Analysis of interactions among variables of renewable energy projects:a case study on renewable energy project in India

This study highlights the variables associated with the implementation of renewable energy (RE) projects for sustainable development in India, by using an interpretive structural modeling (ISM) - based approach to model variables' interactions, which impact RE adoption. These variables have been categorized under enablers that help to enhance implementation of RE projects for sustainable development. A major finding is that public awareness regarding RE for sustainable development is a very significant enabler. For successful implementation of RE projects, it has been observed that top management should focus on improving highdriving power enablers (leadership, strategic planning, public awareness, management commitment, availability of finance, government support, and support from interest groups).

A sustainable supply chain study of the Indian bioenergy sector

In India, more than one third of the population do not currently have access to modern energy services. Biomass to energy, known as bioenergy, has immense potential for addressing India’s energy poverty. Small scale decentralised bioenergy systems require low investment compared to other renewable technologies and have environmental and social benefits over fossil fuels. Though they have historically been promoted in India through favourable policies, many studies argue that the sector’s potential is underutilised due to sustainable supply chain barriers. Moreover, a significant research gap exists. This research addresses the gap by analysing the potential sustainable supply chain risks of decentralised small scale bioenergy projects. This was achieved through four research objectives, using various research methods along with multiple data collection techniques. Firstly, a conceptual framework was developed to identify and analyse these risks. The framework is founded on existing literature and gathered inputs from practitioners and experts. Following this, sustainability and supply chain issues within the sector were explored. Sustainability issues were collated into 27 objectives, and supply chain issues were categorised according to related processes. Finally, the framework was validated against an actual bioenergy development in Jodhpur, India. Applying the framework to the action research project had some significant impacts upon the project’s design. These include the development of water conservation arrangements, the insertion of auxiliary arrangements, measures to increase upstream supply chain resilience, and the development of a first aid action plan. More widely, the developed framework and identified issues will help practitioners to take necessary precautionary measures and address them quickly and cost effectively. The framework contributes to the bioenergy decision support system literature and the sustainable supply chain management field by incorporating risk analysis and introducing the concept of global and organisational sustainability in supply chains. The sustainability issues identified contribute to existing knowledge through the exploration of a small scale and developing country context. The analysis gives new insights into potential risks affecting the whole bioenergy supply chain.

Enhanced renewable energy adoption for sustainable development in India:interpretive structural modeling approach

Poverty alleviation and social upliftment of rural India is closely linked with the availability and use of energy for development. At the same time, sustainable supply of clean and affordable renewable energy sources is required if development is to be sustainable, so that it does not cause any environmental problems. The purpose of this paper is to determine the key variables of renewable energy implementation for sustainable development, on which the top management should focus. In this paper, an interpretive structural modeling (ISM) - based approach has been employed to model the implementation variables of renewable energy for sustainable development. These variables have been categorized under ‘enablers’ that help to increase the implementation of renewable energy for sustainable development. A major finding of this research is that public awareness regarding renewable energy for sustainable development is a very significant enabler. In this paper, an interpretation of variables of renewable energy for sustainable development in terms of their driving and dependence powers has been examined. For better results, top management should focus on improving the high-driving power enablers such as leadership, strategic planning, public awareness, top management support, availability of finance, government support, and support from interest groups.

Role of community acceptance in sustainable bioenergy projects in India

Community acceptance has been identified as one of the key requirements for a sustainable bioenergy project. However less attention has been paid to this aspect from developing nations and small projects perspective. Therefore this research examines the role of community acceptance for sustainable small scale bioenergy projects in India. While addressing the aim, this work identifies influence of community over bioenergy projects, major concerns of communities regarding bioenergy projects and factors influencing perceptions of communities about bioenergy projects. The empirical research was carried out on four bioenergy companies in India as case studies. It has been identified that communities have significant influence over bioenergy projects in India. Local air pollution, inappropriate storage of by-products and credibility of developer are identified as some of the important concerns. Local energy needs, benefits to community from bioenergy companies, level of trust on company and relationship between company and the community are some of the prime factors which influence community's perception on bioenergy projects. This research sheds light on important aspects related to community acceptance of bioenergy projects, and this information would help practitioners in understanding the community perceptions and take appropriate actions to satisfy them. © 2014 Elsevier Ltd.

Comparative performance between two photogrammetric systems and a reference laser tracker network for large-volume industrial measurement

This paper determines the capability of two photogrammetric systems in terms of their measurement uncertainty in an industrial context. The first system – V-STARS inca3 from Geodetic Systems Inc. – is a commercially available measurement solution. The second system comprises an off-the-shelf Nikon D700 digital camera fitted with a 28 mm Nikkor lens and the research-based Vision Measurement Software (VMS). The uncertainty estimate of these two systems is determined with reference to a calibrated constellation of points determined by a Leica AT401 laser tracker. The calibrated points have an average associated standard uncertainty of 12·4 μm, spanning a maximum distance of approximately 14·5 m. Subsequently, the two systems’ uncertainty was determined. V-STARS inca3 had an estimated standard uncertainty of 43·1 μm, thus outperforming its manufacturer's specification; the D700/VMS combination achieved a standard uncertainty of 187 μm.