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Renewable Energy Investment Planning...

Ghalebani, Alireza.

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Renewable Energy Investment Planning and Policy Design.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Renewable Energy Investment Planning and Policy Design./
Author:	Ghalebani, Alireza.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2016,
Description:	119 p.
Notes:	Source: Dissertation Abstracts International, Volume: 77-09(E), Section: B.
Contained By:	Dissertation Abstracts International77-09B(E).
Subject:	Industrial engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10107827
ISBN:	9781339712109

Renewable Energy Investment Planning and Policy Design.
Ghalebani, Alireza.

Renewable Energy Investment Planning and Policy Design. - Ann Arbor : ProQuest Dissertations & Theses, 2016 - 119 p.

Source: Dissertation Abstracts International, Volume: 77-09(E), Section: B.

Thesis (Ph.D.)--University of South Florida, 2016.

This item is not available from ProQuest Dissertations & Theses.

In this dissertation, we leverage predictive and prescriptive analytics to develop decision support systems to promote the use of renewable energy in society. Since electricity from renewable energy sources is still relatively expensive, there are variety of financial incentive programs available in different regions. Our research focuses on financial incentive programs and tackles two main problem: 1) how to optimally design and control hybrid renewable energy systems for residential and commercial buildings given the capacity based and performance based incentives, and 2) how to develop a model-based system for policy makers for designing optimal financial incentive programs to promote investment in net zero energy (NZE) buildings.

ISBN: 9781339712109Subjects--Topical Terms:

526216
Industrial engineering.

Renewable Energy Investment Planning and Policy Design.
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245 1 0 $a Renewable Energy Investment Planning and Policy Design.
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300 $a 119 p.
500 $a Source: Dissertation Abstracts International, Volume: 77-09(E), Section: B.
500 $a Adviser: Tapas K. Das.
502 $a Thesis (Ph.D.)--University of South Florida, 2016.
506 $a This item is not available from ProQuest Dissertations & Theses.
520 $a In this dissertation, we leverage predictive and prescriptive analytics to develop decision support systems to promote the use of renewable energy in society. Since electricity from renewable energy sources is still relatively expensive, there are variety of financial incentive programs available in different regions. Our research focuses on financial incentive programs and tackles two main problem: 1) how to optimally design and control hybrid renewable energy systems for residential and commercial buildings given the capacity based and performance based incentives, and 2) how to develop a model-based system for policy makers for designing optimal financial incentive programs to promote investment in net zero energy (NZE) buildings.
520 $a In order to customize optimal investment and operational plans for buildings, we developed a mixed integer program (MIP). The optimization model considers the load profile and specifications of the buildings, local weather data, technology specifications and pricing, electricity tariff, and most importantly, the available financial incentives to assess the financial viability of investment in renewable energy. It is shown how the MIP model can be used in developing customized incentive policy designs and controls for renewable energy system.
590 $a School code: 0206.
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