Electricity Pool Trading and Portfolio Modeling

iPool ‘s object oriented technology allows modeling of various market rules and provides quick interactive and visual response for short term and real time pool trading.

Pool Trading

Successful trading and bidding into a competitive electricity pool require the ability to respond quickly to the changing market conditions.

iPool provides the features required to enable quick and appropriate market responses: • Volume position and exposure •Financial position and exposure •Short term and intra-day
forecasting •Competitor Bid Offer Analysis •Fast historical Market Analysis •Interactive what If Market Scenarios

Portfolio Modeling

Energy companies and trading firms will benefit from iPool’s multi-portfolio modeling with its ability to aggregate results and evaluate against historical and simulated market scenarios.  IPool models: •Customer Demand Portfolio •Generation Demand Portfolio •Wholesale Contracts (ISDA and Power Supply Agreements) •Retail Contracts and Tariffs (Single rate and multi-rate Time-Of-Use).

Versatile Generation Modeling

IPool’s object oriented technology enables flexible and detailed modeling of different kinds of power stations, their operating characteristics their associated costs and their supply availability. •Models Coal Fired plants, Gas Turbines, Combine Cycle GTs, Hydros, Pump Storage, Solar, Wind, Biomass and generic stations. •Models production costs using multi-point incremental cost curves, O&M costs, capital charges, network charges, start up costs, carbon costs •Models and tracks energy storage levels, energy limitations and cascaded stations. •Captures historical behavior and use them in simulation

Market Rules and Dispatch Modeling

iPool models the static and dynamic system constraints, the bid offer prices and the reserve offer prices are co-optimized in the pricing and dispatch of generation. •Models different  dispatch and trading intervals •5 minute dispatch and trading •3o minute dispatch and trading •Hourly dispatch and trading •Can use actual and aggregated bid offers •Models transmission inter-

connectors •Models generic dynamic constraints •Models ramp rates •Models static and dynamic loss factors •Models limits on energy storage •Models both supply offers and demand bids •Models market specific pricing rules

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 comparison of actual vs. simulated prices for checking model validity.  iPool has the following relevant features for market analysis and forecasting: •Use 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.

Intelligent Bid Behavior Modeling

Generator bid offers change from day to day and it can be dependent on the participant’s contract portfolio, the system demand, the system constraints and  other market conditions.   Using the actual historical bid offers may not be applicable for forecasting future scenarios.   iPool captures the typical bids of all participants for different calendar days and with its iBid module can model the dynamic responses and adjust them to the prevailing market conditions during simulation.

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. •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 •Provides visual display of outages across time

Monte Carlo Simulation

The chronological sequential type 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.   •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

Load Profiling

The demand profiles of customers can vary according to the industry, according to the type of calendar day and can have different volatilities.  IPool can capture and create load models from the historical demand.   These load models can be used for customer classification, for forecasting, for pricing and for detecting non technical loss events. •Determines and displays hourly ranges of demand by calendar day •Models hourly demand using either averaged or probabilistic load profiles for each calendar day. •Determines peak and off peak energy, load factor, volatility and probability ranges.

Load Pricing

The cost of supplying specific customer load can depend on the level, volatility, and shape of the customer load which can vary for different calendar days.  iPool determines the corresponding peak and off-peak energy price against the market and allows the user to specify tariffs and contracts.   It allows evaluation of different pricing schemes and specify pricing margins. •Determines peak and off-peak energy cost •Determines purchase cost of energy •Evaluates single rate and Time-of-Use tariffs

Meter Data Analysis

The ability to analyze customer meter data is important in a competitive retail market.   iPool can load, process and analyze hundreds of customer meter data. • Load and process varying formats of time intervals – 5, 15, 30 and 60 minute intervals. •Determines peak and off-peak energy, load factor and probability ranges •Display the load profiles of the meter data •Aggregates the load according to user defined classification such as by industry type or by substation location 

Non Technical Loss Detection

Detecting and predicting meter data irregularity or what is known as Non-Technical Loss (NTL) is challenging.   NTL can be caused by malfunctioning metering equipment but the term is generally a euphemism for electricity fraud or theft which can be in the form of meter tampering and illegal connections.  iPool detects and high lights these irregularities and provides the user a way to adjust the detection sensitivity.

Shifting the focus on intelligent trading