| Work Detail |
The proposed algorithm is designed to harvest maximum power in photovoltaic systems that operate in variable weather scenarios. According to its creators, the new approach can be applied in a low-cost microcontroller.
A Polish-Pakistani research team has developed a Coronavirus Optimization (CVO) algorithm for maximum power point tracking (MPPT) in photovoltaic systems operating under partial and complex shading conditions.
The CVO algorithm mimics the behavior of people trying to stay healthy and slow the spread of COVID-19 by observing containment protocols. It is applied in three steps: social distancing, quarantine and isolation.
“The most notable aspect of the CVO method is that it is capable of terminating at any time without using any parameters,” the researchers emphasize. “This condition arises because recovered and dead individuals continue to expand over time, and the newly infected individual is unable to infect new people. After a certain number of iterations, infected people are expected to increase. Furthermore, as dead and recovered individuals are numerous, unhealthy people decrease over time. Thus, the new infected individuals would be smaller compared to the current size from a specific iteration.”
The algorithm considers uniform irradiance (UI), partial shading (PS) and complex partial shading (CPS) conditions. A mathematical model is implemented to distinguish UI, PS and, especially, CPS conditions in photovoltaic installations. “To evaluate performance from the point of view of efficiency, global maximum search time (GM) and steady-state response, statistical analysis is used,” they explain, noting that the power output of a set is the objective function that must be optimized.
The group compared the performance of the CVO algorithm with that of seven well-known algorithms used for MPPT: Perturb and Observe (P&O); Incremental Conductance (InC); Dragonfly Optimization (DFO); Cuckoo Search (CS); Fruit Fly Optimization (FFO); Particle Swarm Optimization (PSO); and Ant Colony Optimization (ACO).
The analysis showed that the proposed algorithm offers better performance than all the others. “The results show that the CVO algorithm has zero oscillations with the shortest settling and convergence time of 0.49 s and 0.51 s respectively,” the group stressed, noting that it can be easily applied on a low-cost microcontroller. “The proposed CVO algorithm has the highest efficiencies of 99.99%, 99.98%, 99.97% and 99.98 for UI, PS1, PS2 and CPS, consequently, among all the under-considered techniques.”
The scientists presented the algorithm in the study “ A Coronavirus Optimization (CVO) algorithm to harvest maximum power from PV systems under partial and complex partial shading conditions ” under partial and complex shade conditions), published in Energy Reports . “The proposed algorithm is also very necessary to extend its execution to decentralized and distributed photovoltaic energy systems,” they conclude. |
