Document Type

Closed Project

Publication Date

Fall 2018

Instructor

Tugrul Daim

Course Title

Technology Assessment and Acquisition

Course Number

ETM 531/631

Subjects

Hierarchical Decision Model, Technology assessment, Smart power grids, Electric vehicles, Electric utilities -- Management

Abstract

The power grid is an incredibly complex and important system, and one of the most impressive engineering works of modern times. Previous research has confirmed that there is significant transformation in the axis of the technology of electric transport to be ready to move from traditional and complex use to smart use to be more beneficial at the social, economic, political and environmental perspectives. These perspectives in the use of intelligent transportation contributes significantly to the provision of energy, cost, and time.

In this research, there were many assessments for the transportation technology which evaluated a range of market-emerging electric vehicle (EV) and electric vehicle service equipment (EVSE) options in order to craft a recommendation for future grid-integration programs capable of providing realistic and affordable assistance to electric utilities during summer peak periods (typically occurring ~20 days/year). This research discussed the most opportune behind-the-meter transportation technologies and products to use for future summer peak Vehicle-to-Grid (V2G) programs in California, Oregon, and/or Washington.

This paper applied a multi-criteria decision model as a methodology known as the Hierarchical Decision Model (HDM), for assessment of current transportation technology to determine the technology options based on experts’ judgments by selecting multiple criteria. By using the pairwise comparison from the software that was made by the five professional experts, the assessment results showed that the likelihood of owner participation is one of the most influential factors to influence the decision-making potential.

Description

This project is only available to students, staff, and faculty of Portland State University.

Persistent Identifier

https://archives.pdx.edu/ds/psu/27283

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