Changes in regulatory requirements, market structures, and operational technologies have introduced complexities that traditional ratemaking approaches can’t address. Poorly designed rates lead to...
Demand Response Drivers
Identifying correlations between adoption rates and market factors.
other potential drivers don’t reveal a correlation with the level of DR. This doesn’t necessarily rule out these factors as possible explanatory variables for DR adoption rates. Rather, additional analysis is needed to better understand their relationship to DR market penetration in the past, and could reveal correlations in the future. In some cases, these drivers might represent untapped opportunities for demand response.
• Weather: DR is often suggested as a mitigating solution for peak electrical demand caused by large cooling loads on hot days. However, average summer temperature extremes show no correlation with levels of DR participation. One explanation for this is a discrepancy in the data. DR participation is expressed in terms of enrollment, which would depend on system planning that typically assumes average weather conditions. It’s likely that DR events are called more often during times of extreme temperatures, and therefore a correlation might emerge if performance data, rather than enrollment, were available.
• Frequent outages: To test the possibility that demand response has been implemented to mitigate blackouts and brownouts, the analysis compared DR levels with the frequency and impact of reliability events. The data source for reliability is a paper from Lawrence Berkeley National Laboratory that tracked the reliability of the U.S. electric power system. 21 No correlation is evident. However, the fact that calls to DR resources are included in the emergency protocols for many electric systems proves that demand response is utilized as a reliability “backstop.” 22
• Load and population growth: In places where growth is significant, demand response has been recommended as an alternative to building new capacity. However, examination reveals no evidence that areas with stronger growth—both electric load and population—have achieved higher levels of DR. The state-level forecasts in the National DR Potential Study provides the data source. 23
• DR incentive levels: Perhaps surprisingly, the level of utility incentives provides for demand response doesn’t appear to be a factor in driving participation. To test incentive level, the analysis compared the average incentive for peak reductions ($/MW) reported in the Energy Information Agency’s Form 861. 24
• Customer attributes: Demand response has been particularly successful among certain sectors and customers with particular attributes. For example, large industrial customers provide bulk reductions under interruptible tariffs, and residential air conditioners are important for direct load control programs. However, the data analyzed for this report haven’t revealed a significant role for customer attributes in driving overall DR levels. Using data from the FERC potential assessment, the analysis examines sectoral mix (residential, commercial, and industrial) and saturation of residential central air conditioners. Neither shows a correlation with DR participation.
Future Drivers of DR Adoption
Several potential future uses of DR could act as drivers of program adoption in the longer term. Expanding markets, increased adoption of technology, energy and climate policy, and even economic recovery are capable of affecting the future of demand response in the coming decade.
While demand response has evolved from interruptible power arrangements between utilities and large industrial customers and direct load control programs that cycle off residential air conditioning, it