Optimal Policies for the Management of a Plug-In Hybrid Electric Vehicle Swap Station

Abstract

Optimizing operations at plug-in hybrid electric vehicle (PHEV) battery swap stations is internally motivated by the movement to make transportation cleaner and more efficient. A PHEV swap station allows PHEV owners to quickly exchange their depleted PHEV battery for a fully charged battery. The PHEV-Swap Station Management Problem (PHEV-SSMP) is introduced, which models battery charging and discharging operations at a PHEV swap station facing nonstationary, stochastic demand for battery swaps, nonstationary prices for charging depleted batteries, and nonstationary prices for discharging fully charged batteries. Discharging through vehicle-to-grid is beneficial for aiding power load balancing. The objective of the PHEV-SSMP is to determine the optimal policy for charging and discharging batteries that maximizes expected total profit over a fixed time horizon. The PHEV-SSMP is formulated as a finite-horizon, discrete-time Markov decision problem and an optimal policy is found using dynamic programming. Structural properties are derived, to include sufficiency conditions that ensure the existence of a monotone optimal policy. A computational experiment is developed using realistic demand and electricity pricing data. The optimal policy is compared to two benchmark policies which are easily implementable by PHEV swap station managers. Two designed experiments are conducted to obtain policy insights regarding the management of PHEV swap stations. These insights include the minimum battery level in relationship to PHEVs in a local area, the incentive necessary to discharge, and the viability of PHEV swap stations under many conditions.

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Document Details

Document Type
Technical Report
Publication Date
Mar 26, 2015
Accession Number
ADA623662

Entities

People

  • Rebecca S. Widrick

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Department Of Defense
  • Discrete Distribution
  • Dynamic Programming
  • Electric Vehicles
  • Energy
  • Energy Storage
  • Governments
  • Hybrid Electric Vehicles
  • Load Monitoring
  • Random Variables
  • Solar Energy
  • Supply Chain
  • Supply Chain Management
  • United States
  • United States Government

Readers

  • Battery Technology and Engineering
  • Marine Propulsion Engineering and Naval Architecture
  • Operations Research