Smart Charging Strategies for Optimal Integration of Plug-In Electric Vehicles Within Existing Distribution System Infrastructure

Mehta, Rahul; Srinivasan, Dipti; Khambadkone, A.M.; Yang, Jing; Trivedi, Anupam

doi:10.1109/tsg.2016.2550559

Cited by 208 publications

(115 citation statements)

References 31 publications

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“…The OS's algorithm is based on a special bidding strategy which includes the EV battery degradation cost to its economic analysis. The EV battery degradation cost is considered also by the algorithm of an OS in [118]. The OS optimally control the EV charging and the V2G system to minimize the total costs of the local EVs operation, and to flatten the PS load profile.…”

Section: Ps Oss Regulating the Charging/discharging Of Electric Vehiclesmentioning

confidence: 99%

Review of Trends and Targets of Complex Systems for Power System Optimization

Vysocky

Mišák

2020

Energies

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Optimization systems (OSs) allow operators of electrical power systems (PS) to optimally operate PSs and to also create optimal PS development plans. The inclusion of OSs in the PS is a big trend nowadays, and the demand for PS optimization tools and PS-OSs experts is growing. The aim of this review is to define the current dynamics and trends in PS optimization research and to present several papers that clearly and comprehensively describe PS OSs with characteristics corresponding to the identified current main trends in this research area. The current dynamics and trends of the research area were defined on the basis of the results of an analysis of the database of 255 PS-OS-presenting papers published from December 2015 to July 2019. Eleven main characteristics of the current PS OSs were identified. The results of the statistical analyses give four characteristics of PS OSs which are currently the most frequently presented in research papers: OSs for minimizing the price of electricity/OSs reducing PS operation costs, OSs for optimizing the operation of renewable energy sources, OSs for regulating the power consumption during the optimization process, and OSs for regulating the energy storage systems operation during the optimization process. Finally, individual identified characteristics of the current PS OSs are briefly described. In the analysis, all PS OSs presented in the observed time period were analyzed regardless of the part of the PS for which the operation was optimized by the PS OS, the voltage level of the optimized PS part, or the optimization goal of the PS OS.

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Section: Ps Oss Regulating the Charging/discharging Of Electric Vehiclesmentioning

confidence: 99%

Review of Trends and Targets of Complex Systems for Power System Optimization

Vysocky

Mišák

2020

Energies

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“…In order to analyze the sensitivity of each constraint in the objective function (1), the comparison is made in (3)- (6). Specifically, C sta in (3) can be rearranged into c 1,i i∈Φ x i + c 2,i i∈Φ y i ; while C dis in (4) can be decomposed into the following format using (7)-(9) when ∆P sub i ≥ P sur :…”

Section: Sensitivity Analysis Of the Problemmentioning

confidence: 99%

“…considered on a game theoretical framework in [8], [15]. Solutions to these optimization problems include greedy algorithm [3], [12], genetic algorithm [6], interior point method [9], gradient methods [8], etc. However, these solutions do not consider the convexification of the constraints.…”

mentioning

confidence: 99%

Electric Vehicle Charging Station Placement Method for Urban Areas

Cui

Weng

Tan

2019

IEEE Trans. Smart Grid

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For accommodating more electric vehicles (EVs) to battle against fossil fuel emission, the problem of charging station placement is inevitable and could be costly if done improperly. Some researches consider a general setup, using conditions such as driving ranges for planning. However, most of the EV growths in the next decades will happen in the urban area, where driving ranges is not the biggest concern. For such a need, we consider several practical aspects of urban systems, such as voltage regulation cost and protection device upgrade resulting from the large integration of EVs. Notably, our diversified objective can reveal the trade-off between different factors in different cities worldwide. To understand the global optimum of large-scale analysis, we add constraint one-by-one to see how to preserve the problem convexity. Our sensitivity analysis before and after convexification shows that our approach is not only universally applicable but also has a small approximation error for prioritizing the most urgent constraint in a specific setup. Finally, numerical results demonstrate the trade-off, the relationship between different factors and the global objective, and the small approximation error. A unique observation in this study shows the importance of incorporating the protection device upgrade in urban system planning on charging stations. Index TermsElectric vehicle charging station, distribution grid, convexification, protective devices upgrade. I. INTRODUCTIONU NDER the Paris agreement signed in 2016, the model of a sustainable urban city -Singapore, pledged to cut emissions intensity by 36% below 2005 levels by 2030. To meet the commitment, emissions reduction worldwide in the transport sector is crucial, and large-scale electric vehicle (EV) adoption in the future is, therefore, utmost essential to Singapore and many other cities/countries. For example, Singapore took several important steps in this direction such as 1) an announcement of a new Vehicular Emissions Scheme and 2) the launch of the electric vehicle car-sharing program, etc. However, one of the major barriers to successful adoption of EVs at a large scale is the limited number of available charging stations. Thus, it is important to properly deploy EV charging infrastructure to enhance the adoption of EVs efficiently.EV charging station placement has therefore been an active research area for intercity and urban infrastructure planning. In freeway charging infrastructure planning, [1] tackles the EV charging station placement problem in a simple round freeway, whereas [2] proposes a capacitated-flow refueling location model to capture PEV charging demands in a more complicated meshed transport network. However, both papers share the similarity of considering the driving range in the freeway. In contrast, the driving range constraints are not prominent in the urban area charging infrastructure planning since the charging stations are easily accessible, therefore, researchers have considered various aspects dedicated for urban area charg...

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“…The group also further focused on deploying energy router, 9 energy transfer route, [10][11][12][13] energy scheduling, and allocation in the EV energy distribution network. 14,15 With the plug-in technology, some new charging strategies can be drawn 16 to help integrating V2G with grid-to-vehicle (G2V) as a whole system, which brought far-reaching significance to follow-up research works. Figure 2 shows an example of the power distribution system based on EVs designed in this article.…”

Section: Related Workmentioning

confidence: 99%

A power storage station placement algorithm for power distribution based on electric vehicle

Wang

et al. 2017

International Journal of Distributed Sensor Networks

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Inspired by the concept of energy internet and energy problems including greenhouse gas emission and regional shortage, this article will propose an idea of electric power distribution using city bus lines running electric vehicles. The designed power distribution system includes renewable energy sources as the energy input, power storage stations placed at some bus stops as the fixed energy output, and bus lines running electric vehicles as the connections between them. As the basic and priority problem, choosing the suitable location to place power storage stations can not only reduce the total number of construction but also increase the utilization rate of each one. Main work involves the two branch algorithms for solving the placement problem; simulation while using real-world transportation data of two city bus maps and analysis about the advantages and disadvantages of algorithms.

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Smart Charging Strategies for Optimal Integration of Plug-In Electric Vehicles Within Existing Distribution System Infrastructure

Cited by 208 publications

References 31 publications

Review of Trends and Targets of Complex Systems for Power System Optimization

Review of Trends and Targets of Complex Systems for Power System Optimization

Electric Vehicle Charging Station Placement Method for Urban Areas

A power storage station placement algorithm for power distribution based on electric vehicle

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