Investigation the Success of Semidefinite Programming for the Estimating of Fuel Cost Curves in Thermal Power Plants

Accurate estimation of fuel cost curve parameters in thermal power plants is great importance because these directly influence the economic dispatch calculations. In this paper, a semidefinite programming (SDP) approach was proposed for functions' plants. The parameter problem designed as minimization problem, where objective function accepted total absolute error (TAE) study. Also, linear, quadratic, and cubic functions were used to estimate parameters. Different types such coal, oil gas preferred simulation studies. results achieved from method compared with that particle swarm optimization (PSO), artificial bee colony (ABC), crow search algorithm (CSA) least square (LES) methods, respectively. performance methods according TAE parameter. Simulation showed SDP more successful than other considered paper. Clearly, present paper has higher potential solve problems.