Security constrained optimal power flow solution of wind-thermal generation system using modified bacteria foraging algorithm

In this work the variability of WP (wind power) has been suitably modelled and incorporated with the thermal generating units. The goal is to operate the wind-thermal generation system in a cost effective manner while maintaining a voltage secure operation with reduction in system loss. These objectives have been formulated in an OPF (optimal power flow) framework. As the wind generation cost model is subjected to intermittent WP, the voltage security aspect is considered during both UE (under estimation) and OE (over estimation) of available WP. This is achieved by suitably incorporating shunt facts devices (STATCOM) to provide reactive power (Q) support during UE scenario and maintaining a spinning reserve of thermal generators during OE scenario. To further utilize the Q-support, the DFIG (doubly fed induction generators) are used in the wind turbine. The combinations of optimum operational paradigms are obtained by optimizing the objective function with ACO (ant colony optimization) and MBFA (modified bacteria foraging algorithm). Finally, after performing several tests the superiority of MBFA optimized scenario over ACO is revealed so that the IEEE30-bus system operates in a voltage secured manner when subjected to N-1 contingencies.