Since the ICI program was introduced, large electricity consumers in Ontario (Class A Electricity Customers) have depended on the IESO Power Data website to analyze, estimate and predict when the Coincident Peak hours will occur. A variety of services are available which take the data from the IESO’s server and communicate it in a more clear and concise way. However, these companies/dashboards all have one downside - they rely solely on the IESO’s data - this can lead to missed Top 5 peaks and more curtailments than necessary.
Historically IESO data has worked out well and for the past 10 years proactive Class A customers have been able to hit all 5 coincident peaks with 10-14 curtailments. Depending on your definition of curtailments and how much time you need to react, 14 curtailments a year to save up-to 40% on your hydro bill is a worthwhile endeavour.
This all sounds great, but unfortunately the times have changed. Due to a few factors which we will get into below, the IESO data can no longer suffice for predicting peak days. Using more advanced methods such as Artificial Intelligence (Machine Learning) has become more important and will be the ONLY way to predict Peak Days.
The IESO receives mandates from the Ministry of Energy to fulfill its duty and keep a reliable electricity system, It's written clearly on their site:
The Independent Electricity System Operator (IESO) works at the heart of Ontario’s power system ensuring there is enough power to keep the lights on, today and into the future.
The IESO's priority is to ensure ensuring a clean, safe, and reliable electricity grid for everyone in Ontario. Predicting Peak Days to help Class A customers save on their GA costs is NOT one of their priorities. They need to predict the Ontario demand in order to balance the supply and ensure there is always enough power available. What does this result in? Typically, the IESO will over-estimate the Ontario Demand as their priority is ensuring reliability. What does this mean for Class A customers? It means that the information received from the IESO may not be 100% reliable in predicting peak days – and it may cause you to curtail more times than is necessary.
On January 15, 2018 the IESO Peak Tracker showed a projected Ontario Peak Demand of 21,194MW at HE19. If you were using the IESO tracker or a service based on IESO data to decide when to curtail, this would look like a great day to reduce your demand and reduce your GA costs.
Unfortunately, if you followed their prediction, you curtailed for no reason and received no benefit from reducing peak demand during this day.
The actual peak ended up being 20,073MW which is 1,121MW lower than what was predicted, and the day did not end up in the Top 10 Peaks for the year. Why did this happen? It is because of a forecasting error and class A customer curtailments. Since the IESO predictions themselves define when a large portion of the Class A customers will curtail, the IESO cannot quantify this value in real time. You cannot accurately estimate something, when your own estimate is causing the thing to happen in the first place!
Curtailment actions differ significantly between summer and winter seasons (i.e. Air Conditioning load is a large driving force in the summer) - it is difficult to know exactly how much curtailment is occurring. In addition to this, the efforts facilities make in reducing load change as the year progresses since different industries have different production cycles. This makes predicting curtailment by others very difficult.
In the past, all of the Ontario Coincident Peaks would occur during office hours or right after office hours. This meant that being proactive and informed during office hours was enough to 'hit the peaks'. As the driving force behind the peaks has continued to shift, and with more and more participants signing on to the ICI program, peaks have occurred on irregular hours or even on weekends.
Edgecom Energy’s pTrack™ Service gives you the peace of mind that the IESO does not – you will be alerted with monthly, weekly, day before and day of alerts. This ensures that all relevant employees receive the peak hour information in a timely manner – without having to sit in front of a computer chasing graphs all month long!
To make sure you have the most accurate and up-to-date information for your ICI Program involvement, you need a smarter approach. pTrack™ uses state of the art software designed by a group of Power Systems PhDs from the University of Waterloo. This AI model predicts when the peaks will occur, how others are curtailing and what changes are happening in the grid on a 5 minute basis.
Any notification service provider or dashboard technology that depends exclusively on this IESO data to predict peak day hours risks a higher degree of uncertainty - and the associated loss of potential savings - ending up costing YOU more. This is why you need Machine Learning to accurately predict the Coincident Peaks.
System-Backed Capacity Import Resources are one of the newer resource classes eligible to participate in the Independent Electricity System Operator (IESO)'s Capacity Auction. This raises the question: What is a System-Backed Capacity Import Resource?
Virtual power plants (VPPs) are the future of our electric grids. The grid's current aging infrastructure was built around electricity flowing in one direction, from the central power plant to the end-user. However, with the introduction and the resulting rise in popularity of distributed energy resources (DERs) like solar panels, wind turbines and battery storage systems, the grid is now required to handle electricity coming from the central power plants and the end-users.
Edgecom Energy is an Independent Electricity System Operator (IESO) market participant that acts as a capacity aggregator for participation in the Capacity Market. Aggregators simplify participating in the Capacity Auction for their customers and reduce the number of moving parts the IESO has to deal with on their end.