<?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>2026-09-22T20:18:25Z</responseDate><request verb="GetRecord" identifier="oai:univendspace.univen.ac.za:11602/3006" metadataPrefix="dim">https://univendspace.univen.ac.za/server/oai/request</request><GetRecord><record><header><identifier>oai:univendspace.univen.ac.za:11602/3006</identifier><datestamp>2026-02-10T06:43:45Z</datestamp><setSpec>com_11602_1923</setSpec><setSpec>com_11602_1914</setSpec><setSpec>com_11602_1897</setSpec><setSpec>com_11602_737</setSpec><setSpec>col_11602_2136</setSpec><setSpec>col_11602_738</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">Nemangwele, Fhulufhelo</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="advisor">Ratshitanga, Mukovhe</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="advisor">Maluta, Eric</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author">Netshilonwe, Pfesesani Shammah</dim:field>
   <dim:field mdschema="dc" element="date">2025</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2025-10-16T07:51:45Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2025-10-16T07:51:45Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued">2025-09-05</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="citation" lang="en_ZA">Netshilonwe, P.S. 2025. Techno-Economic Analysis of Microgrids with Distributed Energy Resources in Rural Limpopo Province, South Africa. . . </dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">https://univendspace.univen.ac.za/handle/11602/3006</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="vancouvercitation" lang="en_ZA">Netshilonwe PS. Techno-Economic Analysis of Microgrids with Distributed Energy Resources in Rural Limpopo Province, South Africa. []. , 2025 [cited yyyy month dd]. Available from: </dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="apacitation" lang="en_ZA">Netshilonwe, P. S. (2025). &amp;lt;i&amp;gt;Techno-Economic Analysis of Microgrids with Distributed Energy Resources in Rural Limpopo Province, South Africa&amp;lt;/i&amp;gt;. (). . Retrieved from </dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="chicagocitation" lang="en_ZA">Netshilonwe, Pfesesani Shammah. &amp;lt;i&amp;gt;&amp;quot;Techno-Economic Analysis of Microgrids with Distributed Energy Resources in Rural Limpopo Province, South Africa.&amp;quot;&amp;lt;/i&amp;gt; ., , 2025. </dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="ris" lang="en_ZA">&#xd;
TY  - Dissertation&#xd;
AU  - Netshilonwe, Pfesesani Shammah&#xd;
AB  - The United Nations&amp;apos; sustainable energy development portfolio indicates that around 1.3 billion people globally still lack access to grid-based electricity, underscoring the urgent need for sustainable energy solutions. In Sub-Saharan Africa, about 13% of the population faces limited electricity access due to challenging terrains, inadequate energy policies, and insufficient investment. High costs of extending the electrical grid further complicate the issue. Regions with potential for renewable energy resources, such as solar and wind, offer opportunities to improve energy access. In South Africa&amp;apos;s Limpopo province, while the electrification rate is 96%, some rural areas remain without electricity due to poor grid infrastructure and unreliable supply caused by load shedding and load reduction. Even where electricity is available, rising energy costs pose a significant burden on economically disadvantaged communities. This deficit of energy supply in rural areas needs attention through microgrid optimisation.
This research aims to techno-economically analyse the feasibility of optimising microgrids in rural Limpopo province, focusing on adopting a system with the least net present cost and levelized cost of energy. Three objectives are the main drive to achieve the aim of this research. The first objective is to provide a review of available and potential renewable energy resources in Limpopo province, focusing on their operational status. Currently, solar PV, biomass, and biogas are available, while geothermal, hydropower, and wind are potential resources. The second objective is to analyse the technical and economic aspects of microgrid optimisation to assess its implementation feasibility without hydrogen production. The third objective evaluates the same elements to determine the feasibility of microgrid implementation with hydrogen production.
The Herman-Beta method was employed for peak load estimation, while Homer Pro analysed maximum daily consumption, developed load profiles, and simulated microgrid configurations. The analysis comprised two parts: one focused on microgrids without hydrogen production and the other with it. The first part evaluated PV/Grid and PV/BES/Grid configurations to identify the optimal microgrid solution for each region. For the hydrogen production configurations, three types of PV modules (250 W, 375 W, and 500 W) with a 48V, 14.4 kWh lithium battery were tested, including PV/H2/Grid and PV/BES/H2/Grid setups.
Microgrid optimisation results without hydrogen production show that the PV/Grid configuration is the most cost-effective option across all areas. For Ga-Masekwa, the LCOE is 2.356 R/kWh with an NPC of R 5.4 M. For Ka-Dzingidzingi, the LCOE is 1.292 R/kWh and NPC R 76 M; for Duthuni, 1.216 R/kWh and R 138.7 M; and for Mookgophong NU, 1.197 R/kWh and R 250.3 M. The findings on microgrids with hydrogen production show that the
PV/H2/Grid configuration is the most cost-effective, offering the lowest NPC and LCOE, and a high return on investment. However, producing green hydrogen requires significant energy, increasing the overall system cost.
Conducting a techno-economic analysis of microgrids with distributed energy resources is essential for assessing their feasibility, sustainability, and cost-effectiveness. This study aids in cost-benefit evaluations, system optimisation, financial risk assessments, and the development of resilient alternative energy systems.&#xd;
DA  - 2025-09-05&#xd;
DB  - ResearchSpace&#xd;
DP  - Univen&#xd;
KW  - Techno-economic analysis&#xd;
KW  - Renewable energy reserves&#xd;
KW  - Microgrids&#xd;
KW  - Homer&#xd;
KW  - Herman-Beta method&#xd;
KW  - Hydrogen production&#xd;
KW  - Net present cost&#xd;
KW  - Levelized cost of energy&#xd;
LK  - https://univendspace.univen.ac.za&#xd;
PY  - 2025&#xd;
T1  - Techno-Economic Analysis of Microgrids with Distributed Energy Resources in Rural Limpopo Province, South Africa&#xd;
TI  - Techno-Economic Analysis of Microgrids with Distributed Energy Resources in Rural Limpopo Province, South Africa&#xd;
UR  - &#xd;
ER  - &#xd;
</dim:field>
   <dim:field mdschema="dc" element="description">MSC in Physics</dim:field>
   <dim:field mdschema="dc" element="description">Department of Physics</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract">The United Nations&amp;apos; sustainable energy development portfolio indicates that around 1.3 billion people globally still lack access to grid-based electricity, underscoring the urgent need for sustainable energy solutions. In Sub-Saharan Africa, about 13% of the population faces limited electricity access due to challenging terrains, inadequate energy policies, and insufficient investment. High costs of extending the electrical grid further complicate the issue. Regions with potential for renewable energy resources, such as solar and wind, offer opportunities to improve energy access. In South Africa&amp;apos;s Limpopo province, while the electrification rate is 96%, some rural areas remain without electricity due to poor grid infrastructure and unreliable supply caused by load shedding and load reduction. Even where electricity is available, rising energy costs pose a significant burden on economically disadvantaged communities. This deficit of energy supply in rural areas needs attention through microgrid optimisation.
This research aims to techno-economically analyse the feasibility of optimising microgrids in rural Limpopo province, focusing on adopting a system with the least net present cost and levelized cost of energy. Three objectives are the main drive to achieve the aim of this research. The first objective is to provide a review of available and potential renewable energy resources in Limpopo province, focusing on their operational status. Currently, solar PV, biomass, and biogas are available, while geothermal, hydropower, and wind are potential resources. The second objective is to analyse the technical and economic aspects of microgrid optimisation to assess its implementation feasibility without hydrogen production. The third objective evaluates the same elements to determine the feasibility of microgrid implementation with hydrogen production.
The Herman-Beta method was employed for peak load estimation, while Homer Pro analysed maximum daily consumption, developed load profiles, and simulated microgrid configurations. The analysis comprised two parts: one focused on microgrids without hydrogen production and the other with it. The first part evaluated PV/Grid and PV/BES/Grid configurations to identify the optimal microgrid solution for each region. For the hydrogen production configurations, three types of PV modules (250 W, 375 W, and 500 W) with a 48V, 14.4 kWh lithium battery were tested, including PV/H2/Grid and PV/BES/H2/Grid setups.
Microgrid optimisation results without hydrogen production show that the PV/Grid configuration is the most cost-effective option across all areas. For Ga-Masekwa, the LCOE is 2.356 R/kWh with an NPC of R 5.4 M. For Ka-Dzingidzingi, the LCOE is 1.292 R/kWh and NPC R 76 M; for Duthuni, 1.216 R/kWh and R 138.7 M; and for Mookgophong NU, 1.197 R/kWh and R 250.3 M. The findings on microgrids with hydrogen production show that the
PV/H2/Grid configuration is the most cost-effective, offering the lowest NPC and LCOE, and a high return on investment. However, producing green hydrogen requires significant energy, increasing the overall system cost.
Conducting a techno-economic analysis of microgrids with distributed energy resources is essential for assessing their feasibility, sustainability, and cost-effectiveness. This study aids in cost-benefit evaluations, system optimisation, financial risk assessments, and the development of resilient alternative energy systems.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="sponsorship">University of Venda and Department of Higher Education&amp;apos;s Nurturing Emerging Scholarship Programme</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent">1 online resource (xiv, 89 leaves)</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso">en</dim:field>
   <dim:field mdschema="dc" element="relation" qualifier="requires">PDF</dim:field>
   <dim:field mdschema="dc" element="rights">University of Venda</dim:field>
   <dim:field mdschema="dc" element="subject">Techno-economic analysis</dim:field>
   <dim:field mdschema="dc" element="subject">Renewable energy reserves</dim:field>
   <dim:field mdschema="dc" element="subject">Microgrids</dim:field>
   <dim:field mdschema="dc" element="subject">Homer</dim:field>
   <dim:field mdschema="dc" element="subject">Herman-Beta method</dim:field>
   <dim:field mdschema="dc" element="subject">Hydrogen production</dim:field>
   <dim:field mdschema="dc" element="subject">Net present cost</dim:field>
   <dim:field mdschema="dc" element="subject">Levelized cost of energy</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_ZA">UCTD</dim:field>
   <dim:field mdschema="dc" element="subject" qualifier="ddc">333.794096825</dim:field>
   <dim:field mdschema="dc" element="subject" qualifier="lcsh">Renewable energy sources -- South Africa -- Limpopo</dim:field>
   <dim:field mdschema="dc" element="subject" qualifier="lcsh">Power resources -- South Africa -- Limpopo</dim:field>
   <dim:field mdschema="dc" element="subject" qualifier="lcsh">Renewable natural resources -- South Africa -- Limpopo</dim:field>
   <dim:field mdschema="dc" element="subject" qualifier="lcsh">Agricultural and energy -- South Africa -- Limpopo</dim:field>
   <dim:field mdschema="dc" element="subject" qualifier="lcsh">Solar energy -- South Africa -- Limpopo</dim:field>
   <dim:field mdschema="dc" element="subject" qualifier="lcsh">Wind power -- South Africa -- Limpopo</dim:field>
   <dim:field mdschema="dc" element="title">Techno-Economic Analysis of Microgrids with Distributed Energy Resources in Rural Limpopo Province, South Africa</dim:field>
   <dim:field mdschema="dc" element="type">Dissertation</dim:field>
   <dim:field mdschema="others" element="access-status">embargo</dim:field>
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