Energies

Research

16 pages, 4561 KiB

Open AccessArticle

Emissions from the Road Traffic of West African Cities: Assessment of Vehicle Fleet and Fuel Consumption

by Madina Doumbia, N’Datchoh E. Toure, Siélé Silue, Véronique Yoboue, Arona. Diedhiou and Célestin Hauhouot

Energies 2018, 11(9), 2300; https://doi.org/10.3390/en11092300 - 01 Sep 2018

Cited by 17 | Viewed by 4483

Abstract

Traffic source emission inventories for the rapidly growing West African urban cities are necessary for better characterization of local vehicle emissions released into the atmosphere of these cities. This study is based on local field measurements in Yopougon (Abidjan, Côte d’Ivoire) in 2016; [...] Read more.

Traffic source emission inventories for the rapidly growing West African urban cities are necessary for better characterization of local vehicle emissions released into the atmosphere of these cities. This study is based on local field measurements in Yopougon (Abidjan, Côte d’Ivoire) in 2016; a site representative of anthropogenic activities in West African cities. The measurements provided data on vehicle type and age, traveling time, fuel type, and estimated amount of fuel consumption. The data revealed high traffic flow of personal cars on highways, boulevards, and backstreets, whereas high flows of intra-communal sedan taxis were observed on main and secondary roads. In addition, the highest daily fuel consumption value of 56 L·day⁻¹ was recorded for heavy vehicles, while the lowest value of 15 L·day⁻¹ was recorded for personal cars using gasoline. This study is important for the improvement of uncertainties related to the different databases used to estimate emissions either in national or international reports. This work provides useful information for future studies on urban air quality, climate, and health impact assessments in African cities. It may also be useful for policy makers to support implementation of emission reduction policies in West African cities. Full article

(This article belongs to the Special Issue Energy Management in Vehicle–Grid–Traffic Nexus)

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13 pages, 3658 KiB

Open AccessArticle

Study on EV Charging Peak Reduction with V2G Utilizing Idle Charging Stations: The Jeju Island Case

by Hye-Seung Han, Eunsung Oh and Sung-Yong Son

Energies 2018, 11(7), 1651; https://doi.org/10.3390/en11071651 - 25 Jun 2018

Cited by 12 | Viewed by 4277

Abstract

Electric vehicles (EVs), one of the biggest innovations in the automobile industry, are considered as a demand source as well as a supply source for power grids. Studies have been conducted on the effect of EV charging and utilization of EVs to control [...] Read more.

Electric vehicles (EVs), one of the biggest innovations in the automobile industry, are considered as a demand source as well as a supply source for power grids. Studies have been conducted on the effect of EV charging and utilization of EVs to control grid peak or to solve the intermittency problem of renewable generators. However, most of these studies focus on only one aspect of EVs. In this work, we demonstrate that the increased demand resulting from EV charging can be alleviated by utilizing idle EV charging stations as a vehicle-to-grid (V2G) service. The work is performed based on data from Jeju Island, Korea. The EV demand pattern in 2030 is modeled and forecasted using EV charging patterns from historical data and the EV and charging station deployment plan of Jeju Island’s local government. Then, using a Monte Carlo simulation, charging and V2G scenarios are generated, and the effect of V2G on peak time is analyzed. In addition, a sensitivity analysis is performed for EV and charging station deployment. The results show that the EV charging demand increase can be resolved within the EV ecosystem. Full article

(This article belongs to the Special Issue Energy Management in Vehicle–Grid–Traffic Nexus)

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16 pages, 2850 KiB

Open AccessArticle

A Study on Coordinated Optimization of Electric Vehicle Charging and Charging Pile Selection

by Lixing Chen, Xueliang Huang, Hong Zhang and Yinsheng Luo

Energies 2018, 11(6), 1350; https://doi.org/10.3390/en11061350 - 25 May 2018

Cited by 14 | Viewed by 4275

Abstract

This paper was intended to explore the mutual influences between electric vehicle (EV) charging and charging facility planning, to establish a two-stage model for optimizing the EVs’ charging and charging piles’ selection. In the first stage, the distribution pattern of the demands for [...] Read more.

This paper was intended to explore the mutual influences between electric vehicle (EV) charging and charging facility planning, to establish a two-stage model for optimizing the EVs’ charging and charging piles’ selection. In the first stage, the distribution pattern of the demands for EV charging, and various EVs were effectively grouped, in order to reduce the amount of computation for solving the second stage model. The goal of the second stage was to minimize the annual investment and electricity purchasing costs on the charging piles, and the coordinated optimization was carried out for EV charging and charging pile selection. The CPLEX and IP_SOLVE packages were used in MATLAB (R2014a/64 bits) to solve the established optimization model. The simulation results showed that, compared with the scheme for selecting the charging pile under the typical charging pattern (TCP), the total cost of the charging pile could be reduced by 6.32% with a scheme under the optimized charging pattern (OCP), thereby promoting the coordinated development of both the EVs and charging facilities. Full article

(This article belongs to the Special Issue Energy Management in Vehicle–Grid–Traffic Nexus)

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20 pages, 10380 KiB

Open AccessArticle

A High-Efficiency Charging Service System for Plug-in Electric Vehicles Considering the Capacity Constraint of the Distribution Network

by Rui Ye, Xueliang Huang, Ziqi Zhang, Zhong Chen and Ran Duan

Energies 2018, 11(4), 911; https://doi.org/10.3390/en11040911 - 12 Apr 2018

Cited by 2 | Viewed by 4216

Abstract

It takes electric vehicles (EVs) a long time to charge, which is bound to influence the charging experience of vehicle owners. At the same time, large-scale charging behavior also brings about large load pressure on, and elevates the overload risk of, the power [...] Read more.

It takes electric vehicles (EVs) a long time to charge, which is bound to influence the charging experience of vehicle owners. At the same time, large-scale charging behavior also brings about large load pressure on, and elevates the overload risk of, the power distribution network. To solve these problems, we proposed a high-efficiency charging service system based on charging reservation and charging pile binding services. The system can shorten the average charging time of EVs and improve the average immediate utilization rate of new energy sources at charging stations (CSs). In addition, the system also guarantees that the EVs are charged within the allowable range of the capacity of the distribution network and avoids overloading of the distribution network caused by the charging of EVs. The key support for the utility of the system is rooted in the three-level CS selection model and the CS energy control algorithm (CSECA) proposed in the research. Finally, the proposed model and algorithm were verified to be valid through numerous simulation experiments. Full article

(This article belongs to the Special Issue Energy Management in Vehicle–Grid–Traffic Nexus)

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17 pages, 2140 KiB

Open AccessArticle

Reduction of Electricity Prices Using the Train to Grid (T2G) System in Urban Railway

by Hyo-Sang Go, In-Ho Cho, Gil-Dong Kim and Chul-Hwan Kim

Energies 2018, 11(3), 501; https://doi.org/10.3390/en11030501 - 27 Feb 2018

Cited by 5 | Viewed by 4296

Abstract

Smart transportation technologies are being rapidly developed for enhancing the smart grid establishment. Such technologies are mostly focused on electric vehicles. However, the electric railroad has advantages in various aspects such as facility construction and utilization over an electric vehicle. Therefore, in this [...] Read more.

Smart transportation technologies are being rapidly developed for enhancing the smart grid establishment. Such technologies are mostly focused on electric vehicles. However, the electric railroad has advantages in various aspects such as facility construction and utilization over an electric vehicle. Therefore, in this paper, we introduce the train-to-grid system using the electric railroads for the smart grid, and propose a reduction method for the electricity prices. The proposed method obtains actual data from the currently operating railroad systems. Furthermore, the number of trains for charging and discharging batteries is decided by using the time-of-use price and the number of railroad operations. The electricity prices are then determined by the energy consumption calculated using the number of trains used for charging and discharging and the capacity of the energy storage system in the trains. The proposed method is simulated using real data, and its superiority is verified by comparing its electric prices with the conventional electricity prices. Full article

(This article belongs to the Special Issue Energy Management in Vehicle–Grid–Traffic Nexus)

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19 pages, 5271 KiB

Open AccessArticle

Research on an Electric Vehicle Owner-Friendly Charging Strategy Using Photovoltaic Generation at Office Sites in Major Chinese Cities

by Su Su, Yong Hu, Tiantian Yang, Shidan Wang, Ziqi Liu, Xiangxiang Wei, Mingchao Xia, Yutaka Ota and Koji Yamashita

Energies 2018, 11(2), 421; https://doi.org/10.3390/en11020421 - 12 Feb 2018

Cited by 7 | Viewed by 3787

Abstract

Electric vehicles (EV) and photovoltaic (PV) generation are widely recognized around the world. Most EV owners in the major Chinese cities are forced to charge their EV batteries at the workplace during the daytime due to the limited space near their homes, which [...] Read more.

Electric vehicles (EV) and photovoltaic (PV) generation are widely recognized around the world. Most EV owners in the major Chinese cities are forced to charge their EV batteries at the workplace during the daytime due to the limited space near their homes, which will increase the peak load during the daytime. On the other hand, the PV output is most likely to have a peak at around noon, which means, PVs could have a potential capability to compensate the EV charging load. An EV owner-friendly charging strategy based on PV utilization which alleviates both the EV charging constraints and the negative impact of the EV charging load on the grid is proposed. The PV utilization for compensating the unconstrained EV charging load is maximized to derive the maximum number of EVs with unconstrained charging. If the actual number of EVs exceeds the maximum number, a portion of EVs have to be charged only from the grid. Then, the line loss is introduced as the optimization objective in which the charging states are regulated. The case study shows that the proposed strategy can successfully increase the number of EVs with unconstrained charging, and reduce the peak-to-peak of the load curve. Full article

(This article belongs to the Special Issue Energy Management in Vehicle–Grid–Traffic Nexus)

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16039 KiB

Open AccessArticle

An Economical Route Planning Method for Plug-In Hybrid Electric Vehicle in Real World

by Yuanjian Zhang, Liang Chu, Zicheng Fu, Nan Xu, Chong Guo, Yukuan Li, Zhouhuan Chen, Hanwen Sun, Qin Bai and Yang Ou

Energies 2017, 10(11), 1775; https://doi.org/10.3390/en10111775 - 03 Nov 2017

Cited by 5 | Viewed by 5292

Abstract

Relieving the adverse effects of automobiles on the environment and natural resources has drawn the attention of numerous researchers. This paper seeks a new path to reach a target by focusing on the synergy of the vehicle and the environment. A real-time economical [...] Read more.

Relieving the adverse effects of automobiles on the environment and natural resources has drawn the attention of numerous researchers. This paper seeks a new path to reach a target by focusing on the synergy of the vehicle and the environment. A real-time economical route planning method for a plug-in hybrid electric vehicle (PHEV) is proposed. Three main contributions have been made. Firstly, a real comparison test is performed to provide rudimentary understanding of the difference in energy usage and route planning between PHEVs and conventional vehicles. Secondly, an approach to obtain PHEV customized data is developed for road weight calculation, which is the essential step in route planning. This method incorporates traffic data from conventional vehicles with the PHEV simulation model, obtaining the required data. Thirdly, the travel expense estimation model (TEEM) is designed. The TEEM could be applied to calculate the road weight of each road segment considering the impact on energy consumption with respect to environmental factors, providing the grounds for route planning. The proposed method to plan an economical route is evaluated, and the results justify its validation and ability to improve fuel economy. Full article

(This article belongs to the Special Issue Energy Management in Vehicle–Grid–Traffic Nexus)

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3962 KiB

Open AccessArticle

Transactive Demand Side Management Programs in Smart Grids with High Penetration of EVs

by Poria Astero, Bong Jun Choi, Hao Liang and Lennart Söder

Energies 2017, 10(10), 1640; https://doi.org/10.3390/en10101640 - 18 Oct 2017

Cited by 15 | Viewed by 4101

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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6224 KiB

Open AccessArticle

A Pontryagin Minimum Principle-Based Adaptive Equivalent Consumption Minimum Strategy for a Plug-in Hybrid Electric Bus on a Fixed Route

by Shaobo Xie, Huiling Li, Zongke Xin, Tong Liu and Lang Wei

Energies 2017, 10(9), 1379; https://doi.org/10.3390/en10091379 - 11 Sep 2017

Cited by 66 | Viewed by 6801

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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