Optimal Photovoltaic Energy Harvesting System at Remote Seismic Node

Abstract

We have developed an optimal Photovoltaic Energy Harvesting System at the remote seismic node to sustain the remote seismic node. This node is a continuous application for monitoring the geodynamics of the earth for long-term and persistent. However, due to the constraints of solar cells and low funding of seismic installations, a simple and optimal energy harvesting system is required at the remote seismic node. So, this novel design focuses on using fitting curve equations as models to extract parameters of the photovoltaic module. This is to predict instantaneous duty cycle levels across synchronous buck DC-DC converter for optimal energy conversion. The converter regulates the supercapacitor as energy storage to deliver longer runtime at the remote seismic node. The conventional techniques concentrate on improving the hardware and charging to sustain power at the remote seismic node. Yet, energy is lost by the DC-DC converter, and the lead-acid battery usually used exhibits energy leakage and a shorter lifecycle. Thus, the contribution of this work is to design a relatively less computational maximum power point tracking based on a simple curve fitting technique to sustain the lifecycle of the node. In this proposed design, selected light-dependent resistors to mimic a pyranometer and formulate equations from specific photovoltaic module characteristics are considered. This correlates the optimal duty cycle levels with the ambient irradiance and temperature variables, while validation was done with an experimental setup of Computer Controlled Photovoltaic System. The non-linear characteristics relationship between the irradiance, temperature, and voltage levels is linearized with the selected PV module parameters in curve fitting equation models. These models are implemented in C programming as an algorithm to be processed by 8-bit microcontroller and deliver duty cycle levels across pulse width modulation to drive the converter. The performance of our approach is evaluated with the Computer Controlled Photovoltaic System with a deviation between 2.5 % to 5 % based on tabulated results and graphs.