Optimal assessment of smart grid based photovoltaic cell operational parameters using simulated annealing

Abstract

With the ever-increasing load demand throughout the globe, natural renewable resources integrated into the existing network architecture for sustainable energy production are gaining considerable significance. Photovoltaic (PV) generation systems is one such technique to deal with the worldwide challenge for achieving green energy and low carbon footprint while simultaneously providing emission free electrical power from solar radiations. In this paper, we consider smart grid architecture connecting the end-users and the utility power plant with solar energy sources through an effective power optimization system. Multiple performance criteria associated with solar cell operation are evaluated and analyzed using the simulated annealing algorithm. These objectives considered for optimization include the cell saturation current, photo-generated current, material band gap, cell temperature, annualized life cycle cost, fill factor and cell efficiency. The formulated optimization conditions are specified in terms of two independent variables of cell ambient temperature and cell illumination. Moreover, the adaption of distinct values of short circuit current coefficients on the light originated current is measured. Through extensive simulation experiments, two disparate annealing procedures of fast annealing and Boltzmann annealing are applied coupled with three categories of temperature update schemes, viz. exponential, logarithmic and linear.

Leveraging PSO algorithms to achieve optimal stand-alone microgrid performance with a focus on battery lifetime

“…The minimum, average, and maximum values of the SOC, represented by SOC min, SOC mean, and SOC max, respectively, are used as indicators for the discharge of the battery and as limitations on the battery's charge [30], [31]. The power output of the batteries, represented by 𝑃 𝑏𝑎𝑡 , should be balanced with the load in order to maintain a stable microgrid system [32], [33]. The demand for load must also be balanced in accordance with the rules of the microgrid system, following in (7).…”

Recent research and developments of degradation assessment and its diagnosis methods for solar PV plant: a review

“…Furthermore, quick annealing and logarithmic temperature updates show the maximum band gap. The quick annealing and linear temperature upgrade technique, on the other hand, improves the material band gap by about 96.7% [13]. Solar panels are designed to withstand exposure to UV radiation, but over time, this can cause the protective coatings on the panels to degrade, leading to reduced efficiency and power output.…”