Wind Energy in the National Electricity Market. Masterclass for the Restructured Electricity Industry August 2005 CEEM, 2005

Transcription

1 Wind Energy in the National Electricity Market Masterclass for the Restructured Electricity Industry August 2005 CEEM, 2005

2 Outline Wind energy as intermittent generation Intermittent generation- definition & issues Trends in wind farm installations in Australia Planning issues Network-related issues Power variability issues Forecasting; spot & derivative markets Commercial viability of wind farms in the NEM 2

3 Wind energy as intermittent generation Renewable energy fluxes are time-varying: Solar, wind, hydro (tidal), biomass, geothermal, wave Wind & solar are non-storable: Can be described as intermittent 3

4 Intermittent generation (NEC) National Electricity Code (NEC) definition of intermittent generation: A generating unit whose output is not readily predictable, including, without limitation, solar generators, wave turbine generators, wind turbine generators and hydro generators without any material storage capability Issues identified by NEMMCO: Forecasting; Frequency Control Ancillary Services (FCAS); voltage control; management of network flows 4

5 The power in the wind Doubling the wind speed increases the power eightfold but doubling the turbine area only doubles the power. 5

6 Australian wind resource (Estimate of background wind (m/s) AGO) 6

7 The drought risk: rainfall in Australia, 2002 What about wind? (WMO Annual Report 2002) Antarctic vortex strengthening & shrinking, taking rainfall south (ABC TV, 18/9/03) 7

8 Comparing AusWEA forecast ( & readily acceptable (RA) wind capacity for Australia Qld NSW Vic SA Tas WA Aus Inst MW App MW Total MW RA MW

9 Australian wind farm planning AusWEA best practice guidelines: State handbooks & planning protocols: NSW (SEDA); Victoria (SEAV): Project-based, some variations between states Stages in the process (AusWEA): Site selection; feasibility; detailed assessment, development application; construction; operation; decommissioning 9

10 Australian wind farm planning experience to date Limited experience to date: Some strong support, some strong opposition Mixed federal, state & local government approvals process lacks coherence: Project based - may not manage cumulative issues & interactions well Other industries have a comprehensive planning framework, eg: Strong, state-based planning framework for the minerals industry 10

11 Network issues for wind farms #1 Networks are shared, centrally planned resources: Must limit network disturbances caused by wind farms Wind farms must survive disturbances from the network Renewable resources are often distributed differently from fossil fuel resources: Weak network conditions likely to be more common in Australia & New Zealand than Europe or North America Network must be built to carry peak flows: Want good estimates of aggregation & seasonal effects Benefits of staged development of wind resources: Network savings; reduced voltage & frequency impacts 11

12 Network issues for wind farms #2 Wind turbine starting & stopping transients: Severity can be alleviated by soft-start & high wind-speed power-management Some wind turbine designs: May cause voltage distortions: Harmonics &/or transients May have poor power factor, eg: Uncompensated induction generator May not ride-through system disturbances Temporary voltage or frequency excursions 12

13 Wind turbine type comparison (Slootweg & Kling, 2003, 13

14 Size of wind turbines used by Western Power ( 14

15 Wind turbine starting transients for Esperance 2 MW wind farm 9 x 225 kw turbines with squirrel cage IG Magnetisation inrush current may cause a voltage dip - starts should be spaced out (Rosser, 1995) 15

16 Network connection issues & examples Approximate ability of a transmission line to accept a wind farm: 66kV 20MVA 132kV 100MVA 330kV 200MVA Constraints may be determined by several factors: Thermal, voltage, fault clearance, quality of supply Thermal ratings depend on line temperature & wind speed Relevant wind farm rating is its maximum output, not the sum of turbine rated powers: Coincident output of the connected wind turbines 16

17 Connection costs to 330kV (Transgrid, 2002) Wind farm number Total wind MW Conn. cost $M Conn.cost $/kw , Important to capture economies of scale of grid connection 17

18 Wind resource & network issues in South Australia Good wind resources along entire coastline including: Eyre Peninsula Yorke Peninsula Fleurieu Peninsula Kangaroo Island South-East Sites available for up to 2000MW Map: ESIPC,

19 Eyre Peninsula Backbone network upgrade to support 500MW wind Estimated cost of 275kV backbone upgrade: $140M or $280/MW assuming equally shared by 500MW of wind. Wind may not have to pay full cost of backbone upgrade. (Meritec, 2002) 19

20 NEMMCO concerns about wind energy (NEMMCO, 2003) Frequency control in normal operation: Frequency regulating service costs ~5 $/MWH Security control - largest single contingency Will wind farms ride-through disturbances? Interconnection flow fluctuations: Exceeding flow limit may cause high spot price Forecast errors due to wind resource uncertainty: Five minute dispatch forecast (spot price) Pre-dispatch & longer term (PASA & SOO) forecasts 20

21 Western Power s proposed wind penalty charge (c/kwh) (Western Power, 2002) 21

22 Demand forecast errors South Australia,2004 Q4 (NECA, 04Q4 Stats, 2005) 22

23 Spectral analysis of Danish long-term wind data (17 years of data) Spectral gap between weather and local turbulence phenomena (Sorensen, 2001, Fig 2.110, p194) 23

24 Forecasting the output of wind farms 30 minute horizon (FCAS & spot market): Turbulence spectrum - likely to be uncorrelated for turbines spaced > 20 km: Then % power fluctuations ~ N -0.5 eg for 100 identical wind farms spaced >20 km apart, %fluctuation in total power ~ 0.1x%fluctuation for 1 farm 30 minutes to ~3 hours: ARMA model best predictor of future output > 3 hours - NWP model best predictor: Key issue: predicting large changes in output of appropriate groups of wind farms 24

25 2-hour prediction for Lake Benton wind farm, USA 138 turbines, 103.5MW, hourly data (Hirst, 2001) Two-hour ahead prediction of wind power: MW Pred (T+2) = xMW(T) + [MW(T) - MW(T-1)] 25

26 Combined output of 2 wind farms 80 km apart (Gardner et al, 2003) 26

27 Cross-correlation function between the output powers of 2 wind farms 80 km apart (Gardner et al, 2003) 27

28 Cross-correlations between measured power outputs of German wind farms (Giebel (2000) Riso National Lab, Denmark) 28

29 Cross-correlations between 34 years of 12-hourly data for all grid points (Giebel (2000) Riso National Lab, Denmark) 29

30 Wind energy duration curve for Northern Europe (normalised to average) (Giebel (2000) Riso National Lab, Denmark) 30

31 Predicting the output of a wind turbine 6, 12, 18, 24, 36 & 48 hours ahead (Focken et al, 2002) 48 & 36 hr predictions: Front timing later than actual 48 & 36 hr predictions: Front timing ok but not magnitude 31

32 Wind power scenario forecasting (Jende, 2005) Actual: ---- Aust Govt is spending $15m on a wind power forecasting system to facilitate high levels of wind power penetration 32

33 CSIRO Windscape TM model ( Windscape derives location-specific wind forecasts from a Numerical Weather Prediction model (Steggle et al, CSIRO, March 2002) 33

34 (Steggle et al, CSIRO, March 2002) Windscape predictions of annual mean wind speed at 65 m, showing nested model results More rapid changes in colour Wind probably energy in the NEM imply CEEM higher 2005 local turbulence 34

35 SEDA NSW Wind atlas ( 35

36 Hampton Wind Farm, NSW (2x660 kw Vestas, connected to different 11 kv feeders) 3 Second data being collected Turbulence probably fairly high at this site Induction generators may not ride through voltage dips well. 36

37 Issues for NEM spot market Wind farms will operate as price takers : Generate whenever wind is blowing NEM spot market prices are volatile with a rectangular price distribution: Prices are usually low, sometimes high Timing of high prices not easily predicted Value of wind energy in the spot market: Will depend on how regularly wind farms are producing when spot prices are high 37

38 Price-demand plots for NEM regions NSW (top) & SA (bottom) Jan-Mar 2004 ($/MWH vs MW) (NECA, 04Q1 Stats, 2004) 38

39 Smoothed NEM Regional Ref Prices (RRPs) since market inception (NECA, 04Q4 Stats, 2005) 39

40 Annual average RRP flat contract prices (NECA, 04Q4 Stats, 2005) 40

41 Forward prices for wind energy Wind farms may have to accept a lower price than flat contract due to uncertainty in production: Daily Seasonal, Annual (Giebel (2000) Riso National Lab, Denmark) 41

42 60 Renewable Energy Certificate Prices (A$/MWH) (Offer, 2003)

43 Wind farms marginal at $70/MWH (PWC, 2002) 43

44 Conclusions Intermittent generation: Brings new challenges for electricity industry restructuring (technical, market design, regulation) Wind energy: The first significant form of intermittent generation Network connection issues: often distributed differently to traditional resources Planning issues - visual & bird impacts: Regional, rather than project specific Forecasting & system security issues Often not cost-competitive on electricity price alone 44