Modified radial movement optimization (MRMO) technique for estimating the parameters of fuel cost function in thermal power plants

Accurate estimation of coefficients of fuel cost function in thermal power plants is an important problem for economical operation of a power system. In this paper, a novel stochastic method called modified radial movement optimization (MRMO), is developed for estimating fuel cost coefficients of thermal generating units. Radial movement optimization is a novel global optimization technique used to solve the complex optimization problems. In this work, four case studies are considered for implementing the RMO technique in fuel cost parameter estimation problems. The coefficients of fuel cost curve functions in thermal power plants are found for first, second and third order models. Valve point effect is included in a third order model for estimating the cost coefficients for 13 unit systems using the proposed method. The results show that the RMO settles at local optima. Hence the algorithm is modified and termed as MRMO to converge on better results. From the results, it is inferred that the MRMO outperforms other techniques like particle swam optimization (PSO), teaching learning based optimization (TLBO), least error square (LES), artificial bee colony (ABC) algorithm based on the low total error.