The promise and hype surrounding the smart grid far exceeds its current capabilities. In no area is this truer than with Demand Response (DR) programs for the commercial building sector, which is responsible for 20% of energy demand and emissions in the U.S.  These concentrated pools of demand are a nightmare for ever more strained utility grids, especially in major cities. As a result, utilities have created DR programs to provide financial incentives for building owners to reduce energy consumption during peak periods. Why would utilities pay end users to reduce power? The alternative is to build more power plants, which will cost the industry billions down the road.

DR "successes" in our industry are trumpeted far and wide as utilities launch new programs and initial customer contracts are signed. However, there are some fundamental issues looming that have and will continue to limit the success of these programs as they are rolled out across the commercial building sector. There are a number of enormous challenges to be addressed, including:

  • The risk to tenant service levels posed by DR events
  • The execution complexities of intelligently managing through DR events, especially in large, complex buildings, and
  • The capital requirements necessary to fund the people or systems needed to ensure building owners and managers can address these issues

Despite the potentially huge scale of DR programs and dollars in our industry, the current technologies and systems in place to help utilities and the commercial building sector execute DR programs are surprisingly rudimentary. Examples of this "ManualDR" are:  

  • Manual DR signals -- e.g., emails, phone calls, text messages -- from the utility or DR aggregator to building managers to let them know a DR event is coming
  • Manual changes to energy systems (e.g., building manager turning off lights or an HVAC chiller) to execute load reduction as best as possible
  • Limited ability to estimate how much load reduction occurred vs. target
  • Limited ability to predict or determine the tenant comfort impact from the changes in the response
  • Bill reconciliation and credit in 60-90 days when the data is collected and processed by the utility

How can building owners confidently participate in DR events this way? How can a utility build a scalable, effective DR program reaching the hundreds or thousands of customers they need to on these sorts of mechanisms? They can't. If you talk to commercial building owners or utilities, you will learn that the commercial sector has not been adopting DR programs nearly as often as one would expect. This lack of adoption is one of the big reasons for the introduction by many leading utilities of the Peak Day Price (PDP) tariff program, which charges 10 times to 15 times the normal rates during peak periods. Unlike the voluntary incentive programs, large commercial customers are automatically moved onto the PDP program unless they opt out by adopting another DR plan.

Why are the DR programs not working? Basically, because existing energy management systems and practices in the commercial sectors were not created in a DR world.  The vast majority of the innovation to date from the industry has been directed "outside the meter" (e.g., outside of the building) from leaders such as EnerNOC and Silver Spring. But in reality, these DR programs will not succeed unless there is a corresponding amount of innovation "inside the meter." This is the domain of vendors like Honeywell, Schneider-Electric and Johnson Controls, which, though they are all large companies with broad offerings, are not names synonymous with innovation, and don't have a lot of incentives to radically change their mature, stable and fairly concentrated industry. 

To their credit, a number of these companies are now starting to focus on these problems either individually or in partnerships. Thanks to the work of the government labs like Lawrence Berkeley, industry bodies and some leading vendors, more intelligent automated solutions and standards like OpenADR are being piloted in the market, but things are moving slowly. Even these emerging "AutoDR" solutions still leave much to be desired, as they basically consist of:

  • An electronic signal from the utility or DR aggregator to the building management system (BMS), and
  • A pre-programmed, fixed set of changes executed by the BMS over the building to respond to the DR event

However, common shortcomings include:

  • No ability to predict what actual load can be tolerably shed by the building
  • No regard to current or forecast weather conditions on the day
  • Limited ability to predict or determine the tenant comfort impact from response
  • Limited ability to validate the load shed vs. target in real time
  • Results are best efforts based on the fit between the pre-programmed response and the specific situation on the day of the event

In order to provide a scalable, widely-adopted and valuable smart grid program for the commercial building sector, the industry needs a fundamental increase in the intelligence of their "inside the meter" DR systems, and they need to be tightly integrated with the"outside the meter" systems, as well. 

 This next generation of DR might well be known as "Optimized DR." Components will need to include:

  • An initial electronic signal from the utility/ DR aggregator to the building manager, and then subsequent signals as the DR event progresses in the region with updates on any additional requirements
  • An automated response from the building's energy systems back to the utility/ aggregator to confirm the precise capacity of load shedding available given current conditions
  • Incorporation of the DR event into the building's energy optimization plan for that day, with the energy plan tailored to comply with the event while minimizing tenant comfort impact
  • Dynamic adjustments to the energy plan and load shedding based on any changes to conditions (inside or outside the building) during the day
  • Estimated and real-time validation of actual load shedding vs. target
  • Estimated and real-time understanding of tenant impact of response
  • Estimated and real-time understanding of economic benefits of participating
  • Confirmation back to utility or DR aggregator immediately after the event confirming actual results

If the industry is to deal with these major barriers to adoption and achieve its potential in terms of the smart grid, it must move from "ManualDR" and the emerging "AutoDR" to the future's "OptimizedDR" for commercial buildings.  While my company, BuildingIQ, now offers "DRiQ," the world's first OptimizedDR solution (see www.BuildingIQ.com), we need a range of solutions from the major Inside the Meter vendors to move the industry forward.