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Hybrid renewable energy systems with photovoltaic and energy storage systems have gained popularity due to their cost-effectiveness, reduced dependence on fossil fuels and lower CO2 emissions. However, their techno-economic advantages are crucially dependent on the optimal sizing of the system. Most of the commercially available optimization programs adopt an algorithm that assumes repeated weather conditions, which is becoming more unrealistic considering the recent erratic behavior of weather patterns. To address this issue, a data-driven framework is proposed that combines machine learning and hybrid metaheuristics to predict weather patterns over the lifespan of a hybrid renewable energy system in optimizing its size. The framework uses machine learning tree ensemble methods such as the cat boost regressor, light gradient boosting machine and extreme gradient boosting to predict the hourly solar radiation and load demand. Nine different hybrid metaheuristics are used to optimize the hybrid renewable energy system using forecasted data over 15 years, and the optimal sizing results are compared with those obtained from 1-year data simulation. The proposed approach leads to a more realistic hybrid renewable energy system capacity that satisfies all system constraints while being more reliable and environmentally friendly. The proposed framework provides a robust approach to optimizing hybrid renewable energy system sizing and performance evaluation that accounts for changing weather conditions over the lifespan of the system.

Information on the rheological characteristics of clathrate hydrate slurry is vital due to its diverse applications including hydrate slurry transportation as in seawater desalination by gas hydrate process, gas delivery through slurry pipelines, cold thermal energy storage, and secondary refrigeration by hydrate slurries. The current study experimentally investigated the rheological behavior of Tetrafluoroethane (Freon) hydrate slurry formed from R-134a and water serving as a medium for sea water desalination. Experiments were performed in a flow loop with a volume of 5.68 L and an inner pipe diameter of 21.5 mm, which was immersed in a constant temperature bath to maintain hydrate stable condition. Experiments were conducted with two phases in the loop; solid hydrate particles and liquid water. The hydrate solid volume fraction ranged from 15.8 to 31.7 vol%. Pressure drops along the straight section of the pipe were monitored while temperature, solid volume fraction and flow rate were kept const...

Seawater desalination technology utilizing gas hydrates consists of three primary processes: the formation of hydrate slurry from seawater and treatment gas, the removal of concentrated saltwater from the hydrate slurry, and the decomposition of dewatered hydrate back into treatment gas and potable water. Tetrafluroethane (R134a) was found to be a favored treatment gas, since it can form clathrate hydrate under relatively low pressure at near deep seawater temperature of around 275 K. Thorough recoveries of treatment gas dissolved in removed concentrated brine, in hydrate decomposed water, and in waste salt water are crucial to reduce the release of greenhouse gas, and to improve the economic feasibility. The present study investigated the influences of mechanical agitation and ultrasonic stimulation upon vacuum degassing of decomposed hydrate water which is saturated with R134a at 1 bar pressure. The experimental results indicate that the target concentration of 500 ppm can be achieved within 30 s of degassing. Energy economy analyses were also performed under different combinations of agitation and ultrasound intensities to provide the basic knowledge needed to design degassing reactors for seawater desalination pilot plant producing 2 tons of potable water per day. If the degassing time exceeds 87 s, the energy consumption is estimated to cost more than the value of being recovered R134a.

The effect of ultrasonic waves on formation and dissociation kinetics of gas hydrates has been experimentally studied by several researchers. Some results indicated that ultrasonic waves have the effect of reducing gas hydrate induction time before the initiation of hydrate formation, while others reported on the effect of prohibiting the growth kinetics during hydrate formation. There have also been reports regarding an increase in the amount of gas consumed and a decrease in the hydrate formation time. The present study examines the influence of ultrasonic waves on gas hydrate dissociation. Gas hydrate formation and dissociation occurred in a temperature-controlled 15 L horizontal cylindrical reactor. The reactor was agitated with a pair of flat blades installed in radial direction and a pair of rollers, which were driven by a motor connected through a magnetic coupler. R-134a, a gas that can form hydrates at a relatively low pressure, was used to form gas hydrate slurry. Dissociation was augmented by 20 kHz ultrasonic waves generated with a piezoelectric converter and transmitted through a vibrating horn whose tip was in contact with the hydrated slurry in the reactor. To compare the effect of energy input in the form of ultrasonic waves with that of the same amount of heat input, equivalent amount of heat was provided to the reactor. Dissociation rate and the accumulated dissociation time were compared between the cases of heat addition and ultrasonic wave irradiation. Results show that not only does the dissociation rate increase with an increase in the ultrasonic wave power, but the irradiation of ultrasonic waves also enhances the dissociation of R-134a hydrate more effectively than the application of an equivalent amount of energy in the form of heat at the same location.

The need of a sustainable clean future has paved the way for environmental friendly electric vehicle technology. In electric vehicles, overloading is limited by the maximum temperature rise in the electric motor. Although an improved cooling jacket design is of vital importance in lowering the maximum temperature of the motor, there has not been as much study in the thermal analysis of motors compared to electromagnetic design studies. In this study, a three-dimensional steady state numerical method is used to investigate the performance of a cooling jacket using water as the primary coolant of a three-phase induction motor with special emphasis on the maximum temperature and the required pumping power. The effective thermal conductivity approach is employed to model the stator winding, stator yoke, rotor winding and rotor yoke. Heat transfer by induced air is treated as forced convection at the motor ends and effective conductivity is obtained for air in the stator-rotor gap. Motor power losses, i.e., copper and iron losses, are treated as heat generation sources. The effect of bearings and end windings is not considered in the current model. Pressure and temperature distributions under various coolant flow rates, number of flow passes and different cooling jacket configurations are obtained. The study is successful in identifying the hot spots and understanding the critical parameters that affect the temperature profile. The cooling jacket configuration affects the region of maximum temperature inside the motor. Increasing the number of flow passes and coolant flow rate decreases maximum motor temperature but results in an increase in the pumping power. Of the cooling jacket configurations and operating conditions investigated, a cooling jacket with six passes at a flow rate of 10 LPM with two-port configuration was found to be optimal for a 90-kW induction motor for safe operation at the maximum output.

Effective hydraulic conductivity of a statistically anisotropic heterogeneous medium is obtained for steady two-dimensional flows employing stochastic analysis. Flow equations are solved up to second order and the effective conductivity is obtained in a semi-analytic form depending only on the spatial correlation function and the anisotropy ratio of the hydraulic conductivity field, hence becoming a true intrinsic property independent of the flow field. Results are obtained using a statistically anisotropic Gaussian correlation function where the anisotropy is defined as the ratio of integral scales normal and parallel to the mean flow direction. Second order results indicate that the effective conductivity of an anisotropic medium is greater than that of an isotropic one when the anisotropy ratio is less than one and vice versa. It is also found that the effective conductivity has upper and lower bounds of the arithmetic and the harmonic mean conductivities.

Verification of a stochastic model which models the phenomena of flow and transport in a nonstationary conductivity field [Rubin and Seong, 1994] is attempted with field data from the Waste Isolation Pilot Plant (WIPP) site near Carlsbad, New Mexico. The nonstationarity is manifested as a spatial linear trend in the mean log conductivity field. Analysis of the log conductivity and the hydraulic head data shows that the site corresponds to Rubin and Seong's α2 model, where the mean flow direction and the gradient of mean log conductivity are normal to each other. The experimental semivariogram of the log conductivity obtained from field data strongly suggests that it is nonstationary and can be fit with a Gaussian covariance function. The α2 model is successful in predicting the experimental semivariogram of the head obtained from the field data, especially in capturing the finite sill characteristics. The stationary model predicts an unbounded semivariogram at large distances. Solute travel times are also investigated by comparing the travel time cumulative distribution function (CDF) resulting from the stationary and the nonstationary hydraulic conductivity models. The stationary model predicts a higher CDF at early times and hence overestimates the very early travel times to the regulatory plane of compliance than the α2 model.

This paper describes an investigation of flow and transport phenomena in heterogeneous, nonstationary formations, where the log conductivity is the superposition of a linear trend and a stationary fluctuation. The problem of flow and transport in a steady, two-dimensional flow without recharge is investigated analytically for an infinite flow domain. General results are obtained for any space dimensionality, but applications were limited to the case of two-dimensional flow in the horizontal plane. The log conductivity field is assumed to have a linear trend. We limited the scope of this study to the cases where the trend is either parallel or normal to the head gradient and to small variance in the log conductivity. This paper presents results for the moments of the velocity and the hydraulic head, the effective conductivity, macrodispersion coefficients, solute mass breakthrough curves, and travel time distributions, all in terms of the parameters of the log conductivity field and the boundary conditions. The effects of the trend in the conductivity on these results are analyzed and compared with those obtained when the apparent trend is neglected. The results may be used for predicting transport phenomena extending over distances of many integral scales, as well as for interpretationmore » of field data where the presence of a trend is suspected. 25 refs., 12 figs.« less