(NEPTUNE) Installation Energy Resilience Using Machine Learning for Continuity of Operations Plan (COOP) and Adaptive Basing

Abstract

ABSTRACT: The proposed work will (a) develop an automated process for translating satellite imagery andGIS information back-and-forth from an electrical power system analysis tool, (b) simulate threats toevaluate continuity of operations plans for outages and contingency scenarios, (c) enhance software toolsXENDEE and ArcGIS to equip an installation commander, public works, engineering, and GIS teams withcapability to rapidly evaluate options and communicate effectively across teams, and (d) update theContinuity of Operations Plan (COOP) in association with teams at MCAS Miramar.This work has direct significance for Engineering Planners and Public Works that need capability to rapidlyevaluate system upgrades and alternative configurations to maintain energy resilience and continuity ofoperations, and further, to communicate that information with the base Commander and associatedpersonnel for faster decision making. Four tasks generate a minimum viable product for evaluation byMCAS Yuma. Dual-use applications will also be sought for civilian sector work for rural electrification,refugee camps, growing real estate developments, university campuses, and electric utilities.Navy benefits include an up-to-date baseline model of the MCAS Yuma electrical power system that PublicWorks can use to evaluate options, track performance, and visualize system status. The project will alsoidentify near-term opportunities to enhance energy performance and reduce O&M costs as directed by DoDDirective 4180.01 DoD Energy Policy. Machine learning algorithms will be used to develop powernetwork configurations that counter off-base threats to the APS grid/microgrid and on-base threats toNAVFAC infrastructure from attacks, equipment failure, and other outages. This addresses requests in DoDInstruction 4170.11 Installation Energy Management, Naval Research and Development, Navy EnergySecurity Framework, and MCICOM Installation neXt Resilience Symposium. Further, this work also hasapplications to operational energy and adaptive basing as outlined in the National Defense Strategy, mostnotably for rapidly evaluating alternatives to provide flexibility for transitioning from contingency toenduring scenarios.

Document Details

Document Type
DoD Grant Award
Publication Date
Apr 29, 2020
Source ID
N000142012246

Entities

People

  • Nathan G. Johnson

Organizations

  • Arizona State University
  • Office of Naval Research
  • United States Navy

Tags

Readers

  • Data Mining and Knowledge Discovery.
  • Emergency Management and Homeland Security.
  • Energy Conservation and Renewable Energy Engineering.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • Space