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The utilization of renewable energy to run desalination plants has enormously expanded in the last two decades. In this study, a grid-connected hybrid solar-wind system is proposed to power a small-scale Reverse Osmosis (RO) desalination unit. In a case study, the system's performance has been analyzed under the weather conditions of the Eastern Province, Saudi Arabia. A numerical model has been developed based on a mixed-integer linear programming (MILP) approach to design and size the proposed system. The developed model is solved on an hourly basis to capture hourly variations of weather conditions with the aim to obtain an efficient design to operate the RO plant and supply freshwater to a small community living in a remote area at minimum cost. The developed model allows finding the optimal number of wind turbines, the number of photovoltaic (PV) modules, and the energy purchased from the national grid. Since the desalination energy consumption depends on the feed water conditions, two energy consumption rates are considered, namely, 2 and 4 kWh/m3. The results show that brackish water can be purified for the two different energy requirements at a cost varying between 1.72 and 1.84 $/m3, respectively.
Ahmed M. Ghaithan; Ahmad Al-Hanbali; Awsan Mohammed; Ahmed M. Attia; Haitham Saleh; Omar Alsawafy. Optimization of a solar-wind- grid powered desalination system in Saudi Arabia. Renewable Energy 2021, 178, 295 -306.
AMA StyleAhmed M. Ghaithan, Ahmad Al-Hanbali, Awsan Mohammed, Ahmed M. Attia, Haitham Saleh, Omar Alsawafy. Optimization of a solar-wind- grid powered desalination system in Saudi Arabia. Renewable Energy. 2021; 178 ():295-306.
Chicago/Turabian StyleAhmed M. Ghaithan; Ahmad Al-Hanbali; Awsan Mohammed; Ahmed M. Attia; Haitham Saleh; Omar Alsawafy. 2021. "Optimization of a solar-wind- grid powered desalination system in Saudi Arabia." Renewable Energy 178, no. : 295-306.
Saudi Arabia, with no perennial rivers, is considered to be an arid land where water losses in the Water Distribution Network (WDN) supply increase the need for sea water desalination. This paper provides a reliability model to enhance the WDN for a water pumping station in Saudi Arabia. The paper utilizes the Fault Tree Analysis (FTA) reliability tool to mitigate water supply stoppages. In the case under study, the pump station utilizes two groundwater aquifers in the eastern part of Saudi Arabia to meet the raw water demand through a water distribution network (28 km-long pipelines). Data has been gathered from the maintenance history to estimate the system reliability based on the loss of water by which each component of the system is assessed on its contribution to the overall system reliability and water supply. The findings revealed that system availability can be improved by adding a new pump in the booster station which further enhances the availability of the system to 99.99% and saves the WDN more than 740,974.60 gallons of water loss per year. It is hoped that the paper's recommendations will enhance reliability practices in similar water network stations.
Laith Hadidi; Awsan Mohammed; Ahmed Ghaithan; Firas Tuffaha. A holistic reliability system approach of a water distribution network in Saudi Arabia. Water Supply 2021, 1 .
AMA StyleLaith Hadidi, Awsan Mohammed, Ahmed Ghaithan, Firas Tuffaha. A holistic reliability system approach of a water distribution network in Saudi Arabia. Water Supply. 2021; ():1.
Chicago/Turabian StyleLaith Hadidi; Awsan Mohammed; Ahmed Ghaithan; Firas Tuffaha. 2021. "A holistic reliability system approach of a water distribution network in Saudi Arabia." Water Supply , no. : 1.
A considerable amount of the oil used in Saudi Arabia is consumed to generate power. In an effort to minimize such consumption, the government of Saudi Arabia has established an ambitious part of the 2030 Vision that includes 96 strategic objectives. In recent years, the advancement in information technology has made it possible to develop accurate prediction models of energy consumption for constructed facilities, which can assist with establishing plans to reduce future energy consumption. This research proposes a regression-based model for predicting the energy consumption of one of the most significant energy-consuming types of facilities in Saudi Arabia: schools. The model was developed utilizing 350 actual data points of energy consumption gathered from schools operating in the eastern province of Saudi Arabia. The factors affecting consumption of energy were identified from two sources. The first was a review of the literature, and the second was interviews with local experts. A sensitivity analysis indicated that the most important factors (i.e., inputs/independent variables) affecting energy consumption (i.e., output) were AC capacity and building age. An investigation of the correlations among the independent variables revealed that the highest correlation of 0.864 was found between the total built area and total roof area. The developed model was validated using 35 new data points of school buildings across the eastern province of Saudi Arabia. The results show that the model predicted the energy consumption of school buildings with an accuracy higher than 90%. The findings of this study will assist schools and maintenance managers in effectively managing such facilities by allowing them to allocate the required budget in advance. Also, the predictions can be used economic lifecycle analysis.
Awsan Mohammed; Adel Alshibani; Othman Alshamrani; Mohammad Hassanain. A regression-based model for estimating the energy consumption of school facilities in Saudi Arabia. Energy and Buildings 2021, 237, 110809 .
AMA StyleAwsan Mohammed, Adel Alshibani, Othman Alshamrani, Mohammad Hassanain. A regression-based model for estimating the energy consumption of school facilities in Saudi Arabia. Energy and Buildings. 2021; 237 ():110809.
Chicago/Turabian StyleAwsan Mohammed; Adel Alshibani; Othman Alshamrani; Mohammad Hassanain. 2021. "A regression-based model for estimating the energy consumption of school facilities in Saudi Arabia." Energy and Buildings 237, no. : 110809.
The unloading of petroleum products is a complex and potentially dangerous operation since the unloading system contains complex interdependency components. Any failures in one of its components lead to a cut in the petroleum supply chain. Therefore, it is important to assess and evaluate the reliability of the unloading system in order to improve its availability. In this context, this paper presents the operation philosophy of the truck unloading system, failure modes of the components within the system, and a bottom-up approach to analyze the reliability of the system. In addition, it provides reliability data, such as failure rates, and mean time between failures of the system components. Furthermore, the reliability of the whole system was calculated and is presented for different time periods. The critical components, which are major contributors towards the system reliability, were identified. To enhance the system reliability, a reliability-based preventive maintenance strategy for the critical components was implemented. In addition, the preventive maintenance scheduling was identified based on the reliability plots of the unloading system. The best schedule for preventive maintenance of the system was determined based on the reliability function to be every 45 days for maintaining the system reliability above 0.9. Findings reveal that the reliability of the unloading system was significantly improved. For instance, the system reliability at one year improved by 80%, and this ratio increased dramatically as the time period increased.
Awsan Mohammed; Ahmed Ghaithan; Mashel Al-Saleh; Khalaf Al-Ofi. Reliability-Based Preventive Maintenance Strategy of Truck Unloading Systems. Applied Sciences 2020, 10, 6957 .
AMA StyleAwsan Mohammed, Ahmed Ghaithan, Mashel Al-Saleh, Khalaf Al-Ofi. Reliability-Based Preventive Maintenance Strategy of Truck Unloading Systems. Applied Sciences. 2020; 10 (19):6957.
Chicago/Turabian StyleAwsan Mohammed; Ahmed Ghaithan; Mashel Al-Saleh; Khalaf Al-Ofi. 2020. "Reliability-Based Preventive Maintenance Strategy of Truck Unloading Systems." Applied Sciences 10, no. 19: 6957.
The need for resilience and an agile waste management system in Saudi Arabia is vital to control safely the rapid growth of its municipal solid waste (MSW) with minimal environment toll. Similarly, the domestic energy production in Saudi Arabia is thriving and putting a tremendous pressure on its huge reserves of fossil oil. Waste to energy (WTE) plants provides a golden opportunity for Saudi Arabia; however, both challenges (MSW mitigation and energy production) are usually looked at in isolation. This paper at first explores the potential of expanding the WTE energy production in the eastern province in Saudi Arabia under two scenarios (complete mass burn with and without recycling). Secondly, this study analyzes the effect of 3Rs (reduce, reuse, recycle) practices implementation in a residential camp (11,000 population) to influence the behavior of the camp’s citizens to reduce their average waste (kg/capita). The results of the 3R-WTE framework show a potential may reach 254 Megawatt (MW) of electricity by year 2030. The 3R system implementation in the camp reduced MSW production from 5,625 tons to 3000 tons of household waste every year, which is considered lower than what the surrounding communities to be produced in the same area.
Laith Hadidi; Ahmed Ghaithan; Awsan Mohammed; Khalaf Al-Ofi. Deploying Municipal Solid Waste Management 3R-WTE Framework in Saudi Arabia: Challenges and Future. Sustainability 2020, 12, 5711 .
AMA StyleLaith Hadidi, Ahmed Ghaithan, Awsan Mohammed, Khalaf Al-Ofi. Deploying Municipal Solid Waste Management 3R-WTE Framework in Saudi Arabia: Challenges and Future. Sustainability. 2020; 12 (14):5711.
Chicago/Turabian StyleLaith Hadidi; Ahmed Ghaithan; Awsan Mohammed; Khalaf Al-Ofi. 2020. "Deploying Municipal Solid Waste Management 3R-WTE Framework in Saudi Arabia: Challenges and Future." Sustainability 12, no. 14: 5711.
This paper proposes a new solution based on tuned-parameter simulated annealing algorithm to obtain near-optimum solutions for solving large multi-objective multi-product supply chain design problem. The selected objective functions are: maximize the total profit, minimize the total supply chain risk, and minimize the supply chain emissions. The characteristics of the algorithm are developed and presented, then coded and tested. Since there is no benchmark available in the existing and state-of-the-art papers, the results acquired by the developed algorithm are compared with the results obtained by an improved augmented ε-constraint algorithm embedded in the General Algebraic Modeling System (GAMS) software for small-scale, medium-scale, and large-scale instances of the multi-objective supply chain problem. The results indicate that the developed simulated annealing algorithm is able to obtain acceptable solutions with reasonable computational time.
Awsan Mohammed; Salih Duffuaa. A Meta-Heuristic Algorithm Based on Simulated Annealing for Designing Multi-Objective Supply Chain Systems. 2019 Industrial & Systems Engineering Conference (ISEC) 2019, 1 -6.
AMA StyleAwsan Mohammed, Salih Duffuaa. A Meta-Heuristic Algorithm Based on Simulated Annealing for Designing Multi-Objective Supply Chain Systems. 2019 Industrial & Systems Engineering Conference (ISEC). 2019; ():1-6.
Chicago/Turabian StyleAwsan Mohammed; Salih Duffuaa. 2019. "A Meta-Heuristic Algorithm Based on Simulated Annealing for Designing Multi-Objective Supply Chain Systems." 2019 Industrial & Systems Engineering Conference (ISEC) , no. : 1-6.