Optimal power flow solution of wind integrated power system using modified bacteria foraging algorithm

• The research work optimizes the generation cost of wind and thermal power systems.
• The solution is sought in an optimal power flow frame work formulating it as an optimization problem.
• Objective function takes into account the reactive power generation capability of DFIG.
• The optimization results obtained with BFA gives faster, better and more secured schedule compared to GA.

Owing to the intermittent nature of wind flow, optimal power flow in a power system with considerable wind energy penetration is a challenging issue. In this paper an OPF solution is proposed for IEEE 30 bus power system modified by replacing three conventional generators with equivalent wind energy conversion systems (WECS).The uncertain nature of wind power has the risk of over or under estimating the capacity of available wind power. This uncertainty has been suitably modeled and included in the OPF framework. Moreover, to justify the limitation of reactive power generation capability of doubly fed induction generator based WECS during under estimation, additional cost component corresponding to external reactive power (Q) generating sources has been added in the objective function. The scheduling problem of WECS integrated power system is solved by formulating it as an optimization problem. Genetic algorithm and a modified bacteria foraging algorithm are employed separately to determine the optimal schedule. The optimal solution obtained with a modified version of BFA has been found to give better results compared to GA. The results depict the impact of wind and thermal scheduling on total system cost and reiterate the need of additional support of reactive power resources to maintain stable voltage profiles of the wind–thermal system.