This paper proposes a new metaheuristic optimization algorithm based on ancient war strategy. The proposed War Strategy Optimization (WSO) is based on the strategic movement of army troops during the war. War strategy is modeled as an optimization process wherein each soldier dynamically moves towards the optimum value. The proposed algorithm models two popular war strategies, attack and defense strategies. The positions of soldiers on the battlefield are updated in accordance with the strategy implemented. To improve the algorithm’s convergence and robustness, a novel weight updating mechanism and a weak soldier’s relocation strategy are introduced. The proposed war strategy algorithm achieves good balance of the exploration and exploitation stages. A detailed mathematical model of the algorithm is presented. The efficacy of the proposed algorithm is tested on 50 benchmark functions and four engineering problems. The performance of the algorithm is compared with ten popular metaheuristic algorithms. The experimental results for various optimization problems prove the superiority of the proposed algorithm.

Increased penetration of wind energy systems has serious concerns on power system stability. In spite of several advantages, doubly fed induction generator (DFIG) based wind energy systems are very sensitive to grid disturbances. DFIG system with conventional vector control is not robust to disturbances as it is based on PI controllers. The objective of this paper is to design a new vector control that is robust to external disturbances. To achieve this, inner current loop of the conventional vector control is replaced with sliding mode control. In order to avoid chattering effect and achieve finite time convergence, the control gains are selected based on positive semi-definite barrier function. The proposed barrier function adaptive sliding mode (BFASMC) is evaluated by testing it on a benchmark multi-machine power system model under various operating conditions. The simulated results show that the proposed method is robust to various disturbances.