Hybrid optimization MPPT tech for PV systems under partial shading

Researches in India have used the adaptive network-based fuzzy inference system (ANFIS) and the grey wolf optimization (GWO) algorithm to develop an MPPT technique that reportedly increases the PV source voltage of an array under partial shading conditions.

Proposed DC-DC converter circuit fed PV system with hybrid optimization MPPT controller

Image: Vellore Institute of Technology, scientific reports, Creative Commons License CC BY 4.0

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Researchers at the Vellore Institute of Technology in India have conceived a new hybrid maximum power point tracker (MPPT) method to improve energy yield in PV systems operating under partial shading conditions.

The proposed technique utilizes an adaptive network-based fuzzy inference system (ANFIS), which is a special type of artificial neural network using the Takagi–Sugeno fuzzy inference system. The ANFIS is mainly intended to limit the disadvantages of fuzzy and neural network controllers, and in PV systems its goal is to reduce faults.

“The rules of ANFIS approximate the PV function from a nonlinear way to a linear way,” the scientists said. “Also, this network is used in energy management systems for the smooth operation of PV-fed batteries.”

The new method is also based on the use of controllers relying on the grey wolf optimization (GWO) algorithm, which mimics the social behavior of grey wolves in hunting.

“In this algorithm, there are four major parameters which are alpha, beta, delta, plus omega,” the research team noted. “The alpha (α) variable is illustrated as an optimal solution from the different possible solutions or leader wolf. Similarly, the beta (β), and delta (δ) constants are selected as the second, and third-best optimal solutions from the search space. The normal wolf solution is given by omega (ω).”

The proposed configuration, according to its creators, provides for optimized wolves’ exploration convergence ratio, while balancing their population and search for space. It also ensures that PV voltage is supplied to the power DC-DC converter for enhancing the PV source voltage to meet future microgrid voltages.

The scientists tested the performance of the MPPT technique and the associated solar system-fed converter circuit in a series of simulations conducted on a 3-diode model PV array via the Matlab-Simulink software. A source-side capacitor filtered the PV power ripples and protected the switches at rapid variations of supply voltages. A supply inductor charged the supply voltage of PV under the MOSFET forward bias condition and smoothened the supply voltage.

“The MOSFET is used because its properties are less gate-to-source voltage required for going to conduct, operates high efficiency at low rated voltages, consists of high source resistance to limit the gate current, quick working response, plus less possibility of damage,” the academics explained.

The simulation considered parameters such as oscillations across MPP, output power extraction, settling time of the MPP, dependency on the PV modeling, operating duty value of the converter, error finding accuracy of MPPT, algorithm complexity, tracking speed, periodic tuning required, and the number of sensing parameters utilized.

The research group claimed the new hybrid MPPT technique can provide “good results” when compared with other MPPT methods, with the PV source voltage rising from one level to another level. “The merits of the utilized converter are easy understanding, high reliability, plus lower price to implement,” it added.

The findings were introduced in the paper “A novel on design and implementation of hybrid MPPT controllers for solar PV systems under various partial shading conditions,” published in scientific reports.

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