Analysis Of The Performance Of An Optimization Model For Time-Shiftable Electrical Load Scheduling Under Uncertainty

Abstract

To ensure sufficient capacity to handle unexpected demands for electric power, decision makers often over-estimate expeditionary power requirements. Therefore, we often use limited resources inefficiently by purchasing more generators and investing in more renewable energy sources than needed to run power systems on the battlefield. Improvement of the efficiency of expeditionary power units requires better managing of load requirements on the power grids and, where possible, shifting those loads to a more economical time of day. We analyze the performance of a previously developed optimization model for scheduling time-shiftable electrical loads in an expeditionary power grids model in two experiments. One experiment uses model data similar to the original baseline data, in which expected demand and expected renewable production remain constant throughout the day. The second experiment introduces unscheduled demand and realistic fluctuations in the power production and the demand distributions data that more closely reflect actual data. Our major findings show energy grid power production composition affects which uncertain factor(s) influence fuel consumption,and uncertainty in the energy grid system does not always increase fuel consumption by a large amount. We also discover that the generators running the most do not always have the best load factor on the grid, even when optimally scheduled.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2016
Accession Number
AD1031484

Entities

People

  • John A Olabode

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Climate Change Adaptation
  • Electric Power
  • Electrical Loads
  • Energy
  • Energy Consumption
  • Energy Management
  • Energy Storage
  • Energy Systems
  • Experimental Design
  • Fuel Consumption
  • Generators
  • Humanitarian Assistance
  • Load Monitoring
  • Management Personnel
  • Military Operations
  • National Security
  • Renewable Energy

Readers

  • Electrical Engineering
  • Life Cycle Cost Analysis
  • Operations Research