What makes iPool unique in its power, speed and versatility in modeling the complex interactions in a competitive electricity market and operation of a power system is that it was developed from the ground using object oriented analysis, design and programming.
OBJECT ORIENTED SIMULATION TECHNOLOGY
Object Oriented designed programs differs with traditional programs in that it employs interacting objects, interdependent units of code, that simulate operation of complex real life systems. This means, each component of the system, the market and the power structure, are modeled as objects which responds to their environment and interacts with one another accordingly . It differs with traditional approaches which use procedural programming which requires step by step procedure known in advance to solve a problem.. With iPool’s Object Oriented technology, changes in market rules such as pricing rules and dispatch and trading intervals can be modeled easily. This is not possible with traditional procedural programs because they are tailor made to solve specific problems using specific step by step procedure. This Object Oriented technology of iPool is what makes not only fast and versatile but highly interactive and visual with its color coded tables and charts.
FUZZY INFERENCE SYSTEM TECHNOLOGY
The trading an dispatch prices in the electricity market are subject not only to the system demand and supply availability but in a very significant way to the bid and offers of participant generators, retailers and consumers. These bids and offers are not static. Traders respond to the changing market conditions by changing their bid and offer to the pool. The iPool software is equipped with a fuzzy inference system or fuzzy logic which models the bidding behavior such that they respond accordingly to the changes in the market condition during simulation. For example, if the energy storage goes below certain level, the bid offers change of the pump storage plant can change accordingly to preserve the stored energy for times where it is most beneficial to use. Another example is when a station unit goes on outage, the bid offers of the remaining station units in a portfolio can change proportionately to compensate for the lost capacity in order to fulfill a contracted capacity requirement.
SEQUENTIAL CHRONOLOGICAL MONTE CARLO
Monte Carlo is a mathematical technique that employs repeated simulation of a stochastic system in order to arrive at a statistically valid result. The nature of the operation of an electricity market and a power system are probabilistic. Generator units break down and the timing and duration of their outages, unless they were planned, are quite random. These supply outages affect the spot prices significantly and they are often the cause of extreme price jumps. It is of prime importance in forecasting and planning in the long term to be able to quantify the effect of these random supply outage events. The iPool software models these supply outages and other random events in a way that is close to reality – that is in a chronological sequential manner using mean time to fail and repair parameters of each generating unit in the system that iPool also determines from historical data. It simulates each dispatch interval of a year in consideration of the random outage supply events and other events. It does the full year simulation repeatedly and each time with a different set of random events. These chronological sequential way of Monte Carlo simulation provides the most accurate method of forecasting prices as it is able to model the extreme price jumps which represent the tail end part of the price duration curve. Not all Monte Carlo techniques used in the power industry are the same. Non sequential non chronological implementation are faster but they are not able to model the extreme price jumps and the corresponding tail end of the price duration curve which are highly important in planning and forecasting.