Predicting Peaks to Curtail Charges
Businesses in Ontario, Canada, like the family-owned commercial orchard Agloma Orchards, face some of the highest electricity costs in North America. This is in part due to electricity charges based on their facilities’ peak demand levels during the five one-hour periods times when grid demand is as its highest throughout the year.
Algoma Orchards and Enel X came up with a solution to both impact the community and reduce annual electricity costs. If they could predict when the grid is at peak demand and reduce their demand at the right time, they could reduce these charges significantly. To accomplish this, Algoma Orchards participates in Enel X’s system peak predictor program, which uses a complex predictive model to assess the daily likelihood of a system peak event on the grid based on an analysis of weather information and market data.
The orchard’s energy storage system—which consists of 520 kW/1,040 kWh of capacity in lithium-ion batteries—automatically charges the battery system when energy prices are the lowest and seamlessly transitions to stored energy when system peaks are most likely. This comprehensive solution enables Algoma Orchards to efficiently use stored energy to save $100,000 a year, all while preventing disruption to production in its facilities or the quality of the company’s products.
Everyone Wins with Energy Storage
The owners of Marcus Garvey Apartments, a 625-unit apartment complex in Brooklyn, New York, understand that the value of distributed energy resources extends beyond the confines of their buildings. That’s why they worked closely with Enel X to model a microgrid consisting of a 300 kW energy storage system, a 400 kW solar photovoltaics (PV) system, and a 400 kW fuel cell.
The ability to self-generate, store, and consume power on-site not only enables them to participate in demand response programs offered by New York City, but also provides valuable resources when energy prices spike or in the event that the grid goes down.
The combined distributed energy resources are equipped with Enel X’s DER Optimization Software, which leverages machine learning to automate the deployment of stored energy for maximum financial performance. The system does this by taking both internal variables, like energy consumption and operational behavior, and external variables, like energy market prices and tariffs, into account. This optimization helps more than just Marcus Garvey Village—it enables the building to provide valuable capacity to the grid to help keep the lights on and energy prices in control in its community.
With energy storage, businesses of all kinds can manage rising time-based electricity costs through automatic deployment of stored energy, participation in regional incentive programs, and savings in energy expenditure.
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