Electric Vehicles for merchandise transportation: Integrated planning taking into acount the electrical distribution system

2018 ◽  
Vol 16 (8) ◽  
pp. 2192-2198
Author(s):  
Juan David Sanchez Arango ◽  
Andres Arias Londono ◽  
Mauricio Granada Echeverri
Keyword(s):  
Electric Vehicles ◽  
Distribution System ◽  
Integrated Planning ◽  
Electrical Distribution

scholarly journals Electric Vehicles in Jordan: Challenges and Limitations

2021 ◽  
Vol 13 (6) ◽  
pp. 3199
Author(s):  
Laith Shalalfeh ◽  
Ashraf AlShalalfeh ◽  
Khaled Alkaradsheh ◽  
Mahmoud Alhamarneh ◽  
Ahmad Bashaireh
Keyword(s):  
Electric Vehicles ◽  
Distribution System ◽  
Distribution Systems ◽  
Environmental Benefits ◽  
System Stability ◽  
Loading Conditions ◽  
Stability Margins ◽  
High Penetration ◽  
Node Distribution ◽  
The Impact

An increasing number of electric vehicles (EVs) are replacing gasoline vehicles in the automobile market due to the economic and environmental benefits. The high penetration of EVs is one of the main challenges in the future smart grid. As a result of EV charging, an excessive overloading is expected in different elements of the power system, especially at the distribution level. In this paper, we evaluate the impact of EVs on the distribution system under three loading conditions (light, intermediate, and full). For each case, we estimate the maximum number of EVs that can be charged simultaneously before reaching different system limitations, including the undervoltage, overcurrent, and transformer capacity limit. Finally, we use the 19-node distribution system to study these limitations under different loading conditions. The 19-node system is one of the typical distribution systems in Jordan. Our work estimates the upper limit of the possible EV penetration before reaching the system stability margins.

scholarly journals High-Accuracy Power Quality Disturbance Classification Using the Adaptive ABC-PSO as Optimal Feature Selection Algorithm

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1238
Author(s):  
Supanat Chamchuen ◽  
Apirat Siritaratiwat ◽  
Pradit Fuangfoo ◽  
Puripong Suthisopapan ◽  
Pirat Khunkitti
Keyword(s):  
Feature Selection ◽  
Power Quality ◽  
Distribution System ◽  
Classification Accuracy ◽  
Selection Algorithm ◽  
Feature Selection Algorithm ◽  
Electrical Distribution ◽  
Power Quality Disturbance ◽  
Optimal Feature Selection ◽  
Optimal Feature

Power quality disturbance (PQD) is an important issue in electrical distribution systems that needs to be detected promptly and identified to prevent the degradation of system reliability. This work proposes a PQD classification using a novel algorithm, comprised of the artificial bee colony (ABC) and the particle swarm optimization (PSO) algorithms, called “adaptive ABC-PSO” as the feature selection algorithm. The proposed adaptive technique is applied to a combination of ABC and PSO algorithms, and then used as the feature selection algorithm. A discrete wavelet transform is used as the feature extraction method, and a probabilistic neural network is used as the classifier. We found that the highest classification accuracy (99.31%) could be achieved through nine optimally selected features out of all 72 extracted features. Moreover, the proposed PQD classification system demonstrated high performance in a noisy environment, as well as the real distribution system. When comparing the presented PQD classification system’s performance to previous studies, PQD classification accuracy using adaptive ABC-PSO as the optimal feature selection algorithm is considered to be at a high-range scale; therefore, the adaptive ABC-PSO algorithm can be used to classify the PQD in a practical electrical distribution system.

Integrating plug-in- electric vehicles with the distribution system

2009 ◽  
Author(s):  
A. Maitra ◽  
J. Taylor ◽  
D. Brooks ◽  
M. Alexander ◽  
M. Duvall
Keyword(s):  
Electric Vehicles ◽  
Distribution System

scholarly journals Smart charging for electric vehicles to minimise charging cost

2017 ◽  
Vol 231 (6) ◽  
pp. 526-534 ◽  
Author(s):  
Yue Wang ◽  
David Infield ◽  
Simon Gill
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Distribution System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Low Voltage ◽  
Wholesale Price ◽  
Heuristic Method ◽  
Domain Model ◽  
Smart Charging

This paper assumes a smart grid framework where the driving patterns for electric vehicles are known, time variations in electricity prices are communicated to householders, and data on voltage variation throughout the distribution system are available. Based on this information, an aggregator with access to this data can be employed to minimise electric vehicles charging costs to the owner whilst maintaining acceptable distribution system voltages. In this study, electric vehicle charging is assumed to take place only in the home. A single-phase Low Voltage (LV) distribution network is investigated where the local electric vehicles penetration level is assumed to be 100%. Electric vehicle use patterns have been extracted from the UK Time of Use Survey data with a 10-min resolution and the domestic base load is generated from an existing public domain model. Apart from the so-called real time price signal, which is derived from the electricity system wholesale price, the cost of battery degradation is also considered in the optimal scheduling of electric vehicles charging. A simple and effective heuristic method is proposed to minimise the electric vehicles’ charging cost whilst satisfying the requirement of state of charge for the electric vehicles’ battery. A simulation in OpenDSS over a period of 24 h has been implemented, taking care of the network constraints for voltage level at the customer connection points. The optimisation results are compared with those obtained using dynamic optimal power flow.

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