Smart grid load shedding of consumer appliances during peak periods is challenged by the need to have trustworthy responses from these appliances. A new design shows how this can be achieved with a “trust-but-verify” framework.
One strategy for getting load reductions during periods of peak demand is for Energy Service Providers (ESPs) to maintain direct control over a class of consumer loads. This has tradeoffs against allowing indirect control by a consumer through means like variable pricing. Direct control has the advantage that the ESP has better knowledge of how and when to shed loads, but direct control assumes the existence of appliances that can be relied upon to receive, and act on, load shed commands from the ESP. This introduces a problem with the trust the ESP can place in consumer appliances. Approaches that place trust in appliances, like relying on special chips that enable ESP access, make direct controls more expensive and difficult to deploy. On the other hand, consumer “free riders”, who accept discount programs for direct control but fail to respond to load shed signals, make enforcement problematic if there is no ESP technical control.
I worked with a team that includes students from the TCIPG project and Andrew Wright from N-Dimension to develop a technique for direct control that is based on a “trust but verify” technique called Non-Intrusive Load Shed Verification (NILSV). The idea is to use Non-Intrusive Load Monitoring (NILM) on smart meters to monitor power usage and from this to form an estimate of whether load shed instructions are being respected by consumers. The main novelty required by the technique was a form of distributed NILM (dNILM) which does heavy-weight NILM calculations at the ESP backend while doing light-weight monitoring on the smart meter. We did some preliminary tests of the technique to show general feasibility using monitoring of appliances in homes.
The over-all approach for NILSV is described in an article in an IEEE Pervasive special issue on smart energy systems , and details of the dNILM algorithms were presented at ISGT .
- Non-Intrusive Load Shed Verification, David C. Bergman, Dong Jin, Joshua P. Juen, Naoki Tanaka, Carl A. Gunter and Andrew K. Wright. IEEE Pervasive Computing, Special Issue on Smart Energy Systems, volume 10, number 1, pages 49-57, 2011.
- Distributed Non-Intrusive Load Monitoring, David C. Bergman, Dong Jin, Joshua P. Juen, Naoki Tanaka, Carl A. Gunter and Andrew Wright. IEEE/PES Conference on Innovative Smart Grid Technologies (ISGT ’11), Anaheim, CA, January 2011.