Wind Energy Feasibility Study for Generating Electricity at Al-Aqiq City, Saudi Arabia
- Saeed A. Al-Ghamdi
- Reseived: 6 December 2020 Received in Revised Form: 23 January 2021 Accepted: 25 January 2021
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Daily and monthly mean wind speed variations in King Saud airport, Al-Aqiq, KSA are collected and studied to investigate electricity generation feasibility. Diurnal, monthly and annual mean wind speeds and wind power are determined. The mean wind speeds in Al-Aqiq city, over one-year time period at a main direction of south-southwest, are about 3.31, 5.09 and 6.13 m/s at hub heights of 10, 50 and 100m, respectively. The diurnal study showed that the wind speed at hub height of 10m remains above 3.0m/s from 09:00 AM to 10:00 PM and below it during the rest of the day hours. It also showed that the wind speed at hub heights of 50m and 100m remains above 3.0m/s during all hours of the day. Wind energy generation was considered for 45 wind turbines of different sizes at hub heights of 10m, 50m and 100m. The highest capacity factors of the turbine models having a maximum hub height of 50m are recorded by Aeronautica Windpower 33-225 as 17.5%, and 37.1% at heights of 10m and 50m, respectively. The highest capacity factors are recorded for Yinhe among turbine models having a maximum hub height of 100m as 40.0% and 48.1%, at heights of 50m and 100m, respectively. These results indicate that it is feasible to generate power from wind energy in the Al-Aqiq region for providing energy demands.
Road Obstacles Detection by Learning the Driving Behavior
- Nizar Alsharif
- Reseived: 31 August 2020 Received in Revised Form: 26 October 2020 Accepted: 3 November 2020
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It is common for road users who are driving in, or to, a mountainous region to face road obstacles. In addition to many economic and environmental effects, road obstacles can threat road users lives. These obstacles, such as Water torrents and Rock falls, may cause the road to be fully blocked or semi-blocked. This work investigates the driving behavior along the roads with obstacles using on-board units (OBUs) to detect and report road obstacles. The system will not only help road users, but also support the different governmental and commercial parties by providing real-time information about road and driving conditions. In this work a dataset for the driving patterns is collected by the aid of car driving volunteers. Driving behavior descriptor is proposed based on radial distance shape signature. Two classifiers are used to detect the road obstacles: 1-Nearest Neighbor (1-NN) classifier and Neural Network-based classifier. The first classifier achieves 92.1% correct classifications versus 94.5% success percentage for the second classifier, respectively.
Proposed PV Systems for Albaha University at Al-Baha Region, Saudi Arabia
- Gamal A.W. Hazza
- Reseived: 27 June 2020 Received in Revised Form: 1 September 2020 Accepted: 15 September 2020
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The feasibility of PV systems has been investigated to supply some of the electrical demands of Albaha University (BU) buildings which are currently fed by conventional energy sources through the Saudi Electricity Company (SEC) power system. This task was implemented through a proposed standalone PV system for outdoor yards lighting and on-grid PV systems for educational and administration buildings. Initially, a survey was conducted about solar panels, their uses and developments, and the types of electrical inverters and their uses to take into consideration to design the proposed on-grid PV system. The technical data of the electrical network that connects between the SEC power system and the BU buildings are collected and analyzed. Electrical load readings of the various buildings of the BU have been collected. Also, different weather data have been collected such as temperature, solar radiation, and wind speed, etc. from the Al-Baha Domestic Airport Weather Station and the station of King Abdullah City for Atomic and Renewable Energy (K.A.CARE) located on the roof of the Faculty of Science, BU. Finally, the proposed PV systems designed based on different scenarios of collected data for the different buildings and outdoor yards and the economic and environmental impact of the proposed PV systems have been verified from the point of view of its contribution to reduce the energy consumption from the SEC and its contribution to reduce harmful carbon dioxide emissions.
Antidiabetic Effect of Leaves Aqueous Extracts of Three Endemic Plants in Al-Mandaq Governorate, Al-Baha, KSA on Diabetic Rats
- Khalid S. Al-Zahrani
- Reseived: 28 March 2020 Received in Revised Form: 17 May 2020 Accepted: 30 May 2020
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Diabetes mellitus (DM) is a metabolic disorder resulting from a defect in insulin secretion/action or both. This study was designed to evaluate the effects of extracts of three plants namely, Olea europea subsp. Africana (O.), Ziziphus spina-christi (Z.), and Rumex nervosus (R.) on alloxan-induced diabetic rats. In this study thirty male Albino rats, body weight of 300-320g were divided into 5 groups (6 each). Diabetes was induced by intraperitoneal injection with sterile cold saline solution of alloxan (120 mg/kg body weight). The aqueous extracts of plants were orally administrated to diabetic rats for 22 days (twice a day). The daily used dose was 300 mg/kg body weight. Blood glucose levels were measured two hours before treatment and 1, 2, and 3 weeks after administration of extracts using glucometer. Cholesterol and triglycerides concentrations were estimated at seven-day intervals. Histopathological examination of the pancreas was also carried out at the end of the experiment. Blood glucose levels were significantly decreased with extracts of O. and Z. while, R. extract did not show significantly changes in glucose levels. Cholesterol and triglycerides concentrations were slightly decreased in the group treated with R. Improvement of histopathological features of the pancreas was observed in the groups treated with O. and Z.
