Performance evaluation of optimal photovoltaic-electrolyzer system with the purpose of maximum Hydrogen storage

A. Khalilnejad, A. Sundararajan, A. I. Sarwat

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

Power electronics-based electrolyzer systems are prevalently in current use. This paper proposes the more recently employed directly coupled photovoltaic (PV) electrolyzer systems. Equipped with accurate electrical models of the advanced alkaline electrolyzer, PV system and Hydrogen storage tank simulated using MATLAB, the system's performance for a full week is analyzed using Miami, Florida's meteorological data. A multi-level Genetic Algorithm (GA)-based optimization facilitates maximum hydrogen production, minimum excess power generation, and minimum energy transfer loss. The crucial effect of temperature on the overall system performance is also accounted for by optimizing this parameter using GA, maintaining operating conditions close to the Maximum Power Point (MPP) of the PV array. The results of the analysis have been documented to show that the optimal system for a 10 kW electrolyzer can produce, on an average, Hydrogen of 0.0176 mol/s, when the system is operating with 6.3% power loss and 2.4% power transfer loss.

Original languageEnglish
Title of host publicationConference Record - 2016 IEEE/IAS 52nd Industrial and Commercial Power Systems Technical Conference, I and CPS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467386715
DOIs
StatePublished - Jun 10 2016
Externally publishedYes
Event52nd IEEE/IAS Industrial and Commercial Power Systems Technical Conference, I and CPS 2016 - Detroit, United States
Duration: May 1 2016May 5 2016

Publication series

NameConference Record - Industrial and Commercial Power Systems Technical Conference
Volume2016-June

Conference

Conference52nd IEEE/IAS Industrial and Commercial Power Systems Technical Conference, I and CPS 2016
Country/TerritoryUnited States
CityDetroit
Period05/1/1605/5/16

Funding

This work is supported by the National Science Foundation under Grant No. 1541108. Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and not necessarily reflect the views of NSF.

FundersFunder number
National Science Foundation1541108

    Keywords

    • Advanced alkaline electrolyzer
    • Genetic Algorithm
    • Hydrogen production
    • Photovoltaic
    • directly coupled system

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