This study presents a methodology for optimizing the power from a fleet of engines that use associated gas as fuel. The effects of engine degradation on optimized power, energy, and electricity revenue have been evaluated.
The Cranfield University TURBOMATCH has been used to simulate a 296MW reheat gas turbine. Four scenarios were considered — clean, optimistic, medium, and pessimistic. Genetic algorithm was used in optimizing the power generated from the fleets.
In the sequence of clean, optimistic, medium, and pessimistic fleets, the optimization results show that the total optimized power values are 7324.6, 7245.1, 7164.0, and 7074.4MW respectively. In the same sequence, the total energy generated is 64.2, 63.5, 62.8, and 61.9 billion kWh. In a similar sequence still, the electricity revenue is 8.487, 8.390, 8.298, and 8.192 billion US dollars respectively. In comparison with the clean, engine degradation resulted in a 1.09%, 2.19%, and 3.42% decrease in energy for the optimistic, medium, and pessimistic degraded fleets respectively. In the same sequence as the decrease in energy, degradation resulted in a 1.15%, 2.23%, and 3.48% decrease in electricity revenue.
The methodology and results presented in this paper would serve as a guide for associated gas investors in the economic utilization of this fuel resource. This is innovative; it has not been done with the Alstom GT-26 engine.