Abhik Kumar Das

A Statistical Model for Wind Power on the Basis of Ramp Analysis

Abstract Due to stochastic nature of wind distribution, wind power output comes with unscheduled changes called ramp events. In this paper, a semi-analytical approach is considered to analyze the distribution of ramp events. A simple empirical equation is derived based on the probability of wind ramp events considering the stochastic nature of wind power distribution for the Indian state of Karnataka. The proposed functional relationship shows a satisfactory approximation of the actual distribution of ramp events and helps to estimate the statistical behaviour of wind output in terms of frequency of ramp events for pre-defined threshold power outputs.

Using the Gini index to measure the inequality in infrastructure services provided within an urban region

In this article, we suggest the use of the Gini index to measure the inequality in infrastructure services provided within an urban region. We develop a functional form for the Lorenz curve, the basis of measurement of the Gini index. The sparse nature of data available to measure the distribution of infrastructure services within an urban region makes estimating the Lorenz curve challenging. However, the proposed functional form for the Lorenz curve requires a sparse amount of data (only 25th and 50th percentile) and it is simple to estimate and compute the coefficients of the equation as well as the Gini index. Our methodology is shown to be relatively accurate in estimating the Gini index for national level income data compared to other formulations found in the literature. In this paper, with the help of collected data, we demonstrate the use of the Gini index to characterise urban regions in terms of their accessibility of public infrastructure services.

Quantifying photovoltaic power variability using Lorenz curve

Short-term variability of utility-scale solar PhotoVoltaic (PV) plant is a significant issue for grid reliability. It is necessary to quantify the solar power variability in order to analyze the power variations on the electricity distribution network. In this paper, a Lorenz curve-based method is described to quantify the variability of power output from a megawatt-scale solar PV plant. The proposed method is used to analyze the power variability of Yelesandra PV power plant located in the state of Karnataka, India.

Developing a GIS based plume rose for industrial chemical incident preparedness and response

The variable nature of wind speed and direction affects the critical zones of chemical incidents (spills and effluents). We describe a method to develop a GIS based “plume rose” using its corresponding wind rose to map the areas that might be affected by a chemical release incident. The plume rose can thus be used in the preparation and response phases of emergency management for an industrial chemical incident. In this study we examine an industrial region in Bangalore, India and show that seasonal variation in winds significantly change the nature (size and direction) of the plume rose. The annual plume rose is coarse and inadequate for effective planning and response for this location. Thus the GIS based monthly plume-rose is more effective for planning and response management.

A simple explicit model approximating the relationship between speed and density of vehicular traffic on urban roads

With the increase in simulation of urban environments for the purpose of planning, modelling vehicular traffic has become important. Since empirical evidence on traffic flow is relatively sparse, models are being increasingly used for planning urban roads and environments. In this paper, a simple, explicit model is proposed to approximate the speed versus density of vehicular traffic flow. The model, which uses two parameters derived from simple measurements of real-time traffic data, allows for a prediction of the approximate relationship for congested as well as uncongested vehicular traffic flow. The proposed model is especially useful in conditions where available data is sparse and can be invaluable for the modelling and simulation of urban environments.