The advent of competitive electricity markets and the continuing deployment of the smart grid and Advance Metering Infrastructure in the electricity industry present both challenges and opportunities in the power industry. The iPool software provides energy companies and power consumers a user-friendly tool for managing market risk, forecasting prices, profiling and pricing demand in the competitive power industry.
- iPool’s graphical and intuitive user interface design makes it easy to use with visual access to information. The tree navigation and tabbed forms interface provides easy drill down and aggregated view of prices, generation, load and financial data.
- iPool’s innovative use of Object Oriented technology provides fast and flexible interactive simulation ideal for applications such as:
- Forecasting Short and Medium Term Electricity Pool Prices and Generation, iPool uses accurate Market Bid-Based dispatch optimization and has Intelligent Bid Behaviour Modelling that responds dynamically to changing market conditions using Fuzzy Inference System technology.
- Load Profiling and Pricing of Customer meter data against the market and against different Tariffs and contracts, it Models Generator and Retailer Portfolios with the ability to group and aggregate multiple portfolios, and Models both Wholesale contracts and Retail Tariffs.
KEY TECHNOLOGIES OF IPOOL
What’s under the hood?
OBJECT ORIENTED SIMULATION TECHNOLOGY
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 up using object oriented analysis, design and programming. 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 an independent object which responds to its environment and interacts with another object according to its intended behavior. It differs with traditional approaches that use procedural programming method. The traditional method 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 it not only fast and versatile but highly interactive and visual with its color coded tables and charts.
FUZZY INFERENCE SYSTEM TECHNOLOGY
The trading and 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 at that same time. The iPool software is equipped with a fuzzy inference system (also known as fuzzy logic) which models the bidding behavior such that bids respond in accordance with the kind and degree of change in the market condition during simulation. For example, if the energy storage goes below a certain level, the bid offers of the pump storage plant can adjust 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 random. The randomness follow a particular probability distribution curve called the Weibull curve which is similar to an exponential distribution. 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 especially 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 availability parameters of each generating unit in the system that iPool can also determine 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. This 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.