Ken Hejmanowski, Director of Product Management
January 6, 2017

Utilities have created Demand Response (DR) programs as one of their tools to help them balance their operations by managing the flip side of supply. By decreasing demand from their customers at peak times, they’re able to reduce the total supply they must produce, and thus avoid higher costs involved with increasing supply, as well as avoid the risk of generating too little electricity to meet demand.

DR programs rely upon customers volunteering to participate in a series of events in exchange for financial incentives. During DR events, participating customers must drop —and validate— their energy demand by agreed-upon amounts in order to qualify for the financial incentives.

The methods used by participants to live up to their DR obligations have been largely manual and rather brute force. Many times, it means that a facility manager must push buttons or throw levers to do things such as:

  • Turn off lights
  • Shut down some elevators
  • Shut down heating, venting and air-conditioning (HVAC) equipment
  • Reduce HVAC usage through re-setting temperature set points
  • Shut down production processes
  • Shift production processes to other times

Many times, these things are done in ways that significantly impact occupant comfort and productivity; yet 90% of a business’ operating costs is tied up in people and their productivity. According to the report, Health, Wellbeing & Productivity in Offices, by the World Green Building Council (Sept. 2014), employee productivity drops by 6% when temperature exceeds the maximum comfort level. So, while a 10% variation in energy cost might contribute only a small amount to the bottom line for a single building, it can have a disproportionate impact on the business’ total operating cost.

typicalbusinessoperatingcost

 

Impact of Temperature on Productivity and Relative Operating Cost

The BuildingIQ 5i Platform is the foundation for a DR service that automates the receipt of DR event notifications from utilities, and automatically responds —at the scheduled time— by shedding HVAC load that typically comprises up to 50 percent of a building’s total load. And it does so while maintaining occupant comfort. Furthermore, DR by BuildingIQ is unique to each building as it controls the existing HVAC system based on a constant learning cycle of modeling the building and the building management system (BMS), the thermal characteristics of the building itself, predictive control, and testing/validation of results. Finally, automated measurement & verification is built into BuildingIQ’s DR service to facilitate the qualification for utility incentives and reporting.

This results in a vast improvement in:

  • the ease and reliability with which customers can earn associated incentives,
  • a business’ ability to maintain normal operations and productivity during a DR event, and
  • enabling utilities to ensure that demand drops as expected, when expected.

Even so, there is another opportunity for utilities and customers when it comes to managing supply and demand, and that is through the incorporation and intelligent management of alternative energy sources. These alternative sources can include solar, wind, cogeneration, battery storage, and thermal storage. By predicting the need to shift to alternative sources at key times —in order to reduce demand, and then automating the ability to switch between sources and/or blend them— demand can be reduced at the least cost and least disruption to normal activities.

Each alternative energy source has its own characteristics as to total capacity, availability, costs, and relationships to weather. Understanding these is key in the development of an automated system such as the 5i platform that understands exactly when they should be brought into the supply mix and for how long. These characteristics and relationships can be captured by machine learning; and predictive models can be developed and integrated as part of a more comprehensive DR service, as well as optimized energy management outside of DR.

To make this more concrete, let’s imagine a scenario where a building has an automated DR system that incorporates alternative energy source management, is equipped with solar panels, battery storage, and thermal storage (via ice tanks), and assume that a DR event is issued from a utility for an unusually hot and humid day. The DR system does the following:

24 Hours pre-Event

  • Receives an automated signal from the utility giving 24-hour notice for a DR event
  • Sends an acknowledgement back to the utility
  • Schedules the drop to be automatically executed in the building at the specified start time
  • Checks a multitude of factors including its thermal model of the building, the weather forecast, the tariff schedule, and the event requirements such as start time, duration, and drop amount
  • Checks the availability of the alternative energy sources between receipt of the signal and the coming day
  • Compares all the data to expected weather conditions
  • Determines that even though the building usually uses its full solar capacity, significant cloud cover is expected to impact solar production, so the building will actually require more grid power than usual
  • Schedules both the battery storage and thermal storage to charge fully during night time hours when electricity is cheapest
  • Calculates a control plan for the next day that guarantees that the required demand drop will be achieved at the time and for the duration of the event

Event Day

  • Alters normal HVAC operations ahead of the event so that building zones enter the event preconditioned to be able to drift as much as possible through the event, and thus require minimal power input to maintain comfort. (Drift is defined as allowing the temperature to slowly increase from the lowest setpoint to the highest determined temperature range, or band, required to maintain tenant comfort.)
  • Feathers battery storage, thermal storage, solar, and grid energy to achieve the required demand drop at the minimum cost and while maintaining occupant comfort throughout the event
  • Adapts in real-time, and indeed, makes adjustments as it turns out that the forecasted cloud cover is less than expected, and more solar power is available
  • As the end of the DR event approaches, the DR system prepares to return to normal operations. As it does so, it plans to avoid system snap back which could result in occupant discomfort

Post-Event

  • Ramps back to normal operation to avoid bounce-back (sudden high energy usage) while maintaining occupant comfort

The DR system, by virtue of its modeling, learning and predictive control abilities, has modified the building HVAC system controls before, during, and after the event in order to shed the expected amount of load at the least possible cost. BuildingIQ is pushing forward with the integration of alternative energy sources into its 5i platform and increasing the intelligence of its DR service. The additional opportunities we offer utilities and building owners to manage both the supply- and demand-side of the grid is exciting stuff already, and getting more so every day.