PJM Interconnection to Test Price Demand Response Program

June 23, 2011
PJM Interconnection is implementing a on a Price Response Demand demonstration project.

PJM Interconnection is implementing a price response demand demonstration project that shows how locational marginal price paired with distributed intelligence can drive automated residential demand response in the home.

Using Tendril Connect and UISOL’s Open Automated Demand Response (OpenADR) price server, the project allows PJM to test the end-to-end integration of a near real-time price response demand program and better manage electricity demand—making real-time pricing available to consumers at five-minute intervals at the nodal level.

“The ability to manage electricity usage using demand management tools with distributed intelligence could revolutionize the relationship between utilities and their customers,” said Dr. Scott Coe, UISOL VP of Wholesale Markets. “If the assumptions we are making in this pilot around pricing models and communication protocols are right, utilities and consumers will no longer need to surrender to the high energy cost and reliability impacts of uninformed residential consumption.”

The benefits to utilities and other demand response providers are two-fold. First, they can aggregate load from residential customers in smaller increments and in more sophisticated ways that do not inconvenience the customer. For example, by adjusting temperatures on thermostats by one or two degrees during various points in the day, utilities can lower overall demand in their service area, thereby avoiding an emergency event or paying a short-term increase in the wholesale market rate for electricity – resulting in cost savings for consumers.

Second, transparency into residential consumption at the nodal level with near-real-time pricing will mitigate the utilities’ need to purchase high-priced energy on the wholesale markets. It could also lead to better integration of renewable energy into the grid, as regional transmission organizations and utilities gain insight into the consumption patterns of end users and match it with the availability of renewable energy resources throughout the day.

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