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STEPS A Stochastic Top-down Electricity Price Simulator Martin Peat.

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Presentation on theme: "STEPS A Stochastic Top-down Electricity Price Simulator Martin Peat."— Presentation transcript:

1 STEPS A Stochastic Top-down Electricity Price Simulator Martin Peat

2 Motivation 70% of NZ electricity provided by hydro-generation, so normal changes in price primarily result from fluctuations in demand or hydro-generation capacity Hydro-generation capacity is dependent on reservoir level so our model should reflect this Tool for price takers who: –Procure and contract electricity –Manage small hydro reservoirs Single reservoir optimisation (HERO paper) –Driven by price duration curves –Need to relate PDC to market state –Build a market state that depends on storage using STEPS

3 Background of Model EPOC presentations by James Tipping of a top- down model for Hydro Storage Levels and Spot Prices Tipping has an innovative valuation water as a function of storage level Revisit the model for the purpose of small reservoir optimisation Build application to keep track of the model Tipping, J. (2004) Incorporating Storage Levels into a Model for New Zealand Spot Prices, EPOC Winter Workshop 2004 Tipping, J. (2005) A Model for New Zealand Hydro Storage Levels and Spot Prices, EPOC Winter Workshop 2005

4 Benmore Weekly Price Series

5 Escribano Model As proposed by Escribano et al (2002) Deterministic component –Captures trend and seasonality –based on storage level (Tipping 2004) Stochastic component –Autoregressive –Volatility Escribano, A., Pena, J., Villaplana, P. (2002) Modelling Electricity Prices: International Evidence, Working paper 02-27, Universidad Carlos III de Madrid

6 Tippings Model Daily average prices at Benmore Two components proposed by Tipping –Water value model –Water release model Model can run independently

7 Tipping (2004) uses water value as deterministic component, based on the residual storage between the current storage level and the 10 th percentile of storage levels over the past 25 years Water Value Model

8 Tipping (2004) uses water value as deterministic component, based on the residual storage between the current storage level and the 10 th percentile of storage levels over the past 25 years Water Value Model

9 Tipping (2004) uses water value as deterministic component, based on the residual storage between the current storage level and the 10 th percentile of storage levels over the past 25 years Water Value Model

10 Tipping (2004) uses water value as deterministic component, based on the residual storage between the current storage level and the 10 th percentile of storage levels over the past 25 years Take storage level from COMITfree website Water Value Model

11 Storage difference used in modified Water Value model –parameters c, w, x, y vary with time in the form: Week RSL Water Value This gives continuity and prevents jumps in prices between seasons

12 Release Model STEPS weekly release model, based on Tippings daily model Minimum release, β 0, considers: –Generation required as demand is not met without using some hydro-generation –Environmental factors –Capacity constraints –Contracts

13 Model Fitting Parameters for the price and release models were estimated using historical data –Benmore spot prices ( ) –Inflow, release and storage sequences obtained from M-co ( ) Least squares method used to fit both models

14 Fitted to BEN Price Series

15 Simulating Price Trajectories Price Trajectories are calculated given an initial storage level and some inflow sequence:

16 Back-casting PDC

17 Simulation: Jan 2001

18 Simulation: Jan 2006 Risk Analysis

19 Simulation: Sep 2007

20 Simulation: Sep 2005

21 Simulation: May 2006

22 Simulation: Feb 2003

23 Simulation: Dec 2007

24 2008 Highs Graph of dec 07- aug 2008 Separation of prices Relative Storage Level

25 Simulation: Aug 2008 PtPt PtPt ~

26 Model Enhancement Selecting inflow sequences based on current year conditions to narrow confidence interval Build model using South Island storage Complete implementation of initial price correction Maximum likelihood estimator for parameters Test poisson jumps from the Escribano model

27 Uses Analysis of historical events Assessing effects of constraints on release and storage levels Generation and Demand side tool for price takers Planning hedge contracts Optimisation of hydro-electric reservoir (HERO) –Using forecast to create price duration curves –Building market state based on curves, thus based on storage

28 Conclusions Weakness is when price separation occurs due to market and network structure Strength of the model is in the simplicity Model can run as stand alone application STEPS LIVE forecast


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