skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Applying DER-CAM for IIT Microgrid Explansion Planning

Abstract

The Distributed Energy Resources Customer Adoption Model (DER-CAM) is an economic and environmental model of customer DER adoption. This model has been in development at the Lawrence Berkeley National Laboratory since 2000. The objective of the model is to find optimal DER investments while minimizing total energy costs or carbon dioxide (CO2) emissions, or achieving a weighted objective that simultaneously considers both criteria. The Illinois Institute of Technology (IIT) Microgrid project started in August 2008, and the majority of the project was completed in May 2013. IIT Microgrid, funded mostly by a grant from the U.S. Department of Energy as well as State and philanthropic contributions, empowers the campus consumers with the objective of establishing a smart microgrid that is highly reliable, economically viable, environmentally friendly, fuel-efficient, and resilient in extreme circumstances with a self-healing capability. In this project, we apply DER-CAM to study the expansion planning of the IIT Microgrid. First, the load data, environmental data, utility data, and technology data for the IIT Microgrid are gathered and organized to follow the DER-CAM input requirements. Then, DERCAM is applied to study the expansion planning of the IIT Microgrid for different cases, where different objectives in DER-CAM and different utilitymore » conditions are tested. Case 1 considers the objective of minimizing energy costs with fixed utility rates and 100% electric utility availability. Case 2 considers the objective of minimizing energy costs with real-time utility rates and 4 emergency weeks when the IIT Microgrid does not have access to the electric utility grid and has to operate in island mode. In Case 3, the utility rates are restored to fixed values and 100% electric utility availability is assumed, but a weighted multi-objective (Obj: a × costs + b × CO2 emissions, where a and b are weights for cost minimization and CO2 emissions minimization) is utilized to consider both energy costs and CO2 emissions. On the basis of the test results, the IIT Microgrid has the potential to benefit from investments in more DER technologies. The current annual energy costs and CO2 emissions for the IIT Microgrid are 6,495.1 k$ and 39,838.5 metric tons, respectively. This represents the baseline for this project.« less

Authors:
 [1];  [1];  [2];  [2]
  1. Illinois Inst. of Technology, Chicago, IL (United States)
  2. Argonne National Lab. (ANL), Argonne, IL (United States)
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1260255
Report Number(s):
ANL/ESD-16/6
127680
DOE Contract Number:  
AC02-06CH11357
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
29 ENERGY PLANNING, POLICY, AND ECONOMY; 54 ENVIRONMENTAL SCIENCES

Citation Formats

Shahidehpour, Mohammad, Li, Zuyi, Wang, Jianhui, and Chen, Chen. Applying DER-CAM for IIT Microgrid Explansion Planning. United States: N. p., 2016. Web. doi:10.2172/1260255.
Shahidehpour, Mohammad, Li, Zuyi, Wang, Jianhui, & Chen, Chen. Applying DER-CAM for IIT Microgrid Explansion Planning. United States. doi:10.2172/1260255.
Shahidehpour, Mohammad, Li, Zuyi, Wang, Jianhui, and Chen, Chen. Tue . "Applying DER-CAM for IIT Microgrid Explansion Planning". United States. doi:10.2172/1260255. https://www.osti.gov/servlets/purl/1260255.
@article{osti_1260255,
title = {Applying DER-CAM for IIT Microgrid Explansion Planning},
author = {Shahidehpour, Mohammad and Li, Zuyi and Wang, Jianhui and Chen, Chen},
abstractNote = {The Distributed Energy Resources Customer Adoption Model (DER-CAM) is an economic and environmental model of customer DER adoption. This model has been in development at the Lawrence Berkeley National Laboratory since 2000. The objective of the model is to find optimal DER investments while minimizing total energy costs or carbon dioxide (CO2) emissions, or achieving a weighted objective that simultaneously considers both criteria. The Illinois Institute of Technology (IIT) Microgrid project started in August 2008, and the majority of the project was completed in May 2013. IIT Microgrid, funded mostly by a grant from the U.S. Department of Energy as well as State and philanthropic contributions, empowers the campus consumers with the objective of establishing a smart microgrid that is highly reliable, economically viable, environmentally friendly, fuel-efficient, and resilient in extreme circumstances with a self-healing capability. In this project, we apply DER-CAM to study the expansion planning of the IIT Microgrid. First, the load data, environmental data, utility data, and technology data for the IIT Microgrid are gathered and organized to follow the DER-CAM input requirements. Then, DERCAM is applied to study the expansion planning of the IIT Microgrid for different cases, where different objectives in DER-CAM and different utility conditions are tested. Case 1 considers the objective of minimizing energy costs with fixed utility rates and 100% electric utility availability. Case 2 considers the objective of minimizing energy costs with real-time utility rates and 4 emergency weeks when the IIT Microgrid does not have access to the electric utility grid and has to operate in island mode. In Case 3, the utility rates are restored to fixed values and 100% electric utility availability is assumed, but a weighted multi-objective (Obj: a × costs + b × CO2 emissions, where a and b are weights for cost minimization and CO2 emissions minimization) is utilized to consider both energy costs and CO2 emissions. On the basis of the test results, the IIT Microgrid has the potential to benefit from investments in more DER technologies. The current annual energy costs and CO2 emissions for the IIT Microgrid are 6,495.1 k$ and 39,838.5 metric tons, respectively. This represents the baseline for this project.},
doi = {10.2172/1260255},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2016},
month = {4}
}

Technical Report:

Save / Share: