Advanced metering infrastructure (AMI) evaluations will benefit greatly from creating an appropriate DR portfolio as part of the overall solution.
In the Energy Policy Act of 2005 (EPACT...
Granular customer data will revolutionize megawatt markets.
which the industry is unaccustomed. Historically, electric and gas utilities have developed and deployed aggregate load-forecasting models in order to determine the amount of capital expenditure required to meet long-term load growth. While these analytical models do consider the impact of required maintenance and retirement of generation assets, their load-forecasting capabilities are somewhat limited. Smart technologies will substantially increase the precision, while significantly increasing the complexity, of the forecast.
Smart technologies significantly will increase the transparency of the T&D system by placing remotely controlled and monitored devices on the grid. These devices will be located at customer premises, at sub-stations, or directly on feeders. In other words, system operators will have visibility and access to the grid, the power flow in the system and finally to load and consumption data on a household-by-household basis. To take advantage of this amount of information and translate it into products in the wholesale market that will reduce the customer cost of service, utilities and power providers will have to gather, process, and analyze the information being generated by the system.
As utilities and power providers attain capabilities to crunch this vast amount of data and get better visibility into their system and customer behaviors, they will be able to incorporate demand-side assets in their wholesale portfolios and increase their ability to price these assets in the market. This negative generation—EE, conservation, and DR—will become dispatchable as regular supply assets and will become even more prominent in wholesale markets.
What is important to recognize is that the physical and workforce requirements of providing these data analytical capabilities are part of the overall system costs to tapping into any potential benefits of load-management activities. Overall, the level of granularity appropriate for accurate, yet not burdensome, forecasting programs hasn’t been defined. What is clear, however, is that getting the demand forecasts right is a critical step in incorporating demand-side assets into wholesale that doesn’t allow for a large margin for error.
Once a utility or a power provider has built the infrastructure and support staff necessary for creating accurate load forecasts that incorporate both supply and demand resources, the next critical question is: What if customers fail to act and EE, conservation, or DR program goals aren’t met?
The visibility of individual loads and the ability to aggregate in meaningful segments will allow utilities to identify quickly and correct customer behavior by changing the financial incentives they pay customers as part of these load and consumption control programs, such as EE, conservation and DR. This payment to customers determines the true cost of demand-side resources and their place on the dispatch stack. Today, these incentives are at best evaluated and adjusted on a yearly true-up, but after smart technologies, these true-ups can be as frequent as each billing cycle. The corrections naturally will try to adjust the design of these incentives to promote favorable customer behaviors and responses. These efforts will increase the magnitude of data gathering and analysis efforts necessary for a high-performing utility.
Success in the New Wholesale Market
The wholesale market will become more competitive