Automated Synthesis of Hybrid Energy Network Optimization using A* & Ensemble Forecasting Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/6969z314g

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  • This thesis describes a method for automatically generating and evaluating small-scale off-grid energy systems. Such systems are comprised of components such as solar panels, residential-scale wind turbines, batteries, inverters and charge controllers. These disparate components are assembled into feasible networks through the use of topological optimization and graph grammar rules. The evaluation of candidates is done through the use of A* and Beam search algorithms and ensemble forecasting. Resulting networks are intended to provide users with optimal configurations that are cost-effective and reliable. In the results, the approach is tested with real historical climate data and real user data (from two different residential homes and location) recorded hourly throughout the year. Optimal networks are found to be dependent on the connections between each component within the network, the hour to hour information, and the geographical location of the network.
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  • description.provenance : Submitted by Jonathan Luc (lucjo@oregonstate.edu) on 2015-12-19T04:51:46Z No. of bitstreams: 2 license_rdf: 1379 bytes, checksum: da3654ba11642cda39be2b66af335aae (MD5) LucJonathanH2015.pdf: 1303060 bytes, checksum: a530961490c3b3280b9077318f99971d (MD5)
  • description.provenance : Made available in DSpace on 2015-12-24T00:24:55Z (GMT). No. of bitstreams: 2 license_rdf: 1379 bytes, checksum: da3654ba11642cda39be2b66af335aae (MD5) LucJonathanH2015.pdf: 1303060 bytes, checksum: a530961490c3b3280b9077318f99971d (MD5) Previous issue date: 2015-12-10
  • description.provenance : Approved for entry into archive by Laura Wilson(laura.wilson@oregonstate.edu) on 2015-12-24T00:24:55Z (GMT) No. of bitstreams: 2 license_rdf: 1379 bytes, checksum: da3654ba11642cda39be2b66af335aae (MD5) LucJonathanH2015.pdf: 1303060 bytes, checksum: a530961490c3b3280b9077318f99971d (MD5)
  • description.provenance : Approved for entry into archive by Julie Kurtz(julie.kurtz@oregonstate.edu) on 2015-12-22T19:12:14Z (GMT) No. of bitstreams: 2 license_rdf: 1379 bytes, checksum: da3654ba11642cda39be2b66af335aae (MD5) LucJonathanH2015.pdf: 1303060 bytes, checksum: a530961490c3b3280b9077318f99971d (MD5)

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