Dynamic Performance Evaluation of Photovoltaic Three-Diode Model-Based Rung-Kutta Optimizer

Abstract

This paper employs the Rung-Kutta optimizer (RKO) to investigate and analyze the dynamic performance of PV units represented using three-diode model (TDM). The paper can be categorized into three phases; In phase one, efforts are exerted to adapt the proposed optimizer RKO for extracting the optimal unknown parameters of the TDM for two widely used PV units namely PWP201/36 and STM6-40/36 modules. In the second phase, comprehensive comparisons between different recent well-known and challenging optimizers such as interior search algorithm, heap-based optimizer, artificial ecosystem-based optimizer, particle swarm optimizer and many more versus the RKO to indicate its effectiveness and viability. It can be confirmed after fair investigations that the RKO generates the lowest value of the root mean square errors (i.e. 2.050683 mA and 1.712171 mA for TDM PWP201/36 and TDM STM6-40/36 modules, respectively) In addition to that, other comparisons between one-, two- and three-diode models (i.e. SDM, DDM and TDM) using the RKO and other optimizers are made. Lastly, the optimal cropped parameters of the PWP201/36 module are used to create a full Simulink model when it is loaded by switched reluctance motor to analyze and study the dynamic performance of this PV module as a representative case under varied loading scenarios. Many parameters in regards to the SRM and behavior of the PV unit are traced and expansively discussed. It can be stated that the investigated results and comparisons indicate apparently the viability of the RKO improving the PV performance and suggests it to tackle other engineering optimization problems.

Keywords

• Models of solar generating units
• parameters’ extraction
• optimization methods
• dynamic performance assessments
• switched reluctance motor