Assessment of (mu)grid distributed energy resource potential using DER-CAM and GIS

Edwards, Jennifer L. ; Marnay, Chris ; Bartholomew, Emily ; Ouaglal, Boubekeur ; Siddiqui, Afzal S. ; LaCommare, Kristina S.H.

Lawrence Berkeley National Laboratory

关键词: Natural Gas;    Power Generation;    Information Systems;    Heat Recovery;    32 Energy Conservation, Consumption, And Utilization;   

DOI  :  10.2172/803770
RP-ID  :  LBNL--50132
RP-ID  :  AC03-76SF00098
RP-ID  :  803770

美国|英语

来源: UNT Digital Library

【 摘 要 】

This report outlines an approach to assess the local potential for deployment of distributed energy resources (DER), small power-generation installations located close to the point where the energy they produce will be consumed. Although local restraints, such as zoning, building codes, and on-site physical barriers are well-known frustrations to DER deployment, no analysis method has been developed to address them within a broad economic analysis framework. The approach developed here combines established economic optimization techniques embedded in the Distributed Energy Resource Customer Adoption Model (DER-CAM) with a geographic information system (GIS) analysis of local land-use constraint. An example case in the San Diego area is developed from a strictly customer perspective, based on the premise that future development of DER may take the form of microgrids ((mu)Grids) under the control of current utility customers. Beginning with assumptions about which customer combinations h ave complementary energy loads, a GIS was used to locate specific neighborhoods in the San Diego area with promising customer combinations. A detailed energy analysis was conducted for the commercial/residential area chosen covering both electrical and heat energy requirements. Under various scenarios, different combinations of natural gas reciprocating engines were chosen by DER-CAM, ranging in size from 25 kW to 500 kW, often with heat recovery or absorption cooling. These generators typically operate throughout the day and are supplemented by purchased electricity during late-night and early-morning hours, when utility time-of-use prices are lowest. Typical (mu)Grid scenarios displaced about 80 percent of their annual gas heat load through CHP. Self-generation together with absorption cooling dramatically reduce electricity purchases, which usually only occur during nighttime hours.