Master of Engineering in Energy Technology
http://dl.lib.uom.lk/handle/123/70
2024-03-28T11:03:44ZEvaluation of hourly solar radiation models to estimate radiation on inclined surfaces in day zone of Sri Lanka
http://dl.lib.uom.lk/handle/123/18317
Evaluation of hourly solar radiation models to estimate radiation on inclined surfaces in day zone of Sri Lanka
Abeyrarthna, ARMUE
An analysis of global, beam and diffuse solar radiation on horizontal and 7° tilt about east west axis and facing due south orientation at Hambanthota was carried out to assess the solar resource potential in dry zone of Sri Lanka. The calculated monthly averaged daily insolation for dry zone was found to be varying between 16.30 MJ/m2/day to 22.75 MJ/m2/day with the annually averaged daily insolation of 20.07 MJ/m2/day. Calculated annually averaged beam horizontal radiation was 10.87 MJ/m2/day and diffuse horizontal radiation was found to be 9.19 MJ/m2/day while 0.56 was the annual average clearness index indicating that partly cloudy sky throughout the year. Horizon brightness coefficients of Perez et al (1990) was modified using diffuse radiation data of Hambanthota. Modified model was used for the estimation of titled radiation on due south faced surfaces. Diffuse tilted daily insolation and global tilted insolation for -45° to +45° inclined surfaces with 1° increments was estimated and monthly and annual optimum tilt angles were derived. The calculated monthly optimum tilt angle varied between -26° to +27° while having annual optimum tilt angle of -2°. Hence, tilting towards due south by same angle as latitude is not the recommended optimum tilt for fixed axis systems. Optimum tilt angle for beam radiation was derived and it was found that annual optimum tilt angle for beam radiation is 6° facing towards the due south. The derived maximum solar resource potential was 2068 kWh/m2 per annum for fixed system at -2° tilt angle and 2169 kWh/m2 per annum for monthly tracking system which is 5% higher than the horizontal potential. It is proposed to assess the solar resource potential for tilted surfaces with different surface azimuth angles by using modified Perez et al (1990) model in future. It is also possible to modify the coefficients of circumsolar brightness components of Perez et al (1990) model for better results.
2018-02-20T00:00:00ZA Neural network based model for forecasting the power output of a commercial scale photovoltaic power plant
http://dl.lib.uom.lk/handle/123/20927
A Neural network based model for forecasting the power output of a commercial scale photovoltaic power plant
Manchanayaka MAAP
Solar photovoltaic (PV) is penetrating electrical grids with a substantial growth of new additions, as a result of renewable energy policies and plans implemented locally and globally. However, the intermittent nature of the availability of solar energy brings an uncertainty into electrical power systems making it complex for power management and integrating into existing electricity infrastructure. This has been a key issue in promoting renewable energy in developing countries. Accurate solar power forecasts in different time horizons can play a vital role to bring down the uncertainty by a significant margin. In this work, a neural network (NN) model was coupled with a decomposition and transposition (D&T) model to forecast day(s) ahead hourly PV output of a grid connected 1 MW solar PV plant located in Hambantota, Sri Lanka. Historical weather and solar radiation data for last 14 years were collected from two APIs (Application Programming interfaces) for the location of PV plant and variation of global horizontal irradiation (GHI) with percentage cloud cover, rain, temperature, relative humidity, and wind speed were analysed. The selected parameters from the analysis together with day and hour numbers were fed in to the NN model through a scaling layer and trained it using Levenberg–Marquardt backpropagation algorithm. Optimum NN model was selected by changing the hidden layer sizes and calculating the mean squared error. The forecasted GHI values of the optimized NN model were decomposed to diffuse horizontal irradiance (DHI) and direct normal irradiance (DNI) using Erbs correlation, as the first step of D & T model. Then, DHI and DNI components were converted to global tilted irradiance (GTI) using HDKR correlation, in order to calculate solar PV output, including possible plant specific losses. The correlation coefficient (R) between GHI output and target values of the trained NN model for an unseen testing data set was observed to be 0.86. For final model, mean percentage forecasting accuracy was observed to be 86% with 12% standard deviation. The model could be adopted to any commercial or utility scale solar PV plant which is in a tropical climate region.
2022-01-01T00:00:00ZExperimental investigation on black pepper drying in a hot air cabinet dryer for optimized energy performance
http://dl.lib.uom.lk/handle/123/21357
Experimental investigation on black pepper drying in a hot air cabinet dryer for optimized energy performance
Virantha EAI
Open sun drying is the widely used passive method for black pepper drying, but due to its
limitations such as unavailability on rainy days, lack of controllability, degradation of food
quality, loss of volatile oil, and improper drying, the active dryers have become more popular
than the open sun drying method. Among these active dryers, tray dryers are extremely popular
in medium and small-scale black pepper processing industries because they are small in size,
simple in design and lower capital cost comparative to other dryers. It is extremely important
to identify the optimum drying temperature and the hot air velocity for black pepper drying
process on a convective tray dryer to minimize the total energy while improving the quality of
the black pepper. The drying properties of black pepper were examined in a convective thermal
tray dryer during this investigation. In house built experimental setup was used to understand
the variations of moisture ratio (MR) during the drying. The experiments were carried out in
different temperatures of 50 °C, 55 °C and 60 °C and, for three different air speeds of 0.4ms
,
0.8 ms
-1
and 1.2 ms
-1
. The observed experimental results were fitted with the existing drying
models. Model coefficients and constants were evaluated by using the MS Excel software. The
Logarithmic model was discovered as the best drying model to explore the black pepper drying
on a convective hot air tray dryer with an average RMSD (root mean square deviation) of
0.0140. The total amount of time required to decrease the moisture content (MC) to 12%
(minimum secure storage MC) in dry basis under various drying settings were computed using
the logarithmic model equation. The total drying energy required to dry 1 kg of raw black
pepper for different drying conditions was calculated and, a surface plot of total drying energy
against temperature and air speed was generated. Based on the contours of the surface plot, the
drying conditions which minimize the total drying energy were determined.
2022-01-01T00:00:00ZNumerical study of microchannel heat transfer with nanofluid based two - phase slug flow
http://dl.lib.uom.lk/handle/123/20934
Numerical study of microchannel heat transfer with nanofluid based two - phase slug flow
Siriwardana SSGC
Microfluidics has recently gained research attention for its high-end thermal
applications, including micro heat exchangers, Lab on a Chip, micro reactors, and
MEMS. It has been proven that the addition of suitable nanoparticles to a fluid can
enhance the heat transfer efficiency in microchannels, both in single phase and
liquid-liquid two-phase flow. In general, slug flow is said to be the most efficient in
heat transfer. However, the investigation performed on liquid-liquid slug flow with
added nanoparticles was found to be very limited. Hence, this study numerically
investigates the heat transfer characteristics in microchannels with liquid-liquid two-
phase fluid flow (water and light mineral oil) with added nano particles (AI2O3).
The VOF method and phase field equations were solved using ANSYS Fluent and
COMSOL Multiphysics to capture two-phase flow interfaces. Adaptive mesh
refinement techniques were employed to reduce computational power while
maintaining sharp interfaces between fluid phases. The Eulerian mixture model was
used
to solve the cases containing nanoparticles. Numerical results were validated
against published experimental data reported by [1] and [2].
Simulations were conducted for a 3000 micron long microchannel with a diameter of
100 microns for fluid velocity, ranging from 0.1 m/s to 0.5 m/s. First, 1 kW/cm2 of
heat flux is introduced to the channel wall after 1000 microns to mimic the microchip
heat generation, also allowing flow to be developed.
Results have shown that using nanoparticles in either phase significantly increases
heat transmission. This can be amplified even more when used in the secondary
phase, by 58 percent compared with liquid-liquid two phase slug flow. This was
accomplished with a nanoparticle fraction of 0.05 v/v in the secondary fluid phase.
The addition of nanoparticles to the primary fluid increased heat transfer by 34%. The
findings of this study can be used to improve MEMS and micro-to-macro systems that
move heat.
2022-01-01T00:00:00Z