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A Benchmarking Framework for Sensitivity and Comparative Analysis of Energy Harvesting Strategies via Retractable Wind Energy Harvesters

Gadola, Guy (2019) A Benchmarking Framework for Sensitivity and Comparative Analysis of Energy Harvesting Strategies via Retractable Wind Energy Harvesters. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Abstract

Wind power is well known for being variable. Our main insight is that one can take advantage of variability by appropriately building wind-energy harvesters that may be stowed/retracted when winds are calm. We refer to harvesters that can be deployed and retracted on command as retractable wind-energy harvesters (RWEHs). Among other advantages, stowed harvesters do not block views, do not constrain avian life, and do not make noise, and thus can increase the neighborliness of harvesting wind near or within a residential community.

RWEH control algorithms help owners to achieve the neighborliness that might be required by an RWEH hosting community while helping RWEHs' efficiency. The stowing requirements, or operation limitation agreements (OLAs), specify conditions when the retractable harvesters should be stowed (e.g., when it is not windy).

In this work, we contribute a suite of benchmarks to compare RWEH control algorithms, three families of control algorithms, and a simulator with which to run the algorithms. The benchmark suite provides workloads formed from the following workload components: 1. specifications of a harvester to be controlled, 2. a set of historical windspeeds from 30 weather stations, and 3. a variety of stowing requirements.

We derived OLAs from a survey of 304 respondents in which survey-takers were asked whether they would support RWEHs viewable from where they live and when the RWEHs should be hidden or stowed.


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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Gadola, Guygpg4@pitt.edugpg4
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairMosse, Danielmosse@cs.pitt.edu
Committee MemberJones, Alexakjones@pitt.edu
Committee MemberMelhem, Ramimelhem@cs.pitt.edu
Committee MemberReed, Greggfr3@pitt.edu
Committee MemberZnati, Taiebznati@pitt.edu
Date: 27 September 2019
Date Type: Publication
Defense Date: 30 July 2019
Approval Date: 27 September 2019
Submission Date: 9 August 2019
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 363
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Computer Engineering
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: renewable energy, benchmarking, control algorithms, wind
Related URLs:
Date Deposited: 27 Sep 2019 15:05
Last Modified: 04 Nov 2019 16:59
URI: http://d-scholarship.pitt.edu/id/eprint/37659

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