Developing Infrastructure for Interconnecting Transportation Network and Electric Grid

Kim, Seok; Damnjanovic, Ivan; Texas Transportation Institute

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Developing Infrastructure for Interconnecting Transportation Network and Electric Grid

2011-09-01
By Kim, Seok ; Damnjanovic, Ivan

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English

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Details:

Creators:

Kim, Seok ; Damnjanovic, Ivan

Kim, Seok ; Damnjanovic, Ivan Less -
Corporate Creators:

Texas Transportation Institute
Corporate Contributors:

Texas A&M University
Subject/TRT Terms:

[+]

Decision Making Decision Making--Mathematical Models Decision Support Systems Electric Power Network Electric Vehicle Charging Electric Vehicles Mathematical Models Network Analysis (Planning)--Texas Parking Facilities Parking Facilities--Planning--Mathematical Models PEV, Research Hub Transportation Network
Publication/ Report Number:

SWUTC/11/161006-1
Resource Type:

Tech Report
Geographical Coverage:

Texas ; United States

Texas ; United States Less -
TRIS Online Accession Number:

01367381
OCLC Number:

781169384
Edition:

Research report.
Corporate Publisher:

Southwest Region University Transportation Center (U.S.)
NTL Classification:

NTL-ENERGY AND ENVIRONMENT-Alternative Fuels;NTL-ENERGY AND ENVIRONMENT-ENERGY AND ENVIRONMENT;NTL-ENERGY AND ENVIRONMENT-Environment Impacts;NTL-PLANNING AND POLICY-PLANNING AND POLICY;
Abstract:

This report is primarily focused on the development of mathematical models that can be used to support decisions regarding a charging station location and installation problem. The major parts of developing the models included identification of the problem, development of mathematical models in the form of bilevel and stochastic programming problems, and development of a solution approach using a meta-heuristic method. PEV parking building problem was formulated as a bilevel programming problem in order to consider interaction between transportation flow and a manager decisions, while the charging station installation problem was formulated as a stochastic programming problem in order to consider uncertainty in parameters. In order to find the best-quality solution, a genetic algorithm method was used because the formulation problems are NP-hard. In addition, the Monte Carlo bounding method was used to solve the stochastic program with continuous distributions. The results of this study provide managerial implications for developers and operators of parking building.
Format:

PDF
Funding:

10727
Collection(s):

University Transportation Centers US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:0ed30b73b86353f1a48d3a10bcc1b01109bd5f5dd262d89791c7608fd0d81a31
Download URL:

https://rosap.ntl.bts.gov/view/dot/23870/dot_23870_DS1.pdf
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Developing Infrastructure for Interconnecting Transportation Network and Electric Grid

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