Optimal Parameter Identification of Single-Sensor Fractional Maximum Power Point Tracker for Thermoelectric Generator

Abstract

A thermoelectric generator (TEG) is used for converting temperature difference and into DC directly to electric energy based on the Seebeck effect. This new technology has attracted researchers of sustainable energy. The energy obtained from the TEG depends on the temperature difference between the two sides of the TEG. A reliable MPP “maximum power point” tracker (MPPT) is mandatory to guarantee that the TEG is working close to the MPP under different operational conditions. There are two common methods that have been widely used to track the MPP: hill climbing (HC) and incremental conductance (INR). The HC method is very fast in tracking the MPP; however, oscillation can occur under a high steady state. On the contrary, the INR method needs more time to track the MPP but does not oscillate around the MPP. To overcome these issues, fractional control is adopted. Furthermore, the proposed MPPT requires only a single current sensor, as opposed to conventional MPPTs, which require at least two sensors: current and voltage sensors. The cost of the control system is reduced when the number of sensors is reduced. Hunger games search optimization is used to estimate the parameters of a single sensor optimized fractional MPPT (OFMPPT). During the optimization process, three parameters were assigned as decision variables: proportional gain, integral gain, and order, with the objective function being the TEG’s energy. The results demonstrated the superiority of OFMPPT in both transient and steady state compared to HC and INR.

Uncertainty Observer-Based Control for a Class of Fractional- Order Non-Linear Systems with Non-Linear Control Inputs

“…The purpose of the controller is the optimization of the energy extraction process, a popular approach concerning the utilization of a Maximum Power Point Tracking (MPPT). Notably, a number of studies have explored the use of fractional-order controllers within the MPPT, with noteworthy contributions from works such as those presented in [15][16][17][18].…”

Optimized Fractional Maximum Power Point Tracking Using Bald Eagle Search for Thermoelectric Generation System

“…Despite their benefits, thermoelectric generation systems are constrained by their low efficiency and high cost in comparison to other energy conversion technologies. However, research into more efficient materials, manufacturing techniques, and system design is ongoing in order to enhance the performance of this technology for future widespread use [13,14]. A DC-DC converter matches the load impedance to the internal resistance of the TEG and tracks the maximum power point with an MPPT algorithm, which adjusts the duty cycle of the converter to achieve the desired output voltage and current.…”