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Modelling large-scale wind penetration in New Zealand with Plexos

Modelling large-scale wind penetration in New Zealand with Plexos. Magnus Hindsberger EPOC winter workshop Auckland, 5 September 2008. Outline. Background Plexos model Wind output series Reserve requirements Model results Interaction with plug-in hybrid electric vehicles Future work.

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Modelling large-scale wind penetration in New Zealand with Plexos

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  1. Modelling large-scale wind penetration in New Zealand with Plexos Magnus Hindsberger EPOC winter workshop Auckland, 5 September 2008

  2. Outline • Background • Plexos model • Wind output series • Reserve requirements • Model results • Interaction with plug-in hybrid electric vehicles • Future work

  3. Wind power integration in New Zealand- a scenario analysis of 15-25 % wind power in the electricity market in 2025 Iben Moll Rasmussen Mikkel Windolf

  4. Background of analysis • Current wind capacity: 321 MW • Current projects: ~ 6000 MW • Need to understand: • Wind variability issues, such as reserve requirements, grid flows and market price impacts • Interaction with electric vehicles, including charging on a day to day basis

  5. MS Access Plexos model overview • Developed by Drayton Analytics, now Energy Exemplar • PLEXOS 4.0 released in 2000. Plexos 5.0 appeared 2008 • Co-optimization engine based on PhD thesis of Glenn Drayton (University of Canterbury, 1997) • PLEXOS licensed in 17+ countries worldwide • PLEXOS consists of 4 main modules: • LT-Plan • PASA • MT-Plan • ST-Plan

  6. Wind data • Starting point: • 1 wind farm output series, 2004+ • 1 wind speed series measured at 70 m, 2005+ • 1 wind speed series measured from the top of a building, 2005-2007 • For the first model, 3 regional series were used based on the data above. • Newly obtained: • Multiple 10 m. data series from around NZ • 3 data series from Belmont Regional park

  7. Verification Plexos input files Real wind farm output Wind power modelling in Plexos 30 wind speed time series Exp. regional utilisation time Method: • Point measurement to wind farm or regional output • Generic power curve • Mix of Vestas and Siemens turbines Wind output series Scaled wind output series

  8. Wind farm output • Method to go from point estimates to wind farm/region output

  9. Estimating smoothing Belmont Regional Park sites: • Tower 21 30 m. • Tower 66A 44 m. • Tower 75: 42 m.

  10. Wind series Data from NIWA: 2005-2007, typically measured at 10 m.

  11. Achievements • 1 hour resolution allowing short-term issues to be analysed. • Using historical data where good records are available, limit our number of wind series compared with using synthetic data. • But it provides the following benefits: • Regional correlation is kept • Correlation with demand is kept (if same demand year is used) • Much better than our previous data

  12. Reserves modelling • Most simple model is persistence forecast: • Wind(T+1) = Wind(T) • May be too simple as not taking into account point on power output curve

  13. +400 MW - 600 MW Reserves modelling Typically harder to predict timing of a change than the magnitude of the change as shown below (Western Denmark case)

  14. Reserves modelling One has to be created per island and per year of wind data

  15. Reserves modelling • Wind risk is in addition to normal reserves as set by risk-setting unit: • Reservest = LargestRiskt + WindRiskt • For this analysis, we fixed largest risk to North Island CCGT and South Island generator at Clyde. • Will create a separate reserve market in Plexos in the future and go back to dynamic risk for the generators/HVDC.

  16. 90 % renewables Wind scenarios Wind energy share ~10% ~15% ~15% ~25%

  17. Not analysed Expected results • Increased wind penetration will lead to: • Less efficient thermal generation • Higher reserve costs • Higher costs for peaking capacity • Higher transmission costs • Dispersed wind will lead to lower costs than a concentrated wind development • Market prices may be lowered significantly

  18. Same max capacity, but high difference in costs Clear diversification benefit Results - reserves Costs of reserves for persistence forecast vs. a more accurate forecast

  19. Results - Transmission Transmission losses Transmission congestion More (compact) wind appear to lead to higher transmission related costs

  20. Little non-zero SRMC capacity Results - Generation Generation share in 2025 (normal inflow year)

  21. Wind impact on prices • Wind revenue vs. average revenue in Western Denmark, ~20% wind (annual energy) and export capability

  22. Results – Market prices 25% wind scenario lower price significantly when generation is high Also impact on wind spill

  23. Cheaper Cheaper National costs assessment

  24. Interaction with Plug-in Hybrid Electric Vehicles (PHEV)

  25. Why of interest • Due to the large potential for renewable electricity generation in NZ, PHEV’s and later on EV’s are likely in larger scale. • This will affect the power system as: • Energy demand will be bigger • Load duration curve will change (charging) • They may provide reserve capacity (V2G) • They may be used for peak shifting (V2G) • They will also improve the revenue of wind

  26. Modelling in Plexos • Daily energy requirement (per region) • Based on vehicle forecast and daily distance travelled • Currently free to choose time of recharge • Max capacity (offtake or delivered) based on assumptions on recharge on standard household installations (220 V – 14 Amps) • Cut-off price if petrol is cheaper, can be an issue during dry years. A $2/L petrol price was used.

  27. PHEV recharging example

  28. PHEV price paid & cost savings It was previously shown that more wind power led to lower prices. Potential wholesale price increase and thus extra wind generator revenue (less subsidy) yet to be analysed

  29. More wind PHEV demand PHEV’s may increase price in high wind generation hours PHEV impact on prices Price Demand Supply Generation

  30. Future directions

  31. Future direction • Internalise experience • Value of HVDC overload capacity • Wind/hydro interaction • Competition modelling • Cournot and RSI • Grid Development Strategy • Extend wind/PHEV work to 2050 • Understand peak capacity requirement including Demand Side Response • Wind power variability and investment decisions in LT

  32. GDS overview Objective: To form a long term National Grid development strategy taking into account: • New Zealand's future social, environmental and economic requirements; and • long-term technology trends. Process: The GDS process is likely to take about 18 months, culminating in a final strategy in the first half of 2010.

  33. GDS process • Scenario work package started last Friday. RFI published with deadline 19 September. http://www.gridnewzealand.co.nz/grid-development-strategy

  34. Questions ?

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