Title :
A linear programming methodology for the optimization of electric power-generation schemes
Author :
Khodr, H.M. ; Gómez, J.F. ; Barnique, L. ; Vivas, J.H. ; Paiva, P. ; Yusta, J.M. ; Urdanet, A.J.
Author_Institution :
Departamento de Conversion y Transporte de Energia, Simon Bolivar Univ., Caracas, Venezuela
fDate :
8/1/2002 12:00:00 AM
Abstract :
A mathematical model, based upon the application of a linear-integer programming algorithm, is presented for the optimum selection of independent electric power-generation schemes in industrial power systems, taking reliability considerations into account. The problem is formulated as a mathematical programming problem-considering investment costs, fuel costs, operation and maintenance costs, power balance, maximum and minimum limits on the generated power of the units, along with reliability considerations, such as the unavailability of the generation scheme. These considerations include assumptions made and simplifications performed to obtain an accurate enough linear model. The problem is solved using a conventional branch and bound algorithm for linear-integer programming, yielding to the optimum number of units, as well as the corresponding size and type. Results are presented for the application of the proposed methodology to a real case of an industrial power system. The technique has proven to be a valuable tool for the planning engineer.
Keywords :
costing; industrial power systems; integer programming; investment; linear programming; power generation economics; power generation planning; tree searching; branch and bound algorithm; electric power-generation schemes optimisation; fuel costs; independent electric power-generation schemes selection; industrial power systems; investment costs; linear programming methodology; linear-integer programming; maintenance costs; mathematical programming; operation costs; power balance; power generation limits; reliability considerations; Costs; Fuels; Industrial power systems; Investments; Linear programming; Mathematical model; Mathematical programming; Optimization methods; Power generation; Power system reliability;
Journal_Title :
Power Systems, IEEE Transactions on
DOI :
10.1109/TPWRS.2002.800982