Ontario’s top commercial and industrial energy consumers are dealing with unintended consequences due to recent growth experienced by the IESO’s Industrial Conservation Initiative (ICI).

A large portion of a Class A customer’s bill is their monthly global adjustment charge. As an energy conservation measure, companies have to pay a percentage of the system-wide GA charges, but their portion isn’t determined by their cumulative or even average monthly energy use, instead, it’s determined by how much they contribute to the five peak demand hours over a 12-month period.

Global Adjustment (GA):

The electricity bill component that covers the cost of building new electricity infrastructure in the province, maintaining existing resources, as well as providing conservation and demand management programs.

Five Coincidental Peak Hours (5CP):

The five hours each year when the electricity usage in the Province of Ontario is at its highest.

This conservation program encourages Class A customers – top commercial and industrial energy consumers – to use various demand response technologies like peak prediction software and battery energy storage to predict these peak hours, and then lower electricity usage as much as possible during this critical time.

More and more companies are using the same publicly available data (IESO Peak Tracker) to predict peak hours, making it harder to accurately predict and causing a large increase in “false peak” and “double peak” days.

False Peak:

Occurs when the publicly available data, provided by the IESO, predicts that a peak will occur, but either due to changing usage patterns or a strong demand response from businesses, electricity usage becomes lower than expected and no peak day develops. (Source: EnPowered)

Double Peaks:

When many businesses reduce their usage at the same time in response to a forecasted peak, causing a massive decrease in energy usage. Instead, peaks occur the hour before and after the target hour, creating the so-called Double Peaks. (Souce: EnPowered)

We’ll assume the most basic demand management strategy available to all Class A customers using public data is a partial or complete operational shutdown. If they miss the true peak, this creates a double loss: lost productivity and lost energy savings. However, by combining peak prediction software with battery energy storage, businesses can more accurately predict top demand days and continue to operate at full capacity through false or double peaks while still achieving savings.

Let’s see how.

Solutions

Peak Prediction Software

Peak prediction software such as EnPowered Predictions uses machine learning and meta-pattern analysis to forecast both provincial energy usage and market response, generating 50% more accurate predictions. Without their software, EnPowered says Class A customers shut down on average 34 times during the year for 5-hour increments in the hopes of riding out the full peak. With the industry’s most accurate predictions, EnPowered users are able to catch all five peak hours a year, while only responding 10 times for a maximum of 2 hours each time. That’s 170 hours of lost production versus only 20.

EnPowered also says that “by properly managing the ICI Program, a business can save up to 70% of its annual electricity costs”.

Battery Energy Storage Systems (BESS)

In 2020 there was 436 MW of Class A energy storage installed in Ontario, outputting approximately 33,500 MWh of electricity per year. A recent study by Power Advisory LLC for Energy Storage Canada forecasts that at a moderate rate of economic recovery, this will more than double to 1,000 MW of battery energy storage installed by 2030, outputting 64,500 MWh a year.

So what’s driving the adoption of batteries as an efficient strategy to beat the increasingly elusive 5PC?

Batteries are charged from the grid during off-peak hours and programmed to discharge at periods of peak demand to reduce GA charges. For Class A customers, in order to offset energy consumption this high, a battery will typically range in size from 500 kW to several MW.

There are several strategies to achieve maximum cost savings, but here are two of the most common:

  • The battery is completely charged in preparation for a peak hour and during this time, the company stops drawing power from the grid and relies exclusively on energy storage.
  • A company with a narrow peak demand will continue to use the grid, but once provincial energy demand approaches the IESO’s daily peak threshold, they begin to withdraw a portion of their energy needs from storage for a gradual discharge to ensure their Peak Demand Factor is fixed at a set rate.

Battery energy storage systems are well worth the upfront capital investment. Power Advisory calculated that the annual average savings for Class A customers were more than $500/kW, assuming businesses hit all 5 peak hours.

Conclusion

Pairing peak prediction software with battery energy storage ensures Class A customers achieve maximum GA savings by accurately predicting peak hours while reducing grid draw in real-time and enabling continuing operations powered by an on-site battery.