Environmental and economic impacts of increased utilization of natural gas in the electric power generation sector: Evaluating the benefits and trade-offs of fuel switching

Abstract

This study aims to evaluate the impact of different fuel mix options for their environmental and economic effects on electricity production systems. Four scenarios were developed (S1, S2, S3, and S4) and compared with the base case over a three-month modeling episode using the state of Kuwait as a geographic domain. Natural gas (NG) penetration was gradually increased for S1, S2, and S3 compared to the base case at proportions that were subject to each scenario's definition, whereas S4 was more of a worst-case scenario that assumed that all natural gas consumption at every power plant in the base case was replaced by crude oil. An air quality model, AERMOD, was used to simulate how the emission scenarios influenced the concentrations of NOx, SO2, PMtotal and CO. The results showed a dramatic decrease in NOx, SO2, and PMtotal emissions in the first three scenarios. This reduction was associated with higher levels of natural gas penetration in the fuel mix. The percentage reductions in NOx, SO2, and PMtotal emissions were highest in S3 (36.8%, 98.9%, and 72.3%, respectively); however, the emissions of the same pollutants increased in S4 (5.5%, 90.1%, and 64.8%, respectively). In concordance with these results, the 1-hr average concentrations were inversely correlated with the contribution of natural gas to the mix. Notably, CO emissions differed from the prevalent trend. The total emissions and the 1-h average concentration of carbon monoxide increased in the first three scenarios, with maximum increases of 55.4% and 37.7%, respectively, but were lower in S4 (48.3% and 39.0%, respectively). Finally, cost analysis showed that increased utilization of NG in the fuel mix could reduce the cost of consumed energy since NG has the lowest energy cost per MMBtu (14.8 USD/MMBtu) and relatively high calorific values (LHV = 47.13 MJ/kg, HHV = 52.21 MJ/kg). The total energy cost was most reduced in S3 (9.0%), while the worst-case scenario (S4) showed a 9.3% increase in fuel cost.