STEPS A Stochastic Top-down Electricity Price Simulator

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STEPSA Stochastic Top-down Electricity Price
Simulator

• Martin Peat

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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

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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
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Benmore Weekly Price Series
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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
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Tippings Model

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

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Water Value Model

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

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Water Value Model

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

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Water Value Model

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

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Water Value Model

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

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Water Value Model

• Storage difference used in modified Water Value
  model
• parameters c, w, x, y vary with time in the form

• This gives continuity and prevents jumps in
  prices between seasons

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Release Model

• STEPS weekly release model, based on Tippings
  daily model
• Minimum release, ß0, considers
• Generation required as demand is not met without
  using some hydro-generation
• Environmental factors
• Capacity constraints
• Contracts

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Model Fitting

• Parameters for the price and release models were
  estimated using historical data
• Benmore spot prices (1999-2007)
• Inflow, release and storage sequences obtained
  from M-co (1926-2007)
• Least squares method used to fit both models

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Fitted to BEN Price Series
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Simulating Price Trajectories

• Price Trajectories are calculated given an
  initial storage level and some inflow sequence

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Back-casting PDC 1999-2008
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Simulation Jan 2001
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Simulation Jan 2006

• Risk Analysis

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Simulation Sep 2007
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Simulation Sep 2005
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Simulation May 2006
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Simulation Feb 2003
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Simulation Dec 2007
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2008 Highs
Graph of dec 07- aug 2008 Separation of prices
Relative Storage Level
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Simulation Aug 2008
Pt

Pt
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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

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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

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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

http//epoc.esc.auckland.ac.nz8000/steps.html