An Assessment of Onshore and Offshore Wind Energy Potential in India Using Moth Flame Optimization

Wind energy is one of the supremely renewable energy sources and has been widely established worldwide. Due to strong seasonal variations in the wind resource, accurate predictions of wind resource assessment and appropriate wind speed distribution models (for any location) are the significant facets for planning and commissioning wind farms. In this work, the wind characteristics and wind potential assessment of onshore, offshore, and nearshore locations of India—particularly Kayathar in Tamilnadu, the Gulf of Khambhat, and Jafrabad in Gujarat—are statistically analyzed with wind distribution methods. Further, the resource assessments are carried out using Weibull, Rayleigh, gamma, Nakagami, generalized extreme value (GEV), lognormal, inverse Gaussian, Rician, Birnbaum–Sandras, and Bimodal–Weibull distribution methods. Additionally, the advent of artificial intelligence and soft computing techniques with the moth flame optimization (MFO) method leads to superior results in solving complex problems and parameter estimations. The data analytics are carried out in the MATLAB platform, with in-house coding developed for MFO parameters estimated through optimization and other wind distribution parameters using the maximum likelihood method. The observed outcomes show that the MFO method performed well on parameter estimation. Correspondingly, wind power generation was shown to peak at the South West Monsoon periods from June to September, with mean wind speeds ranging from 9 to 12 m/s. Furthermore, the wind speed distribution method of mixed Weibull, Nakagami, and Rician methods performed well in calculating potential assessments for the targeted locations. Likewise, the Gulf of Khambhat (offshore) area has steady wind speeds ranging from 7 to 10 m/s with less turbulence intensity and the highest wind power density of 431 watts/m2. The proposed optimization method proves its potential for accurate assessment of Indian wind conditions in selected locations.publishedVersio

Prediction of gas holdup in the three-phase fluidized bed: air/Newtonian and non-Newtonian liquid systems

The application of the three-phase fluidization technology in wastewater treatment and other biochemical processes has been regularly addressed in the past decades. For the design and development of the threephase fluidized bed reactors, knowledge of the hydrodynamic parameter such as gas holdup is essential and hence in this paper an attempt has been made to study the effect of fundamental and operating variables on gas holdup. On the basis of the experimental results, a unified correlation has been developed to predict gas holdup in the fluidized bed using the Newtonian and the non-Newtonian liquids. The experimental results showed good agreement with those predicted according to the developed correlation

Left and Right Censoring for Expected Time to Seroconversion – A Shock Model Approach

The time to cross-antigenic threshold of the infected person’s is a vital event. Once the accumulated number of events exists from the persons which as a certain threshold level, it could be viewed as a “Break down pointâ€Â. The important characteristic for the antigenic diversity threshold for a person is the time to attain the break down point. In this paper, a shock model approach is proposed to obtain the expectation time to attain the threshold level. Attempt to find patients censoring value is also seen. Graphical illustrations are provided for the use of the model

COD reduction studies of paper mill effluent using a batch recirculation electrochemical method

The conventional method of treating pulp and paper mill effluent involves the biological oxidation by bacterial action of aerobic and anaerobic conditions and aerobic lagooning method, which are less efficiency of removing COD. To overcome the drawbacks of the existing treatment process, in the present work an attempt has been made to study the electro oxidative destruction of the pulp and paper mill effluent using an electrochemical method and the effect of various parameters such as concentration of supporting electrolytes, current densities, flow rates of electrolyte and reservoir volumes of the effluent were conducted. From the experimental results it is observed that the rate of reduction of COD of the effluent increased with an increase in the supporting electrolyte (sodium chloride) concentration, current density where as it decreased with increase in the reservoir volume and the flow rate of electrolyte. The residence time distributions studies have also been conducted to study the behavior of the electrochemical reactor

COD reduction studies of paper mill effluent using a batch recirculation electrochemical method

The conventional method of treating pulp and paper mill effluent involves the biological oxidation by bacterial action of aerobic and anaerobic conditions and aerobic lagooning method, which are less efficiency of removing COD. To overcome the drawbacks of the existing treatment process, in the present work an attempt has been made to study the electro oxidative destruction of the pulp and paper mill effluent using an electrochemical method and the effect of various parameters such as concentration of supporting electrolytes, current densities, flow rates of electrolyte and reservoir volumes of the effluent were conducted. From the experimental results it is observed that the rate of reduction of COD of the effluent increased with an increase in the supporting electrolyte (sodium chloride) concentration, current density where as it decreased with increase in the reservoir volume and the flow rate of electrolyte. The residence time distributions studies have also been conducted to study the behavior of the electrochemical reactor

An Assessment of Onshore and Offshore Wind Energy Potential in India Using Moth Flame Optimization

Wind energy is one of the supremely renewable energy sources and has been widely established worldwide. Due to strong seasonal variations in the wind resource, accurate predictions of wind resource assessment and appropriate wind speed distribution models (for any location) are the significant facets for planning and commissioning wind farms. In this work, the wind characteristics and wind potential assessment of onshore, offshore, and nearshore locations of India—particularly Kayathar in Tamilnadu, the Gulf of Khambhat, and Jafrabad in Gujarat—are statistically analyzed with wind distribution methods. Further, the resource assessments are carried out using Weibull, Rayleigh, gamma, Nakagami, generalized extreme value (GEV), lognormal, inverse Gaussian, Rician, Birnbaum–Sandras, and Bimodal–Weibull distribution methods. Additionally, the advent of artificial intelligence and soft computing techniques with the moth flame optimization (MFO) method leads to superior results in solving complex problems and parameter estimations. The data analytics are carried out in the MATLAB platform, with in-house coding developed for MFO parameters estimated through optimization and other wind distribution parameters using the maximum likelihood method. The observed outcomes show that the MFO method performed well on parameter estimation. Correspondingly, wind power generation was shown to peak at the South West Monsoon periods from June to September, with mean wind speeds ranging from 9 to 12 m/s. Furthermore, the wind speed distribution method of mixed Weibull, Nakagami, and Rician methods performed well in calculating potential assessments for the targeted locations. Likewise, the Gulf of Khambhat (offshore) area has steady wind speeds ranging from 7 to 10 m/s with less turbulence intensity and the highest wind power density of 431 watts/m2. The proposed optimization method proves its potential for accurate assessment of Indian wind conditions in selected locations