Search

Landfills have high potency as renewable energy sources by producing biogas from organic waste degradation. Landfills biogas (LFG) can be used for power plant purposes instead of allowing it to flare to the atmosphere which contributes to the global warming. The aim of this work was to introduce and examine an optimization model for maximizing the power generation of Al Ghabawi landfill in Amman city, Jordan. The optimization process focused on studying the effect of several operating parameters within the landfill power plant. To achieve this goal, a combustion model had been built and validated against a set of historical real data obtained from the landfill operator. In addition to that, an Artificial Neural Network (ANN) model had been built to perform a multi-objective optimization to obtain the optimal power generation conditions for Al Ghabawi landfill. The combustion model along with the ANN model aim to estimate the best engine operating conditions based on the actual daily data of the landfill. The engine operating parameters includes the intake pressure and temperature, the ignition time and the equivalence ratio. The results of the study indicate that the current operating parameters can be optimized to maximize the gensets power generation. Based on the daily data of the produced LFG, the optimal operating conditions for the landfill are 2.32 bar for the intake pressure, 303 K for the intake temperature, 0.9-1.0 for the equiveillance ratio and for the ignition time it is 13 degrees before the top dead center (BTDC). These optimized operating parameters can maximize the landfill power generation by at least 1 MW for each genset.

In this study, single and aggregated forecasters of half-hourly global horizontal irradiance are assessed. The models are the standard persistent model and four newly proposed static, dynamic, moving average, and amplified persistent models. These sub-forecasters are aggregated using equal, annual optimal, and monthly optimal weights. A particle swarm optimizer was used to find those weights. Measured data, obtained from two desert sites for the years 2015–2018, was used for fitting and training the different models, while the data of the year 2019 was used to test their prediction capabilities. For the single forecasters, the dynamic model is the most accurate, followed by the static and average models. When the aggregated model of annual optimal weights was tested, the three contributing forecasters were the dynamic, average, and amplified models. The dynamic forecaster held the largest weight due to its prediction superiority during overcast and partially cloudy days. When monthly optimal weights were used, all forecasters contributed, and the dynamic model held the largest weight during winter but not in the summer when the clear sky condition is dominant. The aggregated model was the most precise, with relative mean square errors lower than 15.0% and coefficients of determination higher than 98.8%.

The paper aims to solve drawbacks associated with Gas Turbine GT by integrating a novel cascaded system into a combined cycle simultaneously. Parabolic trough collectors preheat the air at the combustion chamber inlet, then drive an absorption inlet-air cooling cycle that controls the ambient-air temperature at the compressor's inlet. This study uses the 2nd law of thermodynamics to estimate the maximum available energy, calculate the electric exergy efficiency, and explore the maximum irreversible exergy destruction in the system's components. Artificial Neural Network was employed to develop a multi-objective optimization by linking data collected from equations in the Engineering Equation Solver software with Matlab. Spider diagrams investigated the effect of varying several key operating parameters on the performance of the system, identifying gas turbine as the highest irreversibility sub-unit and the solar field parabolic trough collectors as the second. Design improvement for the combustion chamber can reduce 303.6 MW, and for parabolic trough collectors field reduce 58.9 MW. Artificial neural networks with multi-objective optimization maximized the electric exergy destruction to 46.19% and minimized the exergy destruction to 489.4 MW, relative to the corresponding values from the simple design point.

The increasing demand for gas turbines motivates the need to improve their performance and reduce the associated exhaust pollutants. Steam injection is an effective technique for boosting p...

Batteries are often used to overcome the intermittency of renewable energy resources, which are associated with tremendous metal depletion, environmental impact, and human health hazards. Thermal energy storage (TES) systems are often disregarded in such large-scale plans for producing electricity directly due to the losses encountered in the conversion process. In this work, however, we show, using Jordan as a case study, that the integration of TES with renewable energy systems to cover the demand is indeed feasible, and such an integration can cover 100% of the energy demand. Six different configurations were used to conduct this analysis, namely Photovoltaic (PV)-TES, PV-wind-TES, PV-concentrated solar power (CSP)-TES, PV-CSP-wind-TES, PV-CSP-Li-ion battery, and finally, PV-CSP-wind-Li-ion battery. The simulation was optimized to scan all of Jordan searching for the installation sites of the highest demand-supply matching and, at the same time, the lowest levelized cost of electricity. The optimal systems’ techno-economic parameters were then extracted and compared, showing that the integration of TES to renewable power generation systems is not only feasible and can cover 100% of the demand, but also can offset the huge need for the more common but perilous alternative, i.e., the Li-ion batteries and their associated metal depletions and hazards.

Live foliage for some tree and shrub species can support flaming fire spread at much higher moisture content than dead fuel materials. However, the role of live fuels in forest fires has been controversial in the past decades. Although ignition and spread statistical data for live and dead fuels exist in the literature, a clear understanding of the fundamental difference in the burning behavior is missing. To illuminate the role of live fuel on forest fire spreading, a laboratory ignition experiment was designed to examine the burning behavior of live Norway spruce needles. A Schlieren-Infrared combined measurement apparatus was developed with a spatial resolution of 0.75 mm and a time resolution of 0.0025 s, to visualize/measure the ignition behavior of live fuels. Schlieren and IR images revealed that the ejection of live fuel volatiles can alter the flame direction and induce previously unaccounted heating of the nearby fuel. Depending on the conditions, these interferences could heat and modify the heat flux received by the adjacent fuels. To analyze each of these outcomes, a scaling analysis using the law approach was performed. First, theoretical equations were developed and validated against a set of previously published experimental data. After the characteristic equations were verified, we used them to assess the volatile ejection phenomenon. We found that adjacent fuels were preheated by hot volatiles ejected from the heated live needle, and direct flame contact ignited the adjacent fuels. Our IR experiments confirmed the outcomes of the scaling analysis. The rapid ejection of volatiles was also found to propel burning needles far from the burning branch, resulting in micro-spotting.

In this study, the Al-Qatrana powerplant of Jordan, comprising a combined cycle, was integrated with a proposed solar power and thermal energy storage system. This study aims to conduct a comprehensive transient analysis and introduce an operating methodology for the smooth transition between the different system’s operating modes. First, a comparison between the conventional powerplant and the proposed system was presented. Results showed that the integration could lead to a 41 MW improvement in output power, a 10.2 % increase in efficiency, and a 9.2 % relative decrease in SFC at design conditions. After that, shaving the summer peak load of the year 2040 using the proposed system was investigated, following the Jordanian National Electric Power Company vision, where the existing plant will be incapable of coping with the load demand. Hence, the solar and storage systems were utilized to boost the plant’s power. The system was able to meet the 2040 summer peak load and overcome the challenges that stem from the dynamic nature of the load demand and the solar radiation availability. Finally, a feasibility analysis was conducted, the results showed that the return of investment period is 8.58 years, which is encouraging.

The incorporation of energy storing units into hybrid systems reallocates the excess electricity to meet demand requirements in the deficiency periods. This study seeks to determine the optimal size of a Photovoltaic (PV)/wind/biomass hybrid system with and without energy storage built on the base of boosting the demand–supply fraction ( DSF ) and the renewable energy fraction (FR) with a net present value larger than or equals to zero. The Generalized Reduced Gradient algorithm has been utilized in this study to evaluate the optimal components’ capacities of the proposed system. Middle East Technical University Northern Cyprus Campus was used as a case study. The proposed system consists of 1.79 MW PV, 2 MW wind and 0.92 MW biomass systems with 24.39 MWh pumped hydro storage system and 148.64 kWh batteries achieving FR of 99.59%, DSF of 98.86%, and a cost of electricity equals to 0.1626 $/kWh. The simulations results proved that the integration of a hybrid energy storage system with the PV/wind/biomass system ensures very high autonomy approaching almost 99%. Finally, considering the significant excess energy produced by the tri-hybrid system, this excess could also be allocated towards meeting the campus’s thermal and domestic hot water demands creating a polygeneration power system.

In this study, we evaluated the fundamental physical behavior during droplet formation and flow from a rotary bell spray in the absence of an electrostatic field. The impact of a wide range of operating parameters of the rotary bell sprayer, such as flow rates, rotational speeds, and spatial positioning, on droplet sizes and size distributions using a three-dimensional (3-D) mapping was studied. The results showed that increasing the rotational speed caused the Sauter mean diameter of the droplets to decrease while increasing flow rate increased the droplet sizes. The rotational speed effect, however, was dominant compared to the effect of flow rate. An increase in droplet size radially away from the cup was noted in the vicinity of the cup, nevertheless, as the lateral distances from the cup and rotational speed were increased, the droplet sizes within the flow field became more uniform. This result is of importance for painting industries, which are looking for optimal target distances for uniform painting appearance. Furthermore, the theoretical formulation was validated with experimental data, which provides a wider range of applicability in terms of environment and parameters that could be tested. This work also provides an abundance of measurements, which can serve as a database for the validation of future droplet disintegration simulations.

When planning for the transition to 100% renewable grids, areas of high solar-insolation or wind energy are often looked at as alluring sites for installation to match a country’s hourly or total demand. Due to the intermittent nature of renewable energies that generate a supply–demand mismatch, this often required relatively large energy-storage systems. In this work, however, we show using Jordan as a case study, and through comparison to previous designs, that a single high-potential-site system is devious, and optimization of multiple sites to simultaneously feed into the grid can lead to a much higher renewable energy system (RES) fraction (>99%) even without storage systems; a result of utilizing the superposition of the varying energy-supply profiles at different sites to match the demand profile. Multi-objective optimization was performed using the global ParetoSearch algorithm, with RES and demand–supply fractions (DSF) on one hand, and the Levelized Cost of electricity on the other hand as a conflicting objective. Results showed that a hybrid solar-wind system optimized at multiple locations can supply 99% of the hourly demand in Jordan, forecasted for the year 2050 without an energy storage system (ESS). Additionally, the size of the RES without ESS is reduced by almost 16% when multiple sites were used compared to a single high potential location, with better matching of 99.33%. Even with an energy storage system, multiple locations led to a 14% reduction in the RES size and almost three folds reduction in ESS size compared to the single location approach.

Many developing countries like Jordan, suffer from the lack of natural resources required to supply their energy demand. As such, maximum utilization of the available energy and renewable resources becomes a necessity. ALQatrana powerplant in Jordan; operating on a combined cycle suffers from sensitivity to ambient air temperatures and the lack of full utilization of waste heat of the flue gas. In this work, the plant was simulated using the engineering equation solver, and the simulation was validated against the actual powerplant data. A cascade of absorption and mechanical chillers for inlet air cooling, along with a CSP system were proposed. These auxiliary systems were also simulated and validated against literature, then integrated with the actual power plant cycle. Results showed that using the hybrid system for inlet air cooling with a combined cycle, can be more appealing in terms of power boosting and economical profit, compared to using either alone. The proposed system showed a relative increase in power by 22.8%, a 4.3% increased efficiency, and a relative decrease in SFC by 8.4%, compared to the actual power plant. Moreover, due to the hybrid inlet air cooling unit, the system exhibited low sensitivity to variation in ambient temperatures; hence, a stable power augmentation with relative change of only 0.9% over the range of temperatures (10–50) ℃. Additionally, compared to a duct burner integration, the proposed system, led to 6.4 million dollars annual saving in fuel consumption, with a 15% less CO2 emission for equivalent power production. A comprehensive feasibility study was also performed; showing a return of investment period equal to 5.3 years, which is very promising.

This study introduces the design of a novel condenser for air conditioning systems. Enhancement of performance of the system was manifested by increasing the coefficient of performance (COP), decreasing the pressure drop and the power consumed by the refrigerant compressor and the cooling water pump. The design consists of an adiabatic double-pipe heat exchanger with longitudinal rectangular fins. This model can enhance heat transfer coefficient and expose more area per unit length. This novel design supersedes other conventional condenser designs by 4.7% higher COP, 8.2% lower water pressure drop, 4.68% lower compressor power. Two refrigerants have been examined in the study; R-134a which is used in commercial and industrial chillers and R-1234ze which has low global warming potential.

Electrostatic rotary bell sprayers (ERBSs) are widely used in the automotive industry. In ERBS, atomization is facilitated using centrifugal forces which disintegrate the paint film inside the cup into droplets at the cup edge. The droplets are then transported by the flow of a shaping air (SA) and electrostatic forces to a target surface, the characteristics of these droplets dramatically influence the quality of a painted surface and the painting transfer efficiency. In the current paper, a novel Schlieren-based visualization of the shaping air in the absence of paint droplets was performed during a qualitative investigation to delineate shaping air flow behavior and its interaction with droplets and droplet transport. An infrared thermographic flow visualization (IRFV) method and droplet size measurement were used to complement the Schlieren data for providing insight into shaping air-droplet interactions. The results demonstrated the impact of different operating conditions on the SA flow pattern, and the influence SA has on the secondary atomization and transport of droplets. Hence, these experimental methods combine with a useful tool for optimizing SA configurations that improve spray quality, droplet transport, and the efficiency of ERBS operations.

Electrostatic Rotary bell (ESRB) atomizers are used as the dominant means of paint application by the automotive industry. They utilize the high rotational speed of a cup to induce primary atomization of a liquid along with shaping air to provide secondary atomization and transport. In order to better understand the fluid breakup mechanisms involved in this process, high-speed shadowgraph imaging was used to visualize the edge of a serrated rotary bell at speeds varying between 5000 and 12,000 RPM and with a water flow rate of 250 ccm. A multi-step image processing algorithm was developed to differentiate between ligaments and droplets during the primary atomization process. The results from this experiment showed that higher bell speeds resulted in a 26.8% reduction in ligament and 22.3% reduction in droplet Sauter Mean Diameters (SMD). Additionally, the ligament (ranging from 40 to 400 μm) diameters formed bimodal distributions, while the droplet (ranging from 40 to 300 μm) diameters formed a normal distribution. Velocities were also measured using particle tracking velocimetry, in which size-dependent velocities could then be computed. Droplet velocities were affected more by rotational speed than droplet SMD, while ligaments were affected by other factors than the rotational speed and ligament SMD.