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Solar energy is a sustainable and inexhaustible renewable energy. Solar-powered PV systems contribute to the cleanest and the most cost-effective electrical energy. However, PV systems are confronted with a nonlinear maximum power point tracking (MPPT) problem caused by partial shading (PS). PS causes the loss of available power. This paper presents a novel Harris hawk optimization (HHO) based MPPT controller to effectively track maximum power under all weather conditions. The effectiveness of the proposed HHO based MPPT is supplemented by a comparative study with perturb and observe algorithm (P&O), dragonfly optimization algorithm (DFOA), particle swarm optimization (PSO), cuckoo search (CS) and grey wolf optimization (GWO). The analytical and statistical analysis is made based on 4 different cases, including fast varying irradiance, PS, complex-PS (CPS), and field atmospheric data of Hefei city of China, to solidify the effectiveness of HHO based MPPT for PV systems in real-world applications. The proposed HHO shows superior performance in tracking maximum power point and faster convergence at the global maximum power point. The improvement of 10–30% in tracking time and more than 90% in random oscillations are effectively achieved by the proposed MPPT technique. Faster maximum power point (MPP) tracking, lower computational burden and higher efficiency are the key contributions of the HHO based MPPT technique. • Novel Harris hawk optimizations (HHO) based MPPT control of PV system is proposed. • HHO is compared with P&O, PSO, GWO, CSA, and DFOA through field atmospheric data and case studies. • HHO outperform competing techniques with 10-30% faster tracking, 4-6% more energy harvest and oscillation reduction 95.45%. • Statistical and quantitative analysis confirms the superior performance of the proposed HHO. [ABSTRACT FROM AUTHOR]