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...

Full description

Bibliographic Details
Main Author: Murray, Angus
Published: University of Aberdeen 2013
Subjects:
620
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