Optimal planning of electric vehicle charging station at the distribution system using hybrid optimization algorithm

Awasthi, Abhishek; Karthikeyan, V.; Padmanaban, Sanjeevikumar; Selvamuthukumaran, Rajasekar; Blaabjerg, Frede; Singh, Asheesh Kumar

doi:10.1016/j.energy.2017.05.094

Cited by 265 publications

(95 citation statements)

References 15 publications

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“…Criteria were selected by extended sustainability theory and by using fuzzy Delphi method. In another article, researchers [8], aimed to solve the optimal siting of electric charging stations problem in Allahabad, India. For solving the mentioned problem, authors implemented a hybrid algorithm based on genetic and particle swarm optimization algorithms.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Due to increase in the usage level of electric vehicles, demand on the electric charging stations increases [7]. The primary challenge of EV charging technology industry is to determine the optimal capacitated and located electric charging stations [8]. There are four presumptions made for EVs charging necessities in Lee and Han's research (2017) [9]: driver selects the shortest route, at the beginning of the route, half of the battery is full, at the end of the route, the battery must not be less than half of the battery and finally the travel range is constant and deterministic.…”

Section: Introductionmentioning

confidence: 99%

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A model for determining the locations of electric charge stations in Istanbul

Daşcıoğlu¹,

Tuzkaya²,

Kılıç³

2019

Pamukkale J Eng Sci

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ÖzThe studies about Electric Vehicles (EV) have gained importance and increased in the last years depending on the environmental concerns of the classic transportation systems. One of the problems to consider at this point is locating the proper points of electric charging stations for EVs. The primary objective of this research is to locate the electric charging stations in Istanbul considering the flow of the paths. The locations of electric charging stations are determined by using a mathematical model based on the flow-refuelling location model with the aim of maximizing the captured flow. The mathematical model is run for various values of "p" and the optimum locations are obtained.Klasik ulaştırma sistemlerinin çevresel kaygıları göz önünde bulundurulduğunda, elektrikli araçlarla (EA) ilgili çalışmalar önem kazanmış ve son yıllarda sayıca artmıştır. Bu noktada ele alınması gereken sorunlardan biri EA'lar için şarj istasyonlarının uygun yerlerinin belirlenmesidir. Bu çalışmanın temel amacı, İstanbul'daki elektrik şarj istasyonlarına ilişkin en uygun konumları yolların akışını değerlendirmeye alarak bulmaktır. Şarj istasyonlarının konumları, yolların kapsanan akışını maksimize etmeyi amaçlayan akış-yakıt ikmal lokasyon modeline dayanan bir model kullanılarak belirlenmiştir. Matematiksel model farklı "p" değerli için çözülmüş ve en iyi lokasyonlar belirlenmiştir.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A model for determining the locations of electric charge stations in Istanbul

Daşcıoğlu¹,

Tuzkaya²,

Kılıç³

2019

Pamukkale J Eng Sci

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“…The main problems for construction of charging infrastructures include the capacity of the supply source, length of power supply feeders, and so on [30].…”

Section: Constraints From Power Networkmentioning

confidence: 99%

Planning of Electric Vehicle Charging Infrastructure for Urban Areas with Tight Land Supply

Guo

Yang

2018

Energies

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Motivated by the development of electric vehicles (EVs), this paper addresses the planning of EV charging infrastructures (EVCIs). Considering that the optimal locations for EVCIs in most cities with a tight land supply are difficult to obtain, it is significant to study the planning of EVCIs in such cities. This paper proposes a planning method and model of EVCIs under the condition that alternative locations of centralized charging infrastructures (CCIs) are known. Firstly, based on the principle of energy equivalence, the sales volume of the fuel of gas stations in the planned area is converted into the equivalent electric quantity (EEQ) and the EEQ is divided according to the demands of different EVs for charging. Then, an equal product of the load and distance (EPLD) criterion is used to distribute the EEQ to CCIs and distributed charging infrastructures (DCIs) located in areas for load forecasting. The final plan is given out after checking the constraints and planning rationality. In addition, the net present value (NPV), the average charging distance, and the total harmonic distortion (THD) rate are used to evaluate the planning scheme. Finally, the feasibility and practicability of the proposed method are verified by a case study in Beijing.

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“…The storage is able to level demand and minimize the peak demand from the grid. In addition, in some cases, the electricity bill can also be reduced with the storage [64][65][66][67]. Jochen Linssen et al developed Battery-Photovoltaic-Simulation (BaPSi) model to run techno-economic study of PV-battery systems.…”

Section: Peak Shaving Via Solar Pv-battery Storage Systemmentioning

confidence: 99%

Grid-Tied Photovoltaic and Battery Storage Systems with Malaysian Electricity Tariff—A Review on Maximum Demand Shaving

et al. 2017

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Under the current energy sector framework of electricity tariff in Malaysia, commercial and industrial customers are required to pay the maximum demand (MD) charge apart from the net consumption charges every month. The maximum demand charge will contribute up to 20% of the electricity bill, and will hence result in commercial and industrial customers focussing on alternative energy supply to minimize the billing cost. This paper aims to review the technical assessment methods of a grid-connected solar photovoltaic (PV)-battery storage system-with respect to maximum demand shaving. An effective battery storage system can provide the extra energy needed during the peak energy consumption periods, as well as when renewable energy (RE) sources go offline. Based on the reviews, maximum demand shaving with good Return-of-Investment (ROI) can be achieved by considering the actual load profile, technical, and economic aspects of the solar PV-battery system and the Malaysian electricity tariff for commercial and industrial customers.

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Optimal planning of electric vehicle charging station at the distribution system using hybrid optimization algorithm

Cited by 265 publications

References 15 publications

A model for determining the locations of electric charge stations in Istanbul

A model for determining the locations of electric charge stations in Istanbul

Planning of Electric Vehicle Charging Infrastructure for Urban Areas with Tight Land Supply

Grid-Tied Photovoltaic and Battery Storage Systems with Malaysian Electricity Tariff—A Review on Maximum Demand Shaving

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