Search

Because textile industries are intensely water-consuming and generate a huge quantity of wastewater, the present study examines the scope of using solar thermal technology to treat wastewater from textile industries. A hybrid technology, comprising a compound parabolic concentrator-based solar thermal system in conjunction with a Membrane Distillation (MD) system, is experimented with for wastewater treatment in textile industries. The MD system requires a water temperature of around 90 °C for efficient functioning. The advanced MD technology using waste heat combined with solar heat to meet the system's thermal load is technologically evaluated for an experimental textile industry in India. Moreover, the present study critically analyses the techno economics of the proposed hybrid technology. A detailed financial analysis has revealed that, besides technological superiority, the recommended technology is also financially rewarding for wastewater treatment in the textile industry. To cope with the delayed payback period, financial incentives are recommended so that the system becomes a lucrative technological option. [ABSTRACT FROM AUTHOR]

Given the concern for maintaining voltage stability in power systems integrated with renewable power systems due to a mismatch in generation and demand, there remains a need to invoke flexible alternating current transmission system (FACTS) devices in the distribution network. The present paper deals with identifying the locations of placement of a static var compensator in an experimental IEEE 14-bus system; the voltage drop in different buses in an IEEE 14-bus system is calculated by the standard formula. The total voltage drop in the network (TVDN) is also calculated as a reference. The ranking of buses in order of decreasing voltage drop is made, and the weak buses are identified as those showing the maximum or near-maximum voltage drop for the installation of a Static Var Compensator (SVC). The optimum usable size is calculated using a Genetic Algorithm approach to optimize the installation cost. After size optimization, installing a 2 MW solar generator is considered for the weak and most potential bus, which suffers from voltage drops or power loss. Based on the generator at the weakest bus, the total power loss in the network is calculated and compared with a similar method to assess the efficiency of the proposed model. Thus, the voltage stability enhancement problem is solved by applying a Genetic algorithm (GA) to optimize SVC size and using the Total Voltage Drop in Network (TVDN) method to identify weak buses in the systems. It is found that the performance of the proposed system is comparable with another existing system. It is further observed that a gain in power loss to 6.56% is achievable by adopting the proposed strategy, and the gain is better than the other system. [ABSTRACT FROM AUTHOR]

This paper analyzes the potential of solar thermal systems for being employed for process heating in cotton-based textile industries. The technological capability of a flat plate collector (FPC) to meet the solar industrial process heating (SIPH) requirement in yarn production is assessed. Moreover, the usability of a parabolic trough collector (PTC) in meeting the technological mandates of SIPH in fabric processing units is critically examined. Further, this paper reports the findings of a study on the potential cost advantage of solar process heating over the conventional process heating practices in cotton-based textile industries. The approach involves the selection of the locations of sample textile industries and the employable solar collector technologies, as well as assessment of financial reward, if any. Eight different cotton-based textile industries located in different geographical domains (in India) are selected. The selected textile industries are situated within the textile hubs existing in different states across India. Analysis of technoeconomic benefit derivable in selected textile industries using FPC for hot water generation and PTC for steam generation is presented. In the case of FPC-based SIPH systems, the maximum value of solar fraction is estimated to be 0.30 and the corresponding estimation for the levelized cost of useful thermal energy (LCUTE) delivered comes out as INR 790/GJ to INR 1020/GJ. On the other hand, in case of parabolic-trough-solar-concentrator-based SIPH systems, LCUTE is estimated in the range of INR 1030/GJ to INR 1610/GJ. From a critical analysis of financial viability in consideration of related factors such as payback time and return on investment in SIPH, it appears that the SIPH systems for hot water generation may be a good choice, whereas SIPH systems for steam generation are seen to have longer payback periods and lower returns on investment, and, therefore, it seems that adequate financial support from central and state governments with additional supports from bilateral or multilateral organizations may enable them to become a sustainable technology option. [ABSTRACT FROM AUTHOR]

In this paper, the quality of a source of drinking water is assessed by measuring eight water quality (WQ) parameters using 710 samples collected from a water-stressed region of India, Jodhpur Rajasthan. The entire sample was divided into ten groups representing different geographic locations. Using American Public Health Association (APHA) specified methodology, eight WQ parameters, viz., pH, total dissolved solids (TDS), total alkalinity (TA), total hardness (TH), calcium hardness (Ca-H), residual chlorine, nitrate (as NO3−), and chloride (Cl−), were selected for describing the water quality for potability use. The quality of each parameter is examined as a function of the zone. Taking the average parametric values of different zones, a unique number was used to describe the overall quality of water. It was found that the average value of each parameter varies significantly with zones. Further, we used neural network (NN) modeling to map the nonlinear relationship between the above eight parametric inputs and the water quality index as the output. It can be observed that the NN designed in the present work acquired sufficient learning and can be satisfactorily used to predict the relational pattern between the input and the output. It can further be observed that the water quality index (WQI) from this work is highly efficient for a successful assessment of water quality in the study area. The major challenge to uniquely describing the drinking water quality lies in understanding the cumulative effect of various parameters affecting the quality of water; the quantified figure is subjected to debate, and this paper addresses the difficulty through a novel approach. The framework presented in this work can be automated with appropriate equipment and shall help government agencies understand changing water quality for better management. [ABSTRACT FROM AUTHOR]