When customers sell demand response into a regional capacity market (such as PJM’s Reliability Pricing Model, known as the RPM), how much credit should they earn for agreeing to curtail demand and...
Demanding More from DR
Customer-specific demand-response strategies become more sophisticated.
faced by potential participants and program sponsors is that the cost of implementing load reduction sometimes exceeds its market value. Another issue is that from the customer’s perspective, the actual load reduction delivered by program participants varies greatly from customer to customer. These issues cause a significant inequity among program participants both from their value to the program and from the program’s impact on individual comfort, convenience, or business impact.
Consider a scenario where the DR provider is the electric utility and the program is residentially focused. A utility picks a DR technology vendor and deploys a pilot to test the performance ( i.e., load reduction) of the load-control system. The results show 0.3-kW load reduction for each customer unit vs. the 1 kW needed for a cost-effective solution, so the utility then abandons the program on lack of financial merit.
Even though the data shows the load reduction was inadequate, no one questions the methodology or strategy being used to control the load. Often the control strategy being deployed isn’t examined in the context of the local appliance load conditions. Somehow, it became ingrained in the industry that only one kind of control schedule can be implemented with residential heating, ventilating, and air conditioning (HVAC) control—in this case the magic 50-percent duty cycle. The reality is that that the 50-percent control strategy being tested is only applicable to the utility that developed it, and it probably was developed more than 20 years ago.
When this real-life scenario occurred at a large West Coast electric utility, industry experts suggested that another control strategy could have delivered the necessary load reduction. That concept was rejected, however, because the tested strategy was the one commonly used throughout the industry. The 50-percent duty cycle approach didn’t work, however, because the typical residential HVAC system was hitting the grid with 2.3 kW of demand, not 4 kW as assumed in the test (see “HVAC Load Control—A Flawed Test”). It just happened that the local HVAC industry had a habit of over-sizing their installations to the point where the natural duty cycle of those systems was relatively low even during hot summer afternoons. A fixed duty cycle, based on program assumptions, rather than on local appliance run-time statistics, was doomed to failure. A correct control strategy that accounts for true demand, easily could deliver at least 1 kW of load reduction, while still allowing the HVAC system to deliver significant cooling.
• Adaptive Control : One of the methods employed today to improve load reductions is sometimes known as adaptive control, which has been tested and revised many times over the last 20 years. The first version was called the smart duty cycler, and was tested in the early 1980s at a large southern utility. The basic concept never has changed—install intelligence in the device connected to the load and program that device to forecast the next hour’s natural duty cycle. Once that forecast is made, it’s easy to calculate what the new run time of the appliance needs to be in order to deliver the