| Autor: |
Duncan, Dauda, Mangwala, Mmoloki, Mtengi, Bokani, Zungeru, Adamu Murtala, Prabaharan, S. R. S., Diarra, Bakary, Ambafi, James Garba, Gaboitaolelwe, Jwaone |
| Předmět: |
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| Zdroj: |
International Review of Electrical Engineering; Mar/Apr2024, Vol. 19 Issue 2, p119-131, 13p |
| Abstrakt: |
An optimal energy harvesting system is required at the remote seismic node due to the constraints of photovoltaic cells and high cost of seismic installations. The conventional approach concentrates on upgrading the hardware and charging to sustain the power at the node. However, the DC-DC converter as electrical conditioning unit and the lead-acid battery as an energy storage medium lose electrical energy, usually characterized by energy leakage and a shorter lifecycle. In the first contribution, a developed algorithm is modelled around the curve-fitting equations and embedded in a common 8-bit microcontroller-based MPPT system. The MPPT algorithm controls the curve equations using polynomial regression and approximates the order of the equation to track optimal electrical power. This enables the prediction of instantaneous duty cycle levels across synchronous buck DC-DC converters for optimal energy conversion. The second contribution is the implementation of a system that involves a dedicated supercapacitor energy storage as a buffer and charge controller for the stability of the current flow through the remote seismic node. Most conventional MPPT predicting procedures initiated will result to expensive computational costs, especially for a relatively high-consuming power system. The contributions of this work allow relatively less computational yet Maximum Power Point Tracking (MPPT) for low-power remote seismic nodes. Therefore, a longer continuous runtime and sustainable electrical energy are achieved. In addition, the proposed approach was validated using Computer Controlled Photovoltaic System (CCPS). The curve fitting equation models linearized the non-linear characteristic relationship between the irradiance, temperature, and voltage levels with the selected photovoltaic module parameters. These models are implemented in C programming code as an algorithm, embedded in an 8-bit microcontroller, and deliver optimal duty cycle levels across the converter. Implying any low-cost microcontroller can be deployed due to simple computational processes. The performance of the proposed approach is evaluated with the CCPS with a deviation between 2.5 % and 5 % based on tabulated results and graphs. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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