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Omid Rahbari   Dr.  University Educator/Researcher 
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Omid Rahbari 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

Edmundas Kazimieras Zavadskas

234 shared publications

Vilnius Gediminas Technical University

Farivar Fazelpour

27 shared publications

Department of Energy Systems Engineering, South Tehran BranchIslamic Azad University Tehran Iran

Majid Vafaeipour

12 shared publications

Department of Mechanical and Aerospace Engineering, Syracuse University, USA

Mohammad H. Valizadeh

1 shared publications

Shiraz University of Technology

Publication Record
Distribution of Articles published per year 
(2013 - 2017)
Total number of journals
published in
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/
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 8 Reads 0 Citations Placement of Wind Farms Based on a Hybrid Multi Criteria Decision Making for Iran Fahime Heidarzadeh, Mohammad Hossein Morshed Varzandeh, Omid... Published: 03 November 2014
Proceedings of The 4th World Sustainability Forum, doi: 10.3390/wsf-4-e009
DOI See at publisher website ABS Show/hide abstract
In the current century, energy is become as one of the most critical issues in human's life. Due to global warming, air pollution and the other problems caused by fossil fuels, one of the appropriate sources which is renewable and is invested is wind energy. Iran has a good potential for using wind energy based on its geographical features. Therefore, to have the best productivity for employing wind energy, locating farm winds in a suitable site is a delicate issue. This research applied a hybrid MCDM method for prioritizing potential cities in Iran to install wind farms. In this regard, Step-wise Weight Assessment Ratio Analysis (SWARA) is employed to rank criteria and Weighted Aggregates Sum Product Assessment (WASPAS) applied for evaluating alternatives. In this study 10 cities are detected as high potential places for this aim. Eventually, the most appropriate city is identified as the best place to set up farm winds, and a comprehensive GIS map depicts the results. The results of this research can be used in decision making and planning of energy management in top level of managing requirements of countries in all respects.
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
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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 4 Citations Considerable parameters of using PV cells for solar-powered aircrafts Farivar Fazelpour, Majid Vafaeipour, Omid Rahbari, Reza Shir... Published: 01 June 2013
Renewable and Sustainable Energy Reviews, doi: 10.1016/j.rser.2013.01.016
DOI See at publisher website
BOOK-CHAPTER 5 Reads 1 Citation Assessment of Solar Radiation Potential for Different Cities in Iran Using a Temperature-Based Method Farivar Fazelpour, Majid Vafaeipour, Omid Rahbari, Mohammad ... Published: 01 January 2013
Agent and Multi-Agent Systems: Technologies and Applications, doi: 10.1007/978-3-642-36645-1_19
DOI See at publisher website