The Experts below are selected from a list of 132 Experts worldwide ranked by ideXlab platform
S.m. Shaahid - One of the best experts on this subject based on the ideXlab platform.
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Wind resource assessment of eastern coastal region of Saudi Arabia
Desalination, 2007Co-Authors: M.a. Elhadidy, S.m. ShaahidAbstract:Abstract Depleting oil and gas reserves, combined with growing concerns of global warming, have made it inevitable to seek energy from renewable energy sources such as Wind. The utilization of energy from Wind is becoming increasingly attractive and is being widely used/disseminated for substitution of oil-produced energy, and eventually to minimize atmospheric degradation. Quantitative assessment of Wind resource is an important driving element in successful establishment of a Wind farm/park at a given location. More often than not, Windenergy resources are relatively better along coastlines. In the present study, hourly mean Wind-speed data of the period 1986–1997 recorded at the solar radiation and meteorological station, Dhahran (26°32′ N, 50°13′ E, eastern coastal plain of Saudi Arabia), have been analyzed to present different characteristics of Wind speed in considerable depth such as: yearly, monthly, diurnal variations of Wind speed, etc. The long-term monthly average Wind speeds for Dhahran range from 4.2–6.4 m/s. More importantly, the study deals with impact of hub height on Wind energy generation. Attention has also been focussed on monthly average daily energy generation from different sizes of commercially available Wind Machines (150, 250, 600 kW) to identify optimum Wind machine size from energy production point of view. It has been found that for a given 6 MW Wind farm size, at 50 m hub height, cluster of 150 kW Wind Machines yields about 48% more energy as compared to 600 kW Wind Machines. Literature shows that commercial/residential buildings in Saudi Arabia consume an estimated 10–40% of the total electric energy generated. So, concurrently, as a case study, attempt has been made to investigate/examine the potential of utilizing hybrid (Wind+diesel) energy conversion systems to meet the load requirements of hundred typical 2-bedroom residential buildings (with annual electrical energy demand of 3512 MWh). The hybrid systems considered in the present case-study consist of different combinations of Wind Machines (of various capacities), supplemented with battery storage and diesel back-up. The deficit energy generated from the back-up diesel generator and the number of operational hours of the diesel system to meet a specific annual electrical energy demand of 3512 MWh have also been presented. The diesel back-up system is operated at times when the power generated from Wind energy conversion systems (WECS) fails to satisfy the load and when the battery storage is depleted. The evaluation of hybrid system shows that with seven 150 kW WECS and three days of battery storage, the diesel back-up system has to provide 17.5% of the load demand. However, in absence of battery storage, about 37% of the load needs to be provided by the diesel system.
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Parametric study of hybrid (Wind + solar + diesel) power generating systems
Renewable Energy, 2000Co-Authors: M.a. Elhadidy, S.m. ShaahidAbstract:Abstract The combined utilization of renewables such as solar and Wind energy is becoming increasingly attractive and is being widely used for substitution of oil-produced energy, and eventually to reduce air pollution. In the present investigation, hourly Wind-speed and solar radiation measurements made at the solar radiation and meteorological monitoring station, Dhahran (26°32′N, 50°13′E), Saudi Arabia, have been analyzed to study the impact of key parameters such as photovoltaic (PV) array area, number of Wind Machines, and battery storage capacity on the operation of hybrid (Wind + solar + diesel) energy conversion systems, while satisfying a specific annual load of 41,500 kWh. The monthly average Wind speeds for Dhahran range from 4.1 to 6.4 m/s. The monthly average daily values of solar radiation for Dhahran range from 3.6 to 7.96 kWh/m2. Parametric analysis indicates that with two 10 kW Wind Machines together with three days of battery storage and photovoltaic deployment of 30 m2, the diesel back-up system has to provide about 23% of the load demand. However, with elimination of battery storage, about 48% of the load needs to be provided by diesel system.
Shafiqur Rehman - One of the best experts on this subject based on the ideXlab platform.
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Wind power characteristics of seven data collection sites in Jubail, Saudi Arabia using Weibull parameters
Renewable Energy, 2017Co-Authors: M.a. Baseer, Shafiqur Rehman, Josua P. Meyer, Mahbub AlamAbstract:Abstract The Wind characteristics of seven locations in Jubail, Saudi Arabia were analysed by using five years of Wind data of six sites and three years data of one site at 10 m above ground level (AGL). The highest annual mean Wind speed of 4.52 m/s was observed at Industrial area (east) and lowest of 2.52 m/s at Pearl beach with standard deviations of 2.52 and 1.1 m/s respectively. Weibull parameters were estimated using maximum likelihood, least-squares regression method (LSRM) and WAsP algorithm. The most probable and maximum energy carrying Wind speed were found by all the three methods. The correlation coefficient (R2), root mean square error (RMSE), mean bias error (MBE) and mean bias absolute error (MAE) showed that all three methods represent Wind data at all sites accurately. However, the maximum likelihood method is slightly better than LSRM followed by WAsP algorithm. The Wind power output at all seven sites from five commercially available Wind Machines of rated power from 1.8 to 3.3 MW showed that Jubail industrial area (east) is most promising. The energy output from a 3 MW Wind machine at this site was found to be 11,136 MWh/yr. with a plant capacity factor (PCF) of 41.3%.
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Wind energy resources assessment for Yanbo, Saudi Arabia
Energy Conversion and Management, 2003Co-Authors: Shafiqur RehmanAbstract:The paper presents long term Wind data analysis in terms of annual, seasonal and diurnal variations at Yanbo, which is located on the west coast of Saudi Arabia. The Wind speed and Wind direction hourly data for a period of 14 years between 1970 and 1983 is used in the analysis. The analysis showed that the seasonal and diurnal pattern of Wind speed matches the electricity load pattern of the location. Higher Winds of the order of 5.0 m/s and more were observed during the summer months of the year and noon hours (09:00 to 16:00 h) of the day. The Wind duration availability is discussed as the percent of hours during which the Wind remained in certain Wind speed intervals or bins. Wind energy calculations were performed using Wind Machines of sizes 150, 250, 600, 800, 1000, 1300, 1500, 2300 and 2500 kW rated power. Wind speed is found to remain above 3.5 m/s for 69% of the time during the year at 40, 50, 60, and 80 m above ground level. The energy production analysis showed higher production from Wind Machines of smaller sizes than the bigger ones for a Wind farm of 30 MW installed capacity. Similarly, higher capacity factors were obtained for smaller Wind Machines compared to larger ones.
M.a. Elhadidy - One of the best experts on this subject based on the ideXlab platform.
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Wind resource assessment of eastern coastal region of Saudi Arabia
Desalination, 2007Co-Authors: M.a. Elhadidy, S.m. ShaahidAbstract:Abstract Depleting oil and gas reserves, combined with growing concerns of global warming, have made it inevitable to seek energy from renewable energy sources such as Wind. The utilization of energy from Wind is becoming increasingly attractive and is being widely used/disseminated for substitution of oil-produced energy, and eventually to minimize atmospheric degradation. Quantitative assessment of Wind resource is an important driving element in successful establishment of a Wind farm/park at a given location. More often than not, Windenergy resources are relatively better along coastlines. In the present study, hourly mean Wind-speed data of the period 1986–1997 recorded at the solar radiation and meteorological station, Dhahran (26°32′ N, 50°13′ E, eastern coastal plain of Saudi Arabia), have been analyzed to present different characteristics of Wind speed in considerable depth such as: yearly, monthly, diurnal variations of Wind speed, etc. The long-term monthly average Wind speeds for Dhahran range from 4.2–6.4 m/s. More importantly, the study deals with impact of hub height on Wind energy generation. Attention has also been focussed on monthly average daily energy generation from different sizes of commercially available Wind Machines (150, 250, 600 kW) to identify optimum Wind machine size from energy production point of view. It has been found that for a given 6 MW Wind farm size, at 50 m hub height, cluster of 150 kW Wind Machines yields about 48% more energy as compared to 600 kW Wind Machines. Literature shows that commercial/residential buildings in Saudi Arabia consume an estimated 10–40% of the total electric energy generated. So, concurrently, as a case study, attempt has been made to investigate/examine the potential of utilizing hybrid (Wind+diesel) energy conversion systems to meet the load requirements of hundred typical 2-bedroom residential buildings (with annual electrical energy demand of 3512 MWh). The hybrid systems considered in the present case-study consist of different combinations of Wind Machines (of various capacities), supplemented with battery storage and diesel back-up. The deficit energy generated from the back-up diesel generator and the number of operational hours of the diesel system to meet a specific annual electrical energy demand of 3512 MWh have also been presented. The diesel back-up system is operated at times when the power generated from Wind energy conversion systems (WECS) fails to satisfy the load and when the battery storage is depleted. The evaluation of hybrid system shows that with seven 150 kW WECS and three days of battery storage, the diesel back-up system has to provide 17.5% of the load demand. However, in absence of battery storage, about 37% of the load needs to be provided by the diesel system.
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Parametric study of hybrid (Wind + solar + diesel) power generating systems
Renewable Energy, 2000Co-Authors: M.a. Elhadidy, S.m. ShaahidAbstract:Abstract The combined utilization of renewables such as solar and Wind energy is becoming increasingly attractive and is being widely used for substitution of oil-produced energy, and eventually to reduce air pollution. In the present investigation, hourly Wind-speed and solar radiation measurements made at the solar radiation and meteorological monitoring station, Dhahran (26°32′N, 50°13′E), Saudi Arabia, have been analyzed to study the impact of key parameters such as photovoltaic (PV) array area, number of Wind Machines, and battery storage capacity on the operation of hybrid (Wind + solar + diesel) energy conversion systems, while satisfying a specific annual load of 41,500 kWh. The monthly average Wind speeds for Dhahran range from 4.1 to 6.4 m/s. The monthly average daily values of solar radiation for Dhahran range from 3.6 to 7.96 kWh/m2. Parametric analysis indicates that with two 10 kW Wind Machines together with three days of battery storage and photovoltaic deployment of 30 m2, the diesel back-up system has to provide about 23% of the load demand. However, with elimination of battery storage, about 48% of the load needs to be provided by diesel system.
B. V. Sanker Ram - One of the best experts on this subject based on the ideXlab platform.
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An ANN Control of Maximum Power Point Tracking for Grid Connected Wind Machines
International Review of Automatic Control (IREACO), 2014Co-Authors: S. Sundeep, G. Madhusudhana Rao, B. V. Sanker RamAbstract:This research work investigates about the Wind energy conversion system will receive the extensive attention among the various renewable energy systems. The extraction of the maximum possible power available Wind energy is an important area of research among the speed sensorless MPPT control of Wind area. This paper presents a power point tracking (MPPT) Technique for high performance Wind turbine with induction Machines based on expert systems (Artificial Neural Networks). In this paper, an ANN has been trained in off-line to learn about Wind turbine characteristics of the torque with the Wind speed and the speed of the machine which will be deployed in online for measuring the speed of the Wind and torque. The reference speed of the machine is then calculated based on the control of the signal power feedback (PSF). Voltage oriented control of the machine is further integrated with an expert sensorless technique. The proposed method was simulated and conformed on the actual circuit in online
Mahbub Alam - One of the best experts on this subject based on the ideXlab platform.
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Wind power characteristics of seven data collection sites in Jubail, Saudi Arabia using Weibull parameters
Renewable Energy, 2017Co-Authors: M.a. Baseer, Shafiqur Rehman, Josua P. Meyer, Mahbub AlamAbstract:Abstract The Wind characteristics of seven locations in Jubail, Saudi Arabia were analysed by using five years of Wind data of six sites and three years data of one site at 10 m above ground level (AGL). The highest annual mean Wind speed of 4.52 m/s was observed at Industrial area (east) and lowest of 2.52 m/s at Pearl beach with standard deviations of 2.52 and 1.1 m/s respectively. Weibull parameters were estimated using maximum likelihood, least-squares regression method (LSRM) and WAsP algorithm. The most probable and maximum energy carrying Wind speed were found by all the three methods. The correlation coefficient (R2), root mean square error (RMSE), mean bias error (MBE) and mean bias absolute error (MAE) showed that all three methods represent Wind data at all sites accurately. However, the maximum likelihood method is slightly better than LSRM followed by WAsP algorithm. The Wind power output at all seven sites from five commercially available Wind Machines of rated power from 1.8 to 3.3 MW showed that Jubail industrial area (east) is most promising. The energy output from a 3 MW Wind machine at this site was found to be 11,136 MWh/yr. with a plant capacity factor (PCF) of 41.3%.
