Research Papers: Alternative Energy Sources

Optimizing the Reliability and Performance of Remote Vehicle-to-Grid Systems Using a Minimal Set of Metrics

[+] Author and Article Information
Annette G. Skowronska

Warren, MI 48397-5000;
Mechanical Engineering Department,
Oakland University,
Rochester, MI 48309

David J. Gorsich

Warren, MI 48397-5000

Vijitashwa Pandey

Industrial and Systems Engineering Department,
Oakland University,
Rochester, MI 48309

Zissimos P. Mourelatos

Mechanical Engineering Department,
Oakland University,
Rochester, MI 48309

1Corresponding author.

Contributed by the Internal Combustion Engine Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received January 3, 2015; final manuscript received March 28, 2015; published online April 27, 2015. Assoc. Editor: Stephen A. Ciatti.

This material is declared a work of the U.S. Government and is not subject to copyright protection in the United States. Approved for public release; distribution is unlimited.

J. Energy Resour. Technol 137(4), 041204 (Jul 01, 2015) (7 pages) Paper No: JERT-15-1001; doi: 10.1115/1.4030317 History: Received January 03, 2015; Revised March 28, 2015; Online April 27, 2015

Vehicles connected to electric systems are considered “plug-in” vehicles. They can be an integral part of a microgrid. Ground vehicles have become more electrified over time, providing electrical power for the propulsion system (hybrid) and a complex suite of auxiliary power systems, enhancing their use in microgrids. Optimizing the microgrid system for performance and reliability considering many external loads and sources is a challenging problem. This is especially true when the plug-in vehicles may enter and leave the microgrid randomly becoming either sources or loads. The microgrid is a repairable system. Recent work has shown that multiple metrics are needed to fully account for the performance of repairable systems under uncertainty. In this paper, we propose a decision-based framework to design and maintain repairable systems for optimal performance and reliability using a set of metrics such as minimum failure free period (MFFP), number of failures in planning horizon, and cost. Optimal tradeoffs among a minimal set of metrics (MSOM) can be used in the design and maintenance of these systems. The optimal solution includes the initial design, the system maintenance throughout the planning horizon, and the protocol to operate the system. Critical remote military installations with plug-in vehicles connected to the microgrids require careful consideration of cost and repair strategies because of logistical challenges in performing repairs and supplying necessary spare parts in unsafe locations. We show how a MSOM helps to solve the complex optimization problem of finding the best microgrid power management strategy considering performance, reliability, and cost.

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Grahic Jump Location
Fig. 1

Schematic of load and source profiles over time. Sources are turned off and on (dispatched) to closely match the load. The load is dispatched if the maximum supply cannot meet it.

Grahic Jump Location
Fig. 2

MTBF represents the expected time to failure correctly only for symmetric distributions (center pdf, solid line). Most systems fail before MTBF for right-skewed distributions and after MTBF for left-skewed distributions.

Grahic Jump Location
Fig. 3

Availability is high if the ratio of repair time to operation time is small. It depends on whether the system is in steady-state or initial (transient) state of operation.

Grahic Jump Location
Fig. 4

Schematic of the SCMG

Grahic Jump Location
Fig. 5

Power management protocol for microgrid

Grahic Jump Location
Fig. 6

Pareto front over MFFP, number of failures, and cost



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