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Special Issue "Energy Management in Vehicle–Grid–Traffic Nexus"

A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: 1 May 2018

Special Issue Editors

Guest Editor
Prof. Dr. Xiaosong Hu

Department of Automotive Engineering, Chongqing University, China
Website | E-Mail
Interests: management and control of energy storage systems; optimal control ofalternative-energy vehicles forsustainable transportation; energy internet; vehicle–traffic–grid–home nexus; automated vehicles
Guest Editor
Prof. Dr. Weihao Hu

Department of Electrical Engineering, Alborg University, Denmark
Website | E-Mail
Interests: wind power generation; intelligent energy systems; sustainable energy; renewable power generation
Guest Editor
Dr. Chen Lv

Advanced Vehicle Engineering Centre, Cranfield University, UK
Website | E-Mail
Interests: energy conversion and management of electrified vehicles; energy-efficiency cyber-physical systems; advanced control of alternative-energy vehicles for sustainable transportation; automated vehicles

Special Issue Information

Dear Colleagues,

This Special Issue focuses on energy management in the context of vehicle–grid–traffic interactions for a sustainable energy future. Its overarching goal is to present such a synergy through an integrated vision that may come both from specialized and from interdisciplinary articles. High-caliber research and survey papers are sincerely solicited to cover a broad range of topics, including advanced energy management in electrified vehicles, smart grid, and automated/connected driving, energy analysis of vehicle–grid interplay, information-enriched energy controls in smart city. Of course, design and control issues in the vehicle–traffic–grid–home nexus and energy internet will be definitely considered, from an energy management perspective. Papers submitted to this Special Issue will be subject to a peer review procedure with the aim of rapid and wide dissemination of their contents.

Prof. Dr. Xiaosong Hu
Prof. Dr. Weihao Hu
Dr. Chen Lv
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

• energy management
• electrified vehicles
• smart grid
• intelligent transportation system
• vehicle–traffic–grid nexus

Published Papers (2 papers)

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Research

Open AccessArticle Transactive Demand Side Management Programs in Smart Grids with High Penetration of EVs
Energies 2017, 10(10), 1640; doi:10.3390/en10101640
Received: 18 September 2017 / Revised: 6 October 2017 / Accepted: 13 October 2017 / Published: 18 October 2017
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Abstract
Due to environmental concerns, economic issues, and emerging new loads, such as electrical vehicles (EVs), the importance of demand side management (DSM) programs has increased in recent years. DSM programs using a dynamic real-time pricing (RTP) method can help to adaptively control the
[...] Read more.
Due to environmental concerns, economic issues, and emerging new loads, such as electrical vehicles (EVs), the importance of demand side management (DSM) programs has increased in recent years. DSM programs using a dynamic real-time pricing (RTP) method can help to adaptively control the electricity consumption. However, the existing RTP methods, particularly when they consider the EVs and the power system constraints, have many limitations, such as computational complexity and the need for centralized control. Therefore, a new transactive DSM program is proposed in this paper using an imperfect competition model with high EV penetration levels. In particular, a heuristic two-stage iterative method, considering the influence of decisions made independently by customers to minimize their own costs, is developed to find the market equilibrium quickly in a distributed manner. Simulations in the IEEE 37-bus system with 1141 customers and 670 EVs are performed to demonstrate the effectiveness of the proposed method. The results show that the proposed method can better manage the EVs and elastic appliances than the existing methods in terms of power constraints and cost. Also, the proposed method can solve the optimization problem quick enough to run in real-time. Full article
(This article belongs to the Special Issue Energy Management in Vehicle–Grid–Traffic Nexus)
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Open AccessArticle A Pontryagin Minimum Principle-Based Adaptive Equivalent Consumption Minimum Strategy for a Plug-in Hybrid Electric Bus on a Fixed Route
Energies 2017, 10(9), 1379; doi:10.3390/en10091379
Received: 1 August 2017 / Revised: 8 September 2017 / Accepted: 8 September 2017 / Published: 11 September 2017
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Abstract
When developing a real-time energy management strategy for a plug-in hybrid electric vehicle, it is still a challenge for the Equivalent Consumption Minimum Strategy to achieve near-optimal energy consumption, because the optimal equivalence factor is not readily available without the trip information. With
[...] Read more.
When developing a real-time energy management strategy for a plug-in hybrid electric vehicle, it is still a challenge for the Equivalent Consumption Minimum Strategy to achieve near-optimal energy consumption, because the optimal equivalence factor is not readily available without the trip information. With the help of realistic speeding profiles sampled from a plug-in hybrid electric bus running on a fixed commuting line, this paper proposes a convenient and effective approach of determining the equivalence factor for an adaptive Equivalent Consumption Minimum Strategy. Firstly, with the adaptive law based on the feedback of battery SOC, the equivalence factor is described as a combination of the major component and tuning component. In particular, the major part defined as a constant is applied to the inherent consistency of regular speeding profiles, while the second part including a proportional and integral term can slightly tune the equivalence factor to satisfy the disparity of daily running cycles. Moreover, Pontryagin’s Minimum Principle is employed and solved by using the shooting method to capture the co-state dynamics, in which the Secant method is introduced to adjust the initial co-state value. And then the initial co-state value in last shooting is taken as the optimal stable constant of equivalence factor. Finally, altogether ten successive driving profiles are selected with different initial SOC levels to evaluate the proposed method, and the results demonstrate the excellent fuel economy compared with the dynamic programming and PMP method. Full article
(This article belongs to the Special Issue Energy Management in Vehicle–Grid–Traffic Nexus)
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