Power management for storage mechanisms including battery, supercapacitor, and hydrogen of autonomous hybrid green power system utilizing multiple optimally-designed fuzzy logic controllers

R. Zahedi and M.M. Ardehali

Energy, 2020, vol. 204, issue C

Abstract: For proper power management of autonomous hybrid green power systems (HGPS), the fluctuating nature of renewable energy sources necessitates considerations for control system and integration of storage mechanisms with short-term and long-term operational characteristics. Further, operational and maintenance costs as well as reliability of HGPS to meet time varying load must be accounted for in the design process of controllers. The goal of this study is to develop multiple optimally-designed fuzzy logic controllers (FLCs) for power management of storage mechanisms including battery stack (BT), supercapacitor (SC), and hydrogen tank based on minimum operational cost and acceptable level of reliability for simulation modeling and operational performance analyses of an autonomous HGPS consisting of wind turbines, photovoltaic collectors, and fuel cell, based on actual load data. It is found that the optimization of rule bases as well as membership functions of multiple FLCs results in lower current fluctuations for BT and SC, while operation and maintenance costs and loss of power supply probability values are significantly reduced. The results confirm the importance of utilizing SC in addition to the BT and hydrogen tank, as the power density of SC provides for substantial peak power reduction during autonomous HGPS operation. It is determined that the design optimization of multiple FLCs for power management of storage mechanisms achieves an increase in hydrogen storage level to 98% at the end of one week operation, a reduction of 56% in the average current for BT stack, and participation rate of 23.63% for SC during highest hourly load peak.

Keywords: Power management; Hybrid green power system; Battery; Supercapacitor; Hydrogen; Fuel cell; Fuzzy logic control; Optimization (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:204:y:2020:i:c:s0360544220310422

DOI: 10.1016/j.energy.2020.117935

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