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For optimization of electricity production, especially in the thermal power plant required analysis of input-output characteristics and operated load properly. Inputoutput characteristics will oversee the curve and detected the plant need for maintenance or not. Input-output characteristics can be calculated by least squares quadratic regression method. operated load properly, making electricity production corresponding maximum desired load with lowest cost. Loadi calculations performed by dynamic genetic algorithm method. This method is applied to data from PT. PJB UP Gresik in July 2015 and has saving 3.162,9147 KNM fuel consumption and $22.773 fuel costs compared PJB. While applied to data Desember 2012 has saving 16.532,2189 liters fuel consumption and Rp. 1.131.369.852 fuel costs compared PJB. Method of dynamic genetic algorithm can divide load accordance the reference, while the PSO has a difference of -1 to 42 MW and has 245,24 liter fuel consumption and fuel costs Rp. 1.477.569 more efficient than PSO methode. While the method of SA has a difference of -0.0001 to 0.0001 MW. Dynamic genetic algorithm has 50.511,12 liters of fuel consumption and fuel costs Rp. 304.329.523 more efficient than mtode SA.

berkala sainstek

Analisis Karakteristik Input-Output dan Optimasi Biaya Pembangkitan Menggunakan Metode Quadratic Least Square Regression dan Metode Dynamic Genetic Algorithm