Modelling of Indoor Lighting Energy Harvesting System for IoT

Network communications has seen to be evolving with the rise of Internet of
Things (IoT). Low powered IoT devices consume less power and can be powered up
using an energy harvesting system instead of using batteries. Due to the wide
availability of indoor lighting in offices, hospitals and any indoor environment of a
building, energy can be harvested through these sources. A photovoltaic panel that
converts light energy into electrical energy is used to harvest the power from these
indoor lighting. Thus, it is important to have an accurate model of photovoltaic panel
that can predict and estimate its performance at all operating condition. This is
important because most manufacturers provide datasheet values only at open circuit
point, short circuit point and maximum power point. This project discusses a
methodology for modelling an accurate Single Mechanism Five Parameter (1M5P)
model for indoor light energy harvesting.