For decentralized electrification in remote areas, small-sized wind energy systems (WESs) are considered sustainable and affordable solution when employing an efficient, small-sized component converter integrated with a less-sophisticated, cost-effective MPPT controller. Unfortunately, using a conventional buck DC/DC converter as a MPP tracker suffer from input current discontinuity. The latter results in high ripples in the tracked rectified wind power which reduces the captured power and affects system operation especially in standalone applications which are self-sufficient and independent of grid support. Furthermore, these ripples propagate to the machine side causing vibration and torque stress which impacts turbine performance and safety. To solve this issue, a large electrolytic capacitor is placed at the buck converter input to buffer these ripples, yet at the cost of larger size, losses and reduced reliability. Oppositely, the developed C1, D4 and D6 buck converters have the merit of continuous input current at small component-size. In this paper, dynamic modelling of these three converters is developed to select the one with the least input current ripples to replace the traditional buck converter in the considered WES system. Consequently, fluctuations in the tracked power are minimized and the large buffer capacitor is eliminated. This enhances system lifetime, reduces its cost and increases tracking efficiency. Moreover, mechanical power and torque fluctuations are minimized, thus maintaining machine protection. Furthermore, a sensorless MPPT algorithm, based on converter averaged state-space model, is proposed. Being dependent on variable-step P&O algorithm, the proposed approach features simple structure, ease of control and a compromise between tracking time and accuracy besides reduced cost due to the eliminated current sensor. Simulation results verified the effectiveness of the selected converter applying the proposed MPPT approach to efficiently track the wind power under wind variations with cost-effective realization.