Modelling and heuristic optimization of a hydrogen producing renewable energy system
The reliable supply of hydrogen to a vehicle re-fuelling station has been tackled in this thesis. A currently operational system based on supplying energy from a bio-generator, fuelled from biogas generated by organic matter in an Anaerobic Digester, formed the basis of an expanded renewable energy...
Main Author: | |
---|---|
Published: |
University of Aberdeen
2013
|
Subjects: | |
Online Access: | http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.582687 |
id |
ndltd-bl.uk-oai-ethos.bl.uk-582687 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-bl.uk-oai-ethos.bl.uk-5826872015-12-03T04:01:00ZModelling and heuristic optimization of a hydrogen producing renewable energy systemMurray, Angus2013The reliable supply of hydrogen to a vehicle re-fuelling station has been tackled in this thesis. A currently operational system based on supplying energy from a bio-generator, fuelled from biogas generated by organic matter in an Anaerobic Digester, formed the basis of an expanded renewable energy system. The criterion for the new design was the supply of energy to an electrolyser/compressor/storage system at minimum cost and minimum interruption to supply. By separating hydrogen production from energy generation, the operating parameters of the electrolyser and compressor were optimized, leading to an energy load profile that guaranteed a reliable supply of hydrogen sufficient to fuel the daily needs of up to two hydrogen fuelled vehicles. Based on the energy load profile, a renewable energy system was designed around the existing bio-generator. A multi-objective optimization by Genetic Algorithm was employed to design a hybrid renewable energy system that minimized lifetime costs and unmet load. The resulting design consisted of a mixture of wind turbines, batteries, inverters/rectifiers, as well as the bio-generator. A control strategy that directed the interaction of all components was also produced. Multi-objective optimization by Genetic Algorithm was found to be a reliable, efficient method in designing a complex hybrid renewable energy system with non-linear characteristics. The results of modelling and simulation showed that an uninterrupted supply of energy could be produced, based on specific meteorological conditions, at a minimal cost. The research has shown that it is possible to develop a design that produces hydrogen reliably purely from renewable energy sources. The design is flexible enough to integrate other renewable energy sources and technologies as they develop.620Renewable energy sourcesUniversity of Aberdeenhttp://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.582687http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=202138Electronic Thesis or Dissertation |
collection |
NDLTD |
sources |
NDLTD |
topic |
620 Renewable energy sources |
spellingShingle |
620 Renewable energy sources Murray, Angus Modelling and heuristic optimization of a hydrogen producing renewable energy system |
description |
The reliable supply of hydrogen to a vehicle re-fuelling station has been tackled in this thesis. A currently operational system based on supplying energy from a bio-generator, fuelled from biogas generated by organic matter in an Anaerobic Digester, formed the basis of an expanded renewable energy system. The criterion for the new design was the supply of energy to an electrolyser/compressor/storage system at minimum cost and minimum interruption to supply. By separating hydrogen production from energy generation, the operating parameters of the electrolyser and compressor were optimized, leading to an energy load profile that guaranteed a reliable supply of hydrogen sufficient to fuel the daily needs of up to two hydrogen fuelled vehicles. Based on the energy load profile, a renewable energy system was designed around the existing bio-generator. A multi-objective optimization by Genetic Algorithm was employed to design a hybrid renewable energy system that minimized lifetime costs and unmet load. The resulting design consisted of a mixture of wind turbines, batteries, inverters/rectifiers, as well as the bio-generator. A control strategy that directed the interaction of all components was also produced. Multi-objective optimization by Genetic Algorithm was found to be a reliable, efficient method in designing a complex hybrid renewable energy system with non-linear characteristics. The results of modelling and simulation showed that an uninterrupted supply of energy could be produced, based on specific meteorological conditions, at a minimal cost. The research has shown that it is possible to develop a design that produces hydrogen reliably purely from renewable energy sources. The design is flexible enough to integrate other renewable energy sources and technologies as they develop. |
author |
Murray, Angus |
author_facet |
Murray, Angus |
author_sort |
Murray, Angus |
title |
Modelling and heuristic optimization of a hydrogen producing renewable energy system |
title_short |
Modelling and heuristic optimization of a hydrogen producing renewable energy system |
title_full |
Modelling and heuristic optimization of a hydrogen producing renewable energy system |
title_fullStr |
Modelling and heuristic optimization of a hydrogen producing renewable energy system |
title_full_unstemmed |
Modelling and heuristic optimization of a hydrogen producing renewable energy system |
title_sort |
modelling and heuristic optimization of a hydrogen producing renewable energy system |
publisher |
University of Aberdeen |
publishDate |
2013 |
url |
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.582687 |
work_keys_str_mv |
AT murrayangus modellingandheuristicoptimizationofahydrogenproducingrenewableenergysystem |
_version_ |
1718143446254878720 |