Utilities are leaving no stone unturned in their search for ways to save electricity. Federal incentives will support new technologies and projects, but can those incentives overcome structural...
Demanding More from DR
Customer-specific demand-response strategies become more sophisticated.
more accurate and more efficient. In today’s world, it’s still best to have some default constraints programmed into the controller in case the algorithm calculates what would appear to be an extreme control strategy, like the 100-percent off strategy that was implemented in that original test.
• Customer Comfort Impacts : Although the results of adaptive control strategies do deliver increased load reductions, there’s no mechanism in them to help levelize comfort impacts. Ensuring comfort is an important part of the overall opportunity to increase equity, fairness and customer acceptance across program participants.
Obviously, it’s much easier for a customer who has a 10-kW HVAC system to give up 1 kW of load than it is for a customer who has a 3-kW HVAC system. If they’re both driven to deliver 1 kW, there would be a significant discrepancy in customer comfort impacts between them. Also, customers who have multiple zones of HVAC might be more willing to allow some zones to be curtailed more aggressively than others—as long as the zones are physically isolated.
Considering that fact, newer versions of the so-called adaptive algorithms now are being designed with the capability of being customized by downloading customer-specific parameters that will go even further in minimizing comfort impact variations, while simultaneously managing the load reductions being delivered from various size installations. By providing the algorithm with parameters such as the HVAC connected load (kW), the control strategy can be optimized to not only guarantee that all participants contribute load reductions, but that customers’ relative BTU reductions per hour also are considered. This optimization example is one more method of increasing equity amongst program participants, which in the long run will help insure the program’s overall success.
Most discussions are on the assumption that control devices directly manage the running characteristics and duty cycle of HVAC systems. But another variant that’s now common is the so-called smart thermostat, which allows the option to implement either duty-cycle control or temperature setbacks.
Both approaches accomplish load reductions, but aren’t tied to the same control methodology. For a temperature setback, the utility effectively is reducing the natural run time of the unit, except now it’s hardwiring that duty cycle to a temperature. This can be attractive to the customer because it offers a clearly defined level of comfort impact and guarantees it across all participants ( i.e., everybody’s setpoint is increased by 3 degrees). This will occur at the expense of levelized load reduction, but in aggregate the program still will deliver an average load reduction per participant that meets the cost-effectiveness test. Most utilities, having a choice, will let load reductions vary from customer to customer, while opting for a levelized comfort impact. The control strategy—temperature setback in this case—still must be modulated by the load-control system to meet the required aggregate load-reduction values, but at least comfort impacts are levelized across all program participants.
DR and Ancillary Services
The opportunity to use DR for delivering some of the ancillary generation services required to operate a utility has been promoted for years. Efforts to