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Majid Vafaeipour   Mr.  Graduate Student or Post Graduate 
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Majid Vafaeipour published an article in September 2017.
Top co-authors
Marc A. Rosen

437 shared publications

Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, Ontario, L1G 0C5, CANADA

Omid Rahbari

6 shared publications

Young Researchers and Elite Club, South Tehran Branch, Islamic Azad University, Tehran, Iran

12
Publications
25
Reads
3
Downloads
65
Citations
Publication Record
Distribution of Articles published per year 
(2012 - 2017)
Total number of journals
published in
 
9
 
Publications See all
Article 0 Reads 5 Citations An optimal versatile control approach for plug-in electric vehicles to integrate renewable energy sources and smart grid... Omid Rahbari, Majid Vafaeipour, Noshin Omar, Marc A. Rosen, ... Published: 01 September 2017
Energy, doi: 10.1016/j.energy.2017.06.007
DOI See at publisher website
CONFERENCE-ARTICLE 7 Reads 0 Citations Developing Realistic Designs for Wind Farms: Incorporation of an Imperialist Competitive Algorithm Kaamran Raahemifar, Marc Rosen, Omid Rahbari, Mohammad Hosse... Published: 03 November 2014
Proceedings of The 4th World Sustainability Forum, doi: 10.3390/wsf-4-e013
DOI See at publisher website ABS Show/hide abstract
The optimal positioning of wind turbines plays an important role in acquiring the anticipated output power from wind farms. This paper addresses challenges related to typical restriction assumptions for turbine arrangements in wind farms with a candidate selection approach. A hybrid quadratic assignment problem-imperialist competitive algorithm (QAP-ICA) method with an initial candidate points' selection (ICPS) approach is applied to two case studies. This hybrid algorithm is used to obtain optimal layout designs in terms of maximum efficiency. The current study incorporates previously utilized indicators from the literature for wind farms, such as wake effects, turbine hub height, rotor diameter, and transmission losses, and proposes additional criteria such as load-bearing capacity of soil and its restrictions. This is done to make the method applicable for realistic cases, and to assimilate the comments of expert designers. The consequence of an optimal layout design can be superior performance with the proposed algorithm compared to previous similar studies. An efficiency improvement of about 4% is attained for the first case considered, and the algorithm provides reasonable optimal wind farm design layouts for the second case, in which reductions of power losses of the wind farm are considered.
CONFERENCE-ARTICLE 7 Reads 2 Citations Performance of Neural Wavelet and ANFIS Algorithms for Short-Term Prediction of Solar Radiation and Wind Velocities Mohammad Hossein Morshed Varzandeh, Omid Rahbari, Majid Vafa... Published: 03 November 2014
Proceedings of The 4th World Sustainability Forum, doi: 10.3390/wsf-4-e010
DOI See at publisher website ABS Show/hide abstract
Prediction of wind and solar energy is deemed one of the most important contributory factors towards sustainability. Along the same lines, to harvest energy and guarantee the safety of a place, accurate information about the future of the region is needed. To achieve the target, this paper predicts solar irradiation and wind velocity time series by two robust artificial intelligence algorithms which are called Wavelet and ANFIS (Adaptive Network Fuzzy Inference System). The data used for the predictor system are obtained from a meteorological station in Tehran, Iran.  The results show that a) robustness of both algorithms for prediction of wind velocities and solar irradiation b) superior strength of Wavelet to ANFIS for prediction of solar irradiation c) ANFIS makes a better prediction of Wavelet for wind velocities.
Article 0 Reads 33 Citations Assessment of regions priority for implementation of solar projects in Iran: New application of a hybrid multi-criteria ... Majid Vafaeipour, Sarfaraz Hashemkhani Zolfani, Mohammad Hos... Published: 01 October 2014
Energy Conversion and Management, doi: 10.1016/j.enconman.2014.05.083
DOI See at publisher website
Article 5 Reads 3 Citations Application of sliding window technique for prediction of wind velocity time series Majid Vafaeipour, Omid Rahbari, Marc A. Rosen, Farivar Fazel... Published: 18 May 2014
International Journal of Energy and Environmental Engineering, doi: 10.1007/s40095-014-0105-5
DOI See at publisher website ABS Show/hide abstract
The uncertainty caused by the discontinuous nature of wind energy affects the power grid. Hence, forecasting the behavior of this renewable resource is important for energy managers and electricity traders to overcome the risk of unpredictability and to provide reliability for the grid. The objective of this paper is to employ and compare the potential of various artificial neural network structures of multi-layer perceptron (MLP) and radial basis function for prediction of the wind velocity time series in Tehran, Iran. Structure analysis and performance evaluations of the established networks indicate that the MLP network with a 4-7-13-1 architecture is superior to others. The best networks were deployed to unseen data and were capable of predicting the velocity time series via using the sliding window technique successfully. Applying the statistical indices with the predicted and the actual test data resulted in acceptable RMSE, MSE and R2 values with 1.19, 1.43 and 0.85, respectively, for the best network.
Article 0 Reads 6 Citations Towards realistic designs of wind farm layouts: Application of a novel placement selector approach Omid Rahbari, Majid Vafaeipour, Farivar Fazelpour, Michel Fe... Published: 01 May 2014
Energy Conversion and Management, doi: 10.1016/j.enconman.2014.02.010
DOI See at publisher website
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