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Today's power systems simulation tools don't provide the analysis capabilities needed to study the forces driving change in the energy industry. The combined influence of fast-changing information technology, novel and cost-effective distributed energy resources, multiple and overlapping energy markets, and new business strategies result in very high uncertainty about the success of these important innovations. Concerns expressed by utility engineers, regulators, various stakeholders, and consumers can be addressed by GridLAB-D. Some example uses include:

Rate structure analysis

Multiple differentiated energy products based on new rate structure offerings to consumers is very attractive to utilities because it creates the opportunity to reveal demand elasticity and gives utilities the ability to balance supplier market power in the wholesale markets. The challenge is designing rate structures that are both profitable and attractive to consumers. GridLAB-D will provide the ability to model consumer choice behavior in response to multiple rate offerings (including fixed rates, demand rates, time-of-day rates, and real-time rates) to determine whether a suite of rate offerings is likely to succeed.

Distributed resources

The advent of new distributed energy resource (DER) technologies, such as on-site distributed generation, BCHP and Grid-FriendlyTM appliance controls creates a number of technology opportunities and challenges. GridLAB-D will permit utility managers to better evaluate the cost/benefit trade-off between infrastructure expansion investments and distributed resources investments by including the other economic benefits of DER (e.g., increase wholesale purchasing elasticity, improved reliability metrics, ancillary services products to sell in wholesale markets).

Peak load management

Many peak-shaving programs and emergency curtailment programs have failed to deliver the expected benefits. GridLAB-D can be calibrated to observe consumer behavior to understand its interaction with various peak shaving strategies. The impact of consumer satisfaction on the available of peak-shaving resources can be evaluated and a more accurate forecast of the true available resources can be determined. GridLAB-D will even be able to evaluate the consumer rebound effect following one or more curtailment or load-shed events in a single day.

Distribution automation design

GridLAB-D can support some aspects of the design and analysis of distribution automation technology, allowing utilities to offer heterogeneous reliability within the same system but managing power closer to the point of use.