Loading…
Demand Side Management potentials for mitigating energy poverty in South Africa
South Africa is severally posited to be Africa's most industrialized nation with an economy heavily reliant on energy. With depleted electricity reserve margin which led to massive load shedding and rationing of electricity in 2008, Eskom has stepped up the construction of additional power plan...
Saved in:
Published in: | Energy policy 2017-12, Vol.111, p.298-311 |
---|---|
Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c492t-41273280fc57e65ed0523dd66206749a31cb16ff43ce99865974081e9738d82f3 |
---|---|
cites | cdi_FETCH-LOGICAL-c492t-41273280fc57e65ed0523dd66206749a31cb16ff43ce99865974081e9738d82f3 |
container_end_page | 311 |
container_issue | |
container_start_page | 298 |
container_title | Energy policy |
container_volume | 111 |
creator | Monyei, C.G. Adewumi, A.O. |
description | South Africa is severally posited to be Africa's most industrialized nation with an economy heavily reliant on energy. With depleted electricity reserve margin which led to massive load shedding and rationing of electricity in 2008, Eskom has stepped up the construction of additional power plants to cover for growing supply deficits. Emerging trends however favour Demand Side Management (DSM) initiatives as alternatives to building additional supply capacity due to environmental and economic constraints. This research evaluates the electricity per capita for 2007, 2011 and 2016 on provincial basis assuming 100% and 36.8% residential sector consumption of generated electricity to show declining electricity per capita values. A scenario simulation (for 100%, 50% and 30% household participation) of cloth washers and cloth dryers optimal dispatch is then modelled to show the enormous DSM potentials in terms of electricity cost reduction and supply flexibility. A modified genetic algorithm (MGA) is used in the dispatch of participating loads on the Medupi power plant which has been modelled to operate with carbon capture and sequestration (CCS) technology. DSM potentials of 6938.34MW, 3469.18MW and 2081.51MW are computed for 100%, 50% and 30% household participation for cloth washers and cloth dryers.
•Presents declining electricity per capita across the provinces.•Evaluates DSM potential for dispatching cloth washers and cloth dryers.•Presents energy poverty mitigation ability of DSM application.•Discusses DSM policy arguments on pricing, load dispatch and power plant utilization. |
doi_str_mv | 10.1016/j.enpol.2017.09.039 |
format | article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_1984368020</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0301421517305992</els_id><sourcerecordid>1984368020</sourcerecordid><originalsourceid>FETCH-LOGICAL-c492t-41273280fc57e65ed0523dd66206749a31cb16ff43ce99865974081e9738d82f3</originalsourceid><addsrcrecordid>eNp9kDtPwzAUhS0EEuXxC1gsMSdcP-LHwFCVp1TUoTBbwbkprlqnOG6l_ntSysx0lvOdq_sRcsOgZMDU3bLEuOlWJQemS7AlCHtCRsxoUSit9SkZgQBWSM6qc3LR90sAkMbKEZk94LqODZ2HBulbHesFrjFmuunyEKFe9bTtEl2HHBZ1DnFBMWJa7IfCDlPe0xDpvNvmLzpuU_D1FTlrBwiv__KSfDw9vk9eiuns-XUynhZeWp4LybgW3EDrK42qwgYqLppGKQ5KS1sL5j-ZalspPFprVGW1BMPQamEaw1txSW6Pu5vUfW-xz27ZbVMcTjpmjRTKAIehJY4tn7q-T9i6TQrrOu0dA3cw55bu15w7mHNg3WBuoO6PFA4P7AIm1_uA0WMTEvrsmi78y_8AHtx3EA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1984368020</pqid></control><display><type>article</type><title>Demand Side Management potentials for mitigating energy poverty in South Africa</title><source>International Bibliography of the Social Sciences (IBSS)</source><source>ScienceDirect Journals</source><source>PAIS Index</source><creator>Monyei, C.G. ; Adewumi, A.O.</creator><creatorcontrib>Monyei, C.G. ; Adewumi, A.O.</creatorcontrib><description>South Africa is severally posited to be Africa's most industrialized nation with an economy heavily reliant on energy. With depleted electricity reserve margin which led to massive load shedding and rationing of electricity in 2008, Eskom has stepped up the construction of additional power plants to cover for growing supply deficits. Emerging trends however favour Demand Side Management (DSM) initiatives as alternatives to building additional supply capacity due to environmental and economic constraints. This research evaluates the electricity per capita for 2007, 2011 and 2016 on provincial basis assuming 100% and 36.8% residential sector consumption of generated electricity to show declining electricity per capita values. A scenario simulation (for 100%, 50% and 30% household participation) of cloth washers and cloth dryers optimal dispatch is then modelled to show the enormous DSM potentials in terms of electricity cost reduction and supply flexibility. A modified genetic algorithm (MGA) is used in the dispatch of participating loads on the Medupi power plant which has been modelled to operate with carbon capture and sequestration (CCS) technology. DSM potentials of 6938.34MW, 3469.18MW and 2081.51MW are computed for 100%, 50% and 30% household participation for cloth washers and cloth dryers.
•Presents declining electricity per capita across the provinces.•Evaluates DSM potential for dispatching cloth washers and cloth dryers.•Presents energy poverty mitigation ability of DSM application.•Discusses DSM policy arguments on pricing, load dispatch and power plant utilization.</description><identifier>ISSN: 0301-4215</identifier><identifier>EISSN: 1873-6777</identifier><identifier>DOI: 10.1016/j.enpol.2017.09.039</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Building management ; Capacity building approach ; Carbon sequestration ; Cloth ; Computer simulation ; Construction ; Consumption ; Cost control ; Cost reduction ; Demand Side Management ; Driers ; Economic research ; Economics ; Electric power generation ; Electric power plants ; Electricity ; Electricity consumption ; Electricity per capita ; Electricity pricing ; Energy ; Energy management ; Energy policy ; Energy poverty ; Flexibility ; Genetic algorithms ; Industrialized nations ; Load shedding ; MGA ; Participation ; Poverty ; Power plants ; Rationing ; Residential areas ; Residential energy ; Scenario simulation ; Simulation ; Supply & demand ; Technology ; Values ; Washers & dryers</subject><ispartof>Energy policy, 2017-12, Vol.111, p.298-311</ispartof><rights>2017 Elsevier Ltd</rights><rights>Copyright Elsevier Science Ltd. Dec 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c492t-41273280fc57e65ed0523dd66206749a31cb16ff43ce99865974081e9738d82f3</citedby><cites>FETCH-LOGICAL-c492t-41273280fc57e65ed0523dd66206749a31cb16ff43ce99865974081e9738d82f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27866,27924,27925,33223</link.rule.ids></links><search><creatorcontrib>Monyei, C.G.</creatorcontrib><creatorcontrib>Adewumi, A.O.</creatorcontrib><title>Demand Side Management potentials for mitigating energy poverty in South Africa</title><title>Energy policy</title><description>South Africa is severally posited to be Africa's most industrialized nation with an economy heavily reliant on energy. With depleted electricity reserve margin which led to massive load shedding and rationing of electricity in 2008, Eskom has stepped up the construction of additional power plants to cover for growing supply deficits. Emerging trends however favour Demand Side Management (DSM) initiatives as alternatives to building additional supply capacity due to environmental and economic constraints. This research evaluates the electricity per capita for 2007, 2011 and 2016 on provincial basis assuming 100% and 36.8% residential sector consumption of generated electricity to show declining electricity per capita values. A scenario simulation (for 100%, 50% and 30% household participation) of cloth washers and cloth dryers optimal dispatch is then modelled to show the enormous DSM potentials in terms of electricity cost reduction and supply flexibility. A modified genetic algorithm (MGA) is used in the dispatch of participating loads on the Medupi power plant which has been modelled to operate with carbon capture and sequestration (CCS) technology. DSM potentials of 6938.34MW, 3469.18MW and 2081.51MW are computed for 100%, 50% and 30% household participation for cloth washers and cloth dryers.
•Presents declining electricity per capita across the provinces.•Evaluates DSM potential for dispatching cloth washers and cloth dryers.•Presents energy poverty mitigation ability of DSM application.•Discusses DSM policy arguments on pricing, load dispatch and power plant utilization.</description><subject>Building management</subject><subject>Capacity building approach</subject><subject>Carbon sequestration</subject><subject>Cloth</subject><subject>Computer simulation</subject><subject>Construction</subject><subject>Consumption</subject><subject>Cost control</subject><subject>Cost reduction</subject><subject>Demand Side Management</subject><subject>Driers</subject><subject>Economic research</subject><subject>Economics</subject><subject>Electric power generation</subject><subject>Electric power plants</subject><subject>Electricity</subject><subject>Electricity consumption</subject><subject>Electricity per capita</subject><subject>Electricity pricing</subject><subject>Energy</subject><subject>Energy management</subject><subject>Energy policy</subject><subject>Energy poverty</subject><subject>Flexibility</subject><subject>Genetic algorithms</subject><subject>Industrialized nations</subject><subject>Load shedding</subject><subject>MGA</subject><subject>Participation</subject><subject>Poverty</subject><subject>Power plants</subject><subject>Rationing</subject><subject>Residential areas</subject><subject>Residential energy</subject><subject>Scenario simulation</subject><subject>Simulation</subject><subject>Supply & demand</subject><subject>Technology</subject><subject>Values</subject><subject>Washers & dryers</subject><issn>0301-4215</issn><issn>1873-6777</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>7TQ</sourceid><sourceid>8BJ</sourceid><recordid>eNp9kDtPwzAUhS0EEuXxC1gsMSdcP-LHwFCVp1TUoTBbwbkprlqnOG6l_ntSysx0lvOdq_sRcsOgZMDU3bLEuOlWJQemS7AlCHtCRsxoUSit9SkZgQBWSM6qc3LR90sAkMbKEZk94LqODZ2HBulbHesFrjFmuunyEKFe9bTtEl2HHBZ1DnFBMWJa7IfCDlPe0xDpvNvmLzpuU_D1FTlrBwiv__KSfDw9vk9eiuns-XUynhZeWp4LybgW3EDrK42qwgYqLppGKQ5KS1sL5j-ZalspPFprVGW1BMPQamEaw1txSW6Pu5vUfW-xz27ZbVMcTjpmjRTKAIehJY4tn7q-T9i6TQrrOu0dA3cw55bu15w7mHNg3WBuoO6PFA4P7AIm1_uA0WMTEvrsmi78y_8AHtx3EA</recordid><startdate>20171201</startdate><enddate>20171201</enddate><creator>Monyei, C.G.</creator><creator>Adewumi, A.O.</creator><general>Elsevier Ltd</general><general>Elsevier Science Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7TA</scope><scope>7TB</scope><scope>7TQ</scope><scope>8BJ</scope><scope>8FD</scope><scope>DHY</scope><scope>DON</scope><scope>F28</scope><scope>FQK</scope><scope>FR3</scope><scope>H8D</scope><scope>JBE</scope><scope>JG9</scope><scope>KR7</scope><scope>L7M</scope></search><sort><creationdate>20171201</creationdate><title>Demand Side Management potentials for mitigating energy poverty in South Africa</title><author>Monyei, C.G. ; Adewumi, A.O.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c492t-41273280fc57e65ed0523dd66206749a31cb16ff43ce99865974081e9738d82f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Building management</topic><topic>Capacity building approach</topic><topic>Carbon sequestration</topic><topic>Cloth</topic><topic>Computer simulation</topic><topic>Construction</topic><topic>Consumption</topic><topic>Cost control</topic><topic>Cost reduction</topic><topic>Demand Side Management</topic><topic>Driers</topic><topic>Economic research</topic><topic>Economics</topic><topic>Electric power generation</topic><topic>Electric power plants</topic><topic>Electricity</topic><topic>Electricity consumption</topic><topic>Electricity per capita</topic><topic>Electricity pricing</topic><topic>Energy</topic><topic>Energy management</topic><topic>Energy policy</topic><topic>Energy poverty</topic><topic>Flexibility</topic><topic>Genetic algorithms</topic><topic>Industrialized nations</topic><topic>Load shedding</topic><topic>MGA</topic><topic>Participation</topic><topic>Poverty</topic><topic>Power plants</topic><topic>Rationing</topic><topic>Residential areas</topic><topic>Residential energy</topic><topic>Scenario simulation</topic><topic>Simulation</topic><topic>Supply & demand</topic><topic>Technology</topic><topic>Values</topic><topic>Washers & dryers</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Monyei, C.G.</creatorcontrib><creatorcontrib>Adewumi, A.O.</creatorcontrib><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>PAIS Index</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>Technology Research Database</collection><collection>PAIS International</collection><collection>PAIS International (Ovid)</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>International Bibliography of the Social Sciences</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>International Bibliography of the Social Sciences</collection><collection>Materials Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Energy policy</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Monyei, C.G.</au><au>Adewumi, A.O.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Demand Side Management potentials for mitigating energy poverty in South Africa</atitle><jtitle>Energy policy</jtitle><date>2017-12-01</date><risdate>2017</risdate><volume>111</volume><spage>298</spage><epage>311</epage><pages>298-311</pages><issn>0301-4215</issn><eissn>1873-6777</eissn><abstract>South Africa is severally posited to be Africa's most industrialized nation with an economy heavily reliant on energy. With depleted electricity reserve margin which led to massive load shedding and rationing of electricity in 2008, Eskom has stepped up the construction of additional power plants to cover for growing supply deficits. Emerging trends however favour Demand Side Management (DSM) initiatives as alternatives to building additional supply capacity due to environmental and economic constraints. This research evaluates the electricity per capita for 2007, 2011 and 2016 on provincial basis assuming 100% and 36.8% residential sector consumption of generated electricity to show declining electricity per capita values. A scenario simulation (for 100%, 50% and 30% household participation) of cloth washers and cloth dryers optimal dispatch is then modelled to show the enormous DSM potentials in terms of electricity cost reduction and supply flexibility. A modified genetic algorithm (MGA) is used in the dispatch of participating loads on the Medupi power plant which has been modelled to operate with carbon capture and sequestration (CCS) technology. DSM potentials of 6938.34MW, 3469.18MW and 2081.51MW are computed for 100%, 50% and 30% household participation for cloth washers and cloth dryers.
•Presents declining electricity per capita across the provinces.•Evaluates DSM potential for dispatching cloth washers and cloth dryers.•Presents energy poverty mitigation ability of DSM application.•Discusses DSM policy arguments on pricing, load dispatch and power plant utilization.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.enpol.2017.09.039</doi><tpages>14</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0301-4215 |
ispartof | Energy policy, 2017-12, Vol.111, p.298-311 |
issn | 0301-4215 1873-6777 |
language | eng |
recordid | cdi_proquest_journals_1984368020 |
source | International Bibliography of the Social Sciences (IBSS); ScienceDirect Journals; PAIS Index |
subjects | Building management Capacity building approach Carbon sequestration Cloth Computer simulation Construction Consumption Cost control Cost reduction Demand Side Management Driers Economic research Economics Electric power generation Electric power plants Electricity Electricity consumption Electricity per capita Electricity pricing Energy Energy management Energy policy Energy poverty Flexibility Genetic algorithms Industrialized nations Load shedding MGA Participation Poverty Power plants Rationing Residential areas Residential energy Scenario simulation Simulation Supply & demand Technology Values Washers & dryers |
title | Demand Side Management potentials for mitigating energy poverty in South Africa |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-27T05%3A42%3A12IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Demand%20Side%20Management%20potentials%20for%20mitigating%20energy%20poverty%20in%20South%20Africa&rft.jtitle=Energy%20policy&rft.au=Monyei,%20C.G.&rft.date=2017-12-01&rft.volume=111&rft.spage=298&rft.epage=311&rft.pages=298-311&rft.issn=0301-4215&rft.eissn=1873-6777&rft_id=info:doi/10.1016/j.enpol.2017.09.039&rft_dat=%3Cproquest_cross%3E1984368020%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c492t-41273280fc57e65ed0523dd66206749a31cb16ff43ce99865974081e9738d82f3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1984368020&rft_id=info:pmid/&rfr_iscdi=true |