performance investigation of a novel nature-inspired algorithm based maximum power point tracking controller for stand-alone pv systems

A zero-emission photovoltaic system is critical for efficient energy supply and environmental protection. because of the intermittent nature of solar insolation and temperature, the maximum power point tracking controller for the photovoltaic system has become complicated. at each intermittent condition, the photovoltaic array has only one operating point with maximum power output. therefore, a nature-inspired algorithm-based controller is needed to determine the actual maximum operating point at different environmental conditions; thus, it can increase the overall efficiency of the photovoltaic system. this paper proposes a novel maximum power point tracking controller based on a hurricane optimization algorithm hybridised with chaos to improve power tracking in photovoltaic systems. the proposed hybrid algorithm is created by combining chaotic search behaviour with the standard hurricane optimization algorithm in order to increase efficiency. the proposed controller generates the optimal duty cycle for controlling the dc-dc boost converter by tracing the exact maximum operating point on a regular basis. the simulation results show that the proposed hoa -chaos-based mppt controller outperforms inc, p& o, pso and hoa based controllers in terms of efficiency and control.