An Adaptive Hybrid Algorithm for MPPT in Battery-Backed Solar and Wind Energy Systems

Renewable energy systems, including solar, wind and hydro, have gained significant importance in recent years. Although these systems have many advantages, such as being clean and sustainable, their key disadvantage is low efficiency comparing to the energy systems based on fossil fuels. Moreover, more land area and resources are required by renewable energy sources to produce equal amount of energy compared to conventional sources. The efficiency of renewable energy systems can be improved using some selected techniques, which extract maximum power under all possible conditions. In this paper, a comparative analysis of eight different algorithms, including simple and artificial maximum power tracking techniques, has been conducted for wind and solar energy systems with integrated load and storage components. The comparison was based on factors such as efficiency, settling time, oscillations at maximum power point, and complexity of the algorithm. By combining the benefits of artificial intelligence and conventional methods, an adaptive hybrid algorithm that produced superior results is proposed for renewable energy systems.