A New Dynamic Stochastic EV Model for Power System Planning Applications

Citation Author(s):
American University of Sharjah
American University of Sharjah
American University of Sharjah
King Abdulaziz University
King Abdulaziz University
Submitted by:
Hatem Sindi
Last updated:
Wed, 04/29/2020 - 22:53
Data Format:
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The uploaded data file is a part of data used or generated by a model proposed in a paper entitled: “A New Dynamic Stochastic EV Model for Power System Planning Applications”. The proposed model in this paper consists of two sub-models which are the travel behavior and the battery depletion sub-models. The proposed model is taken into consideration the different trip purposes, starting and ending trip times, as well as the corresponding battery depletion. The outcomes from the travel behavior sub-model are the starting times, the ending times and the trips distances. These outcomes are used by the battery depletion sub-model with the environmental conditions to determine the PEV battery depletion by the end of a trip. The outcomes of overall model can be used for long-term studies with different charging strategies.

Finally, the uploaded data file includes many of data set used by this model, for example:

·         The annual, monthly and daily probabilities for each trip purpose used by travel sub-model.

·         The starting and ending times of each trip generated by travel sub-model.

·         The trips distances generated by travel sub-model.

·         The different batteries capacities available in the market to be used by battery depletion sub-model.

·         Temperature data used in the battery depletion sub-model.

·         Generation units’ data and normal demand to be used in the reliability study as an application of the proposed model.



Instructions about Dataset File:

Data set file includes 8 sheets as follow:

1.       Sheet 1 (Trip Information): shows Probability of Annual Trip Purpose, Probability of Monthly Trip Purpose, Probability of Daily Trip Purpose, and probability of Plugin electric vehicles (PEV) classes.

2.       Sheet 2 (Trip Start Time): is considered as one of the outputs from travel behavior sub-model that uses the information in the previous sheet and obtains the probability of starting a trip of a certain purpose through one day.

3.       Sheet 3 (Trip End Time): like sheet 2, but it shows the probability of ending a trip of a certain purpose through one day.

4.       Sheet 4 (Trip Distances): shows the parameters of probability distribution function for each trip purpose used by travel behavior sub-model to obtain the distance of each trip.

5.       Sheet 5 (Battery Capacity in the Market): is used by battery depletion sub-model and it shows Different battery capacities (kWh) and its percentage share according to the market shares in USA.

6.       Sheet 6 (Temperature Data): shows the different temperatures during one year to be used in battery depletion sub-model to determine the battery depletion energy due to usage of PEV A/C or heater.

7.       Sheet 7 (Generation units Data): shows the data of generation units used to generate 5000 virtual scenarios to study the power system reliability as an application for the proposed model.

8.       Sheet 8 (Normal Demand Data): shows the data of normal load demand in P.U to be used in the reliability study. (The Annual peak base power is 185 MW).




Hi Hatem


Can you please share a preprint version of the inferred paper? I seem not to find it online.


Many thanks.


Submitted by Kayode Adetunji on Wed, 05/06/2020 - 03:03

Sir, my name is Rachna Vaish and I am a research scholar in India. Sir, please send me the related paper as I am very interested to know about your work and explore it.


Submitted by Rachna Vaish on Tue, 08/04/2020 - 07:20

Sir, I will be very grateful to you if you can send it to me on pee19001@rgipt.ac.in

Submitted by Rachna Vaish on Tue, 08/04/2020 - 07:22

Dear sir, Its great work if possible kindly sends me related papers at ashiwani2016@gmail.com

Submitted by ashiwani yadav on Wed, 09/09/2020 - 11:26