IMPACT OF EMBEDDED GENERATION
What will PV installations cost the municipality?
Sharing Of Renewable Energy And Energy Efficiency Innovations And Benefits:
Small Scale Embedded Generation Workshop
Karin Kritzinger
25 November 2014
Victoria Hall, Caledon
2014/12/11
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The Centre for Renewable and Sustainable Energy Studies was established in 2007 to facilitate and stimulate
activities in renewable energy study and research at Stellenbosch University.
The Department of Science and Technology has been funding the Renewable and Sustainable Energy (RSE) Hub
at Stellenbosch University since its establishment in August 2006. The aims of the RSE Hub are to develop
human capital, deepen knowledge, and stimulate innovation and enterprise in the field of RSE. Currently the
DST is still sponsoring the work of the Centre with an annual grant administrated by the National Research
Foundation.
Stellenbosch University was designated as the Specialisation Centre in Renewable Energy Technology as part of
the Eskom Power Plant Engineering Institute (EPPEI). The research and teaching activities sponsored by Eskom
focus on concentrating solar power (CSP) and wind energy and also includes the Eskom Chair in Concentrating
Solar Power.
The Sasol Technology group sponsored the new facilities for the Centre for Renewable and Sustainable Energy
Studies as well as the work and facilities of the Solar Thermal Energy Research Group at Stellenbosch University.
Outline
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Background
Studies
Load Profiles
Individual data
Investment decision
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Outline
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Background
Studies
Load Profiles
Individual data
Investment decision
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Background
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Background
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Background
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Background
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Background
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Background
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Background
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Background
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Background
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2014/12/11
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Wildpoldsried produces 321% more energy than it needs
Wildpoldsried, a small village in Germany produces 321% more energy than it needs, and
sells it for $5.7 million.
2014/12/11
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Outline
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Background
Studies
Load Profiles
Individual data
Conclusion
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Eskom – Tobias Bischof- Niemz
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Eskom – Tobias Bischof- Niemz
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Eskom – Tobias Bischof- Niemz
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Eskom – Tobias Bischof- Niemz
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Eskom – Tobias Bischof- Niemz
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SEA – Revenue Impact model
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SEA – Revenue Impact model
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SEA – Revenue Impact model
A 50-85% uptake of EE interventions would be realised across all the economic sectors over the
next 10 years.
PV uptake varies between municipalities – Cape Town 15-50% residential; 15-50% commercial;
3-15% industrial. EThekwini 3-15% residential; 15-50% commercial; 3-15% industrial. Ekurhuleni
– 2-15% residential; 15-50% commercial; 15-50% industrial. Large scale uptake is only expected
thereafter, as the financial case improves.
Uptake of PV in the commercial sector could be as high as 15-50% if current tariff conditions
continue to apply.
Assuming the above uptakes, the overall revenue losses in 10 years’ time for the metro
electricity departments are projected to be between 3-11% (Cape Town), 5-15% (Ekurhuleni)
and 8-15% (eThekwini). The main areas where these losses will occur are residential solar water
heating and EE across all the economic sectors. The impact of PV is relatively minimal, except
potentially in the sections of the commercial sector where the energy tariff is particularly high
(usually small commercial tariff customers).
The overall impact of revenue loss on the poor is a question of political decision making, but up
to 80% of the cross subsidisation of the low income tariff could be affected, or up to half of the
total amount of revenue allowed to be transferred to the rates account.
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SEA – Revenue Impact model
A 50-85% uptake of EE interventions would be realised across all the economic sectors over the
next 10 years.
PV uptake varies between municipalities – Cape Town 15-50% residential; 15-50% commercial;
3-15% industrial. EThekwini 3-15% residential; 15-50% commercial; 3-15% industrial. Ekurhuleni
– 2-15% residential; 15-50% commercial; 15-50% industrial. Large scale uptake is only expected
thereafter, as the financial case improves.
Uptake of PV in the commercial sector could be as high as 15-50% if current tariff conditions
continue to apply.
Assuming the above uptakes, the overall revenue losses in 10 years’ time for the metro
electricity departments are projected to be between 3-11% (Cape Town), 5-15% (Ekurhuleni)
and 8-15% (eThekwini). The main areas where these losses will occur are residential solar water
heating and EE across all the economic sectors. The impact of PV is relatively minimal, except
potentially in the sections of the commercial sector where the energy tariff is particularly high
(usually small commercial tariff customers).
The overall impact of revenue loss on the poor is a question of political decision making, but up
to 80% of the cross subsidisation of the low income tariff could be affected, or up to half of the
total amount of revenue allowed to be transferred to the rates account.
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SEA – PV financial feasibility model
2014/12/11
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GreenCape
2014/12/11
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GreenCape
2014/12/11
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Mott McDonald
The author of this paper proposes that all three SSPVEG mechanisms (selfconsumption, Net-Metering and FIT) are adopted in South Africa but that a phased
approach may be less threatening to all stakeholders involved.
2014/12/11
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City of Cape Town
Potential impact on municipal revenue of small scale own generation and energy
efficiency
Hilton Trollip, Vivienne Walsh, Sumaya Mahomed, Brian Jones
2012
2014/12/11
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City of Cape Town
Presenting PV own-generation as a most-costly option among other renewable
energy/energy efficiency options that could be adopted at significant scale suggests
that a combination of PV and other options could lead to revenue losses of between
17% and 25% of ESD operating expenses from the residential sector alone and
significant additional potential losses driven by similar dynamics in the commercial
sector.
2014/12/11
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City of Cape Town
Figure 7 – Average typical PV production winter
profile overlap with household load profile
2
June
1
TROUGH
Average kW demand
over half hour kW
PV - 21-23 June
0.5
Average kW demand
for geysers
0
0
1.1
2.2
3.3
4.4
5.5
6.6
7.7
8.8
9.9
11
12.1
13.2
14.3
15.4
16.5
17.6
18.7
19.8
20.9
22
23.1
kW
1.5
City of Cape Town
Figure 8 – Average typical PV production midsummer profile overlap with household load
profile
2
January
kW
1.5
1
TROUGH
Household profile
PV - 21-23 Jan
Geyser
0.5
0
Difference
Brian Jones.
2014/12/11
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Potential uptake of rooftop PV
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Impact of PV on Riversdale
• Rooftop PV will reduce electricity sales
• By how much?
– Understand Riversdale’s current electricity revenue
– Understand potential uptake of rooftop PV in Riversdale
• By only a small amount
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–
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Conservative uptake – 146kWp: 0.2% of electricity sales
Generous uptake – 448kWp: 0.66% of electricity sales
All rooftops – 9 840kWp: 11% of electricity sales
Note: max 1 384kWp allowed for Riverdale (NRS097-2-3)
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Outline
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Background
Studies
Load Profiles
Individual data
Investment decision
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Profile view
• A “seasonal version” of same DPET load shape will be found
in GLF load sub-class library.
• A “localised” version of GLF will be found in DProfile mixer for
same given consumption level
• All the tools referencing this consumer class (ie demographic)
are based upon same underlying load models.
• Their visualisation may differ depending upon the analytic
required for their application.
Marcus Dekenah - Enerweb
2014/12/11
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Scenarios Selection
• Characteristic
load profiles
– LSM 7-8
– Variation of load
and generation
– Single-phase vs.
three-phase
– Solar Water
Heating
(Excluded in first
phase)
Dr Gerhard Botha - Eskom
2014/11/12
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Supply Options and Resultant
Profiles
Transformer 2: Industrial, Office Park, CBD
Option 1
Transformer 1: HI Res, Low Income, Med Income
Transformer 2: Industrial, Office Park, Medium Income
Option 2
Transformer 1: CBD, HI Res, Low Income
12/11/2014
Mondi Soni - Eskom
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Average weekday peak
electricity usage of a typical
residential suburban customer
• The residential sector uses
about 17% of the total
electricity generated in
South Africa
16000
14000
12000
10000
Industry
8000
Suburban
6000
Agric
Township
Electrification
Commerce
Mining
Suburban
Industry
Mining
4000
Commerce
2000
Electrification
0
Township
1 2 3
4 5 6
7
8
9 10 11
12 13 14
15 16 17
18 19 20
21 22 23
Agric
• From 7am to 10am in the
morning, and 5pm to 9pm in the
evening – periods of peak
demand in South Africa –
residential demand is up to 35%
of the total demand required.
Source:
•Total End Use Consumption – Eskom ISEP/DSM
•Eskom Integrated Demand Management
Vashna Singh
Barry McColl
Barry McColl
Households usage of
electricity
100.00%
Household has a connection to the
mains electricity supply (%)
90.00%
Electricity for cooking
80.00%
Electricity for lighting
70.00%
Electricity for space heating
60.00%
Note: Cooking, lighting and space
heating expressed as a percentage of
households that are connected to
electricity supply.
50.00%
40.00%
Decrease from 57% in
2005 to 37% in 2013
30.00%
20.00%
Choice of energy usage
for space heating as ‘none’
increased from 12.2% in
2006 to 46% in 2013.
10.00%
0.00%
2005
2006
2007
2008
2009
2010
2011
2012
2013
Sustainability and Innovation -
2014/12/11
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Johannes C Jordaan - Economic Modelling Solutions.
Direct price elasticity of demand
Poorest 10%
1
2
Richest 2%
3
4
Deciles
5
6
7
8
9
10
11
12
13
14
15
(0.01)
(0.05)
(0.07)
Elasticity
(0.10)
Use 9% of
kWh in 2011
(0.15)
(0.15)
(0.19)
(0.20)
(0.18)
(0.20)
(0.25)
(0.24)
(0.25)
(0.27)
(0.26)
Percentiles
(0.27)
(0.28)
(0.28)
(0.30)
Use 4.4% of
kWh in 2011
(0.35)
R40 218
consumption (inkind) per month
per hh
(0.30)
(use 30% of kWh
in 2011)
(0.31)
R8 586 consumption (inkind) per month per hh
Sustainability and Innovation - Support, Lead, Innovate
2014/12/11
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Johannes C Jordaan - Economic Modelling Solutions.
Outline
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Background
Studies
Load Profiles
Individual data
Investment decision
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Energy Efficiency
Average monthly consumption per year
1400
1200
1000
800
600
1263
400
704
458
200
369
300
0
1983
1985
2006
2008
2013
PV generation and load
PV generation and load
Consumption from
CoCT
Dec-13
506
Jun-14
898
Consumption from
PV
127
89
Total Consumption
633
988
PV Production
219
150
PV Fed in
92
60
Dec 1 & 2
June 1 & 2
Outline
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Background
Studies
Load Profiles
Individual data
Investment decision
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Investment decision
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Installation cost
Admin cost (time)
New meter
Sign off
Tariff
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Thank you
karink@sun.ac.za
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