The FERC sent a bold message to the energy industry yesterday, and it was one we were very excited to hear.  By ordering wholesale energy market operators to pay energy market prices for demand response resources, the FERC acknowledged the high value of demand response and empowered DR to reach its full energy conservation potential.

The FERC proposed the decision last year, but by making it official this week, it effectively removed an enormous market barrier to DR’s effectiveness.  Prior to the order, the energy savings, or “negawatts,” generated by demand response programs commanded less compensation than the megawatts created by energy producers. Now, when a net benefits test proves demand response is cost effective, demand response negawatts must also earn the locational marginal price (LMP) normally paid for megawatts.

While my colleagues and I may humbly go so far as to rank negawatts’ value above that of megawatts, we’re certainly thrilled to see the FERC rank them as equals.  I agree with FERC chairman Jon Wellinghoff who said the decision opens the demand response market to innovation while ensuring fair rates for electricity customers.  I’ll go even further and say the new rule stands to have a profoundly positive environmental impact by elevating DR’s presence, consequently reducing the need for power plant operations and electricity generation.

As the organized wholesale market operators implement their new price structures this summer—FERC requires compliance filings by July 22—we’ll be set to deliver the benefits of the new rule to consumers.  Increased compensation for DR products and services means increased revenue to roll back into research and development.  We are ready and willing to spearhead this surge of energy conservation ingenuity that’s surely about to unfold across the industry.

The FERC’s new ruling proves it’s a great time to be in the business of demand side energy management.  We’re happy to be leading the movement and to push this train a lot faster towards its ultimate energy optimization destination.