Determination of Unit Fuel Cost Effect on Optimal Designed Parameters of Delta IV Ughelli Gas Turbine Power Plant Unit

摘要

The effect of variation on optimal decision variables with respect to unit cost of fuel (sensitivity analysis) for optimal performance of 100MW Delta IV ughelli gas turbine power plant unit was determined using optimal operating parameters and exergoeconomics. The optimization tool is an evolutionary algorithm known as Genetic Algorithm (GA). The computer application used in this work is written in matlab programming language. Eight optimal operating parameters of the plant were used: compressor inlet temperature (T_1), compressor pressure ratio (r_p), compressor isentropic efficiency (η_(ic)), turbine isentropic efficiency (η_(it)), turbine exhaust temperature (T_t). Air mass flow rate, fuel mass flow rate and fuel supply Temperature (T_f). These decision variables were optimally adjusted by the Genetic Algorithm (GA) to minimize the objective function. The objective function representing the total operating cost of the plant defined in terms of $ per hour is the sum of operating cost (i.e fuel consumption cost rate), rate of capital cost (i.e optimal investment and maintenance expenses) and rate of exergy destruction cost. The optimal values of the decision variables were obtained by minimizing the objective function. The determined values of the optimal operating variables were r_p = 9.76, η_(ic) = 86.4%, η_(it) = 89.12%, T_3 = 1,481.8K, η_ε = 29%, η_E = 31%, Total Cost Rate = 13292$/hr, W_t = 277.11MW, W_c = 169.63MW, air mass flow rate = 530kg/s and fuel mass flow rate = 7.00kg/s. The variation of optimal decision variables with unit cost of fuel showed that by increasing the unit fuel cost, the pressure ratio (r_p), compressor isentropic efficiency (η_(ic)), exergy efficiency (η_ε), Energy efficiency (η_E), total cost rate, turbine output power (W_t) and compressor input power (W_c) increase. The increase in η_(ic), η_ε, η_E and W_t guarantees less exergy destruction in compressor and turbine as well as less net cycle fuel consumption and operating cost.