Abstract: This study emphasizes solution to the multi objective Optimal Power Flow (OPF) problem in power system embraced with wind power. The OPF problem is formulated and analyzed for two different objectives such as minimization of fuel cost, minimization of active power loss and voltage deviation. The objective function for minimization of fuel cost is incorporated with wind speed variability in terms of over and underestimation cost during the estimation of wind power generation cost. Firefly Algorithm (FA) based optimization technique is used and results were compared with modified Cuckoo Search algorithm and modified particle swarm optimization for solving OPF incorporated with wind power. Due to the penetration of variable wind power generation into the existing power system, voltage deviation issues occur and it may lead to voltage collapse. In order to maintain voltage stability of connected power system network, reactive power management of grid connected windfarms using Static Var Compensator (SVC) is required. The concept of minimizing active power losses while maintaining desirable voltage profile in all buses along with optimized SVC rating under variable wind power penetration has been evaluated as multi objective function. Optimal values for SVC setting are searched using Firefly algorithm in a modified IEEE 30 bus system and its capability is demonstrated by comparison between power losses of the system before and after optimization. The results depict the importance of wind scheduling on total system cost and the need of optimum reactive power compensation to maintain voltage profiles of the grid connected power system.
M.G. Sugirtha and P. Latha, 2016. Firefly Algorithm Based Multi-Objective Optimal Power Flow in the Presence of Wind Power. Asian Journal of Information Technology, 15: 703-711.