Allocation of Plug-In Vehicles' Parking Lots in Distribution Systems Considering Network-Constrained Objectives

Neyestani, Nilufar; Damavandi, Maziar Yazdani; Shafie‐khah, Miadreza; Contreras, Javier; Catalào, João P. S.

doi:10.1109/tpwrs.2014.2359919

Cited by 167 publications

(96 citation statements)

References 20 publications

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“…Thus, these parking lots have to be planned in such a way to take a number of vehicles in every region into account [23]. Furthermore, new parking lots have to be set up where there are more cars [24]. Accordingly, the data of smart parking lots are able to provide profits for both customers and merchants' daily lives in the smart cities.…”

Section: Smart Parking Lotsmentioning

confidence: 99%

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A Review of Smart Cities Based on the Internet of Things Concept

et al. 2017

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Abstract:With the expansion of smart meters, like the Advanced Metering Infrastructure (AMI), and the Internet of Things (IoT), each smart city is equipped with various kinds of electronic devices. Therefore, equipment and technologies enable us to be smarter and make various aspects of smart cities more accessible and applicable. The goal of the current paper is to provide an inclusive review on the concept of the smart city besides their different applications, benefits, and advantages. In addition, most of the possible IoT technologies are introduced, and their capabilities to merge into and apply to the different parts of smart cities are discussed. The potential application of smart cities with respect to technology development in the future provides another valuable discussion in this paper. Meanwhile, some practical experiences all across the world and the key barriers to its implementation are thoroughly expressed.

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Section: Smart Parking Lotsmentioning

confidence: 99%

“…Smart grids concentrated on the environmentally-based schemes incorporating various renewable resources and DR for providing various choices for customers and improving the utilization of facilities [24,51,54]. The DSM problem can be implemented at various levels of the hierarchical smart grid infrastructure.…”

Section: Responsive Customersmentioning

confidence: 99%

A Review of Smart Cities Based on the Internet of Things Concept

et al. 2017

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“…Nodal PEV density model [39][40][41][42] Estimation of the stationary demand density at system nodes Traffic flow model [12,[43][44][45][46][47] Estimation of the spatial demand and mobility of PEVs Real data-based model [48,49] Estimation of the spatial-temporal PEV demand Stochastic model [50][51][52] Considering the uncertainty of PEVs 4.1.1. Nodal PEV Density-Based Model…”

Section: Demand Coverage Model Main Featurementioning

confidence: 99%

“…Variables such as the distance that a PEV travels, PEV arriving/departure time to/from the charging location, and the initial SOC of PEV battery are considered input variables of the probabilistic model [50,51]. For example, the distance travelled can be represented by a long-normal distribution function [50]. Arriving and departure time are modelled by a Gaussian distribution function.…”

Section: Stochastic Planning Modelmentioning

confidence: 99%

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A Survey on PEV Charging Infrastructure: Impact Assessment and Planning

Abdalrahman

Zhuang

2017

Energies

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Plug-in electric vehicles (PEVs) represent a huge step forward in a green transportation system, contribute in reduction of greenhouse gas emission, and reduce the dependence on fossil fuel. Integration of PEVs into the electric power system will result in a considerable addition to electricity demand. Due to PEV mobility, this demand has a random distribution in space and time among distribution system nodes. Therefore, short term forecast of PEV charging demand is more challenging than that for conventional loads. Assessment of PEV impacts on the power system is essential to mitigate the impairments from PEV loads. Optimal planning of PEV charging infrastructure will promote the penetration rate of PEVs and minimize the negative impacts of PEVs on the electric power distribution system and transportation road network. Design of charging facilities with integrated distributed energy resources (DER) is considered a solution to alleviate strain on the grid, reduce the integration cost with the distribution network and the charging cost. In this paper, we present a comprehensive literature survey on modelling of PEV charging demand, impact assessment approaches and tools, and charging infrastructure planning. Moreover, an overview on charging facility design with integrated DER is given. Some future research directions are identified.

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Optimal allocation of EV charging spots along with capacitors in smart distribution network for congestion management

Sachan

Amini

2020

Int Trans Electr Energ Syst

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Summary Rapid growth of electric vehicles (EVs) has necessitated the devolvement of sustainable and easily accessible charging stations. Transport sector electrification and increased popularity of EVs make researcher to search for charging stations. In this paper, a new methodology regarding electric vehicle charging spot is proposed. In the study, allocation of the parking lot and capacitor is suggested for congestion management along with reactive power compensation. To this end, sensitivity analysis is performed by evaluating the inverse Jacobian matrix from the power flow studies. In order to optimally determine the size of parking lot, biogeography‐based optimization (BBO) technique is adopted. The effectiveness of the anticipated technique is tested on adapted IEEE 34‐bus distribution network. The outcome attained by BBO technique is equated with particle swarm optimization.

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Allocation of Plug-In Vehicles' Parking Lots in Distribution Systems Considering Network-Constrained Objectives

Cited by 167 publications

References 20 publications

A Review of Smart Cities Based on the Internet of Things Concept

A Review of Smart Cities Based on the Internet of Things Concept

A Survey on PEV Charging Infrastructure: Impact Assessment and Planning

Optimal allocation of EV charging spots along with capacitors in smart distribution network for congestion management

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