%0 Report %A Johannes J Thiemann %A Nicholas DeForest %A Michael Stadler %A Judy Lai %A Wei Feng %A Kristina Hamachi LaCommare %A Yu Joe Huang %A Chris Marnay %D 2013 %T Identification of Demand Response Potential for Microgrids Using the Distributed Energy Resources Customer Adaption Model, A Case Study of the Alameda County Santa Rita Jail for 2011 %2 LBNL-1005114 %X
As renewable energy production increases and the electricity market paradigm changes Demand Response (DR) programs are at the forefront of the effort to reduce peak loads. Another emerging trend is microgrids, which allow for the integration of renewable distributed energy resources (DER) into power systems controlled at the local level. Therefore, the potential of microgrids to participate in DR simultaneously lowering electricity costs and supporting reliable macrogrid operation should be analyzed.
Santa Rita “Green” Jail (SRJ), run by the local County government, is a microgrid demonstration project integrating 1MW fuel cell, 1.2MW PV and 2MW 4MWh of electrical storage. The interaction of these DER can save electricity costs and lower demand peaks. As the markets and tariffs for DR are not straightforward an analysis is needed to tap the full potential of the installed infrastructure. As a public sector demonstration project SRJ can encourage broader adaption of DER and electric storage.
This report evaluates the potential for DR for SRJ focusing on the value of electric storage under different utility DR programs. Key operating characteristics are determined to ensure viable operation in different use cases. Also, load shed and shift capabilities are evaluated to identify their economic value under DR programs compared to electrical storage. The Distributed Energy Resources Customer Adoption Model (DER-CAM) is able to find the optimal battery operation schedule. DER-CAM was enhanced by DR capabilities and load shed and shift modules to optimize operational behavior based on DER generation, load and DR events.
This report demonstrates how much the microgrid can save by participating in DR. It is identified which DR program is most viable and which barriers and success factors must be considered. Finally, the amount of peak load mitigation that can be delivered to the macrogrid by SRJ to help meet national and federal policy targets for DR is presented.