Application of Multiobjective Technique to Multi-disciplinary Optimal Power Flow Problem Using Refined Foraging Algorithms

The Optimal Power Flow (OPF) is important problem in electric power systems and OPF is a static, non – linear optimization problem of determining the optimal settings of control variables for minimization the cost of generation including sine components, piecewise quadratic cost curve, transmission losses, voltage profile optimization and power flow deviations are proposed in this paper. The OPF problem is not only comprised of cost of generation and includes multidisciplinary comprehensive model. It is an important problem in power systems operation due to operational security considerations and even a small savings per hour translates into large annual saving. A Refined Bacterial Foraging Algorithm [RBFA] is introduced in this paper to solve multi objective optimization problems. The multiobjective is proven and is well in power system problems. The objective of this paper is to introduce RBFA to solve multi disciplinary Optimal Power Flow [MDOPF] based on multi-objective optimization. The new multiobjective BFA is presented for the solution of the comprehensive model for MDOPF. The algorithm is then demonstrated on IEEE 30 bus system and test results provided on the standard system reported in the literature clearly indicates that this method is efficient. The RBFA is motivated by the foraging behavior of the E. coli bacteria and the biological aspects of the bacterial foraging strategies and is well in multi disciplinary high dimensional problems and multiple objective optimization problems. The solution of the MDOPF problem, with a simultaneous and adequate consideration of all its facets with reasonable computing time, is still to be achieved.