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Dr. Osama Ayadi
The University of Jordan

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0 Energy Efficiency
0 Renewable Energy
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Journal article
Published: 10 July 2021 in Water
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In this research, two identical solar stills were designed and constructed to investigate the effect of adding copper and aluminum oxide nanoparticles on the quantity of water produced by solar desalination. The two solar stills were installed side by side, and measurements were recorded simultaneously from both stills. The nanoparticles were added to one still, each at one time but with different concentrations, while the other contained only water. Data acquisition and a weather station were used to record the glass, water, and ambient temperatures in addition to the hourly solar radiation. It was found that the addition of nanoparticles increases the amount of condensate. The most efficient concentrations were found to be 0.4% of Al2O3 and 0.6% of CuO. At these concentrations, an increase in the efficiency of the still equals 7.8%, and 9.62% was recorded. Furthermore, it was found that CuO has a more pronounced effect on the condensate than Al2O3 at all concentrations except at 0.4% concentration.

ACS Style

Mohammad Hamdan; Anas Al Momani; Osama Ayadi; Ahmad Sakhrieh; Francisco Manzano-Agugliaro. Enhancement of Solar Water Desalination Using Copper and Aluminum Oxide Nanoparticles. Water 2021, 13, 1914 .

AMA Style

Mohammad Hamdan, Anas Al Momani, Osama Ayadi, Ahmad Sakhrieh, Francisco Manzano-Agugliaro. Enhancement of Solar Water Desalination Using Copper and Aluminum Oxide Nanoparticles. Water. 2021; 13 (14):1914.

Chicago/Turabian Style

Mohammad Hamdan; Anas Al Momani; Osama Ayadi; Ahmad Sakhrieh; Francisco Manzano-Agugliaro. 2021. "Enhancement of Solar Water Desalination Using Copper and Aluminum Oxide Nanoparticles." Water 13, no. 14: 1914.

Research article
Published: 03 September 2020 in International Journal of Construction Management
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The construction industry is responsible for many negative environmental impacts that include emissions, waste generation, and the use of land, water, and energy. Most previous construction research attention has focussed on the environmental impacts only for material selection and building operation. Nevertheless, the high electrical demand that comes from the use of construction equipment on-site, mainly tower cranes, is considered a critical component of construction sites that is responsible for a significant volume of CO2 emissions and energy consumption. This research aims to study the feasibility of using photovoltaic (PV) systems to power the electric tower cranes used on construction sites, using as a case study The Mall of the Emirates’ expansion project in Dubai. Two concepts of PV systems were designed to power the seven cranes used on site; one connected (on-grid) and the other as a hybrid PV/Diesel system (off-grid). The results indicated that for both cases the solar systems supplied electricity with competitive costs, and reduced the greenhouse gases by substantial amounts. The results are then generalized for different climatic regions; especially for less solar blessed regions. Finally, managerial and policy implications of the study are discussed.

ACS Style

Rana Imam; Osama Ayadi. Powering electric tower cranes by solar energy for sustainable construction. International Journal of Construction Management 2020, 1 -11.

AMA Style

Rana Imam, Osama Ayadi. Powering electric tower cranes by solar energy for sustainable construction. International Journal of Construction Management. 2020; ():1-11.

Chicago/Turabian Style

Rana Imam; Osama Ayadi. 2020. "Powering electric tower cranes by solar energy for sustainable construction." International Journal of Construction Management , no. : 1-11.

Journal article
Published: 01 September 2020 in Journal of Sustainable Development of Energy, Water and Environment Systems
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ACS Style

Lina Jarrar; Osama Ayadi; Jamil Al Asfar. Techno-economic Aspects of Electricity Generation from a Farm Based Biogas Plant. Journal of Sustainable Development of Energy, Water and Environment Systems 2020, 8, 476 -492.

AMA Style

Lina Jarrar, Osama Ayadi, Jamil Al Asfar. Techno-economic Aspects of Electricity Generation from a Farm Based Biogas Plant. Journal of Sustainable Development of Energy, Water and Environment Systems. 2020; 8 (3):476-492.

Chicago/Turabian Style

Lina Jarrar; Osama Ayadi; Jamil Al Asfar. 2020. "Techno-economic Aspects of Electricity Generation from a Farm Based Biogas Plant." Journal of Sustainable Development of Energy, Water and Environment Systems 8, no. 3: 476-492.

Journal article
Published: 10 August 2020 in International Journal of Energy Economics and Policy
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The use of intermittent power supplies, such as solar energy, has posed a complex conundrum when it comes to the prediction of the next days' supply. There have been several approaches developed to predict the power production using Machine Learning methods, such as Artificial Neural Networks (ANNs). In this work, we propose the use of weather variables, such as ambient temperature, solar irradiation, and wind speed, collected from a weather station of a Photovoltaic (PV) system located in Amman, Jordan. The objective is to substitute the aforementioned ambient temperature with the more realistic PV cell temperature with a desire of achieving better prediction results. To this aim, ten physics-based models have been investigated to determine the cell temperature, and those models have been validated using measured PV cell temperatures by computing the Root Mean Square Error (RMSE). Then, the model with the lowest RMSE has been adopted in training a data-driven prediction model. The proposed prediction model is to use an ANN compared to the well-known benchmark model from the literature, i.e., Multiple Linear Regression (MLR). The results obtained, using standard performance metrics, have displayed the importance of considering the cell temperature when predicting the PV power output. Keywords: Renewable Energy, Photovoltaic, Prediction, Cell temperature, Multiple Linear Regression, Artificial Neural Networks.JEL Classifications: C53, Q47.DOI: https://doi.org/10.32479/ijeep.9533

ACS Style

Sameer Al-Dahidi; Salah Al-Nazer; Osama Ayadi; Shuruq Shawish; Nahed Omran. ANALYSIS OF THE EFFECTS OF CELL TEMPERATURE ON THE PREDICTABILITY OF THE SOLAR PHOTOVOLTAIC POWER PRODUCTION. International Journal of Energy Economics and Policy 2020, 10, 208 -219.

AMA Style

Sameer Al-Dahidi, Salah Al-Nazer, Osama Ayadi, Shuruq Shawish, Nahed Omran. ANALYSIS OF THE EFFECTS OF CELL TEMPERATURE ON THE PREDICTABILITY OF THE SOLAR PHOTOVOLTAIC POWER PRODUCTION. International Journal of Energy Economics and Policy. 2020; 10 (5):208-219.

Chicago/Turabian Style

Sameer Al-Dahidi; Salah Al-Nazer; Osama Ayadi; Shuruq Shawish; Nahed Omran. 2020. "ANALYSIS OF THE EFFECTS OF CELL TEMPERATURE ON THE PREDICTABILITY OF THE SOLAR PHOTOVOLTAIC POWER PRODUCTION." International Journal of Energy Economics and Policy 10, no. 5: 208-219.

Journal article
Published: 06 February 2020 in Geothermics
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A new system consisting of photovoltaic thermal-ground source heat pump (PV/T-GSHP) was proposed as a solution for electricity shortage and high electricity consumption in heating buildings in Jordan. The performances of the photovoltaic system and the ground source heat pump system were studied without coupling as in real life and with coupling in a hybrid system using TRNSYS software. The results show that this PV/T-GSHP hybrid system can reduce the photovoltaic panels' temperature by more than 20 °C, and improve the efficiency of electricity production by 9.5 %, simultaneously. And in heating season the average coefficient of performance of the heat pumps increased from 4.6 to 6.2 with a decreament in electricity consumption by 25.7 %. The life cycle cost of the hybrid system decreased by 3.9 % and the net present value inceased by 13.2 % compared to the two systems separated. The model of the PV/T-GSHP system was established using TRNSYS software, an optimmization was made to select the photovoltaic modules' temperature at which cooling starts, followed by technical and economical studies on both systems separated and coupled in a hybrid system. This hybrid system can provide guidance for future related project.

ACS Style

Mohammad Abu-Rumman; Mohammad Hamdan; Osama Ayadi. Performance enhancement of a photovoltaic thermal (PVT) and ground-source heat pump system. Geothermics 2020, 85, 101809 .

AMA Style

Mohammad Abu-Rumman, Mohammad Hamdan, Osama Ayadi. Performance enhancement of a photovoltaic thermal (PVT) and ground-source heat pump system. Geothermics. 2020; 85 ():101809.

Chicago/Turabian Style

Mohammad Abu-Rumman; Mohammad Hamdan; Osama Ayadi. 2020. "Performance enhancement of a photovoltaic thermal (PVT) and ground-source heat pump system." Geothermics 85, no. : 101809.

Journal article
Published: 01 January 2020 in Thermal Science
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It has been shown that using fuel additives play an important role in enhancing the combustion characteristics in terms of efficiency and emissions. In addition, free piston engines have shown capable in reducing energy losses and presenting more efficient and reliable engines. In this context, the objective of the present work is to investigate the effect of using hydrogen as a fuel additive in natural gas homogeneous charge compression ignition free piston engine. To this aim, two models have been iteratively coupled: the combustion model that is used to calculate the heat release of the combustion and the scavenging model that is employed to determine the in-cylinder mixture state after scavenging in terms of its homogeneity and species mass fractions and to obtain the finial pressure and temperature of the in-cylinder mixture. In the former model, the 0-D approach through Cantera toolkit has been considered due to the fact that homogeneous charge compression ignition combustion is very rapid and the fuel-air mixture is well-homogenous, whereas in the latter model, 3-D-CFD approach through AN-SYS FLUENT software is considered to ensure precise calculations of the species exchange at the end of each engine cycle. The effect of hydrogen as a fuel additive has been quantified in terms of the combustion characteristics (e. g., ignition delay, heat release rate, engine overall efficiency and emissions, etc.). It has been shown that hydrogen addition reduces ignition delay time, decreases the in-cylinder peak pressure, while allowing the engine to operate with higher mechanical efficiency as it has high heat release rate, increases the NOx emission levels of the engine, but decreases the CO levels

ACS Style

Mohammad Alrbai; Bashar R. Qawasmeh; Sameer Al-Dahidi; Osama Ayadi. Influence of hydrogen as a fuel additive on combustion and emissions characteristics of a free piston engine. Thermal Science 2020, 24, 87 -99.

AMA Style

Mohammad Alrbai, Bashar R. Qawasmeh, Sameer Al-Dahidi, Osama Ayadi. Influence of hydrogen as a fuel additive on combustion and emissions characteristics of a free piston engine. Thermal Science. 2020; 24 (1 Part A):87-99.

Chicago/Turabian Style

Mohammad Alrbai; Bashar R. Qawasmeh; Sameer Al-Dahidi; Osama Ayadi. 2020. "Influence of hydrogen as a fuel additive on combustion and emissions characteristics of a free piston engine." Thermal Science 24, no. 1 Part A: 87-99.

Original research article
Published: 15 November 2019 in Frontiers in Energy Research
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The capability of accurately predicting the Solar Photovoltaic (PV) power productions is crucial to effectively control and manage the electrical grid. In this regard, the objective of this work is to propose an efficient Artificial Neural Network (ANN) model in which 10 different learning algorithms (i.e., different in the way in which the adjustment on the ANN internal parameters is formulated to effectively map the inputs to the outputs) and 23 different training datasets (i.e., different combinations of the real-time weather variables and the PV power production data) are investigated for accurate 1 day-ahead power production predictions with short computational time. In particular, the correlations between different combinations of the historical wind speed, ambient temperature, global solar radiation, PV power productions, and the time stamp of the year are examined for developing an efficient solar PV power production prediction model. The investigation is carried out on a 231 kWac grid-connected solar PV system located in Jordan. An ANN that receives in input the whole historical weather variables and PV power productions, and the time stamp of the year accompanied with Levenberg-Marquardt (LM) learning algorithm is found to provide the most accurate predictions with less computational efforts. Specifically, an enhancement reaches up to 15, 1, and 5% for the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Coefficient of Determination (R2) performance metrics, respectively, compared to the Persistence prediction model of literature.

ACS Style

Sameer Al-Dahidi; Osama Ayadi; Jehad Adeeb; Mohamed Louzazni. Assessment of Artificial Neural Networks Learning Algorithms and Training Datasets for Solar Photovoltaic Power Production Prediction. Frontiers in Energy Research 2019, 7, 1 .

AMA Style

Sameer Al-Dahidi, Osama Ayadi, Jehad Adeeb, Mohamed Louzazni. Assessment of Artificial Neural Networks Learning Algorithms and Training Datasets for Solar Photovoltaic Power Production Prediction. Frontiers in Energy Research. 2019; 7 ():1.

Chicago/Turabian Style

Sameer Al-Dahidi; Osama Ayadi; Jehad Adeeb; Mohamed Louzazni. 2019. "Assessment of Artificial Neural Networks Learning Algorithms and Training Datasets for Solar Photovoltaic Power Production Prediction." Frontiers in Energy Research 7, no. : 1.

Journal article
Published: 01 October 2019 in Journal of Ecological Engineering
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As renewable energy application is gaining a wide acceptance by end users while considering the fact that renewable energy is intermittent, variable and cannot be expected; the need of storage systems is becoming a necessity at both micro and macro levels. Fuel cell technology is one of the most...

ACS Style

Wala' Nsour; Tamara Taa'Mneh; Osama Ayadi; Jamil AlAsfar. Design of Stand-Alone Proton Exchange Membrane Fuel Cell Hybrid System under Amman Climate. Journal of Ecological Engineering 2019, 20, 1 -10.

AMA Style

Wala' Nsour, Tamara Taa'Mneh, Osama Ayadi, Jamil AlAsfar. Design of Stand-Alone Proton Exchange Membrane Fuel Cell Hybrid System under Amman Climate. Journal of Ecological Engineering. 2019; 20 (9):1-10.

Chicago/Turabian Style

Wala' Nsour; Tamara Taa'Mneh; Osama Ayadi; Jamil AlAsfar. 2019. "Design of Stand-Alone Proton Exchange Membrane Fuel Cell Hybrid System under Amman Climate." Journal of Ecological Engineering 20, no. 9: 1-10.

Journal article
Published: 20 June 2019 in IEEE Access
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The use of data-driven ensemble approaches for the prediction of the solar Photovoltaic (PV) power production is promising due to their capability of handling the intermittent nature of the solar energy source. In this work, a comprehensive ensemble approach composed by optimized and diversified Artificial Neural Networks (ANNs) is proposed for improving the 24h-ahead solar PV power production predictions. The ANNs are optimized in terms of number of hidden neurons and diversified in terms of the diverse training datasets used to build the ANNs, by resorting to trial-and-error procedure and BAGGING techniques, respectively. In addition, the Bootstrap technique is embedded to the ensemble for quantifying the sources of uncertainty that affect the ensemble models’ predictions in the form of Prediction Intervals (PIs). The effectiveness of the proposed ensemble approach is demonstrated by a real case study regarding a gridconnected solar PV system (231 kWac capacity) installed on the rooftop of the Faculty of Engineering at the Applied Science Private University (ASU), Amman, Jordan. Results show that the proposed approach outperforms three benchmark models, including smart persistence model and single optimized ANN model currently adopted by the PV system’s owner for the prediction task, with a performance gain reaches up to 11%, 12%, and 9%, for RMSE, MAE, and WMAE standard performance metrics, respectively. Simultaneously, the proposed approach has shown superior in quantifying the uncertainty affecting the power predictions, by establishing slightly wider PIs that achieve the highest confidence level reaches up to 84% for a predefined confidence level of 80% compared to three other approaches of literature. These enhancements would, indeed, allow balancing power supplies and demands across centralized grid networks through economic dispatch decisions between the energy sources that contribute to the energy mix.

ACS Style

Sameer Al-Dahidi; Osama Ayadi; Mohammed Alrbai; Jihad Adeeb. Ensemble Approach of Optimized Artificial Neural Networks for Solar Photovoltaic Power Prediction. IEEE Access 2019, 7, 81741 -81758.

AMA Style

Sameer Al-Dahidi, Osama Ayadi, Mohammed Alrbai, Jihad Adeeb. Ensemble Approach of Optimized Artificial Neural Networks for Solar Photovoltaic Power Prediction. IEEE Access. 2019; 7 (99):81741-81758.

Chicago/Turabian Style

Sameer Al-Dahidi; Osama Ayadi; Mohammed Alrbai; Jihad Adeeb. 2019. "Ensemble Approach of Optimized Artificial Neural Networks for Solar Photovoltaic Power Prediction." IEEE Access 7, no. 99: 81741-81758.

Journal article
Published: 19 June 2019 in Solar Energy
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Solar thermal and Photovoltaic (PV) systems can save significant amount of non-renewable energy that are utilized to satisfy the energy services for buildings. The falling prices of PV in recent years increased the attractiveness of PV systems. The purpose of this research is to develop a systematic methodology for fair technical and economical comparison of reference and solar assisted systems. For this reason, the annual energy requirements for heating, cooling and DHW for a selected dormitory building under five representative climatic conditions were evaluated using the Hourly Analysis Program (HAP). At the same time, solar thermal and PV systems have been designed and simulated for the same building using Sketchup, Trnsys and PVsyst. Finally, a systematic comparison between the solar systems and five conventional systems have been carried out in terms of primary energy ratio, and Levelized Cost Of Energy (LCOE). For the case of Amman, solar thermal and electric systems achieved a non-renewable primary energy savings of 29% and 100%, respectively, whereas, they achieved LCOE savings of 15% and 62%, respectively compared to the best conventional system. The selection of the best solution for a given project requires a full understanding of the system performance and the interaction of its components rather than the technology efficiency only. This system performance depends on the building envelope, load patterns, availability of solar radiation, roof area availability, energy prices, and policies. Thus, a case-by-case analysis should be done for each project in each climatic region.

ACS Style

Osama Ayadi; Sameer Al-Dahidi. Comparison of solar thermal and solar electric space heating and cooling systems for buildings in different climatic regions. Solar Energy 2019, 188, 545 -560.

AMA Style

Osama Ayadi, Sameer Al-Dahidi. Comparison of solar thermal and solar electric space heating and cooling systems for buildings in different climatic regions. Solar Energy. 2019; 188 ():545-560.

Chicago/Turabian Style

Osama Ayadi; Sameer Al-Dahidi. 2019. "Comparison of solar thermal and solar electric space heating and cooling systems for buildings in different climatic regions." Solar Energy 188, no. : 545-560.

Journal article
Published: 11 October 2018 in Energies
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The unpredictability of intermittent renewable energy (RE) sources (solar and wind) constitutes reliability challenges for utilities whose goal is to match electricity supply to consumer demands across centralized grid networks. Thus, balancing the variable and increasing power inputs from plants with intermittent energy sources becomes a fundamental issue for transmission system operators. As a result, forecasting techniques have obtained paramount importance. This work aims at exploiting the simplicity, fast computational and good generalization capability of Extreme Learning Machines (ELMs) in providing accurate 24 h-ahead solar photovoltaic (PV) power production predictions. The ELM architecture is firstly optimized, e.g., in terms of number of hidden neurons, and number of historical solar radiations and ambient temperatures (embedding dimension) required for training the ELM model, then it is used online to predict the solar PV power productions. The investigated ELM model is applied to a real case study of 264 kWp solar PV system installed on the roof of the Faculty of Engineering at the Applied Science Private University (ASU), Amman, Jordan. Results showed the capability of the ELM model in providing predictions that are slightly more accurate with negligible computational efforts compared to a Back Propagation Artificial Neural Network (BP-ANN) model, which is currently adopted by the PV system owners for the prediction task.

ACS Style

Sameer Al-Dahidi; Osama Ayadi; Jehad Adeeb; Mohammad Alrbai; Bashar R. Qawasmeh. Extreme Learning Machines for Solar Photovoltaic Power Predictions. Energies 2018, 11, 2725 .

AMA Style

Sameer Al-Dahidi, Osama Ayadi, Jehad Adeeb, Mohammad Alrbai, Bashar R. Qawasmeh. Extreme Learning Machines for Solar Photovoltaic Power Predictions. Energies. 2018; 11 (10):2725.

Chicago/Turabian Style

Sameer Al-Dahidi; Osama Ayadi; Jehad Adeeb; Mohammad Alrbai; Bashar R. Qawasmeh. 2018. "Extreme Learning Machines for Solar Photovoltaic Power Predictions." Energies 11, no. 10: 2725.

Journal article
Published: 01 May 2018 in Sustainable Cities and Society
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The high electricity consumption and cost at the University of Jordan has motivated the university to adopt a renewable energy and energy efficiency as one of its strategic objectives for the coming decade. The university has set forth an ambitious goal to achieve 100% electrical energy independence, relying mainly on renewable solar energy using photovoltaic (PV) panels. This study investigates different technical solutions of the grid connected solar PV system; fixed, single-axis and double–axis tracking PV modules. Moreover, two engineering models for the construction of such a project have been investigated; the Build Operate Transfer (BOT) model and the Engineering Procurement Construction (EPC) engineering model. The performance analysis was conducted in terms of final yield, land use and conversion efficiency, while the economic analysis investigates the simple payback period and internal rate of return. The simulation was carried out using a Trnsys model that has been experimentally validated by the authors. It was found that the most attractive choice is the EPC model using the fixed PV system for installation with 32% internal rate of return (IRR) and 3 years payback period. The required system size was 15030 kWp, with an estimated area of 150 thousand squared meters.

ACS Style

Osama Ayadi; Rami Al-Assad; Jamil Al Asfar. Techno-economic assessment of a grid connected photovoltaic system for the University of Jordan. Sustainable Cities and Society 2018, 39, 93 -98.

AMA Style

Osama Ayadi, Rami Al-Assad, Jamil Al Asfar. Techno-economic assessment of a grid connected photovoltaic system for the University of Jordan. Sustainable Cities and Society. 2018; 39 ():93-98.

Chicago/Turabian Style

Osama Ayadi; Rami Al-Assad; Jamil Al Asfar. 2018. "Techno-economic assessment of a grid connected photovoltaic system for the University of Jordan." Sustainable Cities and Society 39, no. : 93-98.

Journal article
Published: 01 March 2018 in Journal of Ecological Engineering
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This research investigates the hybrid CSP-Wind system plant. The model aims to reduce the problem of instability at the grid power output. This instability is caused by the renewable energy sources penetration. Increased penetration of solar energy at the grid power output will result in a high...

ACS Style

Osama Ayadi; Ishraq Alsalhen. Techno-Economic Assessment of Concentrating Solar Power and Wind Hybridization in Jordan. Journal of Ecological Engineering 2018, 19, 16 -23.

AMA Style

Osama Ayadi, Ishraq Alsalhen. Techno-Economic Assessment of Concentrating Solar Power and Wind Hybridization in Jordan. Journal of Ecological Engineering. 2018; 19 (2):16-23.

Chicago/Turabian Style

Osama Ayadi; Ishraq Alsalhen. 2018. "Techno-Economic Assessment of Concentrating Solar Power and Wind Hybridization in Jordan." Journal of Ecological Engineering 19, no. 2: 16-23.

Proceedings article
Published: 01 March 2017 in 2017 8th International Renewable Energy Congress (IREC)
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Several challenges affect solar PV (Photovoltaic) integration with Jordan electricity grid. Major challenges are PV power variability, uncertainty and constructing new transmission lines on unqualified grid. Conventional plants consume fuel to export the electricity to the grid and to the in-house load which requires, in average, 1.6~7.8% from plant generated energy. This study aims to propose new method to indirectly integrate PV with the grid through conventional plants (Hybrid Model). The model consists of conventional power generation and PV plant. During solar radiation availability in-house load is fed from solar field, otherwise part of generated energy will be consumed by internal load. PV SYST 6.40 program was used to simulate a grid connected PV system (8 MWp) equal to the PV system capacity proposed for the hybrid model in the case study. The technical constraints and the economic performance in win-win scenarios were studied and compared. No technical constraints were found and the economic evaluation results of the PV system proposed for the hybrid model showed more attractive investment for Power Producers to install PV system in hybrid scheme (13.2%-IRR, 7 years pay-back period and 16,841,528 USD NPV) against gird-connected PV system (9.9%-IRR, 9 years pay-back period and 12,120,193 USD NPV). Avoided cost for transmission line and fuel saving when applying hybrid model counted as 2,095,000 USD and 782,248 USD/year respectively. Finally, applying hybrid model to operational plants in Jordan would result in 151 MWp PV integrated to the grid with Zero transmission cost.

ACS Style

Ahmad Al Omari; Osama Ayadi. Integrating solar PV with the electricity grid through conventional power plants. 2017 8th International Renewable Energy Congress (IREC) 2017, 1 -6.

AMA Style

Ahmad Al Omari, Osama Ayadi. Integrating solar PV with the electricity grid through conventional power plants. 2017 8th International Renewable Energy Congress (IREC). 2017; ():1-6.

Chicago/Turabian Style

Ahmad Al Omari; Osama Ayadi. 2017. "Integrating solar PV with the electricity grid through conventional power plants." 2017 8th International Renewable Energy Congress (IREC) , no. : 1-6.

Proceedings article
Published: 01 March 2017 in 2017 8th International Renewable Energy Congress (IREC)
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This paper assesses the economic sides of a grid-connected PV system based on a validated model and the feed in tariff regulation in Jordan. The economic model was built based on a calibrated design model at previous work for authors. An economic analysis is conducted based on a proposed PV plant to cover the Jordan University needs of electricity, considering the Engineering Procurement Construction (EPC) and the Build-operate-transfer (BOT) engineering models and three different sun tracking methods. The analysis showed that the most feasible choice is EPC model using the fixed tracking method. The IRR was 34.4% and a simple payback period of 2.86 years.

ACS Style

Rami Al-Assad; Osama Ayadi. Techno-economic assessment of grid connected photovoltaic systems in Jordan. 2017 8th International Renewable Energy Congress (IREC) 2017, 1 -5.

AMA Style

Rami Al-Assad, Osama Ayadi. Techno-economic assessment of grid connected photovoltaic systems in Jordan. 2017 8th International Renewable Energy Congress (IREC). 2017; ():1-5.

Chicago/Turabian Style

Rami Al-Assad; Osama Ayadi. 2017. "Techno-economic assessment of grid connected photovoltaic systems in Jordan." 2017 8th International Renewable Energy Congress (IREC) , no. : 1-5.

Journal article
Published: 31 December 2012 in Energy Procedia
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The objective of this review article is to draw a picture about a promising solar cooling concept, based on the use of concentrating solar collectors, and to define the aspects that need to be considered in future developments. The following topics are covered: an overview of solar cooling systems utilizing concentrating solar collectors worldwide; the reasons behind the selection of these solar collection technologies for solar cooling applications; a quick assessment of the main performance figures for the different solar cooling schemes based on Monte Carlo simulations; the technical requirements of the technologies for future developments. Air-conditioning and refrigeration facilities driven by concentrating solar collectors are still infrequent and the outcomes of this review clearly present the small but steadily growing market of solar cooling systems coupled with concentrating solar collection technologies.

ACS Style

Osama Ayadi; Marcello Aprile; Mario Motta. Solar Cooling Systems Utilizing Concentrating Solar Collectors - An Overview. Energy Procedia 2012, 30, 875 -883.

AMA Style

Osama Ayadi, Marcello Aprile, Mario Motta. Solar Cooling Systems Utilizing Concentrating Solar Collectors - An Overview. Energy Procedia. 2012; 30 ():875-883.

Chicago/Turabian Style

Osama Ayadi; Marcello Aprile; Mario Motta. 2012. "Solar Cooling Systems Utilizing Concentrating Solar Collectors - An Overview." Energy Procedia 30, no. : 875-883.

Journal article
Published: 31 December 2012 in Energy Procedia
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The availability of solar radiation in phase with the seasonal as well as hourly cooling load profiles in most of the office buildings in the Mediterranean region, in addition to the large share of primary energy consumed for air- conditioning applications in office buildings create a high motivation for the utilization of solar cooling technology for such type of buildings. A solar heating and cooling system for an office building in Italy has been designed, installed and monitored within the framework of the EC co-funded project SOLERA aiming at developing highly integrated solar thermal heating and cooling system that is able to achieve a high solar fraction both for the heating and cooling seasons. The analysis of the system performance during 2011 is presented in this paper, with main focus on electricity consumption during summer. The analysis has been carried out according to the monitoring procedure developed within the frame of the IEA SHC Task 38.

ACS Style

Osama Ayadi; Alberto Mauro; Marcello Aprile; Mario Motta. Performance assessment for solar heating and cooling system for office building in Italy. Energy Procedia 2012, 30, 490 -494.

AMA Style

Osama Ayadi, Alberto Mauro, Marcello Aprile, Mario Motta. Performance assessment for solar heating and cooling system for office building in Italy. Energy Procedia. 2012; 30 ():490-494.

Chicago/Turabian Style

Osama Ayadi; Alberto Mauro; Marcello Aprile; Mario Motta. 2012. "Performance assessment for solar heating and cooling system for office building in Italy." Energy Procedia 30, no. : 490-494.