Abstract
Extreme events such as hurricanes cause damages to various infrastructures, including power supply and transportation networks. Restoration of power supply services after extreme events is crucial for disaster response and recovery activities. With damages to transportation and other supply chain networks following extreme events, energy utility companies face significant challenges in achieving faster restoration of power supply services. This was the case for the utility companies in Puerto Rico after Hurricane Maria in 2017. One option for the utility companies in such circumstances will be to temporarily connect impacted populations to reserve generators, strategically located before the event, for quicker restoration of services. The objectives of this article are to: 1) develop a geospatial framework using a multicriteria decision analysis (MCDA) approach for placement of reserve generators and 2) identify strategic locations using 12 criteria representing physical, socioeconomic, environmental, and built environment conditions in Puerto Rico for the placement of reserve generators. Five different approaches are used to determine weights for the 12 criteria used in the MCDA approach. The geospatial framework developed in this article is comprehensive, which along with the weight determination approaches could be adapted to identify potential sites for the placement of additional energy infrastructures, including transformers, mobile stations, and microgrids, to power a city during extreme events.
| Original language | English |
|---|---|
| Article number | 9026775 |
| Pages (from-to) | 659-669 |
| Number of pages | 11 |
| Journal | IEEE Transactions on Engineering Management |
| Volume | 67 |
| Issue number | 3 |
| DOIs | |
| State | Published - Aug 2020 |
Funding
Manuscript received March 15, 2019; revised July 18, 2019, October 5, 2019, and December 1, 2019; accepted December 19, 2019. Date of publication March 6, 2020; date of current version July 16, 2020. This work was supported by the U.S. Department of Energy, Office of Electricity, under contract DE-AC05-00OR22725 with UT-Battelle, LLC. Review of this manuscript was arranged by Department Editor A. Solis. (Corresponding author: Olufemi A. Omitaomu.) S. M. Kotikot was with the Oak Ridge National Laboratory, Oak Ridge, TN 37831 USA. She is now with the Department of Geography, Pennsylvania State University, University Park, PA 16802 USA (e-mail: malaso.susan@gmail. com). This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The U.S. government retains the publisher, by accepting the article for publication, acknowledges that the U.S. government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for U.S. government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (https://energy.gov/downloads/doe-public-access-plan).
| Funders | Funder number |
|---|---|
| US Department of Energy | |
| U.S. Department of Energy | |
| Office of Electricity Delivery and Energy Reliability | DE-AC05-00OR22725 |
Keywords
- Energy infrastructure siting
- geospatial framework
- multicriteria decision analysis (MCDA)
- weighted sum model (WSM)
