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Journal : Proceeding of the Electrical Engineering Computer Science and Informatics

Quasi Z-Source Inverter as MPPT on Renewable Energy using Grey Wolf Technique Quota Alief Sias; Irham Fadlika; Irawan Dwi Wahyono; Arif Nur Afandi
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (923.506 KB) | DOI: 10.11591/eecsi.v5.1682

Abstract

Z-Source Inverter (ZSI) is famous power converter who has capability to deal with voltage sags, improved power factor and wide voltage range of output. Quasi Z Source Inverter (QZSI) is the modern ZSI who has continuous current of input and can reduce stress of the passive component. This paper proposes simple boost QZSI circuit as Maximum Power Point Tracking (MPPT) using Grey Wolf Optimization (GWO) algorithm in photovoltaic system. Grey Wolf algorithm has been compared with the Perturb and Observed (P&O) technique for gaining the maximum power from the sun. Both techniques can get the optimum power of solar panel not only at constant sun light condition but also under varying irradiance levels. The value of average power obtained from GWO technique is greater than P&O. Although the value of solar radiation changes, the output voltage remains stable and both algorithms carry on obtaining optimal power of the sun.
Combined Computational Intelligence Approach for the Power System Optimization Problem Arif Afandi; Irham Fadlika; Langlang Gumilar; Yuni Rahmawati; Quota Alief Sias; Irawan Dwi Wahyono; Yunis Sulistyorini; Farrel Candra WA; Michiko Ryuu Sakura A
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (290.959 KB) | DOI: 10.11591/eecsi.v5.1703

Abstract

This paper presents an adoption of a natural phenomenon as Thunderstorm Algorithm (TA) which is applied to solve a problem of the power production composition under various constraints. This work also introduces artificial salmon tracking algorithm (ASTA) for defining the optimal strategy of the power system on the power consumption. Both algorithms are tested on the IEEE-62 bus system as a selected structure for the mathematical cased model. By considering all parameters, results show that ASTA can be applied to predict the power consumption and TA also has good performances while searching the optimal solution. Moreover, the power production can be presented throughout an economic dispatch problem. Technically, this computation demonstrates the optimal solution with fast convergence and short time consumption. These processes also perform smooth and stable characteristics for the searching completion.