Empirical analysis of rough set categorical clustering techniques based on rough purity and value set

Clustering a set of objects into homogeneous groups is a fundamental operation in data mining. Recently, attention has been put on categorical data clustering, where data objects are made up of non-numerical attributes. The implementation of several existing categorical clustering techniques is challenging as some are unable to handle uncertainty and others have stability issues. In the process of dealing with categorical data and handling uncertainty, the rough set theory has become well-established mechanism in a wide variety of applications including databases. The recent techniques such as Information-Theoretic Dependency Roughness (ITDR), Maximum Dependency Attribute (MDA) and Maximum Significance Attribute (MSA) outperformed their predecessor approaches like Bi-Clustering (BC), Total Roughness (TR), Min-Min Roughness (MMR), and standard-deviation roughness (SDR). This work explores the limitations and issues of ITDR, MDA and MSA techniques on data sets where these techniques fails to select or faces difficulty in selecting their best clustering attribute. Accordingly, two alternative techniques named Rough Purity Approach (RPA) and Maximum Value Attribute (MVA) are proposed. The novelty of both proposed approaches is that, the RPA presents a new uncertainty definition based on purity of rough relational data base whereas, the MVA unlike other rough set theory techniques uses the domain knowledge such as value set combined with number of clusters (NoC). To show the significance, mathematical and theoretical basis for proposed approaches, several propositions are illustrated. Moreover, the recent rough categorical techniques like MDA, MSA, ITDR and classical clustering technique like simple K-mean are used for comparison and the results are presented in tabular and graphical forms. For experiments, data sets from previously utilized research cases, a real supply base management (SBM) data set and UCI repository are utilized. The results reveal significant improvement by proposed techniques for categorical clustering in terms of purity (21%), entropy (9%), accuracy (16%), rough accuracy (11%), iterations (99%) and time (93%). vi

Flow visualization of a dielectric barrier discharge plasma actuator

The optimum operating conditions of dielectric barrier discharge (DBD) plasma actuators were determined using both the quantitative and qualitative methods. The quantitative study was carried out by estimating DBD discharge power using the theoretical and experimental methods. The theoretical analysis was carried out to find a mathematical model, which describe the discharge power of the DBD actuator. The estimated results from the mathematical model were compared with the experimental values obtained from Lissajous figures. The qualitative analysis was used for the plasma flow visualization. The effects of the DBD design parameters were studied through the images captured using a high speed charge-coupled device camera. Simulation work was done in order to obtain an insight of the electric field responsible for the plasma formation using the commercial computer software. The results revealed that the performance of the DBD plasma actuator was influenced by various design parameters, especially by dielectric thickness and controlled by the input voltage characteristics

Investigation of Quantity, Quality and Energy Content of Indigenous Sugarcane Trash in Naoshehro Feroze District, Sindh

Quantity, characteristics, and energy content in sugarcane trash of six different indigenous sugarcane varieties were computed for their possible utilization. Results revealed that the total sugarcane trash weight percentage was 24.0% of the total sugarcane crop. Among all examined varieties, variety 240 produced the highest and the variety HS12 the lowest percentage of sugarcane trash with 28% and 18.6% respectively. Moisture and ash content were found less in brown leaves and more in the tops of sugarcane trash parts. The fixed carbon values in brown leaves, green leaves, and tops of the variety Thatta10 were the highest found, with 18.4%, 15.5%, and 17.3% respectively. Carbon element’s percentage in brown leaves of variety HS12 was the highest with 50.0% and in Thatta10 was the lowest with 43.4%. Highest heating value was found in Thatta10 with 16.0MJ/kg, which is close to the literature reported values

Estimation of Carbon Footprints from Diesel Generator Emissions

The aim of this paper is to estimate the amount of carbon footprints emitted from diesel generators in terms of carbon dioxide. A constant load demand of 1.05 kW per hour (6.3 kW/day) with six hours of operation of a diesel generator per day was selected for this analysis. The fuel consumption rate and carbon footprints in terms of carbon dioxide (CO2) were determined. It was discovered that emission of carbon footprints increased by five folds as emission factor was increased from 1kg to 5 kgCO2/liter. Similarly, the increment of a single kW rated power diesel generator at a constant emission factor increases 1.1 to 1.2 times carbon footprint emissions. It is revealed that the efficiency of diesel generator is inversely proportional to its rated power, fuel consumption rate and CO2 emissions. Therefore, the rated power of selected diesel generator should be close to the required load demand

Performance Modeling And Size Optimization Of A Standalone Photovoltaic System

Standalone photovoltaic (SAPV) systems are emerging source of generating electrical power especially for isolated villages. The remote villages, which cut-off from the national grid and where extension of power transmission lines is expensive due to their geographical conditions. Poor modelling algorithms, high initial capital cost and threat of system breakdown due to improper sizing of SAPV systems impede its growth. The available models were mostly validated by applying the long term (more than twenty years) solar radiation data with small time intervals from developed countries. The procedure for determination of input parameters required for the models was not well explained. The available intuitive sizing methods were found to be imperfect and the numerical methods were complicated and time consuming. Therefore, the development of an appropriate sizing method was necessary which should fill up the gap between complex and imprecise SAPV sizing methods.The aim of this work was to improve the prediction of SAPV system performance by proposing an appropriate sizing method. The original contribution of this work was the development of two mathematical models namely a model for determination of global solar radiation and a model for the estimation of PV module power output. Furthermore, a novel analytical size optimization method was formulated involving load demand on the basis of power reliability and system cost. The adapted global radiation model is different from available models as it incorporates the site specific and environmnetal parameters, which considered as influential input variables. It was found from the study that the adapted global solar radiation model performed well and displayed less than 10% RMSE and 8% MBE as compared to the examined models. The power outputs of PV modules were estimated by development of a single diode equivalent electrical circuit model. The values of input parameters for developed model were computed analytically. The expression for output current from PV module was determined explicitly by Lambert W function and the voltage output was computed numerically by Newton-Raphson method. The developed model executed ± 2% error with the rated power output of a PV module provided by the manufacturers. Furthermore, SAPV components sizing method was formulated with a nonlinear unconstrained optimization technique by using first derivative method. The proposed optimal sizing method determines the required PV array area and battery storage capacity for the system load with least possible cost and predefined power reliability.The results of the adopted models and developed sizing method were validated by conducting sensitivity analysis of model parameters. It was revealed that the most important and sensitive input variable was the total solar radiation with 2.5 times influence over the output results with a sensitivity index of 0.8. The lowest sensitive variable was wind speed with a sensitivity index of less than 0.1. The carbon footprints from diesel generators were estimated and compared with SAPV system emissions for environmental analysis. It is because the diesel generators are most common power producing units in remote areas of Sarawak. The analysis reveals that the power generated by SAPV systems will help to avoid 111 tonnes of CO2 to the atmosphere as compared to a 5kW rated power diesel generator with a load demand of 6.3kW/day. However, the estimated net energy cost occurred from SAPV system was found to be 20 times higher than average electricity tariff in Malaysia. It was found from the study that proposed sizing method is precise and easy to implement than previously available methods. It requires average solar radiation data, which is almost available in every place. It gives a complete procedure for determination of required model parameters and incorporates the load demand besides system cost and power reliability. It is concluded that the proposed optimal sizing method can be successfully implemented for the design, development, size optimization and feasibility study of SAPV systems for the supply of reliable power in isolated villages

Influence of Temperature on Electrical Characteristics of Different Photovoltaic Module Technologies

­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­The aim of this study was to analyse the influence of temperature on electrical characteristics of crystalline and amorphous photovoltaic (PV) modules in outdoor conditions at Nawabshah. The experimental setup was made over the roof of the departmental building. The climatic conditions of site were recorded with the help of HP-2000 Professional Weather Station in three different timings of the day, i.e. morning, noon and evening. The electrical characteristics of the PV modules were recorded with Prova-210 and module temperatures with Prova-830. The maximum intensity of global solar radiation was recorded at noon and ambient temperature in the evening and the relative humidity in the morning hours. It was observed that amorphous module got 0.7°C, 1.0°C and 1.6°C more average temperature than polycrystalline, thin film and monocrystalline modules respectively. The average maximum measured open-circuit voltage was noted from amorphous with 96.7% and minimum from thin film with 81.3% of their respective values on standard conditions, whereas, the average maximum recorded short-circuit current was produced by thin film with 64.9% and minimum by amorphous with 51.4%. The average maximum power was produced by polycrystalline and minimum by amorphous module. It was discovered that the crystalline PV modules gave more fill factor than thin film and amorphous module. Article History: Received January 6th 2018; Received in revised form May 5th 2018; Accepted May 26th 2018; Available online How to Cite This Article: Jatoi, A.R., Samo, S.R. and Jakhrani, A.Q. (2018). Influence of Temperature on Electrical Characteristics of Different Photovoltaic Module Technologies. Int. Journal of Renewable Energy Development, 7(2), 85-91. https://doi.org/10.14710/ijred.7.2.85-9

Performance analysis of a fabricated line focusing concentrated solar distillation system

A line focusing concentrated solar distillation unit was developed and its techno-economic analysis was carried out using batch flow, continuous flow without and with tracking mechanisms. Physical quality parameters of feed and distilled water samples, water temperature at different points, performance analysis and estimated production of developed unit were examined. The examined quality parameters of distilled water were well below permissible limits. The water temperature inside the concentrated tube was in the range of 107.0˚C to 109.0˚C. The quantity of distilled water was observed to be inversely proportional to the amount of total dissolved solids in the water samples. The measured average daily and estimated lifetime yield from the developed unit during batch flow was 4.0 and 13,621.0 liters, for continuous flow without tracking 5.1 and 19,689.0 liters, and with tracking mechanism 5.7 and 21,758.0 liters, respectively. The continuous flow with tracking mechanism was found as best method for the production of distilled water. The total life cycle cost of the project was estimated to be PKR 62,144.00. The estimated unit cost of the distilled water per liter would be PKR 6.06 for continuous flow with tracking and PKR 9.69 for batch flow technique. ©2019. CBIORE-IJRED. All rights reserve

Sensitivity Analysis of a Standalone Photovoltaic System Model Parameters

The values of input variables of any model are cause to undergo changes due to influence of environmental conditions. These changes can be investigated by conducting the sensitivity analysis of input variables with respect to output variables. Sensitivity analysis increases the validity, credibility and assurance of model estimates. The purpose of this study was to identify the most important and sensitive input variables and to prioritize the parameters based on their influence on the model outputs of a standalone photovoltaic (SAPV) system. For that, a normalized local sensitivity analysis and sensitivity index of seven input variables of a SAPV system model with reference to three output parameters namely amount of absorbed solar radiation, maximum photovoltaic (PV) module power output and optimum PV array area has been carried out. It was revealed from the analysis that the most important and sensitive input variable was the amount of total solar radiation and the least important variable was solar azimuth angle and the lowest sensitive variable was wind speed