In recent years, the energy crisis severally appears due to the enormous human development. The renewable energy is a new source for world energy demand nowadays, especially the wind energy. Generally, wind energy is the most promising source for electric power demand in world because of the availability of the high wind speed around the year in several locations. This work investigates the drag type wind turbines, which have strong potential in small electric power generation demands. The scenario of this work is divided into two sections; the first one is the numerical analysis for the conventional Savonius with fully optimizing for the shape of the blade using a genetic algorithm. This optimization is performed to maximize the power coefficient with the same dimension of the conventional Savonius turbine. The second part is conducted experimentally to measure the performance of the conventional Savonius with the two and three blades; in addition, the optimal blade design (S shape) is tested to compare the performance of this new design with the conventional one or standard semi-circular blade. The results indicated that the captured efficiency of the optimal shape blade has the optimum value with 28% in contrasts to 14 and 10% for the two and three blades respectively. •The present work is to optimize the drag type vertical axis wind turbine.•Different designs of drag turbines are studied numerically and experimentally.•Genetic Algorithm is used as optimizer to improve the turbine performance.•Experimental work is performed to validate the performance of the optimal design.•Optimal shape has Cp value with 28% in contrasts to 14% for the conventional design.