Optimal Scheduling of Time-Shiftable Electric Loads in Expeditionary Power Grids

Abstract

Environmental control on the battlefield enhances readiness, reduces casualties, and protects the sensitive equipment upon which U.S. doctrine relies. Purchase and delivery of fuel necessary to provide this service was responsible for an estimated $1.4 billion in costs and 33 resupply convoy casualties per year at the peak of U.S. wars in Iraq and Afghanistan. It is well understood that the current semi-autonomous mode of environmental control unit (ECU) operation results in generators operating at low average loads-and low fuel efficiency-to accommodate periodic unmanaged spikes in peak load. We propose a mechanism to reduce costs through optimal prescriptive management of these ECUs. We exploit the fact that ECU operation is time-shift able to develop a mixed-integer linear programming (MILP) model that optimally schedules ECUs to eliminate unmanaged peak demand, reduce generator peak-to-average power ratios, and facilitate a persistent shift to higher fuel efficiency. Using sensitivity analysis, we quantitatively demonstrate how grid composition, temperature band tolerance, and energy storage capabilities contribute to fuel efficiency under this approach.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2015
Accession Number
AD1009343

Entities

People

  • John G. Sprague

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Business Administration
  • Climate Change
  • Climate Change Adaptation
  • Electric Power
  • Electrical Grids
  • Energy
  • Energy Conservation
  • Energy Consumption
  • Energy Efficiency
  • Energy Storage
  • Energy Systems
  • Fuel Efficiency
  • Heat Transfer
  • Linear Programming
  • Load Monitoring
  • Renewable Energy
  • Test And Evaluation

Readers

  • Energy Conservation and Renewable Energy Engineering.
  • Operations Research
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.