<?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>2026-09-20T04:24:54Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/70820" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/70820</identifier><datestamp>2026-06-06T01:04:59Z</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">Stephen Connors.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Critz, David Karl</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">System Design and Management Program.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department" lang="en_US">System Design and Management 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="date" qualifier="accessioned">2012-05-15T21:15:08Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2012-05-15T21:15:08Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2011</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2012</dim:field>
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   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">793105210</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis (S.M. in Engineering and Management)--Massachusetts Institute of Technology, Engineering Systems Division, February 2012.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">"September 2011." Cataloged from PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (p. 61-62).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">This study investigated the ability of responsive demand to stabilize the electrical grid when intermittent renewable resources are present. The WILMAR stochastic unit commitment model was used to represent a version of the Danish electricity and heat system with an enhanced level of wind generation. The study found that demand response reduced the marginal operating cost of the electrical system 3%. Demand response reduced CO₂ /SO₂ emissions levels 3% by enabling 11% more generation of wind power. Demand resources representing 25% of nameplate wind power and priced at 150% of a gas turbine's marginal cost were a recommended combination that balanced maximum system improvement at minimal ratepayer impact. The system cost benefits of each study case enabled the calculation of a demand curve representing the system operator's willingness to pay fixed costs for capacity from the pool of operating savings. With demand response, wind generators increased profits, coal plants reduced profits slightly, and natural gas plant profit was cut to almost zero. With high levels of unpredictable renewable resources and limited ability to import power, demand response represents a promising technique to balance the grid at low cost.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by D. Karl Critz.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">S.M. in Engineering and Management</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">71 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 
copyright. They may be viewed from this source for any purpose, but 
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   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
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   <dim:field mdschema="dc" element="subject" lang="en_US">System Design and Management Program.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Power system balancing with high renewable penetration : the potential of demand response</dim:field>
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   	&lt;Title>Power system balancing with high renewable penetration : the potential of demand response&lt;/Title>
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   	&lt;PublicationDate>2012&lt;/PublicationDate>
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        	&lt;DisplayName>Critz, David Karl&lt;/DisplayName>
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    &lt;Keyword>Engineering Systems Division.&lt;/Keyword>
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   	&lt;Abstract>This study investigated the ability of responsive demand to stabilize the electrical grid when intermittent renewable resources are present. The WILMAR stochastic unit commitment model was used to represent a version of the Danish electricity and heat system with an enhanced level of wind generation. The study found that demand response reduced the marginal operating cost of the electrical system 3%. Demand response reduced CO₂ /SO₂ emissions levels 3% by enabling 11% more generation of wind power. Demand resources representing 25% of nameplate wind power and priced at 150% of a gas turbine&amp;apos;s marginal cost were a recommended combination that balanced maximum system improvement at minimal ratepayer impact. The system cost benefits of each study case enabled the calculation of a demand curve representing the system operator&amp;apos;s willingness to pay fixed costs for capacity from the pool of operating savings. With demand response, wind generators increased profits, coal plants reduced profits slightly, and natural gas plant profit was cut to almost zero. With high levels of unpredictable renewable resources and limited ability to import power, demand response represents a promising technique to balance the grid at low cost.&lt;/Abstract>
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