B. Ravindra

Bio: B. Ravindra is an academic researcher from Indian Institute of Technology, Jodhpur. The author has contributed to research in topics: Solar power & Photovoltaic system. The author has an hindex of 11, co-authored 30 publications receiving 569 citations. Previous affiliations of B. Ravindra include Technische Universität Darmstadt & Darmstadt University of Applied Sciences.

Gap-Filling Techniques for Solar Radiation Data and Their Role in Solar Resource Assessment

Abstract: Some of the highest solar insolation regions of the world are in the arid and semi-arid zones. These zones have seen large-scale deployment of solar power plants during the previous decade. Data quality analysis of solar radiation information from various sources is significant in this context. Semi-arid zones have large number of clear-sky days per year but are also subjected to other micro-climactic events. All the three components of solar radiation change during these events. The gaps in the solar radiation data sets need to be filled appropriately to obtain a continuous time series that can be used for solar resource assessment and forecasting. A review of the gap-filling techniques and their application to a semi-arid zone solar radiation data set is presented in this work. Further, it is pointed out that various cloud conditions need to be considered while gap filling for a better assessment of bankability of a solar power project.

Development of algorithm to model dispersed gas-liquid flow using lattice Boltzmann method

Abstract: In this paper, we present the algorithm for the simulation of a single bubble rising in a stagnant liquid using Euler-Lagrangian (EL) approach. The continuous liquid phase is modeled using BGK approximation of lattice Boltzmann method (LBM), and a Lagrangian particle tracking (LPT) approach has been used to model the dispersed gas (bubble) phase. A two-way coupling scheme is implemented for the interface interaction between two phases. The simulation results are compared with the theoretical and experimental data reported in the literature and it was found that the presented modeling technique is in good agreement with the theoretical and experimental data for the relative and terminal velocity of a bubble. We also performed the grid independence test for the current model and the results show that the grid size does not affect the rationality of the results. The stability test has been done by finding the relative velocity of a bubble as a function of time for the different value of dimensionless relaxation frequency. The present study is relevant for understanding the bubble-fluid interaction module and helps to develop the accurate numerical model for bioreactor simulation.

Performance of a crystalline silicon photovoltaic power plant during sandstorms

Abstract: Solar photovoltaic power generation has achieved grid parity in a number of countries during the last decade. This revolution has begun in countries where the solar radiation intensity is not very high. Solar resource maps created by a number of agencies worldwide indicate that areas of high intensity of solar radiation suitable solar for power generation are in deserts and semi-arid zones. These regions are dusty and are subjected to both anthropogenic pollution and natural sand storms. The impact of these events on the solar photovoltaic (PV) plant yield is significant. An increase in diffuse component of solar radiation is accompanied by a naturally occurring sand storm. Often the solar panels are tilted at an optimal angle and the global tilted radiation value falling on the panels changes significantly during and after the sand storms. It is noted that the decrease in the power output of a solar photovoltaic plant during such events is high enough to warrant further consideration while forecasting the plant output. Inverter performance during such sand storms is found to be satisfactory. Integrating dust storm monitoring with PV power plant yield prediction algorithms is necessary for an improved operation of PV plants.

Impact of Trend and Seasonality in Forecasting of 5 MW PV Plant Generation using Single Exponential Smoothing Method

Abstract: st century forecasting of solar power generation is an important issue due to grid integration. In these days power shading and heavy load is a major problem in front of conventional power generation sources so grid integration is plays an important role to fill the gap in between demand and supply of power generation. So solar power and conventional power are basic sources of grid integration. Solar power is playing a key role in grid integration. In this work, Solar power generation forecasting is carried out based on the data collected from a 5MW Gujarat Power Cooperation limited solar photovoltaic power plant which is installed in Charanka, Gujarat. In this paper we discussed about the single exponential smoothing for solar power forecasting problem and impact of trend and seasonality on modelling of power generation forecasting.

The Method of Proper Orthogonal Decomposition for Dynamical Characterization and Order Reduction of Mechanical Systems: An Overview

Abstract: Modal analysis is used extensively for understanding the dynamic behavior of structures. However, a major concern for structural dynamicists is that its validity is limited to linear structures. New developments have been proposed in order to examine nonlinear systems, among which the theory based on nonlinear normal modes is indubitably the most appealing. In this paper, a different approach is adopted, and proper orthogonal decomposition is considered. The modes extracted from the decomposition may serve two purposes, namely order reduction by projecting high-dimensional data into a lower-dimensional space and feature extraction by revealing relevant but unexpected structure hidden in the data. The utility of the method for dynamic characterization and order reduction of linear and nonlinear mechanical systems is demonstrated in this study.