<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-20T10:59:47Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/72893" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/72893</identifier><datestamp>2026-06-06T01:06:15Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Ernest J. Moniz, Ignacio J. Peréz-Arriaga and Carlos Batlle López.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Hagerty, John Michael</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Technology and Policy Program.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Engineering Systems Division</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Technology and Policy Program</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2012-09-13T19:00:00Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2012-09-13T19:00:00Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2012</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2012</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/72893</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">808438895</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis (S.M. in Technology and Policy)-- Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2012.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (p. 123-126).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">An increasing awareness of the operational challenges created by intermittent generation of electricity from policy-mandated renewable resources, such as wind and solar, has led to increased scrutiny of the public policies that promote their growth and the regulatory system that maintains operation of a reliable and economically efficient power system. Anecdotal evidence has suggested that hydroelectric generation can provide significant benefits in power systems that have already significantly increased their power generation from intermittent renewable resources. A heuristic-based algorithm for optimizing the scheduling of hydroelectric power generation facilities was developed and integrated into the Low-Emissions Electricity Market Analysis (LEEMA) model to analyze the interaction of generation capacity from wind, thermal, and hydro resources in the economic dispatch of individual generation plants. The algorithm identifies the most costly periods of thermal production, considering fuel, startup and operation and maintenance costs, to determine the optimal schedule of hydro generation within its capacity constraints. The hydrothermal LEEMA model is run on the current Spanish electric power system to identify the impact of introducing hydro generation to a system, varying levels of flexibility in hydro generation, and increasing levels of wind generation. The analysis concludes that hydro generation can significantly reduce the impact of intermittent renewable generation, that the level of flexibility of hydro generation must be understood to determine how beneficial the hydro generation can be, and that hydro generation will delay the most significant impacts of increasing levels of wind generation.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by John Michael Hagerty.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">S.M. in Technology and Policy</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">130 p.</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">M.I.T. theses are protected by &#xd;
copyright. They may be viewed from this source for any purpose, but &#xd;
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permission. See provided URL for inquiries about permission.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Engineering Systems Division.</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Technology and Policy Program.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">The role of hydroelectric generation in electric power systems with large scale wind generation</dim:field>
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   	&lt;Title>The role of hydroelectric generation in electric power systems with large scale wind generation&lt;/Title>
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   	&lt;PublicationDate>2012&lt;/PublicationDate>
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   	&lt;Abstract>An increasing awareness of the operational challenges created by intermittent generation of electricity from policy-mandated renewable resources, such as wind and solar, has led to increased scrutiny of the public policies that promote their growth and the regulatory system that maintains operation of a reliable and economically efficient power system. Anecdotal evidence has suggested that hydroelectric generation can provide significant benefits in power systems that have already significantly increased their power generation from intermittent renewable resources. A heuristic-based algorithm for optimizing the scheduling of hydroelectric power generation facilities was developed and integrated into the Low-Emissions Electricity Market Analysis (LEEMA) model to analyze the interaction of generation capacity from wind, thermal, and hydro resources in the economic dispatch of individual generation plants. The algorithm identifies the most costly periods of thermal production, considering fuel, startup and operation and maintenance costs, to determine the optimal schedule of hydro generation within its capacity constraints. The hydrothermal LEEMA model is run on the current Spanish electric power system to identify the impact of introducing hydro generation to a system, varying levels of flexibility in hydro generation, and increasing levels of wind generation. The analysis concludes that hydro generation can significantly reduce the impact of intermittent renewable generation, that the level of flexibility of hydro generation must be understood to determine how beneficial the hydro generation can be, and that hydro generation will delay the most significant impacts of increasing levels of wind generation.&lt;/Abstract>
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