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Predicting Ontario's system peaks for Class A cost avoidance


When a new Class A peak setting period begins, it is impossible to predict exactly when the top five peaks will occur. Noone knows the exact day, or the exact hour that the peaks will occur.


There is however a way in Ontario to predict when the top ~30 peaks are going to occur. If you are able to target all 30 potential events, you will have a good chance of seeing Class A savings, as your efforts in the 30 potential peaks days will show up when 5 of the 30 turn into real Class A peak days.


Weather forecast for the Toronto area


Weather is the most important factor for predicting system peaks in Ontario's electrical grid. Peaks are most common during heat waves in the summer (temperatures over 28 C), and less common during winter cold snaps. Once we know this, it beomes much easier to start predicting the 30 or so potential peak days mentioned earlier.


To illustrate the effects of high temperatures causing system peaks, we compare the temperatures highs for the Toronto area during all top five peaks in the 2019-2020 peak setting period.



We can see above that all of the top peaks (highlighted in blue) occurred during high temperature days, at least 28 C and above.


The temperature map above also highlights in green a non-peak day where the temperature was fairly low and a system peak wouldn't be expected to happen. This is further illustrated when we analyze the hourly consumption data for the entire province that is provided by the IESO.




The above chart clearly shows the difference between an actual top five peak day (July 5, 2019) in relation to a non-peak day (July 23, 2019). Throughout the entire day, the lower temperature non-peak day always has a lower electrical demand than the higher temperature peak day.


Finally, we mentioned above that the weather map was for the Toronto area. This area is used to predict top system peaks because Toronto has a significant contribution to the electrical demand in the province, which is illustrated to the right.


The graphic shows that out of the approximate 23,000 MW summer demand at the time of the study, 4,560 MW comes directly from the Toronto area - that's 20% of the entire province! A change in Toronto's electrical demand has a large impact on the province's overall system peak.




IESO Peak Tracker tool to target all peaks


To enhance how you target system peaks, the IESO provides a tool that shows their demand forecast for 24-hrs out, along with their 6-day peak demand forecast. The IESO needs to do this work anyways to ensure they have enough supply on the grid, and having access to this data is a great tool.


The Peak Tracker tool's best feature is the 24-hr chart near the top of the page that visualizes the demand projection for the day, along with a yellow bar that shows where the current top 10 peak days are. A sample chart is shown below, showing the 24-hr projection for what ended up being a top system peak in 2019.




From the chart above, you can clearly see when the IESO predicted the peak to happen (hour ending 17, or 4-5 PM EST), and you will see how it was predicted to be higher than all of the current top 10 peaks (the yellow bar).


If you are responsible for reducing GA costs through the Class A rate class, you can make it a routine to check the Peak Tracker tool each morning during the summer to ensure you don't miss a potential peak day.


The other aspect of the Peak Tracker is the listing of the top 10 peak days found closer to the bottom of the page. This section is useful to understand how high the current peaks have been to get a feel for how many MW will actually produce a peak. If we look at the top 10 peaks for 2019, we see they range in electrical demand from 20,533 MW - 21,275 MW. With this knowledge, we can determine that any peak day prediction above 20,500 MW could potentially turn into a peak day during the 2019 peak setting season. Keep in mind that each year could produce a different range of electrical demand that produces a top system peak.


Other important factors in predicting peaks


Other than weather, there can be a few other items to keep in mind when trying to reduce your consumption during potential peak days, which include:



How is your building tracking the peaks?


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