Next Article in Journal
Optimal Scheduling of an Regional Integrated Energy System with Energy Storage Systems for Service Regulation
Previous Article in Journal
Impact of Electric Vehicle Charging Station Load on Distribution Network
Previous Article in Special Issue
Improving Transient Response of Power Converter in a Stand-Alone Microgrid Using Virtual Synchronous Generator
Article Menu
Issue 1 (January) cover image

Export Article

Open AccessArticle
Energies 2018, 11(1), 196; doi:10.3390/en11010196

Optimal Operation of Interdependent Power Systems and Electrified Transportation Networks

Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou 510006, China
Department of Industrial Engineering, Yasar University, Izmir, 35100, Turkey
Author to whom correspondence should be addressed.
Received: 2 January 2018 / Revised: 11 January 2018 / Accepted: 13 January 2018 / Published: 14 January 2018
(This article belongs to the Special Issue Distribution System Operation and Control)
View Full-Text   |   Download PDF [8172 KB, uploaded 17 January 2018]   |  


Electrified transportation and power systems are mutually coupled networks. In this paper, a novel framework is developed for interdependent power and transportation networks. Our approach constitutes solving an iterative least cost vehicle routing process, which utilizes the communication of electrified vehicles (EVs) with competing charging stations, to exchange data such as electricity price, energy demand, and time of arrival. The EV routing problem is solved to minimize the total cost of travel using the Dijkstra algorithm with the input from EVs battery management system, electricity price from charging stations, powertrain component efficiencies and transportation network traffic conditions. Through the bidirectional communication of EVs with competing charging stations, EVs’ charging demand estimation is done much more accurately. Then the optimal power flow problem is solved for the power system, to find the locational marginal price at load buses where charging stations are connected. Finally, the electricity prices were communicated from the charging stations to the EVs, and the loop is closed. Locational electricity price acts as the shared parameter between the two optimization problems, i.e., optimal power flow and optimal routing problem. Electricity price depends on the power demand, which is affected by the charging of EVs. On the other hand, location of EV charging stations and their different pricing strategies might affect the routing decisions of the EVs. Our novel approach that combines the electrified transportation with power system operation, holds tremendous potential for solving electrified transportation issues and reducing energy costs. The effectiveness of the proposed approach is demonstrated using Shanghai transportation network and IEEE 9-bus test system. The results verify the cost-savings for both power system and transportation networks. View Full-Text
Keywords: electrified transportation network; power systems operation; locational marginal price; electrified vehicle; charging station; least cost route optimization electrified transportation network; power systems operation; locational marginal price; electrified vehicle; charging station; least cost route optimization

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Amini, M.H.; Karabasoglu, O. Optimal Operation of Interdependent Power Systems and Electrified Transportation Networks. Energies 2018, 11, 196.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Energies EISSN 1996-1073 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top