Modeling Renewable Microgrids in South Africa
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Modeling Renewable Microgrids in South Africa Bass Connections in Energy Kerim Algul (Pratt '17), Nitish Garg (Pratt MEMP '17), Ryan Hussey (Trinity '17), Cassidee Kido (Pratt '17), Ashley Meuser (Pratt '19), Savini Prematilleke (Pratt '19), Tyler Wakefield (Trinity '18) We would like to thank Bass Connections in Energy for the resources they have provided and thank Dr. Emily Klein, Dr. Josiah Knight, and Chris Dougher for their invaluable guidance. 1.1 billion people around the world have little to no access to reliable electricity. Electricity access is essential to economic growth and development, but cost and physical barriers make it such that connection to the central grid is years away for many rural communities. As shown in Figure 1, many areas in South Africa are still unelectrified. Microgrids can bring power to these communities at a smaller scale, giving them the economic benefits of electricity access without the costs of connecting to the larger grid. Powering the microgrid with energy sources already found in these communities, including wind, solar, and biogas from cattle waste, makes this system self- sustaining with a low environmental impact. This project evaluates the potential for improving electricity access in the KwaZulu-Natal and Eastern Cape regions of South Africa (circled in Figure 1) through the implementation of a microgrid. HOMER, a program developed by the NREL that models microgrids' physical behaviors and costs, was the main tool used in evaluating different microgrid configurations. This analysis proposes three different microgrid configurations and assesses their technical and economic feasibilities. Rural microgrids using combinations of wind, solar PV, and biogas combustion for this region of South Africa are technologically feasible, but will require subsidization from government or NGO sources to be economically viable. However, all three models produce high quantities of excess electricity given their dependence on variable wind and solar coupled with storage. If communities were able to take advantage of unpredictable excess electricity through flexible manufacturing operations that generated income, the systems may become economically viable without subsidization. Likewise, the high likelihood of grid connection throughout SA within 25 years presents opportunities for communities to sell excess electricity to the grid, increasing the economic viability of the systems. Sensitivity: All models are highly sensitive to the availability of cattle waste. In areas that have concentrated livestock operations, the higher availability and lower cost of biomass alter the composition of energy resources to favor biogas combustion, lowering the system cost. Community A: 75 Households Community B: 400 Households Community C: 1250 Households • Electric Load: linear increase with community size • Cattle Waste: linear increase with community size, 2.5 Cattle/Household, 15kg waste/cattle/day, 25% waste reclaimed • Annual electric load increase of 1.5% (Multi-Year Model) • Inflation = 6.5%, Nominal Discount Rate = 8% • Controller capital, replacement, and operation and management costs unknown; assumed zero • Conversion rate: 1 USD: 0.07 ZAR • Average household income: USD $1080.4 • Does not consider cost of transmission infrastructure • <0.01% CH4 reduction per year • Potential 25% N2O reduction per year • Minimal negative battery impacts • Spatial impacts of the wind and solar resources could affect agriculture in the area Community Size (households) Electric Load (kWh/day) Peak Load (kW) PV (kW) Wind (kW) Biogas Generator (kW) Storage (kW) Converter (kW) Cost of Energy Net Present Cost (25 years) Operating Cost Initial Cost 75 98.1 13.81 83.1 0 2 79.47 14.5 $0.273 $204,628 $3,364 $134,145 400 523.3 73.68 349 96 10 298.01 68.1 $0.25 $999,365 $13,815 $709,949 1250 1635.0 230.2 874 207 30 1,142.38 228 $0.243 $3,030,000 $38,622 $2,230,000 Multi-Year Model • PV increases to 130 kW • No change in biogas • Storage increases to 119.16kW • COE increases to $0.317 • Converter increases to 21 kW • NPC increases to $285,797 • OC increases to $4,054 • IC increases to $200,866 Multi-Year Model • PV increases to 420 kW • Wind increases to 900 kW • No change in biogas • No change in storage • COE increases to $0.276 • Converter increases to 90 kW • NPC increases to $1.10 M • OC increases to $14,190 • IC increases to $805,204 Multi-Year Model • PV increases to 1600 kW • Wind increases to 375 kW • No change in biogas • Storage increases to 1,490 kW • COE increases to $0.304 • Converter increases to 350 kW • NPC increases to $4.56M • OC increases to $53,726 • IC increases to $3.44M Introduction Conclusion Model Assumptions Environmental Impacts Figure 1: Electricity Access Map of South Africa Payment Methodology COE ($/kWh) Annual Revenue Present Value (25 Years) NPC ($3,030,000) minus PV HH's pay avg. COE in SA $.100 $59,678 $1,250,240 $1,779,760 HH's pay avg. of 8% of income $.181 $108,040 $2,263,431 $ 776,569 HH pay enough to meet NPC $.243 $145,016 $3,030,000 - Payment Methodology COE ($/kWh) Annual Revenue Present Value (25 Years) NPC ($999,365) minus PV HH's pay avg. COE in SA $.100 $19,100 $400,153 $599,212 HH's pay avg. of 8% of income $.181 $34,573 $724,298 $275,067 HH pay enough to meet NPC $.250 $47,751 $999,365 - Payment Methodology COE ($/kWh) Annual Revenue Present Value (25 Years) NPC ($204,628) minus PV HH's pay avg. COE in SA $.100 $3,581 $75,014 $166,405 HH's pay avg. of 8% of income $.181 $6,482 $135,806 $135,430 HH pay enough to meet NPC $.273 $9,775 $204,628 - Unelectrified Unelectrified without significant population Electrified
Transcript of Modeling Renewable Microgrids in South Africa
ModelingRenewableMicrogrids inSouthAfricaBassConnections
inEnergy
Kerim Algul (Pratt '17), Nitish Garg (Pratt MEMP '17), Ryan Hussey (Trinity '17), Cassidee Kido (Pratt '17), Ashley Meuser (Pratt '19), Savini Prematilleke (Pratt
'19), Tyler Wakefield (Trinity '18)
We would like to thank Bass Connections in Energy for the resources they have provided and thank Dr. Emily Klein, Dr. Josiah Knight, and Chris Dougher for their invaluable guidance.
1.1 billion people around the world have little tono access to reliable electricity. Electricity accessis essential to economic growth and development,but cost and physical barriers make it such thatconnection to the central grid is years away formany rural communities. As shown in Figure 1,many areas in South Africa are still unelectrified.Microgrids can bring power to these communitiesat a smaller scale, giving them the economicbenefits of electricity access without the costs ofconnecting to the larger grid. Powering themicrogrid with energy sources already found inthese communities, including wind, solar, andbiogas from cattle waste, makes this system self-sustaining with a low environmental impact. Thisproject evaluates the potential for improvingelectricity access in the KwaZulu-Natal andEastern Cape regions of South Africa (circled inFigure 1) through the implementation of amicrogrid. HOMER, a program developed by theNREL that models microgrids' physical behaviorsand costs, was the main tool used in evaluatingdifferent microgrid configurations. This analysisproposes three different microgrid configurationsand assesses their technical and economicfeasibilities.
Rural microgrids using combinations of wind, solar PV, andbiogas combustion for this region of South Africa aretechnologically feasible, but will require subsidization fromgovernment or NGO sources to be economically viable.However, all three models produce high quantities ofexcess electricity given their dependence on variable windand solar coupled with storage. If communities were ableto take advantage of unpredictable excess electricitythrough flexible manufacturing operations that generatedincome, the systems may become economically viablewithout subsidization. Likewise, the high likelihood of gridconnection throughout SA within 25 years presentsopportunities for communities to sell excess electricity tothe grid, increasing the economic viability of the systems.Sensitivity: All models are highly sensitive to theavailability of cattle waste. In areas that have concentratedlivestock operations, the higher availability and lower costof biomass alter the composition of energy resources tofavor biogas combustion, lowering the system cost.
CommunityA:75Households
CommunityB:400 Households
CommunityC:1250Households
• ElectricLoad:linearincreasewithcommunitysize• CattleWaste:linearincreasewithcommunitysize,2.5
Cattle/Household,15kgwaste/cattle/day,25%wastereclaimed
• Annualelectric loadincreaseof1.5%(Multi-YearModel)• Inflation=6.5%,NominalDiscountRate=8%• Controllercapital,replacement,andoperationand
managementcostsunknown;assumedzero• Conversionrate:1USD:0.07ZAR• Averagehouseholdincome:USD$1080.4• Doesnotconsidercostoftransmissioninfrastructure
• <0.01%CH4reductionperyear• Potential25%N2Oreductionperyear• Minimalnegativebatteryimpacts• Spatialimpactsofthewindandsolarresourcescould
affectagricultureinthearea
CommunitySize(households)
ElectricLoad
(kWh/day)
PeakLoad(kW)
PV(kW)
Wind(kW)
BiogasGenerator(kW)
Storage(kW)
Converter(kW)
CostofEnergy
NetPresentCost(25years)
OperatingCost InitialCost
75 98.1 13.81 83.1 0 2 79.47 14.5 $0.273 $204,628 $3,364 $134,145400 523.3 73.68 349 96 10 298.01 68.1 $0.25 $999,365 $13,815 $709,9491250 1635.0 230.2 874 207 30 1,142.38 228 $0.243 $3,030,000 $38,622 $2,230,000
Multi-YearModel• PVincreasesto 130kW• Nochangein biogas• Storageincreasesto 119.16kW• COEincreasesto $0.317
• Converterincreasesto 21kW• NPCincreasesto $285,797• OCincreasesto $4,054• ICincreasesto $200,866
Multi-YearModel• PVincreasesto420kW• Windincreasesto900kW• Nochangeinbiogas• Nochangeinstorage
• COEincreasesto $0.276• Converterincreasesto90kW• NPCincreasesto $1.10M• OCincreasesto $14,190• ICincreasesto $805,204
Multi-YearModel• PVincreasesto1600kW• Wind increasesto 375kW• Nochangeinbiogas• Storageincreases to 1,490kW
• COEincreasesto $0.304• Converterincreasesto350kW• NPCincreasesto $4.56M• OCincreasesto $53,726• ICincreasesto $3.44M
Introduction
Conclusion
ModelAssumptions
EnvironmentalImpacts
Figure1:ElectricityAccess MapofSouthAfrica
PaymentMethodology COE($/kWh) AnnualRevenue PresentValue(25Years)
NPC($3,030,000)minusPV
HH'spayavg.COEinSA $.100 $59,678 $1,250,240 $1,779,760HH'spayavg.of8%ofincome $.181 $108,040 $2,263,431 $776,569HHpayenoughtomeetNPC $.243 $145,016 $3,030,000 -
PaymentMethodology COE($/kWh) AnnualRevenue PresentValue(25Years)
NPC($999,365)minusPV
HH'spayavg.COEinSA $.100 $19,100 $400,153 $599,212HH'spayavg.of8%ofincome $.181 $34,573 $724,298 $275,067HHpayenoughtomeetNPC $.250 $47,751 $999,365 -
PaymentMethodology COE($/kWh) AnnualRevenue PresentValue(25Years)
NPC($204,628)minusPV
HH'spayavg.COEinSA $.100 $3,581 $75,014 $166,405HH'spayavg.of8%ofincome $.181 $6,482 $135,806 $135,430HHpayenoughtomeetNPC $.273 $9,775 $204,628 -
Unelectrified
Unelectrified withoutsignificantpopulation
Electrified
