Demand Response A New Option for Wind Integration

1
Demand Response A New Option for Wind
Integration ?

• Marian Klobasa, Dr. Mario RagwitzFraunhofer
  Institute for Systems and Innovation Research
• European Wind Energy Conference 2006
• Athens, 2. March 2006

2
Outline

• Motivation for Demand Response
• Potentials for Demand Response
• Simulation of Wind Energy, Electricity System and
  Demand
• Impacts of Wind Fluctuation on Electricity
  Systems

3
Benefits of Demand Response?

• Improving of system reliability
• Peak load and balancing power can be reduced
• Efficient electricity use by increased
  transparency
• Reduction of price peaks and lower price
  volatility
• Increase of short term price elasticity and
  improvement of market-clearing
• Better market functioning
• Reduced risks for market actors
• Use of demand response as an existing resource
  might need lower investments than new generation
  capacity
• Studies gave evidence of substantial economical
  and technical potentials
• Demand response increases the possibilities for
  wind integration when balance between supply and
  demand is tightening

4
Increased Elasticity can reduce Electricity
Prices
5
Realistic Option?

• Experiences from Scandinavia and Germany
• 24 Jan 2000 (Price peaks up to 400 /MWh)
• Demand response in Sweden 200-1000 MW, in Norway
  800-1100 MW
• 5 Feb 2001 (Price peaks 240 /MWh, 9 hours over
  100 /MWh)
• DR in Sweden up to 700 MW, in Norway up to 500
  MW
• Winter 2002/03 (December-price level 90 /MWh)
• Nordel DR in Norway 800 MW, in Sweden 200 MW
• ECON DR in Norway 1000 MW
• DR in Germany (2005) 200 MW contracted by
  SaarEnergie for minute reserve market

Source FinGrid, SaarEnergie
6
Outline

• Motivation for Demand Response
• Potentials for Demand Response
• Simulation of Wind Energy, Electricity System and
  Demand
• Impacts of Wind Fluctuation on Electricity
  Systems

7
Potential for demand response
8
Example steel production electric arc furnace

• Typical batch process
• Tap to tap time 45 minutes
• Power Supply 100 MW
• Capacity 200 tons
• Yearly production 200 t furnace 1,5 Mio. tons
• Steel price 320 /t (2003), gt 500 /t (2005)
• Turn over 500 700 Mio.
• Additional turn over in balancing market 2,5
  Mio.
• Price for balancing power70 /MW per day
• Price for balancing energy180 /MWh

Source Stahl-Online
9
Technical potential for demand response

• Additional potential
• Tertiary sector 1 GW
• Refrigeration
• Air conditioning
• Residential sector up to 9 GW
• Space heating, warm water
• other

hours
10
Prerequisites for demand response

• Technology Adoption of existing IC technology
  for demand response innovation of IC
  technologies is main driver for system
  optimisation.
• Development of suitable tariffs and business
  models (including extension of intraday markets).
• Consideration of customer behaviour, potential
  benefits and risk for electricity traders.
• Adoption of new demand response business option
  by energy and general management in industrial
  companies.

11
Outline

• Motivation for Demand Response
• Potentials for Demand Response
• Simulation of Wind Energy, Electricity System and
  Demand
• Impacts of Wind Fluctuation on Electricity
  Systems

12
Electricity System Simulation

• Structure of simulation model
• Data for conventional power plants
• Installed capacity, fuel type, combined heat and
  power production, availability
• Electricity demand (incl. load curves)
• Wind generation (based on wind speed data)
• Simulation of power plant operation
• Determined by variable costs, minimum operation
  time
• Results of simulation
• Fuel use, electricity production, CO2-emissions
• Basis for analysis of balancing strategies

13
Simulation of power plant operation
Wind generation
Electricity demand
shift potential
Power plantdatabase
Deviation
Prognosis
Input data
Operation of power plants
Balancing Capacity Balancing Energy
Simulation
Fuel use, electricity production, emissions, costs
Results
14
Simulation of wind generation

• Input data
• DWD-Data (3 years) for 180 locations
• Wind speed
• Pressure und Temperature
• Time interval 10 Minutes
• 10 Turbine types and power curves
• Spatial distribution

gt High resolution time series of wind generation
15
Bottom up model for simulation of the load curve

• Output
• Simulation of yearly load curves of 60 sectors in
  hourly time resolution and total load curve for
  Germany
• Data basis
• UCTE (12 month, 3 typical days,Base year 2000)
• VIK/VDEW Data
• ISI-Load profiles (typical days)
• Method
• Generation of load curves for 6 typical days
• Algorithm for generation of yearly load curves in
  hourly time resolution (basis are 6 typical days)

16
Outline

• Motivation for Demand Response
• Potentials for Demand Response
• Simulation of Wind Energy, Electricity System and
  Demand
• Impacts of Wind Fluctuation on Electricity
  Systems

17
Influence of wind power on power plant operation
Year 2020 Without wind generation
18
Influence of wind power on power plant operation
Year 2020 With 39 GW wind generation
19
Influence of wind power on power plant operation
Wind generation
Year 2020 With 39 GW wind generation
20
Additional balancing power
21
Additional balancing energy
22
Additional balancing costs

• Calculation of balancing costs
• Costs approach opportunity and part load
  costsRange 30 400 /MW per day
• Price approach balancing market pricesRange
  100 2000 /MW per day
• Demand response costs starts at 70 /MW per day.
• Additional balancing power of 6 GW up to 2020
  could lead to an increase between 200 600 Mio.
  .
• 1 GW demand response can lower this value by 25 .

23
Additional balancing costs
24
Conclusion

• Increase of balancing power around 0,1 MW per MW
  wind energy with improved forecast tools.
• Balancing energy around 0,1 MWh per MWh wind
  energy with improved forecast tools.
• Technical potential for demand response is high.
• Demand response starts to be available at 70 /MW
  per day and could lead to significant cost
  decreases.
• Furthermore demand response could compensate
  local fluctuations and could help to delay or
  overcome grid extension measures.
• Main challenge will be the development of markets
  and business models to transfer cost reductions
  to the customers.

25
Acknowledgement
Further Information Wind integration supported
by Demand Response, Final Report in Cooperation
with Vienna University of Technology, Energy
Economics Group www.eeg.tuwien.ac.at

• Project carried out in the framework of the
  program Energy Systems of Tomorrow" an
  initiative of the Austrian Federal Ministry for
  Traffic, Innovation and Technology (BMVIT).

Marian Klobasa M.Klobasa_at_isi.fraunhofer.de www.is
i.fhg.de/e/departm.htm