency of fossil power generation has improved during the last decades and technology development has played a significant role in this improvement. However, several factors can affect the efficiency level, such as operation, maintenance and environment, etc. The economic growth in Saudi Arabia in recent years has increased the demand for electricity. On the supply side, despite the reinforcement of generation stock with new units, the generation efficiency of fossil fuel has not improved significantly and is considered as being amongst the lowest in the world. This, as a result, means further consumption of resources and more emissions being produced. For this study, a new merit order has been produced using mathematical models to optimise the operation of power plants and improve the average efficiency. In addition, a simulation model was built to verify the enhancement. The results of the first stage show, on average, 3.5% improvement in generation efficiency and around a 4.95 Mtonnse reduction in total CO2 produced. In the second stage, the efficiency improved by 6% and the emissions rate dropped by 5.7%.