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Abstract This study aims at to make a heuristic analysis of energy efficiency performance of Indian paper industry in a non-parametric production theoretic approach. Using the data for 2004–05 to 2013–14, radial and non-radial variants of DEA were employed to estimate energy saving potential and identify the relative position of paper industry across the states. Preliminary analysis in terms of energy intensity scores showed declining trends of energy intensity over the period of analysis for most of the states except states like Assam, Chhattisgarh, Kerala and Punjab where it does not decline much. Assuming a variable returns to scale (VRS) technology under the conditions of inherent heterogeneity and market imperfection, the slack-based measure (SBM) reported a much higher energy saving potential than reported by other measures in the study. Further by taking scale efficiency into account, the study documented the higher contribution of pure energy inefficiency in explaining the total energy inefficiency within the paper industry relative to scale inefficiency. Finally, the study recommends the propagation of energy efficiency program through a market-based and regulatory mechanism along with consolidation and technological advancement of individual units, in order to tap vast energy saving potential and thereby ensure the growth and environmental sustainability. Highlights • The paper examined the energy efficiency performance of Indian paper industry. • Both radial (BCC) and the non-radial (SBM) measures of energy efficiency, were applied. • BCC measure reported an energy saving potential of 16%. • SBM measure reported an energy saving potential of 24%, higher than BCC measure. • Scale efficiency implied the relatively higher contribution of pure energy inefficiency. [ABSTRACT FROM AUTHOR]

Abstract: India accounts for 4.5% of industrial energy use worldwide. This share is projected to increase as the economy expands rapidly. The level of industrial energy efficiency in India varies widely. Certain sectors, such as cement, are relatively efficient, while others, such as pulp and paper, are relatively inefficient. Future energy efficiency efforts should focus on direct reduced iron, pulp and paper and small-scale cement kilns because the potentials for improvement are important in both percentage and absolute terms. Under business as usual, industrial energy use is projected to rise faster than total final energy use. A strong focus on energy efficiency can reduce this growth, but CO2 emissions will still rise substantially. If more substantial CO2 emissions reductions are to be achieved then energy efficiency will need to be combined with measures that reduce the carbon intensity of the industrial fuel mix. [Copyright &y& Elsevier]

This paper investigates the relationship between financial development and access to electricity for rural and urban India by incorporating economic growth, trade, and foreign direct investment in energy production function. In doing so, we have applied autoregressive distributed lag bounds testing to examine long run cointegration between the variables by accommodating structural break(s) stemming in the series. Our empirical results indicate the presence of cointegration association between access to electricity and its determinants. We note that financial development enhances access to electricity in rural India but declines it in urban India. Economic growth has positive effect on access to electricity. Trade openness and foreign direct investment lower access to electricity in rural India. In urban India, trade openness and foreign direct investment increase access to electricity. The association between financial development and access to electricity is inverted-U shaped for rural and urban India. This paper would present new policy direction for Indian government to enhance access to electricity by using financial development as an economic tool. • Financial development and access to electricity have a strong linkage. • In India financial development enhances access to electricity in rural area but has adverse effect in urban area. • Rise in economic growth of India has increased the access to electricity. • Growth of Trade Openness and Foreign Direct investment increase access to electricity. [ABSTRACT FROM AUTHOR]

Abstract Addressing environmental concerns alongside economic development and energy transitions is a challenge for all countries and effective policy making requires approaches that can balance all these concerns. In this paper, combining a range of modeling methodologies is proposed as a way of addressing these questions in an integrated manner. The choice of models to be used would depend on the specific characteristics of the system and region being studied. One possible combination of models is discusses in this paper for the specific case of India. The Integrated Modeling Framework (IMF) proposed combines three modeling approaches – i) index decomposition to estimate impacts of structural changes in the economy, ii) constrained optimization to estimate least cost fuel options for the power sector, iii) input-output analysis to estimate economic impacts. The model results indicate that the mode of investment for climate change mitigation is a significant determinant of the impact on economic growth, incomes, and income distribution in India. In some scenarios, higher investments in green energy negatively affects low income households significantly more as compared to other households. The paper also demonstrates how the IMF can be used to determine the reasons for and therefore alleviate the negative impacts. Highlights • An Integrated Modeling Framework (IMF) combining three modeling methods is presented. • IMF built for India, but applicable for other developing countries also. • IMF useful to study balance between energy, environment, economy, and equity. • Negative trade-off between equity and renewable energy transition in some scenarios. • IMF useful for identifying ways to alleviate the negative trade-off. [ABSTRACT FROM AUTHOR]

Microgrid is a promising way to integrate renewable distributed generation into the electric power sector, which has received widespread attention. In this paper, a uniform capacity-constrained optimization model under different power purchase and sale price contracts is developed to explore the optimal green investment strategy for grid-connected microgrid (GCM) with three configuration types. The impact of renewable energy source endowment and incentive policy is focused when macrogrid's generators emit more pollution than GCM's non-renewable generators, such as in China and India. The results show that: (1) GCM with renewable generation can only be invested in a site with relatively abundant renewable endowment; (2) carbon tax effectively promotes the deployment of GCM with renewable generation and achieves carbon emission abatement, but excessive carbon tax cannot incentive investment in the most desired GCM type; (3) a subsidy trap is found under feed-in tariff (FIT) subsidy, which implies that the fade-out or exit of FIT subsidy is beneficial for microgrid's healthy development; (4) and the comparisons under different price contracts emphasize the importance of macrogrid providing non-discriminatory access to feed-in and feed-out services to microgrid. • Investment strategy is explored for grid-connected microgrid (GCM) with three types. • Renewable source endowment and incentive policy determine the investment for GCM. • Excessive carbon tax cannot incentive investment in the most desired renewable GCM. • The fade-out or exit of FIT subsidy is beneficial for healthy GCM deployment due to the subsidy trap. • Emphasizing the importance of macrogrid providing non-discriminatory services to GCM. [ABSTRACT FROM AUTHOR]

Bifacial photovoltaic technology is considered an emerging and promising PV technology. However, the unavailability of proven field data or efficient models prevents the stakeholders from going ahead with this technology. The currently available bifacial performance models have limitations; they are location specific, for a single bifacial PV module alone, or ground-level installed bifacial PV only. This paper develops an experimentally validated view factor-based optical model using the Cross-string rule to predict the power output and bifacial gain for bifacial PV power plants with good accuracy and low computation power and time. An optimal model for the best performance of bifacial PV at any location was also suggested by optimizing the parameters like the pitch, height of installations, and slope. The results show that the year-round performance of bifacial PV in cities in India's five climatic zones is 30.54%–34.93% higher than the monofiacial PV panels at an average ground albedo of 30%. Bi-annual tracking improved a bifacial PV's overall power output and bifacial gain. The financial indicators like Levelised cost of energy, Net present value, Discounted payback period, and Internal rate of return indicate higher financial gain from the bifacial PV power plant compared to monofacial PV power plant. • An experimentally validated novel model of a bifacial PV power plant is developed • Bifacial PV installation parameters are optimised for improved performance • The effect of bi-annual tracking on bifacial PV power plant performance is explored • Bifacial gain and financial indicators for six climatic zones in India are studied [ABSTRACT FROM AUTHOR]

With the advent of grid connected solar panels in India, the requirement of a separate mechanism for metering and billing is foreseen. The policy framework for addressing this need is under process in various states of India. In the smart grid pilot project at Puducherry, India, a simple net metering mechanism has been incorporated to evaluate and understand the performance of green energy generation through solar panels. The present paper draws a comparison between net metering and gross metering mechanisms, through the analysis of net meter data collected for three different types of consumers from the pilot project at Puducherry. Different scenarios have been evaluated to infer the impacts of specialized billing mechanisms as well as the payback periods on investment made for solar energy systems and the savings that is reflected in the monthly bills. Feed in tariff renders full credit to the renewable energy customers on their electricity bills for the amount of green power, which is sent back to the main grid. This simple mechanism of a credit system would prove to be the most important energy policy for a nation to encourage sustainable energy generation. Due to wide variations in tariffs, requirements and efficiency of utilities across the different states in India, a policy which can accommodate mechanisms of community net metering and aggregate net metering had become a necessity. The paper signifies the crucial and immediate necessity for a feasible and acceptable energy policy so as to realize the benefits of power from the sun. [ABSTRACT FROM AUTHOR]

Poor cost recovery rates and large subsidization of the agriculture and households by industrial and commercial users are two of the characteristics of the power sector in India. The paper applies a variety of linear and nonlinear unit root tests and a Kalman filter approach which can host time varying elasticities, to estimate the effects of various macroeconomic factors on the price elasticity for electricity in India during 1975–2013. The estimated price elasticity is −0.21 and the income elasticity is 0.41. The study finds that the electricity demand is affected by macroeconomic parameters such as trade and foreign direct investment. The findings of the study have implications to the policy makers and private investors who wish to invest in electricity supply utilities and infrastructure. The value of the estimated elasticity in the study is relatively smaller as compared to the previous studies reflecting, among other things, the fact that electricity demand is supply driven in India. • The Kalman filter approach hosts time varying elasticities. • The estimated price elasticity is -0.21. • The estimated income elasticity is 0.41. • Electricity demand is affected by trade and foreign direct investment. • Electricity demand is supply driven in India. [ABSTRACT FROM AUTHOR]

of a HOMER based techno-economic assessment of an electricity supply option based on a hybrid system comprising of a PV component, a diesel generator (DG) and electricity grid have been presented in this paper. The study includes analysis of electricity unavailability data for 132 locations in India spread over state capitals, district headquarters, municipal areas and villages. The values of Net Present Cost (NPC) and Cost of Electricity (CoE) have been estimated for 25 selected locations in the country and a comparison with corresponding values for conventional alternative (grid+DG) has also been presented. The study internalizes all relevant location specific parameters. The values of NPC and CoE are lower in the range of 9.5%–36.6% and 16%–33.6% respectively for the proposed system (grid+PV+DG) as compared to conventional system at all 25 locations considered. The inclusion of PV component results in reduced purchase of grid electricity and much lower hours of operation of DG. • Analyzed real-time hourly grid power supply outage status for outdoor telecom towers at 132 locations • Designed optimal hybrid systems for powering BTS in telecom towers at 25 selected locations in India, • Presented a detailed techno-economic comparison of solar PV based hybrid system for powering BTS • The values of NPC and CoE are lower in the range of 9.5%–36.6% and 16%–102.4% respectively for the hybrid system • The PV component results in reduced purchase of grid electricity, DG operation, electricity fed to grid, and CO 2 emissions [ABSTRACT FROM AUTHOR]

The rapid development in technology and changing food habits have drastically altered the cooking method in recent years. Electric ovens are dominating the cooking sector in bakeries, restaurants, and domestic cooking. India holds the second position in terms of revenue generated by the sales of cookers and ovens. The electrical energy requirements are also adding up with electricity-based cooking. In addition, solar energy-dependent solar cooking appliances are available in the market, but they come with their own set of merits and demerits. This paper discusses the new concept and development of an Electric-Solar hybrid cooking appliance. The implemented control mechanism in the fully-featured hybrid OTG (Oven, Toaster, & Griller) oven shows the simplicity and ease of using solar energy in conjunction with electrical energy. The experimental and numerical results show that the temperature distribution inside an electric-solar hybrid oven saves energy up to 51% and takes much less cooking time than electric ovens and solar cooking appliances when operating in hybrid mode. The STEPCO (Solar Thermal-Electric Powered Cooking Oven) oven has demonstrated potential for a relatively quick return on investment, with a payback period of around 2.3 years in hybrid mode and 3.7 years in solar mode. Experimental testing has shown that the hybrid mode of the STEPCO oven achieves an impressive efficiency of 63%, which is significantly higher than that of the electric and solar modes, which are only 35% and 4.0%, respectively. Additionally, the STEPCO oven has the environmental benefit of emitting very little CO 2 during the cooking process when used in hybrid mode and zero CO 2 emissions when used in solar mode. • A novel cooking oven is designed and developed to operate in three modes. • CFD analysis is used to validate the temperature inside the oven in hybrid mode. • The hybrid oven saves up to 51% of energy and reduces annual CO 2 emissions. • The oven has shorter payback times of 2.3 and 3.7 years in hybrid and solar modes. • STEPCO oven has an efficiency of 63% in hybrid, more than solar and electric modes. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents for the first time correlations for greenhouse gas (GHG) emissions from small hydropower schemes in India. In this paper an attempt has been made to develop life cycle GHG emissions correlations for three different types of small hydropower schemes (run-of river, canal based and dam-toe) in India. It has been found out that GHG emissions depend on the head and capacity of the small hydropower project. The results obtained from correlations show good agreement with the estimated results using EIO-LCA (Economic Input–Output-Life Cycle Assessment) technique. These correlations may be useful for the development of new small hydropower (SHP) schemes, as they can be used to predict life cycle GHG emissions based on capacity, head and type of SHP schemes. [Copyright &y& Elsevier]

Abstract: The location selection for thermal power plant (TPP) is a strategic decision, which has significant impact on economic operation of the plant and sustainable development of the region. Further, ranking of the alternative locations, and selection of the most suitable and efficient locations for TPPs is an important multi-criteria decision making problem. This paper proposes an STEEP-fuzzy AHP-TOPSIS based framework for evaluation and selection of optimal locations for TPPs. Potential feasible locations are identified based on social, technical, economical, environmental, and political (STEEP) considerations. The fuzzy AHP, a multi-criteria decision making method, has been applied to determine the weights of qualitative and quantitative criteria impacting location selection process. The fuzzy AHP is adapted to model the linguistic vagueness, ambiguity, and incomplete knowledge. Furthermore, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), a ranking multi-criteria decision making method, has been applied to rank the alternative locations based on their overall performance. The applicability of proposed method is demonstrated by a case study of TPPs location selection in India. The paper brings out a more accurate, effective, and systematic decision support tool for decision makers to conduct the evaluation process and to select optimal locations for TPPs. [Copyright &y& Elsevier]

Wind farm integration with existing main electricity grid is very difficult due to the uncertainty of wind speed, which affects the balancing nature of electrical system. In current competitive power market, it is very challenging to maintain the quality of delivered power to the customers and also maximization of profit for delivered power after integration of such type of intermittent renewable energy sources. This paper presents an efficient optimization approach to achieve the maximum social welfare and profit of consumers as well as maximum profit of generation companies, by minimizing the adverse effect of imbalance cost which is the product of uncertain wind penetration. The optimal placement of Thyristor Controlled Series Compensator (TCSC) & Unified Power Flow Controller (UPFC) devices, with optimal wind generator placement has been incorporated in the proposed method. The real time data for actual and forecasted wind speed has been collected from different identified places of India. Modified IEEE 14 bus and modified IEEE 30 bus test systems are considered in this work for validating and analyzing the effectiveness of the proposed approach. • An optimization approach to optimally allocate TCSC and UPFC with wind farms. • Approach has developed for maximizing social welfare and system profit. • Adverse effect of imbalance cost has been minimized by the proposed approach. • Real time wind speed data has been taken for study the presented approach. • Deregulated power environment is considered for assessing the approaches. [ABSTRACT FROM AUTHOR]

This paper presents an economic and enhanced technological solution for rural electrification of a village Jalalabad, in Ghaziabad District, Uttar Pradesh state, India. The considered system concentrates on optimal sizing of an integrated renewable energy system (IRES) with grid provide a more continuous power supply with respect to the existing system. The different available sources Solar Photo Voltaic (SPV), Battery Energy Storage System (BESS), and a time constrained grid are considered in designing of the system. The system size optimization, sensitivity analysis and techno-economic viability has been done by using a standard software tool HOMER to fulfil the demand of the study area under consideration. A demand response strategy has been applied for the different load profiles. The configuration with the lowest Levelized Cost of Electricity (LCOE) and Total Net Present Cost (TNPC) with maximum value of renewable fraction (RF) has been considered as optimum. This ensures the minimization of the Carbon dioxide (CO 2) emission. A comparative analysis has been presented showing the impact of the demand response on the LCOE and NPC as well as the system size. The economic analysis has been done according to four different cases obtained by varying the fraction (β NELS) of non-essential load shifting. It has been observed that the value of LCOE with the strategy of demand response and optimal resource management under which β NELS = 0.25 is reduced Rs. 11.23/kWh and Rs. 8.36/kWh with the grid tariff Rs.10/kWh and Rs.6/kWh respectively while the value of TNPC Rs. 1.99 × 107 and Rs. 1.48 × 107 respectively with the maximum renewable fraction of 31.06. An exhaustive performance analysis has been done and the obtained results show the effectiveness of proposed resource and demand management to provide 24 × 7 supply with limited, time constrained grid availability. • An economic, enhanced solution for PV & BESS with grid is determined in this study. • Demand response and resource optimization is used to achieve 24 × 7 power supply. • Optimal sizing, sensitivity analysis and energy cost with grid price is analyzed. • Demand response strategy has been used to reduce LCOE & TNPC. • It is found that LCOE & TNPC decrease with fractional non-essential load shift. [ABSTRACT FROM AUTHOR]

This paper investigates the producer-level temporal dynamics of total factor productivity and operational performance changes in coal- and gas-based generators during the 2000–20013 period of major structural reforms in the downstream utilities in India. The total factor productivity is estimated using a recently developed improvement in the Stochastic Frontier panel method that controls for time-invariant unobserved heterogeneity, and the productivity change is decomposed into components of changes in technology frontier, efficiency, scale and allocation. A unique dataset of station-level data for coal and gas plants, that represents about two-thirds of all power generation in India during this period, is constructed for the analysis. The study shows that while there is improvement in the coal generator productivity at the mean rate of 0.20 % per year that converges towards a point of higher efficiency for most plants, the gas generators show a trend of stagnant efficiency and declining total factor productivity at the mean rate of − 0.80 % per year. Unbundling and multi-dimensional utility reform indices are significantly associated with improvement in thermal efficiency and capacity utilization for coal generators. In contrast, utility reforms shows no significant positive influence on gas generators, instead a decline in capacity utilization is observed following unbundling. • Temporal productivity dynamics of Indian coal and gas fired generators is estimated. • Flexible production function separately estimated for coal and gas generators. • TFP of coal plants improved and gas plants declined with downstream utility reforms. • Increase in thermal efficiency and PLF of coal plants linked to utility reforms. • Fuel shortage partly explain stranded capacity and generator productivity losses. [ABSTRACT FROM AUTHOR]

This paper proposes a new hybrid season specific approach to incorporate the seasonality effect in short term load forecasting (STLF). A new season specific similarity concept (SSSC) is utilized to perceive the season specific meteorological necessities (seasonality effect) and integrates them in STLF process. The proposed approach is based on firefly algorithm (FA), support vector machine (SVM) and the new SSSC. The study is conducted in Assam, India and the proposed approach is designed to forecast load during different seasonal native meteorological conditions. Four case studies in four different seasons of a calendar year are carried out. The consideration of seasonality effect is found essential for a precise STLF under diverse seasonal meteorological conditions. This is because the electric load is influenced by different meteorological variables depending on different seasons. The numerical application of the proposed approach demonstrates higher forecasting accuracy in comparison to traditional approach of integrating temperature into STLF without considering any seasonality effect. To uphold the efficacy of the proposed approach, forecasting results are also compared with another traditional approach of integrating multiple meteorological variables into STLF without any seasonal considerations. Hence, the robustness of proposed approach is approved by its superior forecasting ability in all cases. • Offers a season specific approach for short term load forecasting in the study area. • Evaluation of season specific effective meteorological variables on load demand. • Proposes new season specific similarity concept to integrate the seasonality effect. • Integration of ineffective meteorological variable misguide the forecasting process. • The results affirm the superiority of the proposed approach in load forecasting. [ABSTRACT FROM AUTHOR]

Abstract Integrated assessment models are extensively used in the analysis of climate change mitigation and are informing national decision makers as well as contribute to international scientific assessments. This paper conducts a comprehensive review of techno-economic assumptions in the electricity sector among fifteen different global and national integrated assessment models. Particular focus is given to six major economies in the world: Brazil, China, the EU, India, Japan and the US. The comparison reveals that techno-economic characteristics are quite different across integrated assessment models, both for the base year and future years. It is, however, important to recognize that techno-economic assessments from the literature exhibit an equally large range of parameters as the integrated assessment models reviewed. Beyond numerical differences, the representation of technologies also differs among models, which needs to be taken into account when comparing numerical parameters. While desirable, it seems difficult to fully harmonize techno-economic parameters across a broader range of models due to structural differences in the representation of technology. Therefore, making techno-economic parameters available in the future, together with of the technology representation as well as the exact definitions of the parameters should become the standard approach as it allows an open discussion of appropriate assumptions. Highlights • Comparison of technology representation and techno-economic parameters of 15 IAMs. • Structural differences in representing technology in IAMs are identified. • Methods of projecting techno-economic parameters differ across IAMs. • Strict harmonization of techno-economic parameters across models is difficult. • Recommendation to publish techno-economic parameters and technology representation. [ABSTRACT FROM AUTHOR]

Abstract: India’s aspiration for economic growth has consequences for energy growth and CO2 emissions. This paper examines India’s need for energy with 20 year perspectives. From an earlier paper by K. Parikh et al. (2009), demand scenario are examined from the supply perspectives ranging from coal, hydrocarbon, nuclear, hydrogen, hydro and other renewable etc. None of these are substantial and India will have to rely on imports. The need for energy has to be reduced by a drive for energy efficiency and renewable energy. Government programmes for the above are also commented upon. Though India’s CO2 emissions are unlikely to grow very much due to energy scarcity and energy mix the article examines the potential to reduce CO2 emissions and the associated costs involved in various options. It finds that 30% reduction in CO2 emissions by 2030 is feasible but would involve additional costs. The most promising option is to reduce energy demand by various measures to increase energy use efficiency in production and consumption. [Copyright &y& Elsevier]

Abstract: India''s energy challenges are multi-pronged. They are manifested through growing demand for modern energy carriers, a fossil fuel dominated energy system facing a severe resource crunch, the need for creating access to quality energy for the large section of deprived population, vulnerable energy security, local and global pollution regimes and the need for sustaining economic development. Renewable energy is considered as one of the most promising alternatives. Recognizing this potential, India has been implementing one of the largest renewable energy programmes in the world. Among the renewable energy technologies, bioenergy has a large diverse portfolio including efficient biomass stoves, biogas, biomass combustion and gasification and process heat and liquid fuels. India has also formulated and implemented a number of innovative policies and programmes to promote bioenergy technologies. However, according to some preliminary studies, the success rate is marginal compared to the potential available. This limited success is a clear indicator of the need for a serious reassessment of the bioenergy programme. Further, a realization of the need for adopting a sustainable energy path to address the above challenges will be the guiding force in this reassessment. In this paper an attempt is made to consider the potential of bioenergy to meet the rural energy needs: (1) biomass combustion and gasification for electricity; (2) biomethanation for cooking energy (gas) and electricity; and (3) efficient wood-burning devices for cooking. The paper focuses on analysing the effectiveness of bioenergy in creating this rural energy access and its sustainability in the long run through assessing: the demand for bioenergy and potential that could be created; technologies, status of commercialization and technology transfer and dissemination in India; economic and environmental performance and impacts; bioenergy policies, regulatory measures and barrier analysis. The whole assessment aims at presenting bioenergy as an integral part of a sustainable energy strategy for India. The results show that bioenergy technology (BET) alternatives compare favourably with the conventional ones. The cost comparisons show that the unit costs of BET alternatives are in the range of 15–187% of the conventional alternatives. The climate change benefits in terms of carbon emission reductions are to the tune of 110T C per year provided the available potential of BETs are utilized. [Copyright &y& Elsevier]

Abstract: Over the years, significant changes have taken place with regard to the type as well the quantity of energy used in Indian households. Many factors have contributed in bringing these changes. These include availability of energy, security of supplies, efficiency of use, cost of device, price of energy carriers, ease of use, and external factors like technological development, introduction of subsidies, and environmental considerations. The present paper presents the pattern of energy consumption in the household sector and analyses the causalities underlying the present usage patterns. It identifies specific (groups of) actors, study their specific situations, analyse the constraints and discusses opportunities for improvement. This can be referred to “actor-oriented” analysis in which we understand how various actors of the energy system are making the system work, and what incentives and constraints each of these actors is experiencing. It analyses actor linkages and their impact on the fuel choice mechanism. The study shows that the role of actors in household fuel choice is significant and depends on the level of factors – micro, meso and macro. It is recommended that the development interventions should include actor-oriented tools in energy planning, implementation, monitoring and evaluation. The analysis is based on the data from the national sample survey (NSS), India. This approach provides a spatial viewpoint which permits a clear assessment of the energy carrier choice by the households and the influence of various actors. The scope of the paper is motivated and limited by suggesting and formulating a powerful analytical technique to analyse the problem involving the role of actors in the Indian household sector. [Copyright &y& Elsevier]

Abstract: Coal is the abundant domestic energy resource in India and is projected to remain so in future under a business-as-usual scenario. Using domestic coal mitigates national energy security risks. However coal use exacerbates global climate change. Under a strict climate change regime, coal use is projected to decline in future. However this would increase imports of energy sources like natural gas (NG) and nuclear and consequent energy security risks for India. The paper shows that carbon dioxide (CO2) capture and storage (CCS) can mitigate CO2 emissions from coal-based large point source (LPS) clusters and therefore would play a key role in mitigating both energy security risks for India and global climate change risks. This paper estimates future CO2 emission projections from LPS in India, identifies the potential CO2 storage types at aggregate level and matches the two into the future using Asia-Pacific Integrated Model (AIM/Local model) with a Geographical Information System (GIS) interface. The paper argues that clustering LPS that are close to potential storage sites could provide reasonable economic opportunities for CCS in future if storage sites of different types are further explored and found to have adequate capacity. The paper also indicates possible LPS locations to utilize CCS opportunities economically in future, especially since India is projected to add over 220,000MW of thermal power generation capacity by 2030. [Copyright &y& Elsevier]

Abstract: A majority of the Indian population does not have access to convenient energy services (LPG, electricity). Though India has made significant progress in renewable energy, the share of modern renewables in the energy mix is marginal. This paper reviews the status and potential of different renewables (except biomass) in India. This paper documents the trends in the growth of renewables in India and establishes diffusion model as a basis for setting targets. The diffusion model is fitted tot the past trends for wind, small hydro and solar water heating and is used to establish future targets. The economic viability and green house gas (GHG) saving potential is estimated for each option. Several renewables have high growth rates, for example wind, Photovoltaic (PV) module manufacture and solar water heaters. New technologies like Tidal, OTEC, Solar thermal power plants and geothermal power plants are at the demonstration stage and future dissemination will depend on the experience of these projects. [Copyright &y& Elsevier]

Access to energy for cooking is one of the major challenges that rural India faces. Most of the rural households of North-Eastern India rely heavily upon fuelwood and traditional open-fire cookstoves for cooking activities. And everyday collection of fuelwood is time-consuming. Hence, women often gather fuelwood to make charcoal. While the use of charcoal has some advantages, it is not clear whether the investment of time in making charcoal is worthwhile. In this paper, we compare household time investments for fuelwood and charcoal production. The study is done using survey data on Napaam village situated in Sonitpur District of Assam, Northeast India. We developed a model to analyse fuelwood needed and time spent upon the introduction of improved cookstoves and/or charcoal production. This analysis reveals that improved cookstoves using fuelwood results in the least time expenditure on the production of cooking fuel. Whilst introducing charcoal marginally reduces the amount of fuelwood, but increases time spent on cooking, due to the time required to produce the charcoal. Hence, rural households who make their own charcoal spend more time on producing cooking fuel than those households relying on direct use of fuelwood. [ABSTRACT FROM AUTHOR]

Energy planning in many developing Asian countries has neglected the structure of energy demand and how it is likely to evolve as development takes its path. The limited availability of energy consumption data makes it very difficult to assess the energy savings potential at end-use level. Energy planning requires the formulation of a proper modelling framework that supports the definition of energy policies. From the different approaches available, Input - Output (I-O) models are particularly useful, since they allow considering different impacts that can be consistent with different energy policy options. This paper proposes a novel I-O modelling framework by introducing a bottom-up approach into an I-O model which is combined with technical data for the holistic assessment of energy efficient technologies in the residential sector, which can assist energy decision-makers of India on the appraisal of the future impacts of the current national energy saving targets. A large size platform of real data has also been gathered considering different data sources, namely the household building stock characterization, the number of operating days according to the climatic regions of India, the lifetime and the investment cost of equipment. Finally, the main results are discussed and future research opportunities are identified. [ABSTRACT FROM AUTHOR]

One of the key barriers to diffusion of domestic solar water heater in India is its high capital cost. Hence, there is a perception among people that it is not economically viable. The objective of this paper is to check the validity of this perception using net present value as a tool. An explicit formula has been developed from first principle to calculate the net present value of a domestic solar water heater which can be used globally. Scenario analysis has been conducted taking three scenarios: current, pessimistic and optimistic, to understand the spread in net present value. Taking probability of each scenario, expected net present value is calculated. The next objective is to go a further step to simulate using Monte Carlo simulation to attach a probability value with the net present value. Monte Carlo simulation model has been developed for risk assessment of solar water heaters. A range of values of all input variables have been considered assuming a normal distribution curve and based upon that a probability distribution curve of net present value is obtained. It was found that solar water heater is a viable option for east-coastal region of India. [ABSTRACT FROM AUTHOR]

In today's restructuring electricity market, short-term load forecasting (STLF) is an essential tool for the electricity utilities to predict future scenario and act towards a profitable policy. The electric load demand is highly influenced by the thermal inertia due to the climatic factors. These influential climatic factors are different in different regions. Therefore, it is necessary to have a region specific STLF model for load forecasting under regional climatic conditions. This paper proposes a regional hybrid STLF model utilizing SVM with a new technique, called grasshopper optimization algorithm (GOA), to evaluate its suitable parameters. This study is carried out in Assam, a state of India and proposed GOA-SVM model is targeted for forecasting the load under local climatic conditions. The proposed model uses the similar day approach (SDA) to satisfy the regional climatic requirements. The results of the proposed model show better accuracy comparing to results generated with classical STLF model of incorporating temperature universally as the only climatic factor. To further affirm the efficacy of the proposed model, same inputs are delivered in two alternative hybrid models, namely GA-SVM (GA with SVM) and PSO-SVM (PSO with SVM). The results indicate that the proposed model outperforms the other hybrid models. [ABSTRACT FROM AUTHOR]

India is rapidly growing in the economy and population leading to a continuous increase in electricity demand. The wind is a better energy source because of its negligible greenhouse gas emissions, cost competitiveness, price stability, and energy security. This paper presents Geospatial Information System (GIS) based methodology to characterise the offshore wind power potential in the western and the eastern coast of India with technical, economical, and marine ecosystem consideration. Spatial distribution of levelized production cost (LPC) and cost-supply curves was developed under different ocean conditions (human impact on marine ecosystem). The influence of project lifetime, discount rate, and assumptions about investment cost, annual energy production, and availability is presented using sensitivity analysis. Results show that total potential available along the shallow waters (50 m water depth) of Indian coast is approximately equal to 12.8% and 42% respectively of the existing renewable power and wind power capacity. In terms of wind resources and economic costs, the shallow waters of Gujarat and Tamil Nadu states are the best suitable regions for offshore wind power development. [ABSTRACT FROM AUTHOR]

The effects of greenhouse gas emissions, urban air pollution, and rising transport fuel prices, on the low-income capita in India, necessitate appropriate measures to ensure commodities are sustainably available. This paper presents a study whereby biodiesel blends produced from waste cooking oil are optimised for use in urban medium-duty commercial vehicles, accounting for factors of production capacity, economics, and approximated engine characteristics. An artificial neural network model, trained with experimental data, is used to predict performance, combustion, and emission parameters. The results for various biodiesel blends are applied to a standard driving cycle to obtain variations in key factors. A multi objective optimisation is carried out with engine operation parameters to arrive at optimised biodiesel blends varying between 25% and 81% based on different criteria such as minimising fuel cost, enhancing engine efficiency, and reducing emissions. Considerations when choosing blend concentration are discussed in light of different governmental targets. • Artificial neural network model for predicting engine performance using biodiesel. • Consideration of production, performance, economic, and emission criteria. • Optimisation of biodiesel blends for transport in India considering life cycle. • Blends between 25% and 81% achieved depending on optimisation parameters. [ABSTRACT FROM AUTHOR]

India ranks third globally in overall greenhouse gas (GHG) emissions, with power and transportation first and third, respectively, in terms of India's sectoral GHG contributions. Motivated by India's Nationally Determined Contribution goals and stated intent to drive renewables growth and vehicle electrification, this paper explores the connections between India's power and road transportation sectors by investigating the benefits of flexible electric vehicle (EV) charging on a set of hypothetical 2037 Indian power grid infrastructures. Using two production cost models, one simulating optimal unit commitment and hourly dispatch of available generation, the other simulating subhourly real-time dispatch operations, we examine the impact of flexible and inflexible EV charging regimes and vehicle-to-grid integration on generation profiles, peak load shaving, energy storage utilization, and overall emissions. Our techno-economic analysis shows that a number of future grid infrastructure scenarios, despite not specifically accounting for EV growth scenarios, may meet annual and hourly peak demand when combined with flexible EV charging; in contrast, inflexible EV charging, particularly during the early morning, will lead to substantial need for additional generation capacity. Coupled sectoral decarbonization remains tied to the grid generation mix, highlighting the need for continued policy focus on decarbonization of the rapidly growing power sector. • Flexible charging, grid decarbonization policies critical for EV adoption benefits. • Scenario analysis highlights pathways to efficiency gains + emissions reductions. • We quantify net CO 2 emissions from power + road transport with increasing EV load. • V2G reduces unserved reserves, prevents price spikes during extreme power outages. [ABSTRACT FROM AUTHOR]

Environmentally conscious manufacturing (ECM) has become an important strategy and proactive approach for the iron and steel sector of India to produce environment friendly and to reduce manufacturing cost. There are several environmentally conscious manufacturing indicators to evaluate ECM programs. Among those indicators, energy consumption and greenhouse (GHG) emission may be considered critical environmentally conscious manufacturing indicators (CECMI) for Indian iron and steel sector. This paper focuses on forecasting energy consumption and GHG emission for a pig iron manufacturing organization of India because the managers are interested to know the current and future trends of these indicators for better environmental policy. For forecasting purpose, autoregressive integrated moving average (ARIMA) is applied to reveal that ARIMA (1,0,0) × (0,1,1) is the best fitted model for energy consumption. Regarding GHG emission, ARIMA (0,1,4) × (0,1,1) is the best fitted model. In both cases, the forecasts resemble those of the seasonal random trend model, however they appear smoother because the seasonal pattern and the trend are efficiently averaged for energy consumption and as well as GHG emission. Selection of the correct ARIMA models for these indicators will help in accurate forecasting in order to achieve better environmental management practice. [ABSTRACT FROM AUTHOR]

Demand Side Management, an integral feature of smart grid, exhibits high potential in load balancing and load shifting for efficient management of the power grids. Strategically designed DSM mechanisms can help mitigate load shedding and facilitate peak load management of grids. In India, only flat rate and inclining block rate tariff mechanism exist for residential customers. With the onset of 14 smart grid pilot projects in India, there is a need to address the realization of potential underlying various features of a smart grid. As India is a price sensitive market, time of use tariffs and other demand response programs are expected to potentially affect the consumer behavior in power consumption. In this paper, the usage pattern of residential customers, collected from a pilot project in India is analyzed for scaling the potential of DSM strategies. Simulations have been carried out for a price based mechanism as well as an incentive based mechanism to evaluate the underlying potential of DSM exclusively for residential consumers. The results of the simulation indicate that there is a definite scope for load balancing as well as financial savings. [ABSTRACT FROM AUTHOR]

The analytical assessment of 5.05 kWp grid tied photovoltaic plant performance on the system level has been carried out in this study. The solar PV plant has been installed on the roof of the block-A of the Darshan Institute of Engineering and Technology, Rajkot. India. The Darshan Institute of Engineering and Technology has been monitoring and recording all the parameters of 5.05 kWp grid tied solar PV power plant for 3 years. This paper helps in study of the performance and consistency of this system. The final yield, reference yield and performance ratio are observed to vary from 2.96 h/d to 5.43 h/d, 4.22 h/d to 7.29 h/d and 68%–83% respectively. The global in-plane solar radiation at the city of Rajkot is 2212 kWh/m 2 /annum. The average annual measured energy yield of the plant is found to be 1636 kWh/kWp. The total estimated system losses due to irradiance angle, temperature, module quality, array and cell mismatch, AC/DC wiring, MPPT, soiling and dirt, and inverter are found to be 26%. As a whole, the location, soiling pattern, design of PV and maintenance of solar PV system are the primary reasons of energy variability and system energy production. [ABSTRACT FROM AUTHOR]

The rapid growth of air conditioners (ACs) in developing regions exacerbates some of the issues present in their electricity systems. Direct Load Control strategies can manage peak loads for optimizing energy usage for users and utilities. When applied to air conditioning, these strategies can be used for Demand Side Management which has not been fully explored for developing regions. In this paper a novel Direct Load Control mechanism is proposed, wherein control is based on technical constraints (generation capacity). To determine the effects of the proposed mechanism, a case study of the Indian State of Karnataka is carried out. The results indicate 0.88% energy savings and a reduction of almost 2% in regional peak loads in a state where only around 5% of all households have AC units. The case study shows that an AC Direct Load Control can have significant economic and environmental impacts, and can help improve current energy, water and climate issues. Continuous improvements in both energy access and economic conditions of developing regions are leading to a larger number of AC's installed, meaning that a mechanism that enables sustainable AC consumption could be of great use for all the stakeholders in the developing countries' electricity sectors. • A novel Direct Load Control for residential air conditioning is proposed. • The control can be implemented in developing regions without price-based markets. • A case study of the novel control shows a summer demand reduction of 0.88%. • The reduction of the demand leads to environmental and economic benefits. • The proposed control reduces negative impacts of growing air conditioning demand. [ABSTRACT FROM AUTHOR]

Day-ahead load forecasting plays a crucial role in operation and management of power systems. Weather conditions have a significant impact on daily load profile, hence, it follows an almost similar pattern within a season. However, it varies markedly across the seasons. Existing literature on load forecasting adopts a very casual approach in considering the seasonality, based on either calendar month or some meteorological parameter, which is inconsistent and inaccurate, especially during transition periods, thus leading to high forecasting errors. This paper proposes a novel seasonal segmentation approach for day-ahead load forecasting that uses multiple bidirectional Long Short Term Memory (LSTM) networks. An index has been derived from various weather parameters that govern the selection of seasonal models for forecasting purposes. Weighted output from multiple seasonal models is also possible in special cases for better forecasting accuracy. The proposed seasonal segmentation approach avoids the need for frequent model retraining and results in a better forecast accuracy with a relatively simple LSTM structure. The performance of the proposed method has been validated and compared on the actual load data of Madhya Pradesh state (MP), India. The improved results suggest that the proposed approach can be applied reliably for load scheduling applications. • An encoder-decoder Bi-LSTM model with attention is developed to train the models. • An adaptive method for accurate identification of seasonal duration is proposed. • An index based selective and weighted method is developed for optimized forecasts. • Dynamic Time Warping (DTW) is used to adaptively select the forecast models. [ABSTRACT FROM AUTHOR]

In India, power shortage is a major issue for economical growth. According to the data provided by National Load Despatch Centre, peak power shortage in Tamilnadu during the year 2014 varies between 3000 MW and 4000 MW. This power shortage can be reduced by increasing installed capacity of conventional and non-conventional energy sources. But the construction of new generation plants is cost-effective and also power generation is not assured throughout the year. This power shortage can also be minimized by implementing load management in the consumer side. This paper focuses on the reduction of peak demand by the proper operating schedule of major equipments. For this analysis, three rice industries have been considered. The major operating sections in the rice industries are pre-cleaning, soaking, pre-milling and milling. In this proposed work, to reduce the peak demand, the operating time of pre-milling section is rescheduled using the optimization techniques, DE (Differential Evolution), PSO (Particle Swarm Optimization) and ABC (Artificial Bee Colony). The rescheduled results given by DE, PSO and ABC algorithms reduce the peak demand cost of the energy consumed in three rice industries. However, the optimum scheduling obtained by ABC reduces the feeder power flow than the DE and PSO scheduling. [ABSTRACT FROM AUTHOR]

The Indian power sector is experiencing a lot of pressure to supply sustainable electricity at affordable cost due to heavy demand especially in the summer peak season. Most of India's electricity is produced by fossil fueled power plants, which are the source of CO 2 emissions. In this case, renewable energy sources play a vital role in securing sustainable energy without environmental emissions. This paper examines the effects of renewable energy use in electricity supply systems and estimates the CO 2 emissions by developing various scenarios under the least cost approach. The LEAP energy model is used to develop these scenarios. The results show that in a ARET (accelerated renewable energy technology) scenario, 23% of electricity is generated by renewables only, and 74% of CO 2 reduction is possible by 2050. If the maximum energy savings potential is combined with the ARET scenario, the renewables share in electricity supply rises to 36% as compared to the reference scenario, while the CO 2 emission reduction in this case remains at 74%. [ABSTRACT FROM AUTHOR]

As part of a two-part life cycle efficiency and greenhouse gas emission analysis for various automotive fuels in the Indian context, this paper presents the first part, i.e., Tank-to-Wheel analysis of various fuel/powertrain configurations for a subcompact passenger car. The Tank-to-Wheel analysis was applied to 28 fuel/powertrain configurations using fuels such as gasoline, diesel, compressed natural gas, liquefied petroleum gas and hydrogen with various conventional and hybrid electric powertrains. The gasoline-equivalent fuel economy and carbon dioxide emission results for individual fuel/powertrain configuration are evaluated and compared. It is found that the split hybrid configuration is best among hybrids as it leads to fuel economy improvement and carbon dioxide emissions reduction by 20–40% over the Indian drive cycle. Further, the engine efficiency, engine on-off time and regenerative braking energy assessment is done to evaluate the causes for higher energy efficiency of hybrid electric vehicles. The hybridization increases average engine efficiency by 10–60% which includes 19–23% of energy recovered at wheel through regenerative braking over the drive cycle. Overall, the Tank-to-Wheel energy use and efficiency results are evaluated for all fuel/powertrain configurations which show Battery Electric Vehicle, fuel cell vehicles and diesel hybrids are near and long term energy efficient vehicle configurations. [ABSTRACT FROM AUTHOR]

Global competition for crude oil has increased in the past decade with the entry of industrializing nations such as China and India. Yet we still do not know much about the spatial structure of crude oil commodity trade and its evolution over time. In this paper, we apply complex network analysis to examine the geography of global crude oil flows and its evolution based on the United Nations commodity trade database from 1988 to 2013. Attention is given to the geo-visualization of the networks that trace the rise and decline of oil hubs. The results show that world crude oil is characterized by network characteristics that capture both small world and flat world properties. [ABSTRACT FROM AUTHOR]

In this paper, we evaluate opportunities to mitigate CO 2 emission from the power and industry sectors of India by carbon capture and storage. Results show that the total CO 2 emission from 630 power and industrial plants is 1.7 Gtpa. Of this, 0.9 Gtpa comes from power plants and 0.8 Gtpa from industry plants. There is 416.2 Gt of CO 2 storage capacity (mid case scenario) in India, enough to store 237 years of emission. Of this, 412.7 Gt (99%) comes from saline aquifers in 22 sedimentary basins, 1.9 Gt (0.44%) from six major gas fields, and 1.7 Gt (0.41%) from 37 major oil fields. The total mid CO 2 -enhanced oil recovery potential in India is 500 × 106 m3 with the biggest potential found in the following oil fields: Mumbai High (231 × 106 m3), Gandhar (13 × 106 m3), Mangala (17 × 106 m3) and Nahorkatiya (24 × 106 m3) in the states of Gujarat, Maharashtra, Rajasthan and Assam, respectively. Results of a CO 2 source-sink mapping exercise show that in most cases, CO 2 source-sink distance is less than 500 km, and many cases less than 100 km. • India's CO 2 emission is 1.7 Gtpa from the power and industry sectors. • There is 416.2 Gt of subsurface CO 2 storage capacity in India. • There is a total of CO 2 -enhanced oil recovery potential of 5.01 × 108 m3. • A CO 2 -EOR pilot is recommended for the offshore Mumbai High oil field. • Most CO 2 sources can be stored in sinks within a 500 km distance. [ABSTRACT FROM AUTHOR]

This paper examines the role of state level institutional differences in attracting FDI (foreign direct investment) in wind energy in India. The role of institutional differences is measured by means of constructing a policy index using five key policies in wind energy: feed-in-tariff, open access transmission, third party sale, banking, and wheeling charges. Panel data techniques are then employed to investigate the impact of the policy differences on FDI inflow in wind energy for eight Indian states that have significant resource potential over the seven year period (2004–05 to 2010–11) after controlling for several state-specific factors. The results indicate that state-specific policy index for wind energy is significant in attracting FDI in a state irrespective of whether control variables are included or not. [ABSTRACT FROM AUTHOR]

An accurate and objective prediction of coal consumption is important for stabilizing the coal market, ensuring the operating results of coal enterprises. This paper starts with the background value of the traditional GM(1,1) model, extends the model by the extrapolation method, proposes an optimized grey prediction model, deduces the time response equation, studies the relationship between model parameters and model accuracy. Then the model is optimized by simulated annealing algorithm. Three cases verify the validity of model, the results show that its lowest prediction error percentage is 3.1286%, which is better than two classical grey prediction models, Finally, the model is applied to forecast the next five years' consumption of China, India and the United States, which are the world's top three coal consumers. The errors of the proposed models are all about 5%, which is obviously better than the comparison models. The results show that coal consumption in China and India will continue to rise over the next five years, while the United States will decline. These findings are consistent with the current development of the three countries; therefore, the optimized prediction model can effectively predict the coal consumption of the three countries. • The highlights of this article are as follows: • An optimized grey prediction model that can be applied to various data situations is proposed. • The traditional GM(1,1) model is optimized by a simulated annealing algorithm. • The validity of the model is verified by theoretical deduction and case analysis. • The generality and wide applicability of the proposed method are discussed. [ABSTRACT FROM AUTHOR]

Abstract: Most studies on household energy choices have considered income and education as suitable proxies for socio-cultural contexts, primarily because the available data on household energy is from census surveys which are mainly household consumption surveys, not focused energy surveys. Acknowledging the existing data constraints, a more focussed household energy survey was designed for rural India with the aim of better understanding determinants of current energy use patterns, energy choices, to measure the impacts of these factors, and importantly, arrive at key policy insights. This paper revisits the definition of access to include for reliability and quality going beyond conventional understanding. It also relooks at the role of gender in household energy choices. Having established that apart from income, socio-cultural factors may have a greater role in determining household energy choices, the model results indicate electricity access would have a positive impact on cooking energy choices only after meeting a minimum threshold requirement. As women move towards more formal employment, the odds of choosing cleaner fuels increase significantly. Thus, while macro-policies may provide important guidelines and the necessary framework, implementation strategies need to be designed at the local level through a participatory approach making energy an integral part of the development paradigm. [Copyright &y& Elsevier]

Abstract: Attractive economic performance of energy systems is important for their long term sustainability. In this paper, a cost benefit analysis (CBA), standard thermoeconomic analysis, and a new method that combines the two was applied to seven modelled candidate decentralised energy systems for small Indian rural villages. By including elements of CBA in standard thermoeconomics, economic inefficiencies at the component level and revenue adjusted costs of exergy for each stream were ascertained. The analysed systems all produced household and irrigation electricity as well as a secondary product or service, which in some cases utilised waste heat from the electricity generation process. The system that produced distilled water as a secondary product was the most economically sustainable out of those modelled. While the standard thermoeconomic electricity cost remained around 0.5 USD/kWh for all analysed systems, the benefit to cost ratios varied from 0.29 to 0.97, demonstrating differing appeal to outside investment. By incorporating CBA into standard thermoeconomics the accounted revenue produced a larger spread in exergetic costs than standard thermoeconomics (for example, an electricity cost range of 0.217–0.507 USD/kWh), thus providing a better comparison of systems with different energy end uses. [Copyright &y& Elsevier]

Abstract: For India, sustainable strategy means one that is economically, environmentally and socially sustainable. This calls for rapid economic growth to deal with poverty and human development. However, the relatively meagre energy resources of the country pose a huge challenge. At the same time concern for climate change has raised the bar on the use of the one energy resource that India has in some abundance, namely coal. India''s strategy for sustainable development has to explore all options of reducing energy needs, enhancing efficiency of use of conventional energy resources and develop new and renewable sources. The paper identifies various technical options, their potential roles and alternative policy measures to realize them in a cost effective manner. Even for the same objectives different policy instruments are available and how one chooses a particular instrument is often critical for the success. Self-implementing incentive compatible policy that does not create vested interests that would get entrenched should be preferred. [Copyright &y& Elsevier]

Abstract: Biomass is one of the key energy sources in rural India and constitutes 75% of the total energy consumption. In the tough mountain terrain, the consumption pattern depends on the availability of the resources as well as socio-economic conditions of the people. The present study is conducted at Fakot micro-watershed in Garhwal district of Uttarakhand, India. The present paper explores the variations in fuelwood consumption pattern in the watershed level at different altitudes with respect to family size. In the present study, the fuelwood consumption in the watershed is in the range of 455–2388 gm/person/day. Absence of serial autocorrelation in the seasonal fuel consumption data is observed. Season specific models for fuel consumption are proposed. [Copyright &y& Elsevier]

Abstract: This paper addresses the impact of both economic growth and financial development on environmental degradation using a panel cointegration technique for the period between 1980 and 2007, except for Russia (1992–2007). In long-run equilibrium, CO2 emissions appear to be energy consumption elastic and FDI inelastic, and the results seem to support the Environmental Kuznets Curve (EKC) hypothesis. The causality results indicate that there exists strong bidirectional causality between emissions and FDI and unidirectional strong causality running from output to FDI. The evidence seems to support the pollution haven and both the halo and scale effects. Therefore, in attracting FDI, developing countries should strictly examine the qualifications for foreign investment or to promote environmental protection through the coordinated know-how and technological transfer with foreign companies to avoid environmental damage. Additionally, there exists strong output-emissions and output-energy consumption bidirectional causality, while there is unidirectional strong causality running from energy consumption to emissions. Overall, the method of managing both energy demand and FDI and increasing both investment in the energy supply and energy efficiency to reduce CO2 emissions and without compromising the country’s competitiveness can be adopted by energy-dependent BRIC countries. [ABSTRACT FROM AUTHOR]

Abstract: This paper attempts to assess the adequacy of wind power generation systems using the data collected from seven wind farms in Muppandal, Tamilnadu (India) with a total capacity of 37 MW. A Monte Carlo model simulation is incorporated in the algorithm to obtain the hourly power output of wind farms, which also takes into account the unavailability of wind turbines. A typical load demand profile is used to examine the chronological hourly wind power generation for each month. The reliability index of LOLE (loss of load expectation) is used to estimate the reliable contribution of wind farm power generation. [ABSTRACT FROM AUTHOR]

Abstract: In this paper DEA (Data envelopment analysis), a non-parametric approach to frontier analysis, is applied to evaluate the relative performance of 29 EDDs (Electricity Distribution Divisions) of an Indian hilly state, namely Uttarakhand. Input oriented DEA is applied to evaluate the relative overall efficiency, technical efficiency and scale efficiency of EDDs. The results indicate that numerous divisions have scope for improvement in overall efficiency. Most of the utilities are inefficient due to their scale inefficiency rather than technical inefficiency. Further Slack analysis is carried out to formulate improvement directions for relatively inefficient divisions. Particular areas are identified, which are to be improved for overall efficiency enhancement through sensitivity analysis. Different alternatives for reorganization of the EDDs are explored in order to obtain most favorable and balanced scale. The result is envisaged to be instrumental to policy makers and managers to increase the operational efficiency of the EDDs leading to higher profitability of the state electricity board. [ABSTRACT FROM AUTHOR]

Abstract: Due to the growing energy needs along with increasing concerns towards control of greenhouse gas emissions, most developing countries are under pressure to find alternative methods for energy conversion and policies to make these technologies economically viable. Most of the energy is produced from fossil fuel in India which is not a sustainable source of energy. In this paper Indian power sector has been examined by using MARKAL model for introduction of clean coal and advanced nuclear technologies with implementation of energy conservation potential. The result shows that application of clean technologies gives energy security but not significant reduction in carbon dioxide emissions. When clean technologies apply with energy conservation a huge amount of CO2 can be reduced and also economically viable. Three scenarios including base case scenario have been developed to estimate the resource allocations and CO2 mitigation. The clean technologies with maximum savings potential shows 70% CO2 reduction in the year 2045. [Copyright &y& Elsevier]

Abstract: If wind park configurations are globally coordinated across the service area of a power utility, then electricity can be generated for the grid with substantial cost advantages. Based on this premise, the paper introduces a model by which large scale assessment of grid connected wind based power generation may be undertaken for a utility service area. The model can be useful to the policy maker for decisions regarding suitable wind portfolio standards (WPS) definition. The utility on the other hand, may use the model to study its service area for prospective wind based generation. Aspects of the problem modelled include cost-of-energy from individual generating units, daily load variations for the utility with emphasis on limited penetration, features of wind at prospective installation sites, makes of wind energy conversion systems (WECS) available, and recovery of expenditure through revenue. Application of the model to an assessment exercise for the state of Andhra Pradesh (India) is presented as an example. [Copyright &y& Elsevier]