Balancing of Variable Renewable Generation - chalmers.se20och%20milj%F6/...3 Variable renewable...
Transcript of Balancing of Variable Renewable Generation - chalmers.se20och%20milj%F6/...3 Variable renewable...
Dept. of Electric Power Systems
• Two professors, one associate professor, two assistant professors
• Four research groups (each group has 5–10 Ph.D. students and a few postdocs)
- Power System Stability and Control
- Smart Transmission Systems Laboratory
- Power System Operation and Planning
- Electricity Market Research
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Variable renewable generation
• Available capacity is depending on weather.
• High investment costs, negligible variable costs run at available capacity (nondispatchable).
• Examples:
- Run-of-the-river hydro power
- Wind power
- Photovoltaics
- Wave energy
- Tidal energy
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Challenges of nondispatchable generation in power system operation and planning
• Variability. Nondispatchable generation is varying continu-ously depending on weather conditions.
• Forecast errors. Nondispatchable generation can be difficult to predict even for the next day.
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Variability
• Nondispatchable gener-ation is not the only thing varying in a power system.
• Power systems are designed to manage large variations!
MWh
10 000
load
0
20 000
12 24
25 January 201327 July 2013
Source: Svenska kraftnät
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Wind power variations
Storm hits western Denmark
HVDC
HVDC
HVDC
StenungsundKungälvGöteborg
Varberg
Falkenberg
Gnosjö
Halmstad
Ängelholm
Helsingborg
LundMalmö
Trelleborg
(220 k
V)
(220
kV)
(300 k
V)
Lübeck
Flensburg
RinghalsHelsing-borg
Cøpen-hagen
Gothen-burg
MalmöKarlshamn
Norrköping
Oskars-hamn
Hasle
RjukanOslo
Stockholm
Enköping
Nea
Trondheim Umeå
Sundsvall
Loviisa
Olkiluoto
Tallin
HVDC
Kristiansand
Rauma
Forsmark
0 100 200 km
Norway
Finland
Denmark
HelsingforsÅbo
Vasa
Tammerfors
Viborg
Slupsk
reda
ktör
erna
AB
2009
HVDC
HVDC
HVDC
Rostock
The Swedish Natural GasNetwork(high pressure)
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Consequences of variability
• Some units must deviate from their optimal working point.
• Larger need for automatic frequency control.
• Larger need for real-time balancing.
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%10
5
7
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Forecast errors
r
• Most of the trading is done in the day-ahead market.
• Wind power generation is difficult to forecast on the day before.
Day-ahead forecast
–50 +500 +10 +40+30+20–10–20–40 –30
0
MW
forecast erro
0
5
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Intra-day forecast
Forecast error of 100 MW wind power
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Consequences of forecast errors
• Inefficient usage of power system resources.
• Larger need for intra-day trading.
• Larger need for real-time balancing.
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Balancing resources
• Planning target for 2020: 30 TWh wind power
- Equals about 12 000 MW installed capacity.
- Actual wind power generation 2013: 10 TWh.
• A large-scale development of nondispatchable generation will need more balancing resources.
• There is a correlation between nondispatchable generation and reserves.
- High wind power generation less usage of conven-tional generation capacity available for up-regulation.
• How can we utilise the balancing capacity in the most efficient way?
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Balancing using hydro power
• How flexible is the existing Swedish hydro power system considering hydrology and environment court decisions?
• How can producers use hydro power most efficiently in the future? Stochastic daily and weekly planning.
RIVER LULE ÄLVLength: 461 kmInstalled capacity: 4 345 MWMean generation: 14 TWh/yr
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Balancing using combined heat and power
• How can we increase the flexibility of electricity generation in combined heat and power?
• How can producers use combined heat and power in the future? Stochastic daily planning.
MW power
MW
heat
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Balancing using consumers
• How can we use new technical solutions to allow consumers to participate in balancing of variable renewable generation? How willing are consumers to participate?
• How can retailers use consumption flexibility in the future? Stochastic daily planning.
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