A Salp-Swarm Optimization based MPPT technique for harvesting maximum energy from PV systems under partial shading conditions. (1st April 2020) - Mirza, Adeel Feroz; Mansoor, Majad; Ling, Qiang; Yin, Baoqun; Javed, M. Yaqoob
Highlights: A novel MPPT technique is proposed using Salp Swarm Optimization (SSO). SSO saves the computational time and reducing the oscillation. SSO results are compared with PSO, DFO, CS, ABC and PSOGS. SSO improves tracking time, settling time, power tracking and stability. A statistical study authenticates the robustness, sensitivity of the proposed SSO. Abstract: In recent years, solar photovoltaic power generation has been widely used in the world because of its eco-friendly and recyclable nature. It is therefore critical to extract maximum power from solar photovoltaic systems. Numerous maximum power point tracking (MPPT) techniques of solar photovoltaic systems have been proposed. Conventional MPPT techniques are usually limited to uniform weather condition. This paper presents a novel bio-inspired technique for Photovoltaic (PV) systems under various weather condition, which utilizes Salp Swarm Optimization (SSO) for effective MPPT. It makes use of the confined exploitation property of salps to track the maximum available power, especially under Partial Shading (PS), which may severely degrade the output power. Moreover, robustness and efficiency are significantly improved by the proposed SSO technique. The results of SSO in five different weather cases are tested against conventional MPPT techniques, such as Artificial Bee Colony (ABC) Optimization, Particle Swarm Optimization (PSO), PSO-Gravitational Search (PSOGS), DragonFly Optimization (DFO), Cuckoo Search (CS) Optimization, and, Perturb and Observe (P&O) algorithms. The proposed SSO technique can successfully tackle the global maxima (GM) under various weather conditions and demonstrates performance superiority in terms of efficiency, faster tracking, and stable output.