Omid Nematollahi

Bio: Omid Nematollahi is an academic researcher from Pusan National University. The author has contributed to research in topics: Renewable energy & Wind power. The author has an hindex of 18, co-authored 39 publications receiving 988 citations. Previous affiliations of Omid Nematollahi include Malek-Ashtar University of Technology & Isfahan University of Technology.

Solar energy potentials in Iran: A review

Abstract: In the present study, feasibility of using solar energy in different regions of Iran is investigated. For this purpose, maximum, minimum, and average values of annual horizontal radiation were calculated for sixty-three stations. Then, monthly and annual clearness indices and the annual average horizontal radiation map and GIS maps of horizontal radiation (GHR) were prepared for each month of the year. The results show that central and southern regions in Iran, except the coastal areas in the south, receive higher quantities of horizontal radiation. Among these regions, Southern Khorasan and Khuzestan provinces receive significant amounts of solar radiation such that the use of solar systems in these regions will be more economical. Delgan, Mahshahr, Shushtar, Abadeh, and Fadashk stations recorded an annual average horizontal radiation of above 500 W/m2, which shows their potential for photovoltaic applications. These regions may be recommended for further study.

Energy demands and renewable energy resources in the Middle East

Abstract: The energy security and supplies of energy are the key components for progressing countries. Renewable energy resources are rapidly being recognized as clean sources of energy to withstand damages to environment and to avoid future crisis. In this study, energy consumption and energy demands in the progressing Middle East countries are reviewed. First, the growth of energy consumption of the region through recent years is presented which show the rapidly growing energy demand in the Middle East countries. Second, by using RETScreen software data, the potential of the main renewable energies of solar and wind resources are evaluated. Results showed that the Middle East region have a very good potential for using renewable energies. Results are presented as GIS maps of wind speed, wind power density and solar radiation intensity. With using the GIS maps, the great locations for utilizing solar or wind energies are identified. The presented GIS maps may facilitate development of hybrid solar and wind systems within the Middle East region.

Assessment of wind energy in Iran: A review

Abstract: In this study, a ten minute period measuring wind speed data for year 2007 at 10 m, 30 m and 40 m heights for different places in Iran, has been statistically analyzed to determine the potential of wind power generation. Sixty eight sites have been studied. The objective is to evaluate the most important characteristics of wind energy in the studied sites. The statistical attitudes permit us to estimate the mean wind speed, the wind speed distribution function, the mean wind power density and the wind rose in the site at three different heights. Some local phenomena are also considered in the characterization of the site.

Finding the best locations for establishment of solar-wind power stations in Middle-East using GIS: A review

Abstract: Nowadays, renewable energies are more preferable to fossil fuels because of being free, widely available and producing minimal pollution. One of the disadvantages of renewable energy systems is that using only one type of renewable energy cannot guarantee a continuous power generation. To overcome this problem, two or more renewable energy systems should be used simultaneously to compensate for times when one of them is not available or the renewable system should be used aligned with the generator. In addition, another weakness is that they are not accessible in every geographical position and location. It is clear that renewable energy systems can be exploited to their fullest capacity when used in the proper place. Therefore, given the importance of finding suitable places for co-utilization of several renewable energies, present paper attempted to find the ideal locations for construction of hybrid solar-wind power stations in Middle-East using Boolean model in GIS software. The Boolean method is, in a way, a more stringent method compared to the other positioning methods. Therefore, the selected locations will definitely have greater energy potential by using the Boolean method. Data obtained by RETScreen4 software from 400 stations in Middle-East were used for collecting monthly weather information. Results of the current paper may be helpful in creating prospects for sustainable energy development for systems based on natural resources and facilitating the national power transmission and sustainable environmental policies.

A risk-based multi-criteria spatial decision analysis for solar power plant site selection in different climates: A case study in Iran

Abstract: Identifying potential locations for installation of solar power plants is a critical step in utilizing sustainable energy resources. In this study, a GIS-based Multi-Criteria Decision Analysis (GIS-MCDA) technique is used to generate maps that represent potential areas for solar power plants in four provinces with different climate conditions in Iran. The concept of risk is included in the GIS-MCDA process using the Ordered Weighted Averaging (OWA) model. The OWA model can provide various risk-taking (optimistic) and risk-aversion (pessimistic) scenarios to determine the suitable power plant areas. The results of this study indicate that provinces located in an arid climate such as Yazd contain a more suitable area for the solar power plants compared to wet climate provinces (e.g., Mazandaran). The sensitivity analysis of results show that the criterion “fault” has the minimum effect while the criteria “slope” and “road network” have the maximum effects on the area of the highly desirable class.

Classifications, applications, and design challenges of drones: A review

Abstract: Nowadays, there is a growing need for flying drones with diverse capabilities for both civilian and military applications. There is also a significant interest in the development of novel drones which can autonomously fly in different environments and locations and can perform various missions. In the past decade, the broad spectrum of applications of these drones has received most attention which led to the invention of various types of drones with different sizes and weights. In this review paper, we identify a novel classification of flying drones that ranges from unmanned air vehicles to smart dusts at both ends of this spectrum, with their new defined applications. Design and fabrication challenges of micro drones, existing methods for increasing their endurance, and various navigation and control approaches are discussed in details. Limitations of the existing drones, proposed solutions for the next generation of drones, and recommendations are also presented and discussed.

Power Electronics Converters Applications And Design

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The fluid mechanics of natural ventilation

Abstract: Natural ventilation of buildings is the flow generated by temperature differences and by the wind. The governing feature of this flow is the exchange between an interior space and the external ambient. Although the wind may often appear to be the dominant driving mechanism, in many circumstances temperature variations play a controlling feature on the ventilation since the directional buoyancy force has a large influence on the flow patterns within the space and on the nature of the exchange with the outside. Two forms of ventilation are discussed: mixing ventilation, in which the interior is at an approximately uniform temperature, and displacement ventilation, where there is strong internal stratification. The dynamics of these buoyancy-driven flows are considered, and the effects of wind on them are examined. The aim behind this work is to give designers rules and intuition on how air moves within a building; the research reveals a fascinating branch of fluid mechanics.

Accurate photovoltaic power forecasting models using deep LSTM-RNN

Abstract: Photovoltaic (PV) is one of the most promising renewable energy sources. To ensure secure operation and economic integration of PV in smart grids, accurate forecasting of PV power is an important issue. In this paper, we propose the use of long short-term memory recurrent neural network (LSTM-RNN) to accurately forecast the output power of PV systems. The LSTM networks can model the temporal changes in PV output power because of their recurrent architecture and memory units. The proposed method is evaluated using hourly datasets of different sites for a year. We compare the proposed method with three PV forecasting methods. The use of LSTM offers a further reduction in the forecasting error compared with the other methods. The proposed forecasting method can be a helpful tool for planning and controlling smart grids.