Journal
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
Volume 40, Issue 1, Pages 125-135Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ijhydene.2014.10.132
Keywords
Hydrogen energy; Systems optimization; Multi-objective Genetic Algorithm; Experiments; Transient start-up; Life cycle emissions
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Funding
- Edith Cowan University (ECU)
- ECU International Postgraduate Research Scholarship (ECU-IPRS)
- Western Power, a Western Australian State Government owned corporation
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Multi-objective Genetic Algorithms are used to optimise three stand-alone hydrogen systems (WG-H-2, WG/PV-H-2 and PV-H-2) under three different objective functions: minimising (hardware) Net Present Cost - NPC ($), whole Life Cycle Emissions - LCE (CO2-eq/yr) and dumped/Excess Energy -EE (%) at low demand. Optimisations considering Excess Energy haven't been reported before. Simulations are implemented using MATLAB, incorporate experimentally resolved fuel cell start-up transients, and dynamic profiles for wind speed, solar irradiance as well as electric load demand. Results indicate the significance of integrating fuel cell start-up into the LPSP when optimising systems, another aspect not reported before and a modified LPSP is introduced. Furthermore, when sizing energy systems by reducing LCE, EE, and NPC, the favoured hybrid architecture appears to be WG-H-2 over the others studied. For the same LPSP, an interesting finding is that increased renewables penetration (reduced dumped loads) affects the optimised solution but comes at a cost. Copyright (C) 2014, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.
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