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The generic nature of business excellence models and arbitrary approaches followed by organizations to achieve excellence has triggered new approaches to attain excellence; one such approach is to have country- and industry-specific model. World Energy Council has developed an Energy Trilemma Index, which gives relative energy performances of almost 125 countries based on comprehensive energy matrix (affordability, availability and environment impact). Presently, India ranks at 91 as per this index thereby making this sector prudent case for specific excellence model for sector’s overall excellence. The purpose of this paper is to propose European Foundation for Quality Management (EFQM) model with Indian thermal power generating sector specific factors.

The study followed a research approach that combines literature review, qualitative and quantitative techniques. This includes analysis of the literature related to the subject, qualitative analysis to validate gap areas around EFQM model and identify factors critical to Indian thermal power sector. Quantitative analysis was done using SmartPLS 3.2.7 software for structural equation modeling–partial least square.

The research proposes inclusion of Indian thermal power generating sector specific factors in EFQM model, which in turn portrays balanced set of results and corresponding enablers for achieving excellence in the sector. The biggest take away will be sustained and effective contribution toward society and environment by this sector.

This is first of its kind study in India and globally for thermal power generating sector. It will trigger quality consciousness among power generating companies. For India, such excellence mission will definitely help nation to improve efforts toward 24×7 electricity and electricity to all.

The purpose of this paper is to measure technical efficiency of Indian thermal power sector employing the recent by-production approach.

The by-production approach is used in conjunction with data from the Central Electricity Authority (CEA) of India to compute the output-based Färe, Grosskopf, Lovell (FGL) efficiency index and its decomposition into productive and environmental efficiency indexes for the ITPPs

The authors show that given the aggregated nature of data on coal reported by CEA, CEA’s computation of CO₂ emissions through a deterministic linear formula that does not distinguish between different coal types and the tiny share of oil in coal-based power plants, the computed output-based environmental efficiency indexes are no longer informative. Meaningful measurement of environmental efficiency using CEA data is possible only along the dimension of the coal input. Productive efficiency is positively associated with the engineering concept of thermodynamic/energy efficiency and is also high for power plants with high operating availabilities reflecting better management and O&M practices. Both these factors are high for private and centrally owned as opposed to state-owned power-generating companies. The example of Sipat demonstrates the importance of (ultra)supercritical technologies in increasing productive and thermodynamic efficiencies of the ITPPs, while also reducing CO₂ emitted per unit of the net electricity generated.

This paper uses the by-production approach for the first time to measure technical efficiency of ITPPs and highlights how the nature of the Indian data impacts on efficiency measurement.

A systems perspective of waste management allows an integrated approach not only to the five basic functional elements of waste management itself (generation, reduction, collection, recycling, disposal), but to the problems arising at the interfaces with the management of energy, nature conservation, environmental protection, economic factors like unemployment and productivity, etc. This monograph separately describes present practices and the problems to be solved in each of the functional areas of waste management and at the important interfaces. Strategies for more efficient control are then proposed from a systems perspective. Systematic and objective means of solving problems become possible leading to optimal management and a positive contribution to economic development, not least through resource conservation. India is the particular context within which waste generation and management are discussed. In considering waste disposal techniques, special attention is given to sewage and radioactive wastes.

The purpose of this paper is to evaluate the utility-level productivity changes in Indian electricity sector during a period that witnessed structural reforms through several landmark regulatory changes.

A transformed fixed-effect stochastic frontier panel approach accounting for time-invariant unobserved heterogeneity is employed to evaluate the productivity changes, and the inefficiency level in 98 utilities spanning over the years 2001–2010. A flexible translog production model is modeled and estimated, and decomposition of productivity into components of changes in efficiency, scale technology and price effect is computed.

The empirical findings obtained from the present study suggest that the utility-level productivity in Indian electricity sector has generally declined during the observed period of 2001–2010 specifically after the implementation of Electricity Act 2003. Also, it is estimated that the state-level un-bundling of the electricity sector is not significantly associated with utility-level efficiency change. Furthermore, efficiency improvements attributable to increased competition are observed only in the case of smaller gas-based generating utilities.

Earlier studies on the productivity evaluation of Indian electricity industry have applied the non-parametric data envelopment analysis approach, which has several limitations. The novelty of the paper lies in the fact that this paper is one of the first attempts that implement transformed fixed-effect stochastic frontier panel approach and thus disentangle unobserved heterogeneity from inefficiency. Furthermore, it is the only paper that analyzes 98 utilities (51 generating utilities, 38 transmission and distribution licensees and 9 vertically integrated utilities) in a single framework during the period 2001–2010.

This paper studies the efficiency of Indian coal-fired thermal power plants (CTPPs) in by-production of electricity and particulates also known as Suspended Particulate Matter (SPM).

A non-radial directional distance function is optimized using data envelopment analysis to enumerate the overall inefficiency of CTPPs and its components in recent times. Further, second-stage regression analysis is conducted to identify factors that affect the inefficiency of plants.

The low inefficiency score for electricity generation suggests that most CTPPs operate close to the good output frontier. A high degree of emissions inefficiency is a challenge for Indian CTPPs. Ever-rising coal use inefficiency is a hindrance to control SPM emissions. The second stage regression analysis concludes that factors like ownership and capacity utilization play vital roles in determining a plant’s inefficiency level. Privately owned CTPPs have performed better in terms of technical inefficiency and emission inefficiency than plants owned by Central and State governments.

To the best of the authors’ knowledge, this study is one of the few published works that benchmark the productive and environmental performance of Indian CTPPs.

The study aims to identify the possible risk factors for electricity grids operational disruptions and to determine the most critical and influential risk indicators.

A multi-criteria decision-making best-worst method (BWM) is employed to quantitatively identify the most critical risk factors. The grey causal modeling (GCM) technique is employed to identify the causal and consequence factors and to effectively quantify them. The data used in this study consisted of two types – quantitative periodical data of critical factors taken from their respective government departments (e.g. Indian Meteorological Department, The Central Water Commission etc.) and the expert responses collected from professionals working in the Indian electric power sector.

The results of analysis for a case application in the Indian context shows that temperature dominates as the critical risk factor for electrical power grids, followed by humidity and crop production.

The study helps to understand the contribution of factors in electricity grids operational disruptions. Considering the cause consequences from the GCM causal analysis, rainfall, temperature and dam water levels are identified as the causal factors, while the crop production, stock prices, commodity prices are classified as the consequence factors. In practice, these causal factors can be controlled to reduce the overall effects.

From the results of the analysis, managers can use these outputs and compare the risk factors in electrical power grids for prioritization and subsequent considerations. It can assist the managers in efficient allocation of funds and manpower for building safeguards and creating risk management protocols based on the severity of the critical factor.

The research comprehensively analyses the risk factors of electrical power grids in India. Moreover, the study apprehends the cause-consequence pair of factors, which are having the maximum effect. Previous studies have been focused on identification of risk factors and preliminary analysis of their criticality using autoregression. This research paper takes it forward by using decision-making methods and causal analysis of the risk factors with blend of quantitative and expert response based data analysis to focus on the determination of the criticality of the risk factors for the Indian electric power grid.

This paper aims to study the changes in productivity for 25 state‐owned coal‐fired power plants (CFPPs) over a period of seven years (2003‐2010).

The methodology that is utilized in the study follows a non‐parametric approach of data envelopment analysis (DEA) and uses the Malmquist index to estimate the change in productivity of panel samples. In the calculations, the study considers installed capacity, fuel, labour, electricity used, and average operational time as inputs and considers net electricity produced as output.

The results indicate that the average total factor productivity regressed during the investigation period at an annual rate of 2 percent. The decrease in productivity is equally attributed to the technical efficiency change and technological change components, with an average decline in productivity of 1 percent per year. A plant‐wise analysis demonstrates that the Parichha plant recorded an average increase in productivity of 3.9 percent per year that was mainly driven by the technical efficiency change component (4.2 percent).There is little variation in the productivity of small‐size plants when compared with medium and large‐size plants. The productivity of multivaried plants is comparatively lower than BHEL (Bharat Heavy Electricals Limited) make plants.

The impact of size, make and region on change in productivity is examined. This study recommends specific policies that can be implemented to increase the productivity of power plants. The study also provides a contemporary overview of Indian CFPPs that can aid energy planners and plant operators in the monitoring and detection of changes in productivity.

In the wake of the December 2015 Paris COP21 (Conference of Parties), and India's announced renewable energy commitments, Reliance Power is reviewing its renewable energy investments to arrive at a long term strategy for the role of renewable energy in its power generation portfolio and the financing of renewable projects. The case reviews the Indian government's policies to promote renewable energy; the evolution of the renewable energy sector; and Reliance Power's financing of renewable energy investments. The case requires identification of alternative long term strategies and their financing implications. This case serves as an introduction to renewable energy from the perspective of Reliance Power, a large private power generator of the country. These projects also provide a learning opportunity for Reliance Power to deal with fast evolving renewable technologies.

The Indian electricity sector was opened to the private sector under the IPP policy. The NTPC, India's largest and perhaps most efficient generator had to respond to the changing scenario. It set out to set up the Simhadri project in Andhra Pradesh, going beyond to original mandate. The IPP policy, its perversities, the background of the power sector, the problems there in and the response of NTPC are discussed. Case (B) discusses the issues related to Project Planning and Implementation.

Energy supply delivered via various energy projects is an important aspect of energy security for India. Managing supply through various capacity additions for providing continuous electricity 24×7 by 2019 is a significant challenge for the country. In this context, there is a need to assess the present situation of energy generation from the traditional energy projects that are being installed for the purpose of capacity addition. Thus, the purpose of this paper is to develop an inquiry model based on situation-actor-process (SAP), learning-action-performance (LAP) for the Indian energy and power sectors to analyze the status of the supply side of energy security.

A SAP-LAP model is used to synthesize the situations of both the energy and power sectors. For both systems, inquiry- and matrices-based SAP-LAP models have been considered for this purpose. The situation is presented for various issues related to the execution of different types of energy projects. Actors in these sectors are classified by those who are responsible and engaged in the execution of various energy projects. For demonstration purposes, only a thermal energy project is highlighted in this case study. Based on the synthesis of SAP elements, various LAP elements are analyzed which leads to lessons that may be learnt from the case. Suitable actions are identified, followed by an assessment of their impact on the performance of the energy projects.

By developing a framework for a SAP-LAP model for the assessment of energy security, it was found that both sectors need more investment for their sustainable growth and that the actors identified should be proactive in their decision making. Decision making should be based on the sustainable management practices of life cycle management and life cycle costing for the better utilization of energy resources to strengthen overall energy security.

The SAP-LAP analysis is used to explain the supply side of energy security in a managerial context, as applied in the case of the Indian energy and power sectors. However, some other quantitative multiple-criteria decision-making techniques like the preference ranking organization method for enrichment of evaluations, the complex proportional assessment of alternatives, the analytic hierarchy process or qualitative interactions assessment techniques such as interpretive structural modeling (ISM), total interpretive structural modeling (TISM) or the interpretive ranking process can also be explored for the development of an energy security framework.

The synthesis of SAP leads to LAP, which bridges the gap by suggesting improvement actions based on learning from the present situation of power supply, from actors in the industry and from existing processes. The model presents the situation of energy security in terms of the timely execution of energy projects and their impacts on the gross domestic product of the country.

The framework for learning can provide information to the various stakeholders, investors and sector organizations inquiring about various issues related to energy projects and supporting the idea for energy security and sustainability.

The SAP-LAP model is a novel approach for analyzing the present status of energy supply performance in a single model, which can act as the support for decision making in conflicting situations, specifically the conflicting nature of the Indian energy and power sectors.