Minnesota-based Great River Energy told local media that it plans to use OATI’s webDistribute DRMS solution to centrally operate its suite of commercial and industrial load management programmes including its 28 member cooperatives’ businesses.
The cooperative utility will start by deploying the solution in a pilot to determine how webDistribute’s Conservation Voltage Reduction (CVR) feature complies with its members’ grids, reported benzinga.com.
The OATI solution will be provided as a software-as-a-service, hosted from the OATI Private Cloud featuring the North American Electric Reliability Corporation (NERC) critical infrastructure protection compliant data centers.
webDistribute will also provide functionality needed to automatically gather the data required for NERC's Demand Response Availability Data System reporting on an ongoing basis.
Great River Energy is a non-profit electric cooperative generating and transmitting electricity to some 1.7m people in Minnesota region.
Demand response in the US
In other demand response news, Bonneville Power Administration (BPA), an agency of the US Department of Energy responsible for delivering power across the Pacific Northwest, in Q2 2015 announced its usage of big data management company AutoGrid’s demand response optimisation & management system (DROMS) to schedule and signal demand response events.
BPA said that since it started a demonstration project in February, 2015 the utility has used the DROMS system to execute more than 20 events in the range of 18 to 28 megawatts, and, in total, has shed more than 500 megawatt-hours, according to 'Inside Big Data' trade magazine.
As part of the demonstration project, BPA assessed AutoGrid’s DROMS applicability as a centralized operational dashboard to design, manage and operationalize multiple DR efforts.
BPA, a wholesale supplier of electricity to 142 utilities and 490 transmission customers, also determined if the system can indicate the amount of load that it is available to be shed through any of its DR programs.
Monitoring demand response events in real-time and viewing load shed on a minute-by-minute basis to respond to changes in supply from renewable energy sources were also requirements of the project, BPA told 'Inside Big Data'.