Abstract
The operating cost for optimal performance of 100MW Delta IV gas turbine unit of Ughelli power plant was determined using optimum operating parameters and exergoeconomics. The optimizatioon tool is an evolutionary algorithm known as Genetic Algorithm (GA). The computer application used in this work is written in Matlab (Version 2011b) programming language. Eight optimal operating parameters of the plant were involved; compressor inlet temperature (T<sub>1</sub>), compressor pressure ratio (r<sub>p</sub>), compressor isentropic efficiency (η<sub>ic</sub>), turbine isentropic efficiency (η<sub>it</sub>), turbine exhaust temperature (T<sub>4</sub>), air mass flow rate (m<sub>a</sub>), fuel mass flow rate (m<sub>f</sub>) and fuel supply temperature (T<sub>f</sub>). Eight decision variables were optimally adjusted by the Genetic Algorithm (GA) to minimize the objective function. An objective function representing the total operating cost of the plant was defined in terms of <s><span>N</span></s> per hour as sum of operating cost (relating to the fuel consumption), rate of capital cost (relating to capital investment and maintenance expenses), and rate of exergy destruction cost. The optimal values of the decision variables (constraints) were obtained by minimizing the objective function. The GA optimal results obtained were <i>m<sub>a</sub></i>= 530kg/s, <i>m<sub>f</sub></i>= 7.00g/s. The GA operating cost and the component GA optimum results for exergy destruction cost rate and capital investment cost rate required to sustain optimum performance were obtained. The operating cost (<i>Ċ</i><sub>f</sub>), cost of exergy destruction rate (<i>Ċ<sub>D</sub></i>) and capital investment cost rate (Z<sub>K</sub>) for the compressor, combustion chamber and turbine are: (<i>Ċ</i><sub>f</sub>) = <s><span>N</span></s>244.72 per hour giving a variation of -0.57%, <i>Ċ<sub>Dc</sub></i> = <s><span>N</span></s>87,728.32 per hour giving a variation of +13.59%, (Ż<sub>C</sub>) = <s><span>N</span></s>936,016.00 per hour giving a variation of -37.6% , (<i>Ċ</i><sub>DCC</sub>) = <s><span>N</span></s>470,288 per hour, a variation of -88.73%, Ż<sub>CC</sub> = <s><span>N</span></s>93,160.8 per hour, a variation of +305.6%, <i>Ċ</i><sub>Dt</sub> = <s><span>N</span></s>144,278.4 per hour, a variation of -84.31%, Ż<sub>t</sub> = <s><span>N</span></s>1,428,252.8 per hour a variation of +160.1%. These variations were in relation to base results.
Highlights
There is a need to ensure that a given engineering system is performing at the optimal level
The objective this study is to evaluate the operating cost for optimal performance of 100MW Gas Turbine Power Plant using Genetic Algorithm (GA) to minimize the exergy destruction cost rate by optimally adjusting the operating parameters
The objective function is a summation of three important parts; operational cost rate, capital investment cost rate and exergy destruction cost rate
Summary
There is a need to ensure that a given engineering system is performing at the optimal level. This is necessary in many engineering applications since efficiency means cost saved and performance maximized. This is the preferred operating condition for any system and an important criterion to be considered at the design level of any engineering system nowadays [1]. Algorithm was used to minimize the exergy destruction by optimally adjusting the operating parameters. Genetic algorithm was originally designed as simulator but has proven to be a robust optimization technique [3], [4]
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