Electricity Price Forecasting and Market Analysis

iPool Electricity Market Forecasting System

iPool ‘s fuzzy logic based bid behavior modeling provides realistic  market responses within simulation and its object oriented technology  allows it to model the complex dynamic interactions within the power  system for creating more accurate scenarios for long term forecasting  and planning.

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Price Forecasting

 

The key to accurate forecasting is the model’s ability to accurately  model reality. Validating the accuracy of the model is the first step  in forecasting.  iPool’s iView facility shows comparisons of actual vs.  simulated prices for checking model validity.  iPool has the following  relevant features for market analysis and forecasting:

  • Uses actual market provided bid-offer data files with minimal to no manual processing required.
  • iPool’s Bid Aggregator creates typical bid offers for different calendar days from historical bid offers.
  • iPool can auto-detect new incoming units and can extract relevant  forecast parameters from historical scenarios that are user modifiable  for forecasting future scenarios.

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Intelligent Bid Behavior Modeling

 iPool’s use of Object Oriented technology enables complex and  flexible modeling of market events.   These events can include changes  in supply capacity, demand, limits, storage levels, price limits and  even market rules. iPool:

  • Optimizes planned maintenance
  • Models planned and random Outages
  • Models full and partial Outages
  • Models mean time to Fail and Repair
  • Calculates availability parameters from historical data
  • Provides visual display of outages across time

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Event Modeling

 iPool’s use of Object Oriented technology enables complex and  flexible modeling of market events.   These events can include changes  in supply capacity, demand, limits, storage levels, price limits and  even market rules. iPool:

  • Optimizes planned maintenance
  • Models planned and random Outages
  • Models full and partial Outages
  • Models mean time to Fail and Repair
  • Calculates availability parameters from historical data
  • Provides visual display of outages across time

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Monte Carlo Simulation

 The chronological sequential type of the Monte Carlo simulation of  iPool, unlike other type of Monte Carlo simulation, can capture the very  important tail-end part of the price duration curve.   The simulation  can be either market bid-based or non-market cost-based and it can model  various stochastic variables.  iPool does the:

  • Modeling of random generator unit full and partial outages
  • Modeling of random weather for wind generation and demand
  • Modeling of participant bid responses to changes in capacity and market conditions

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