Ordering Technique for the Maximum Power Point Tracking of an Islanded Solar Photovoltaic System

Abstract

The world’s attention has turned towards renewable energy due to escalating energy demands, declining fossil fuel reservoirs, greenhouse gas emissions, and the unreliability of conventional energy systems. The sun is the only renewable energy source that is available every day for a specific period of time. Solar photovoltaic (PV) technology is known for its direct conversion of sunlight into electricity using the photoelectric effect. However, due to the non-linear electrical characteristics, the power output of solar PV cells is bound to a lower value and can not produce the power of which it is capable. To extract the maximum possible power, the PV cell needs to be operated at its maximum power point (MPP) uninterruptedly under numerous weather conditions. Therefore, an electronic circuit driven by a set of rules known as an algorithm is utilized. To date, the flower pollination algorithm (FPA) is one of the most renowned maximum power point tracking (MPPT) algorithms due to its effective tracking ability at the local and global positions. After an in-depth analysis of the design, strengths, weaknesses, and opportunities of the FPA algorithm, we have proposed an additional filtration and distribution process named “Random walk” along with the ordering of solutions, to improve its efficiency and tracking time. The proposed structure named “Ordered FPA” has outperformed the renowned FPA algorithm under various weather conditions at all the standard benchmarks. Simulations are performed in MATLAB/Simulink.

A novel MPPT technology based on dung beetle optimization algorithm for PV systems under complex partial shade conditions

“…Metaheuristic algorithms, which are inspired by nature and human intelligence, offer great advantages in dealing with problems such as nonlinear optimization problems and thus have gradually become a hot research topic for researchers. Reference 29 – 31 proposed three improved flower pollination algorithms and conducted performance tests under changing weather conditions, which showed that the improved algorithms substantially improved the tracking speed and tracking efficiency. Reference 32 proposed a grid-connected PV MPPT technique using an arithmetic optimization algorithm to optimize the parameters of the proportional-integral (PI) controller, but the introduction of the PI controller increased the complexity of the system.…”

Analysis and mitigation of power quality (PQ) issues in 0.3MW solar photovoltaic system (SPV) connected to grid with MPPT tracker and controlled load using PSCAD software

“…The evaluative lens scrutinizes the efficacy of a shunt compensator within a proposed two-machine system, navigating through MATLAB simulations [23]. Optimization algorithms, epitomized by Ordered FPA and Optimized TCA, carve a path toward heightened efficiency in maximum power point tracking (MPPT) within PV systems [24,25]. The proposed optimal microgrid design, a synergistic amalgamation of solar PV, diesel generators, and battery banks, emerges as a paragon of superior performance, validated through simulations employing HOMER Pro software [26].…”

Adaptive Hybrid MPPT Using Artificial Intelligence for an Autonomous PV System

“…The term "maximum power point tracking" (MPPT) refers to the process of optimizing the power output from a PV system while accurately tracking the Global Maximum Power Point (GMPP) [8][9][10]. A stand-alone PV system comprises essential components such as a PV module, MPPT controller, boost converter, and load.…”